WorldWideScience

Sample records for satellite land remote

  1. Models for estimation of land remote sensing satellites operational efficiency

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.

    2017-01-01

    The paper deals with the problem of estimation of land remote sensing satellites operational efficiency. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  2. Estimation of land remote sensing satellites productivity based on the simulation technique

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.; Yakischik, Artem A.

    2017-01-01

    The problem of estimating land remote sensing satellites productivity is considered. Here, productivity is treated as a number of separate survey objects taken in a definite time. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  3. The Global Land Surface Satellite (GLASS Remote Sensing Data Processing System and Products

    Directory of Open Access Journals (Sweden)

    Gongqi Zhou

    2013-05-01

    Full Text Available Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computing system and massive volumes of multi-sensor and multi-temporal remotely sensed data. This manuscript describes the ground Global LAnd Surface Satellite (GLASS product generation system that can be used to generate long-sequence time series of global land surface data products based on various remotely sensed data. To ensure stabilization and efficiency in running the system, we used the methods of task management, parallelization, and multi I/O channels. An array of GLASS remote sensing products related to global land surface parameters are currently being produced and distributed by the Center for Global Change Data Processing and Analysis at Beijing Normal University in Beijing, China. These products include Leaf Area Index (LAI, land surface albedo, and broadband emissivity (BBE from the years 1981 to 2010, downward shortwave radiation (DSR and photosynthetically active radiation (PAR from the years 2008 to 2010.

  4. Environmental impact classification with fuzzy sets for urban land cover from satellite remote sensing data

    Science.gov (United States)

    Zoran, Maria A.; Nicolae, Doina N.; Talianu, Camelia

    2004-10-01

    Urban area is a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in urban's land cover are due to natural and anthropogenic causes. A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic, dynamics processes, and climatic change effects. Synergetic use of quasi-simultaneously acquired multi-sensor data may therefore allow for a better approach of change detection and environmental impact classification and assessment in urban area. It is difficult to quantify the environmental impacts of human and industrial activities in urban areas. There are often many different indicators than can conflict with each other, frequently important observations are lacking, and potentially valuable information may non-quantitative in nature. Fuzzy set theory offers a modern methodology for dealing with these problems and provides useful approach to difficult classification problems for satellite remote sensing data. This paper describes how fuzzy logic can be applied to analysis of environmental impacts for urban land cover. Based on classified Landsat TM, SPOT images and SAR ERS-1 for Bucharest area, Romania, it was performed a land cover classification and subsequent environmental impact analysis.

  5. Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

    Science.gov (United States)

    Xian, George

    2008-01-01

    By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.

  6. Cultivated Land Changes and Their Driving Forces-A Satellite Remote Sensing Analysis in the Yellow River Delta, China

    Institute of Scientific and Technical Information of China (English)

    ZHAO Geng-Xing; G.LIN; J.J.FLETCHER; C.YUILL

    2004-01-01

    Taking Kenli County in the Yellow River Delta, China, as the study area and using digital satellite remote sensing techniques, cultivated land use changes and their corresponding driving forces were explored in this study. An interactive interpretation and a manual modification procedure were carried out to acquire cultivated land information. An overlay method based on classification results and a visual change detection method which was supported by land use maps were employed to detect the cultivated land changes. Based on the changes that were revealed and a spatial analysis between cultivated land use and related natural and socio-economic factors, the driving forces for cultivated land use changes in the study area were determined.The results showed a decrease in cultivated land in Kenli County of 5321.8 ha from 1987 to 1998, i.e.,an average annual decrement of 483.8 ha, which occurred mainly in the central paddy field region and the northeast dry land region. Adverse human activities, soil salinization and water deficiencies were the driving forces that caused these cultivated land use changes.

  7. Monitoring the hydrologic and vegetation dynamics of arid land with satellite remote sensing and mathematic modeling

    Science.gov (United States)

    Zhan, Xiwu; Gao, Wei; Pan, Xiaoling; Ma, Yingjun

    2003-07-01

    Terrestrial ecosystems, in which carbon is retained in live biomass, play an important role in the global carbon cycling. Among these ecological systems, vegetation and soils in deserts and semi deserts control significant proportions in the total carbon stocks on the land surface and the carbon fluxes between the land surface and the atmosphere (IPCC special report: Land Use, Land Use Change and Forestry, June 2000). Therefore, accurate assessment of the carbon stocks and fluxes of the desert and semi desert areas at regional scales is required in global carbon cycle studies. In addition, vegetative ecosystem in semi-arid and arid land is strongly dependent on the water resources. Monitoring the hydrologic processes of the land is thus also required. This work explores the methodology for the sequential continuous estimation of the carbon stocks, CO2 flux, evapotranspiration, and sensible heat fluxes over desert and semidesert area using data from the Jornada desert in New Mexico, USA. A CO2 and energy flux coupled model is used to estimate CO2, water vapor and sensible heat fluxes over the desert area. The model is driven by the observed meteorological data. Its input land surface parameters are derived from satellite images. Simulated energy fluxes are validated for specific sites with eddy covariance observations. Based on the output of spatially distributed CO2 fluxes, carbon accumulations over the desert area during a period of time is calculated and the contribution of the desert ecosystem to the atmospheric carbon pool is discussed.

  8. An inter-comparison of soil moisture data products from satellite remote sensing and a land surface model

    Science.gov (United States)

    Fang, Li; Hain, Christopher R.; Zhan, Xiwu; Anderson, Martha C.

    2016-06-01

    Significant advances have been achieved in generating soil moisture (SM) products from satellite remote sensing and/or land surface modeling with reasonably good accuracy in recent years. However, the discrepancies among the different SM data products can be considerably large, which hampers their usage in various applications. The bias of one SM product from another is well recognized in the literature. Bias estimation and spatial correction methods have been documented for assimilating satellite SM product into land surface and hydrologic models. Nevertheless, understanding the characteristics of each of these SM data products is required for many applications where the most accurate data products are desirable. This study inter-compares five SM data products from three different sources with each other, and evaluates them against in situ SM measurements over 14-year period from 2000 to 2013. Specifically, three microwave (MW) satellite based data sets provided by ESA's Climate Change Initiative (CCI) (CCI-merged, -active and -passive products), one thermal infrared (TIR) satellite based product (ALEXI), and the Noah land surface model (LSM) simulations. The in-situ SM measurements are collected from the North American Soil Moisture Database (NASMD), which involves more than 600 ground sites from a variety of networks. They are used to evaluate the accuracies of these five SM data products. In general, each of the five SM products is capable of capturing the dry/wet patterns over the study period. However, the absolute SM values among the five products vary significantly. SM simulations from Noah LSM are more stable relative to the satellite-based products. All TIR and MW satellite based products are relatively noisier than the Noah LSM simulations. Even though MW satellite based SM retrievals have been predominantly used in the past years, SM retrievals of the ALEXI model based on TIR satellite observations demonstrate skills equivalent to all the MW satellite

  9. Estimation of land surface evapotranspiration with A satellite remote sensing procedure

    Science.gov (United States)

    Irmak, A.; Ratcliffe, I.; Ranade, P.; Hubbard, K.G.; Singh, R.K.; Kamble, B.; Kjaersgaard, J.

    2011-01-01

    There are various methods available for estimating magnitude and trends of evapotranspiration. Bowen ratio energy balance system and eddy correlation techniques offer powerful alternatives for measuring land surface evapotranspiration. In spite of the elegance, high accuracy, and theoretical attractions of these techniques for measuring evapotranspiration, their practical use over large areas can be limited due to the number of sites needed and the related expense. Application of evapotranspiration mapping from satellite measurements can overcome the limitations. The objective of this study was to utilize the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) model in Great Plains environmental settings to understand water use in managed ecosystems on a regional scale. We investigated spatiotemporal distribution of a fraction of reference evapotranspiration (ETrF) using eight Landsat 5 images during the 2005 and 2006 growing season for path 29, row 32. The ETrF maps generated by METRICTM allowed us to follow the magnitude and trend in ETrF for major land-use classes during the growing season. The ETrF was lower early in the growing season for agricultural crops and gradually increased as the normalized difference vegetation index of crops increased, thus presenting more surface area over which water could transpire toward the midseason. Comparison of predictions with Bowen ratio energy balance system measurements at Clay Center, NE, showed that METRICTM performed well at the field scale for predicting evapotranspiration from a cornfield. If calibrated properly, the model could be a viable tool to estimate water use in managed ecosystems in subhumid climates at a large scale.

  10. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran)

    OpenAIRE

    2013-01-01

    Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using...

  11. Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

    Science.gov (United States)

    Broich, M.; Huete, A.; Tulbure, M. G.; Ma, X.; Xin, Q.; Paget, M.; Restrepo-Coupe, N.; Davies, K.; Devadas, R.; Held, A.

    2014-05-01

    Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray-Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in the interior of the

  12. Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

    Directory of Open Access Journals (Sweden)

    M. Broich

    2014-05-01

    Full Text Available Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI. We based our analysis on Enhanced Vegetation Index (EVI data from the MODerate Resolution Imaging Spectroradiometer (MODIS from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB, the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in

  13. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  14. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran

    Directory of Open Access Journals (Sweden)

    Mohammad Maleky

    2013-10-01

    Full Text Available Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using Optimal Index Factor (OIF in ILWIS software. Greenness, brightness and wetness indexes along with NDVI index of land cover were then derived in each period using Fuzzy Art map Supervised Classification, Principal Components Analysis and Tasseled-cap Transformation. The results indicated that Pca2 index can properly demonstrate increasing and decreasing changes among the main components as greenness index can display decreasing and no changes in land uses among tasseled-cap components, while the wetness index would reflect increasing changes in land use with high accuracy. Moreover, the precision and results of NDVI index is so close to that of greenness index. The overall results of the study suggest that the urban surface area is annually increased at a rate of 109.6 ha, which was a major decline in agricultural and range land use.

  15. An investigation of current and future satellite and in-situ data for the remote sensing of the land surface energy balance

    Science.gov (United States)

    Diak, George R.

    1994-01-01

    This final report from the University of Wisconsin-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) summarizes a research program designed to improve our knowledge of the water and energy balance of the land surface through the application of remote sensing and in-situ data sources. The remote sensing data source investigations to be detailed involve surface radiometric ('skin') temperatures and also high-spectral-resolution infrared radiance data from atmospheric sounding instruments projected to be available at the end of the decade, which have shown promising results for evaluating the land-surface water and energy budget. The in-situ data types to be discussed are measurements of the temporal changes of the height of the planetary boundary layer and measurements of air temperature within the planetary boundary layer. Physical models of the land surface, planetary boundary layer and free atmosphere have been used as important tools to interpret the in-situ and remote sensing signals of the surface energy balance. A prototype 'optimal' system for combining multiple data sources into a three-dimensional estimate of the surface energy balance was developed and first results from this system will be detailed. Potential new sources of data for this system and suggested continuation research will also be discussed.

  16. Biophysical applications of satellite remote sensing

    CERN Document Server

    Hanes, Jonathan

    2014-01-01

    Including an introduction and historical overview of the field, this comprehensive synthesis of the major biophysical applications of satellite remote sensing includes in-depth discussion of satellite-sourced biophysical metrics such as leaf area index.

  17. The U.S. Geological Survey Land Remote Sensing Program

    Science.gov (United States)

    ,

    2007-01-01

    The fundamental goals of the U.S. Geological Survey's Land Remote Sens-ing (LRS) Program are to provide the Federal Government and the public with a primary source of remotely sensed data and applications and to be a leader in defining the future of land remote sensing, nationally and internationally. Remotely sensed data provide information that enhance the understand-ing of ecosystems and the capabilities for predicting ecosystem change. The data promote an understanding of the role of the environment and wildlife in human health issues, the requirements for disaster response, the effects of climate variability, and the availability of energy and mineral resources. Also, as land satellite systems acquire global coverage, the program coordinates a network of international receiving stations and users of the data. It is the responsibility of the program to assure that data from land imaging satellites, airborne photography, radar, and other technologies are available to the national and global science communities.

  18. Land use land cover change detection using remote sensing application for land sustainability

    Science.gov (United States)

    Balakeristanan, Maha Letchumy; Md Said, Md Azlin

    2012-09-01

    Land falls into the category of prime resources. Land use and land cover changes are identified as the prime issue in global environmental changes. Thus, it is necessary to initiate the land change detection process for land sustainability as well as to develop a competent land use planning. Tropical country like Malaysia has been experiencing land use and land cover changes rapidly for the past few decades. Thus, an attempt was made to detect the land use and land cover changes in the capital of the Selangor, Malaysia, Shah Alam over 20 years period (1990 - 2010). The study has been done through remote sensing approach using Earth Sat imagery of December 1990 and SPOT satellite imageries of March 2000 and December 2010. The current study resulted that the study area experienced land cover changes rapidly where the forest area occupied about 24.4% of Shah Alam in 1990 has decreased to 13.6% in 2010. Built up land have increased to 29.18% in 2010 from 12.47% in 1990. Other land cover classes such as wet land, wasteland and agricultural land also have undergone changes. Efficient land management and planning is necessary for land sustainability in Shah Alam.

  19. Long term changes in forest cover and land use of Similipal Biosphere Reserve of India using satellite remote sensing data

    Science.gov (United States)

    Saranya, K. R. L.; Reddy, C. Sudhakar

    2016-04-01

    The spatial changes in forest cover of Similipal biosphere reserve, Odisha, India over eight decades (1930-2012) has been quantified by using multi-temporal data from different sources. Over the period, the forest cover reduced by 970.8 km2 (23.6% of the total forest), and most significantly during the period, 1930-1975. Human-induced activities like conversion of forest land for agriculture, construction of dams and mining activities have been identified as major drivers of deforestation. Spatial analysis indicates that 399 grids (1 grid = 1 × 1 km) have undergone large-scale changes in forest cover (>75 ha) during 1930-1975, while only 3 grids have shown >75 ha loss during 1975-1990. Annual net rate of deforestation was 0.58 during 1930-1975, which has been reduced substantially during 1975-1990 (0.04). Annual gross rate of deforestation in 2006-2012 is indeed low (0.01) as compared to the national and global average. This study highlights the impact and effectiveness of conservation practices in minimizing the rate of deforestation and protecting the Similipal Biosphere Reserve.

  20. Long term changes in forest cover and land use of Similipal Biosphere Reserve of India using satellite remote sensing data

    Indian Academy of Sciences (India)

    K R L Saranya; C Sudhakar Reddy

    2016-04-01

    The spatial changes in forest cover of Similipal Biosphere Reserve, Odisha, India over seven decades(1930–2012) in the last century has been quantified by using multi-temporal data from different sources.Over the period, the forest cover reduced by 970.8 km2 (23.6% of the total forest), and most significantlyduring the period, 1930–1975. Human-induced activities like conversion of forest land for agriculture,construction of dams and mining activities have been identified as major drivers of deforestation. Spatialanalysis indicates that 399 grids (1 grid = 1 × 1 km) have undergone large-scale changes in forest cover(>75 ha) during 1930–1975, while only 3 grids have shown >75 ha loss during 1975–1990. Annual netrate of deforestation was 0.58 during 1930–1975, which has been reduced substantially during 1975–1990 (0.04). Annual gross rate of deforestation in 2006–2012 is indeed low (0.01) as compared to thenational and global average. This study highlights the impact and effectiveness of conservation practicesin minimizing the rate of deforestation and protecting the Similipal Biosphere Reserve.

  1. Numerical modeling and remote sensing of global water management systems: Applications for land surface modeling, satellite missions, and sustainable water resources

    Science.gov (United States)

    Solander, Kurt C.

    The ability to accurately quantify water storages and fluxes in water management systems through observations or models is of increasing importance due to the expected impacts from climate change and population growth worldwide. Here, I describe three innovative techniques developed to better understand this problem. First, a model was created to represent reservoir storage and outflow with the objective of integration into a Land Surface Model (LSM) to simulate the impacts of reservoir management on the climate system. Given this goal, storage capacity represented the lone model input required that is not already available to an LSM user. Model parameterization was linked to air temperature to allow future simulations to adapt to a changing climate, making it the first such model to mimic the potential response of a reservoir operator to climate change. Second, spatial and temporal error properties of future NASA Surface Water and Ocean Topography (SWOT) satellite reservoir operations were quantified. This work invoked the use of the SWOTsim instrument simulator, which was run over a number of synthetic and actual reservoirs so the resulting error properties could be extrapolated to the global scale. The results provide eventual users of SWOT data with a blueprint of expected reservoir error properties so such characteristics can be determined a priori for a reservoir given knowledge about its topology and anticipated repeat orbit pass over its location. Finally, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission was used in conjunction with in-situ water use records to evaluate sustainable water use at the two-digit HUC basin scale over the contiguous United States. Results indicate that the least sustainable water management region is centered in the southwest, where consumptive water use exceeded water availability by over 100% on average for some of these basins. This work represents the first attempt at evaluating sustainable

  2. Land remote sensing commercialization: A status report

    Science.gov (United States)

    Bishop, W. P.; Heacock, E. L.

    1984-01-01

    The current offer by the United States Department of Commerce to transfer the U.S. land remote sensing program to the private sector is described. A Request for Proposals (RFP) was issued, soliciting offers from U.S. firms to provide a commercial land remote sensing satellite system. Proposals must address a complete system including satellite, communications, and ground data processing systems. Offerors are encouraged to propose to take over the Government LANDSAT system which consists of LANDSAT 4 and LANDSAT D'. Also required in proposals are the market development procedures and plans to ensure that commercialization is feasible and the business will become self-supporting at the earliest possible time. As a matter of Federal Policy, the solicitation is designed to protect both national security and foreign policy considerations. In keeping with these concerns, an offeror must be a U.S. Firm. Requirements for data quality, quantity, distribution and delivery are met by current operational procedures. It is the Government's desire that the Offeror be prepared to develop and operate follow-on systems without Government subsidies. However, to facilitate rapid commercialization, an offeror may elect to include in his proposal mechanisms for short term government financial assistance.

  3. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  4. Satellite Remote Sensing in Offshore Wind Energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Astrup, Poul

    2013-01-01

    Satellite remote sensing of ocean surface winds are presented with focus on wind energy applications. The history on operational and research-based satellite ocean wind mapping is briefly described for passive microwave, scatterometer and synthetic aperture radar (SAR). Currently 6 GW installed...

  5. Risk management support through India Remote Sensing Satellites

    Science.gov (United States)

    Aparna, N.; Ramani, A. V.; Nagaraja, R.

    2014-11-01

    Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National & International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).

  6. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2014-09-01

    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

  7. Offshore winds mapped from satellite remote sensing

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    2014-01-01

    the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost....... The advantages of microwave satellite remote sensing are 1) horizontal spatial coverage, 2) long data archives and 3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to 6 observations per day with near...

  8. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  9. Surveying earth resources by remote sensing from satellites

    Energy Technology Data Exchange (ETDEWEB)

    Otterman, J.; Lowman, P.D.; Salomonson, V.V.

    1976-04-01

    The techniques and recent results of orbital remote sensing, with emphasis on Landsat and Skylab imagery are reviewed. Landsat (formerly ERTS) uses electronic sensors (scanners and television) for repetitive observations with moderate ground resolution. The Skylab flights used a wider range of electro-optical sensors and returned film cameras with moderate and high ground resolution. Data from these programs have been used successfully in many fields. For mineral resources, satellite observations have proven valuable in geologic mapping and in exploration for metal, oil, and gas deposits, generally as a guide for other (conventional) techniques. Water resource monitoring with satellite data has included hydrologic mapping, soil moisture studies, and snow surveys. Marine resources have been studied, with applications in the fishing industry and in ocean transportation. Agricultural applications, benefiting from the repetitive coverage possible with satellites, have been especially promising. Crop inventories are being conducted, as well as inventories of timber and rangeland. Overgrazing has been monitored in several areas. Finally, environmental quality has also proven susceptible to orbital remote sensing; several types of water pollution have been successfully monitored. The effects of mining and other activities on the land can also be studied. The future of orbital remote sensing in global monitoring of the Earth's resources seems assured. However, efforts to extend spectral range, increase resolution, and solve cloud-cover problems must be continued. Broad applications of computer analysis techniques are vital to handle the immense amount of information produced by satellite sensors.

  10. Land Use / Land Cover Classification of kanniykumari Coast, Tamilnadu, India. Using Remote Sensing and Gis Techniques

    Directory of Open Access Journals (Sweden)

    Hajeeran Beevi.N,

    2015-07-01

    Full Text Available The land use/ land cover details of Kanniyakuamri coast which is Located in the southern part of Tamil Nadu (India is studied. Satellite imagery is used to identify the Land use/ Land cover status of the study area. The software like ERDAS and Arc GIS are used to demarcate the land use / Land cover features of Kanniyakuamari coast. Remote sensing and GIS provided consistent and accurate base line information than many of the conventional surveys employed for such a task. The total area of Kanniyakumari coast is 715 sq.km. The land use / land cover classes of the study area has been categorized into thirteen such as Plantation, Sandy area, Water logged area, Scrub forest, Crop Land, Water bodies, Land with scrub, Reserve forest, Land without Scrub, Salt area, Beach Ridge, Settlement and Fallow land on the basis NRSA Classifications. Among these categories, land with scrub land is predominantly found all over the study area, It is occupied about 336.36 sq.km (44.61 percent, Crop Land 273.82 sq.km(38.29 percent, water bodies lands sharing about 20.44 sq.km (2.85 percent , settlement occupied with 6.96 sq.km (0.97 percent, and Fallow land was occupied 13.98 sq.km ( 1.95 percent .

  11. New Directions in Land Remote Sensing Policy and International Cooperation

    Science.gov (United States)

    Stryker, Timothy

    2010-12-01

    Recent changes to land remote sensing satellite data policies in Brazil and the United States have led to the phenomenal growth in the delivery of land imagery to users worldwide. These new policies, which provide free and unrestricted access to land remote sensing data over a standard electronic interface, are expected to provide significant benefits to scientific and operational users, and open up new areas of Earth system science research and environmental monitoring. Freely-available data sets from the China-Brazil Earth Resources Satellites (CBERS), the U.S. Landsat satellites, and other satellite missions provide essential information for land surface monitoring, ecosystems management, disaster mitigation, and climate change research. These missions are making important contributions to the goals and objectives of regional and global terrestrial research and monitoring programs. These programs are in turn providing significant support to the goals and objectives of the United Nations Framework Convention on Climate Change (UN FCCC), the Global Earth Observation System of Systems (GEOSS), and the UN Reduction in Emissions from Deforestation and Degradation (REDD) program. These data policies are well-aligned with the "Data Democracy" initiative undertaken by the international Committee on Earth Observation Satellites (CEOS), through its current Chair, Brazil's National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais, or INPE), and its former chairs, South Africa's Council for Scientific and Industrial Research (CSIR) and Thailand's Geo Informatics and Space Technology Development Agency (GISTDA). Comparable policies for land imaging data are under consideration within Europe and Canada. Collectively, these initiatives have the potential to accelerate and improve international mission collaboration, and greatly enhance the access, use, and application of land surface imagery for environmental monitoring and societal adaption to changing

  12. TOWARD CALIBRATED MODULAR WIRELESS SYSTEM BASED AD HOC SENSORS FOR IN SITU LAND SURFACE TEMPERATURE MEASUREMENTS AS SUPPORT TO SATELLITE REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    ASAAD CHAHBOUN

    2011-06-01

    Full Text Available This paper presents a new method for in situ Land Surface Temperature (LST measurements' campaigns for satellite algorithms validations. The proposed method based on Wireless Sensor Network (WSN is constituted by modules of node arrays. Each of which is constituted by 25 smart nodes scattered throughout a target field. Every node represents a Thermal Infra Red (TIR radiation sensor and keeps a minimum size while ensuring the functions of communication, sensing, and processing. This Wireless-LST (Wi-LST system is convenient to beinstalled on a field pointing to any type of targets (e.g. bare soil, grass, water, etc.. Ad hoc topology is adopted among the TIR nodes with multi-hop mesh routing protocol for communication, acquisition data are transmitted to the client tier wirelessly. Using these emergent technologies, we propose a practical method for Wi-LSTsystem calibration. TIR sensor (i.e. OSM101 from OMEGA society measures temperature, which is conditioned and amplified by an AD595 within a precision of 0.1 °C. Assessed LST is transmitted over thedeveloped ad hoc WSN modules (i.e. MICA2DOT from CROSSBOW society, and collected at in situ base station (i.e. PANASONIC CF19 laptop using an integrated database. LST is evaluated with a polynomialalgorithm structure as part of developed software. Finally, the comparison of the mean values of LST(Wi-LST in each site with the Moderate Resolution Imaging Spectro-radiometer (MODIS sensor, obtained from the daily LST product (MOD11C1 developed by the MODIS-NASA Science Team, on board TERRA satellite during the campaign period is provided.

  13. An operational satellite remote sensing system for ocean fishery

    Institute of Scientific and Technical Information of China (English)

    MAOZhihua; ZHUQiankun; PANDelu

    2004-01-01

    Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from-3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75 ℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.

  14. Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

    Science.gov (United States)

    Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

    2011-12-01

    The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan

  15. Satellite Remote Sensing in Seismology. A Review

    Directory of Open Access Journals (Sweden)

    Andrew A. Tronin

    2009-12-01

    Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

  16. Water Quality Assessment using Satellite Remote Sensing

    Science.gov (United States)

    Haque, Saad Ul

    2016-07-01

    The two main global issues related to water are its declining quality and quantity. Population growth, industrialization, increase in agriculture land and urbanization are the main causes upon which the inland water bodies are confronted with the increasing water demand. The quality of surface water has also been degraded in many countries over the past few decades due to the inputs of nutrients and sediments especially in the lakes and reservoirs. Since water is essential for not only meeting the human needs but also to maintain natural ecosystem health and integrity, there are efforts worldwide to assess and restore quality of surface waters. Remote sensing techniques provide a tool for continuous water quality information in order to identify and minimize sources of pollutants that are harmful for human and aquatic life. The proposed methodology is focused on assessing quality of water at selected lakes in Pakistan (Sindh); namely, HUBDAM, KEENJHAR LAKE, HALEEJI and HADEERO. These lakes are drinking water sources for several major cities of Pakistan including Karachi. Satellite imagery of Landsat 7 (ETM+) is used to identify the variation in water quality of these lakes in terms of their optical properties. All bands of Landsat 7 (ETM+) image are analyzed to select only those that may be correlated with some water quality parameters (e.g. suspended solids, chlorophyll a). The Optimum Index Factor (OIF) developed by Chavez et al. (1982) is used for selection of the optimum combination of bands. The OIF is calculated by dividing the sum of standard deviations of any three bands with the sum of their respective correlation coefficients (absolute values). It is assumed that the band with the higher standard deviation contains the higher amount of 'information' than other bands. Therefore, OIF values are ranked and three bands with the highest OIF are selected for the visual interpretation. A color composite image is created using these three bands. The water quality

  17. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, J.F.

    2014-01-01

    Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

  18. Two way satellite communication for telemetrology and remote control

    Science.gov (United States)

    Hanebrekke, H.

    Low-data-rate satellite communication to fixed and floating buoys at sea, remote observation stations, and fishing vessels is studied. Particular attention is paid to Norwegian conditions, that is, high latitude and high mountains. Coverage and reliability measurements utilizing Inmarsat C and Prodat stations have been done along the coast of western and northern Norway, and on major roads in southern Norway. Good coverage is found in the coastal areas, with only 5 percent loss of messages when both the AOR and IOR satellites are used from the same location, whereas the land mobile experiments gave 40 percent to 70 percent loss, depending on the elevation angle. The possibility of using Inmarsat C or Prodat stations in the major fishing areas between Norway, Greenland, and Svalbard and in the Barents Sea are also being investigated. A method of data collection from ocean areas based on the fishing fleet is proposed.

  19. Mapping land degradation and desertification using remote sensing data

    Science.gov (United States)

    Saha, S. K.; Kumar, Munish; Lal, Bhajan; Barman, Alok Kumar; Das, Satyendra Nath

    2006-12-01

    Land degradation is the result of both natural and biotic forces operating on the earth. Natural calamities, over exploitation of land resources, unwise land use and the consequences of high inputs agriculture on soil and water resource are of great concern both at national and international level. It aggravated food insecurity in the world especially in the developing countries that calls for combating land degradation and desertification with scientific means. Development of degraded lands in India is one of the options to enhance food production and to restore the fragile ecosystem. The scientific information and spatial distribution of various kinds of degraded lands is thus essential for formulation of strategic plan to arrest the menace of land degradation. Remote sensing provides an opportunity for rapid inventorying of degraded lands to generate realistic database by virtue of multi-spectral and multi-temporal capabilities in the country. The satellite data provides subtle manifestations of degradation of land due to water and wind erosion, water-logging, salinity and alkalinity, shifting cultivation, etc., that facilitate mapping. All India Soil and Land Use Survey (AISLUS) has undertaken the task of land degradation mapping using remotely sensed data and developed a methodology accordingly. The mapping has been conceptualized as a four-tier approach comprising kind of degradation, severity of degradation, degradation under major landform and major land use. Visual mode of interpretation technique based on image characteristics followed by ground verification has been employed for mapping of degraded lands. Image interpretation key has been formulated based on the spectral signatures of various causative factors of different kinds of degraded lands. The mapping legend has been made systematic and connotative. The extent and spatial distribution of different kinds of degraded lands with degree of severity under major landform and major land use in a

  20. Remote sensing for land management and planning

    Science.gov (United States)

    Woodcock, Curtis E.; Strahler, Alan H.; Franklin, Janet

    1983-05-01

    The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States. Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners. Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes

  1. A new digital land mobile satellite system

    Science.gov (United States)

    Schneider, Philip

    A description is given of the different digital services planned to be carried over existing and planned mobile satellite systems. These systems are then compared with analog services in terms of bandwidth and power efficiency. This comparison provides the rationale for the establishment of a digital land mobile satellite service (DLMSS) to use frequencies that are currently available but not yet assigned to a domestic mobile satellite system in the United States. The focus here is on the expected advantages of digital transmission techniques in accommodating additional mobile satellite systems in this portion of the spectrum, and how such techniques can fully satisfy voice, data and facsimile mobile communications requirements in a cost effective manner. A description is given of the system architecture of the DMLSS service proposed by the Geostar Messaging Corporation (GMC) and the market potential of DLMSS.

  2. LAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    P. Nalina

    2014-01-01

    Full Text Available Land use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. The Nilgiris district of Tamilnadu state in India is the first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by frequent landslides. Therefore in this present study land use land cover dynamics of Nilgiri district has been studied from 1990 to 2010 using Satellite Remote Sensing Technique. The temporal changes of land use and land cover changes of Nilgiris district over the period of 1990 to 2010 were monitored using LISS I and LISS III of IRS 1A and IRS-P6 satellites. Land use dynamics were identified using Maximum likelihood classification under supervised classification technique. From the remote sensing study, it is found that during the study period of 1990 to 2010, area of dense forest increased by 27.17%, forest plantation area decreased by 54.64%. Conversion of forest plantation, Range land and open forest by agriculture and settlement leading to soil erosion and landslides. Tea plantation increased by 33.95% and agricultural area for plantation of vegetables increased rapidly to 217.56% in the mountain steep area. The accuracy of classification has been assessed by forming confusion matrix and evaluating kappa coefficient. The overall accuracy has been obtained as 83.7 and 89.48% for the years 1990 and 2010 respectively. The kappa coefficients were reported as 0.80 and 0.88 respectively for the years 1990 and 2010.

  3. Satellite remote-sensing technologies used in forest fire management

    Institute of Scientific and Technical Information of China (English)

    TIAN Xiao-rui; Douglas J. Mcrae; SHU Li-fu; WANG Ming-yu; LI Hong

    2005-01-01

    Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.

  4. Enhancing the Applicability of Satellite Remote Sensing for PM2.5 Estimation Using MODIS Deep Blue AOD and Land Use Regression in California, United States.

    Science.gov (United States)

    Lee, Hyung Joo; Chatfield, Robert B; Strawa, Anthony W

    2016-06-21

    We estimated daily ground-level PM2.5 concentrations combining Collection 6 deep blue (DB) Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data (10 km resolution) with land use regression in California, United States, for the period 2006-2012. The Collection 6 DB method for AOD provided more reliable data retrievals over California's bright surface areas than previous data sets. Our DB AOD and PM2.5 data suggested that the PM2.5 predictability could be enhanced by temporally varying PM2.5 and AOD relations at least at a seasonal scale. In this study, we used a mixed effects model that allowed daily variations in DB AOD-PM2.5 relations. Because DB AOD might less effectively represent local source emissions compared to regional ones, we added geographic information system (GIS) predictors into the mixed effects model to further explain PM2.5 concentrations influenced by local sources. A cross validation (CV) mixed effects model revealed reasonably high predictive power for PM2.5 concentrations with R(2) = 0.66. The relations between DB AOD and PM2.5 considerably varied by day, and seasonally varying effects of GIS predictors on PM2.5 suggest season-specific source emissions and atmospheric conditions. This study indicates that DB AOD in combination with land use regression can be particularly useful to generate spatially resolved PM2.5 estimates. This may reduce exposure errors for health effect studies in California. We expect that more detailed PM2.5 concentration patterns can help air quality management plan to meet air quality standards more effectively.

  5. Satellite remote sensing of hailstorms in France

    Science.gov (United States)

    Melcón, Pablo; Merino, Andrés; Sánchez, José Luis; López, Laura; Hermida, Lucía

    2016-12-01

    Hailstorms are meteorological phenomena of great interest to the scientific community, owing to their socioeconomic impact, which is mainly on agricultural production. With its global coverage and high spatial and temporal resolution, satellite remote sensing can contribute to monitoring of such events through the development of appropriate techniques. This paper presents an extensive validation in the south of France of a hail detection tool (HDT) developed for the Middle Ebro Valley (MEV). The HDT is based on consecutive application of two filters, a convection mask (CM) and hail mask (HM), using spectral channels of the Meteosat Second Generation (MSG) satellite. The south of France is an ideal area for studying hailstorms, because there is a robust database of hail falls recorded by an extensive network of hailpads managed by the Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA). The results show noticeably poorer performance of the HDT in France relative to that in the MEV, with probability of detection (POD) 60.4% and false alarm rate (FAR) 26.6%. For this reason, a new tool to suit the characteristics of hailstorms in France has been developed. The France Hail Detection Tool (FHDT) was developed using logistic regression from channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor of the MSG. The FHDT was validated, resulting in POD 69.3% and FAR 15.4%, thus improving hail detection in the study area as compared with the previous tool. The new tool was tested in a case study with satisfactory results, supporting its future practical application.

  6. Commercialization of the land remote sensing system: An examination of mechanisms and issues

    Science.gov (United States)

    Cauley, J. K.; Gaelick, C.; Greenberg, J. S.; Logsdon, J.; Monk, T.

    1983-01-01

    In September 1982 the Secretary of Commerce was authorized (by Title II of H.R. 5890 of the 97th Congress) to plan and provide for the management and operation of the civil land remote sensing satellite systems, to provide for user fees, and to plan for the transfer of the ownership and operation of future civil operational land remote sensing satellite systems to the private sector. As part of the planning for transfer, a number of approaches were to be compared including wholly private ownership and operation of the system by an entity competitively selected, mixed government/private ownership and operation, and a legislatively-chartered privately-owned corporation. The results of an analysis and comparison of a limited number of financial and organizational approaches for either transfer of the ownership and operation of the civil operational land remote sensing program to the private sector or government retention are presented.

  7. 基于BJ -1小卫星遥感数据的矿区土地覆盖变化检测%Land Cover Change Detection in Coal Mining Area Using BJ -1 Small Satellite Remote Sensing Data

    Institute of Scientific and Technical Information of China (English)

    陈宇; 杜培军; 唐伟成; 柳思聪

    2011-01-01

    为了评价利用北京一号小卫星(BJ-I)遥感数据监测煤矿区土地利用/地表覆盖变化的效果,针对其数据特点,选择基于图像信息运算和图像信息变换的直接变化检洲法以及分类后比较法,对徐州东矿区2007~2008年土地利用/地表覆盖变化情况进行检测,以对比、评价各种方法在土地利用/地表覆盖变化检测中的应用效果和BJ -1数据的适用性:结果显示,变化矢量分析法的检测精度最高,其后依次为图像比值法、图像差值法和多波段主成分分析法.通过变化检测,确定徐州市东矿区土地利用/地表覆盖变化较为集中的几个区域,包括东矿区北部的青山泉矿、韩桥矿、董庄矿和南部的大黄山矿等地区.%In order to evaluate the performance of monitoring land cover change in mining areas by BJ - 1 small satellite remote sensing data, the authors made an experimental and comparative study of several change detection methods, with the east coal mining district of Xuzhou City in Jiangsu Province as the study area. Direct change detection methods based on image information operation and image information transformation as well as the post -classification comparison method were adopted in the experiment. The results show that the change vector analysis can attain the highest accuracy, followed by the method of image ratio method, image differencing and multi - band principal component analysis. Through the change detection process, several areas with great land cover change were detected, such as Qingshanquan, Hanqiao and Dongzhuang mining areas in northern east mining district and Dahuangshan mining area in southern east mining district.

  8. Determination of regional surface heat fluxes over heterogeneous landscapes by integrating satellite remote sensing with boundary layer observations

    NARCIS (Netherlands)

    Ma, Y.M.

    2006-01-01

    Keywords: satellite remote sensing, surface layer observations, atmospheric boundary layer observations, land surface variables, vegetation variables, land surface heat fluxes, validation, heterogeneous landscape, GAME/Tibet

  9. Using remote sensing imagery and GIS to identify land cover and land use within Ceahlau Massif (Romania

    Directory of Open Access Journals (Sweden)

    GEORGE CRACU

    2014-11-01

    Full Text Available Using remote sensing imagery and GIS to identify land cover and land use within Ceahlău Massif (Romania. In this study we considerer land cover and land use asessment within Ceahlău Massif (Romania using satellite imagery and GIS . To achieve this goal, we used a Landsat 7 ETM + satellite image, which was processed using specialized software in analyzing satellite images and GIS software in several stages:  Downloading, importing and layer stack of all spectral bands composing satellite image;  Establishment of areas of interest for each category of land cover and land use, which were digitized on - screen and for which spectral signatures characteristics were established;  Supervised image classification using Maximum Likelihood Method;  Importing the resulting m ap (raster in GIS environment and creating the final land cover/land use map for Ceahlău Massif. In the study area we identified nine land cover/land use classes: deciduous forests, mixed forests, coniferous forests, secondary grasslands, subalpine vegeta tion, alpine meadows, agricultural land, lakes and built area. By analizing the spatial distribution of these classes, it was found that forests are the best represented class, occupying an area of 188.4 km² (56.4% of total, followed by secondary grassl and, which occupies an area of 68.2 km² (20.4% of total, lakes (26.6 km² or 7.98% of total and agricultural land (16.1 km² or 4.86%

  10. Observations of land-atmosphere interactions using satellite data

    Science.gov (United States)

    Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

    2016-04-01

    Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of

  11. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  12. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

  13. Remote sensing of forest dynamics and land use in Amazonia

    Science.gov (United States)

    Toomey, Michael Paul

    The rich, vast Amazonian ecosystem is directly and indirectly threatened by human activities; remote sensing serves as an essential tool for monitoring, understanding and mitigating these threats. A multi-faceted body of work is described here, addressing three major issues that employ and advance remote sensing techniques for the study of Amazonia and other tropical rainforest regions. In Chapter 2, canopy reflectance modeling and satellite observations were used to quantify the effect of epiphylls on remote sensing of humid forests. Modeling simulations demonstrated sensitivity of canopy-level near infrared and green reflectance to epiphylls on leaves. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and vegetation indices which must be accounted for when using optical remote sensing in humid forests. In Chapter 4, 11 years (2000--2010) of MODIS land surface temperature (LST) data covering the entire Amazon basin were used to ascertain the role of heat stress during droughts in 2005 and 2010. Preliminary accuracy assessments showed that LST data provided reasonably accurate estimates of daytime air temperatures (RMSE = 1.45°C; Chapter 3). There were moderate to strong correlations between LST-based air temperature estimates and tower measurements (mean r = 0.64), illustrating a sensitivity to temporal variability. During both droughts, MODIS LST data detected anomalously high daytime and nighttime canopy temperatures throughout drought-affected regions. Multivariate linear models of LST and precipitation anomalies explained 65.1% of the variability in forest biomass losses, as determined from a wide network of forest inventory plots. These results suggest that models should incorporate both heat and moisture to predict drought effects on tropical forests. In Chapter 5, I performed high spatial and temporal resolution modeling of carbon stocks and fluxes

  14. The role of satellite remote sensing in REDD/MRV

    Science.gov (United States)

    Jonckheere, Inge; Sandoval, Alberto

    2010-05-01

    REDD, which stands for 'Reducing Emissions from Deforestation and Forest Degradation in Developing Countries' - is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. The UN-REDD Programme, a collaborative partnership between FAO, UNDP and UNEP launched in September 2008, supports countries to develop capacity to REDD and to implement a future REDD mechanism in a post- 2012 climate regime. The programme works at both the national and global scale, through support mechanisms for country-driven REDD strategies and international consensus-building on REDD processes. The UN-REDD Programme gathers technical teams from around the world to develop common approaches, analyses and guidelines on issues such as measurement, reporting and verification (MRV) of carbon emissions and flows, remote sensing, and greenhouse gas inventories. Within the partnership, FAO supports countries on technical issues related to forestry and the development of cost effective and credible MRV processes for emission reductions. While at the international level, it fosters improved guidance on MRV approaches, including consensus on principles and guidelines for MRV and training programmes.It provides guidance on how best to design and implement REDD, to ensure that forests continue to provide multiple benefits for livelihoods and biodiversity to societies while storing carbon at the same time. Other areas of work include national forest assessments and monitoring of in-country policy and institutional change. The outcomes about the role of satellite remote sensing technologies as a tool for monitoring, assessment, reporting and verification of carbon credits and co-benefits under the REDD mechanism are here presented.

  15. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  16. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  17. Satellite remote sensing for water erosion assessment: A review

    NARCIS (Netherlands)

    Vrieling, A.

    2006-01-01

    Water erosion creates negative impacts on agricultural production, infrastructure, and water quality across the world. Regional-scale water erosion assessment is important, but limited by data availability and quality. Satellite remote sensing can contribute through providing spatial data to such as

  18. Satellite remote sensing for water erosion assessment: A review

    NARCIS (Netherlands)

    Vrieling, A.

    2006-01-01

    Water erosion creates negative impacts on agricultural production, infrastructure, and water quality across the world. Regional-scale water erosion assessment is important, but limited by data availability and quality. Satellite remote sensing can contribute through providing spatial data to such

  19. Remote sensing place : Satellite images as visual spatial imaginaries

    NARCIS (Netherlands)

    Shim, David

    How do people come to know the world? How do they get a sense of place and space? Arguably, one of the ways in which they do this is through the practice of remote sensing, among which satellite imagery is one of the most widespread and potent tools of engaging, representing and constructing space.

  20. Land cover classification and economic assessment of citrus groves using remote sensing

    Science.gov (United States)

    Shrivastava, Rahul J.; Gebelein, Jennifer L.

    The citrus industry has the second largest impact on Florida's economy, following tourism. Estimation of citrus area coverage and annual forecasts of Florida's citrus production are currently dependent on labor-intensive interpretation of aerial photographs. Remotely sensed data from satellites has been widely applied in agricultural yield estimation and cropland management. Satellite data can potentially be obtained throughout the year, making it especially suitable for the detection of land cover change in agriculture and horticulture, plant health status, soil and moisture conditions, and effects of crop management practices. In this study, we analyzed land cover of citrus crops in Florida using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery from the University of Maryland Global Land Cover Facility (GLCF). We hypothesized that an interdisciplinary approach combining citrus production (economic) data with citrus land cover area per county would yield a correlation between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. While the data from official sources based on aerial photography were positively correlated, there were serious discrepancies between agriculture census data and satellite-derived cropland area using medium-resolution satellite imagery. If these discrepancies can be resolved by using imagery of higher spatial resolution, a stronger correlation would be observed for citrus production based on satellite data. This would allow us to predict the economic impact of citrus from satellite-derived spectral data analysis to determine final crop harvests.

  1. Satellite Remote Sensing in Offshore Wind Energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Astrup, Poul

    2013-01-01

    capacity is found in the European Seas. The European Wind Energy Association, EWEA, expects the cumulative offshore capacity in Europe will reach 150 GW in year 2030. The offshore environment is far less well-known than over land and this increases the challenge of planning, operation and maintenance...

  2. Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

    Science.gov (United States)

    Chen, Xuelong; Su, Bob

    2017-04-01

    Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

  3. Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

    Science.gov (United States)

    Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

    2014-01-01

    Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

  4. China Land Observation Satellite Third User Conference Promotes The Applications Of Domestic Satellite Data

    Institute of Scientific and Technical Information of China (English)

    Zong He

    2009-01-01

    @@ China Land Observation Satellite Third User Conference with the theme of "Strengthening cooperation,enlarging sharing and promoting the application of domestic satellite data" was held on July 16,2009 in Beijing. The conference was hosted by China Centre for Resources Satellite Data and Applications(CRESDA),a subsidiary of China Aerospace Science and Technology Corporation (CASC).

  5. Satellite remote sensing applications for surface soil moisture monitoring: A review

    Institute of Scientific and Technical Information of China (English)

    Lingli WANG; John J.QU

    2009-01-01

    Surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/ atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. Recent technological advances in satellite remote sensing have shown that soil moisture can be measured by a variety of remote sensing techniques,each with its own strengths and weaknesses. This paper presents a comprehensive review of the progress in remote sensing of soil moisture, with focus on technique approaches for soil moisture estimation from optical,thermal, passive microwave, and active microwave measurements. The physical principles and the status of current retrieval methods are summarized. Limitations existing in current soil moisture estimation algorithms and key issues that have to be addressed in the near future are also discussed.

  6. Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

    Science.gov (United States)

    Stow, D.A.; Hope, A.; McGuire, D.; Verbyla, D.; Gamon, J.; Huemmrich, F.; Houston, S.; Racine, C.; Sturm, M.; Tape, K.; Hinzman, L.; Yoshikawa, K.; Tweedie, C.; Noyle, B.; Silapaswan, C.; Douglas, D.; Griffith, B.; Jia, G.; Epstein, H.; Walker, D.; Daeschner, S.; Petersen, A.; Zhou, L.; Myneni, R.

    2004-01-01

    The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations. The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored. ?? 2003 Elsevier Inc. All rights reserved.

  7. Exploring Land use and Land cover change in the mining areas of Wa East District, Ghana using Satellite Imagery

    Science.gov (United States)

    Basommi, Prosper Laari; Guan, Qingfeng; Cheng, Dandan

    2015-11-01

    Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index valueswere used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

  8. Determination of Land Use from Satellite Imagery for Input to Hydrologic Models.

    Science.gov (United States)

    1980-04-01

    Symposium on Remote Sensing of thieK Environment, 23-30 April 1980, San Jose, Costa Rica 19. KEY WORDS - C=Wm*. eO I.W. EII..e.wvm I*FS Week atfm...Fourteenth International Symposium on Remote Sensing of the Environment, 23-30 April 1980, San Jose, Costa Rica DETERMINATION OF LAND USE FROM SATELLITE...Factors in Small Hydropower Planning, Darryl W. Davis, February 1979, 38 pages. #62 Flood Hydrograph and Peak Flow Frequency Analysis, Arlen D. Feldman

  9. Satellite remote sensing of surface energy balance: Success, failures, and unresolved issues in FIFE

    Science.gov (United States)

    Hall, Forrest G.; Huemmrich, Karl F.; Goetz, Scott J.; Sellers, Piers J.; Nickeson, Jaime E.

    1992-11-01

    The FIFE staff science group, consisting of the authors, developed and evaluated process models relating surface energy and mass flux, that is, surface rates, to boundary layer and surface biophysical characteristics, that is, surface states. In addition, we developed and evaluated remote sensing algorithms for inferring surface state characteristics. In this paper we report the results of our efforts. We also look in detail at the sensor and satellite platform requirements (spatial resolution and orbital requirements) as driven by surface energy balance dynamics and spatial variability. We examine also the scale invariance of the process models and remote sensing algorithms, that is, to what degree do the remotely sensed parameters and energy balance relations translate from the patch level where they were developed to the mesoscale level where they are required? Finally, we examine the atmospheric correction and calibration issues involved in extending the remotely sensed observations within a season and between years. From these investigations we conclude that (1) existing formulations for the radiation balance and latent heat components of the surface energy balance equation are valid at the patch level. (2) Many of the surface physiological characteristics that parameterize these formulations can be estimated using satellite remote sensing at both local and regional scales; a few important ones cannot. (3) The mathematical structures relating radiation and surface energy flux to remote sensing parameters are, for the most part, scale invariant over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) study area. The conditions for scale invariance are derived. (4) The precision of satellite remote sensing estimates of surface reflectance, calibrated and corrected for atmospheric effects, is no worse than about 1% absolute. The errors may actually be smaller, but an upper bound of 1% results from sampling variance

  10. Using remotely sensed data to estimate area-averaged daily surface fluxes over a semi-arid mixed agricultural land

    OpenAIRE

    2008-01-01

    Optical remote sensing has been widely used for diagnostics of land surface atmosphere exchanges, including evapotranspiration (ET). Estimating ET now benefits from modeling maturity at local scale, while ongoing challenges include both spatial and temporal issues: influences of spatial heterogeneities on non-linear behavior when upscaling and extrapolation of instantaneous estimates at satellite overpass to the daily scale. Both issues are very important when using remote sensing for managin...

  11. 基于High-1卫星影像的土地整治遥感监测方法研究与实践%Method and application of remote sensing monitoring in land consolidation based on High-1 satellite image

    Institute of Scientific and Technical Information of China (English)

    张兵; 崔希民; 赵彦博; 袁德宝

    2015-01-01

    -added roads and newly-dug ditches by using vector map, which is made after the land consolidation by project undertaker. Furthermore, from the specific monitoring instance of a land consolidation project along Han River i.e. South-to-North Water Transfer Project, by using the method introduced in this paper, we can find the monitoring ratio of newly increased farmlands is 88.40%, newly-added roads 97.34%, and newly-dug ditches 98.26% in the study area. After monitoring, the paper analyzed the causes of the differences of monitoring ratio between the 3, and especially explains the causes of the lower monitoring ratio of newly increased farmlands in details. They are as follows: first, part of newly-cultivated land is got by means of the landfill of ridges, roads and ditches; second, some project areas haven't made vector maps properly, and the layer names can't match the actual objects in the maps, which causes that the extracted information of new land isn't complete; third, the project undertaker cheats on the area of newly-cultivated land. From all above, we can draw a few conclusions. Firstly, High-1 remote satellite images have both panchromatic images of 2 m resolution and multi-spectral images of 8 m resolution, and after processing the images in the early stage, we have used the algorithm of Gram-Schmidt to fuse the 2 types of images and obtained ideal images in space and spectrum resolution, which can satisfy the requirements of monitoring results in land consolidation. Secondly, we have got the monitoring ratio of newly-cultivated land, new roads and new ditches from one project in the land consolidation along Han River. And the specific example shows that the technical methods in the paper are reasonable and effective. Finally, The ArcGIS software platform is used to process remote sensing images, vector maps of land consolidation results and other reference maps, so that different data from different sources can be unified to GIS. During the process of remote

  12. Remote sensing, land cover changes, and vector-borne diseases: use of high spatial resolution satellite imagery to map the risk of occurrence of cutaneous leishmaniasis in Ghardaïa, Algeria.

    Science.gov (United States)

    Garni, Rafik; Tran, Annelise; Guis, Hélène; Baldet, Thierry; Benallal, Kamel; Boubidi, Said; Harrat, Zoubir

    2014-12-01

    Ghardaïa, central Algeria, experienced a major outbreak of cutaneous leishmaniasis (CL) in 2005. Two Leishmania species occur in this region: Leishmania major (MON-25) and Leishmania killicki (MON-301). The two species are transmitted respectively by the sandflies Phlebotomus papatasi and Phlebotomus sergenti and probably involve rodent reservoirs with different ecologies, suggesting distinct epidemiological patterns and distribution areas. The aims of this study were to establish risk maps for each Leishmania species in Ghardaïa, taking into account the specificities of their vectors and reservoirs biotopes, using land cover and topographical characteristics derived from remote sensing imagery. Using expert and bibliographic knowledge, habitats of vectors and reservoirs were mapped. Hazard maps, defined as areas of presence of both vectors and reservoirs, were then combined with vulnerability maps, defined as areas with human presence, to map the risk of CL occurrence due to each species. The vector habitat maps and risk maps were validated using available entomological data and epidemiological data. The results showed that remote sensing analysis can be used to map and differentiate risk areas for the two species causing CL and identify palm groves and areas bordering the river crossing the city as areas at risk of CL due to L. major, whereas more limited rocky hills on the outskirts of the city are identified as areas at risk of CL due to L. killicki. In the current context of urban development in Ghardaïa, this study provides useful information for the local authorities on the respective risk areas for CL caused by both parasites, in order to take prevention and control measures to prevent future CL outbreaks.

  13. Land vehicle antennas for satellite mobile communications

    Science.gov (United States)

    Haddad, H. A.; Pieper, B. V.; Mckenna, D. B.

    1985-01-01

    The RF performance, size, pointing system, and cost were investigated concepts are: for a mechanically steered 1 x 4 tilted microstrip array, a mechanically steered fixed-beam conformal array, and an electronically steered conformal phased array. Emphasis is on the RF performance of the tilted 1 x 4 antenna array and methods for pointing the various antennas studied to a geosynchronous satellite. An updated version of satellite isolations in a two-satellite system is presented. Cost estimates for the antennas in quantities of 10,000 and 100,000 unites are summarized.

  14. Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

    Science.gov (United States)

    Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

    1993-01-01

    Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues

  15. Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2007-01-01

    Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

  16. Monitoring Land Use/Land Cover Changes in a River Basin due to Urbanization using Remote Sensing and GIS Approach

    Science.gov (United States)

    Shukla, S.; Khire, M. V.; Gedam, S. S.

    2014-11-01

    Faster pace of urbanization, industrialization, unplanned infrastructure developments and extensive agriculture result in the rapid changes in the Land Use/Land Cover (LU/LC) of the sub-tropical river basins. Study of LU/LC transformations in a river basin is crucial for vulnerability assessment and proper management of the natural resources of a river basin. Remote sensing technology is very promising in mapping the LU/LC distribution of a large region on different spatio-temporal scales. The present study is intended to understand the LU/LC changes in the Upper Bhima river basin due to urbanization using modern geospatial techniques such as remote sensing and GIS. In this study, the Upper Bhima river basin is divided into three adjacent sub-basins: Mula-Mutha sub-basin (ubanized), Bhima sub-basin (semi-urbanized) and Ghod sub-basin (unurbanized). Time series LU/LC maps were prepared for the study area for a period of 1980, 2002 and 2009 using satellite datasets viz. Landsat MSS (October, 1980), Landsat ETM+ (October, 2002) and IRS LISS III (October 2008 and November 2009). All the satellite images were classified into five LU/LC classes viz. built-up lands, agricultural lands, waterbodies, forests and wastelands using supervised classification approach. Post classification change detection method was used to understand the LU/LC changes in the study area. Results reveal that built up lands, waterbodies and agricultural lands are increasing in all the three sub-basins of the study area at the cost of decreasing forests and wastelands. But the change is more drastic in urbanized Mula-Mutha sub-basin compared to the other two sub-basins.

  17. Application of satellite microwave remote sensed brightness temperature in the regional soil moisture simulation

    Directory of Open Access Journals (Sweden)

    X. K. Shi

    2009-02-01

    Full Text Available As the satellite microwave remote sensed brightness temperature is sensitive to land surface soil moisture (SM and SM is a basic output variable in model simulation, it is of great significance to use the brightness temperature data to improve SM numerical simulation. In this paper, the theory developed by Yan et al. (2004 about the relationship between satellite microwave remote sensing polarization index and SM was used to estimate the land surface SM from AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System brightness temperature data. With consideration of land surface soil texture, surface roughness, vegetation optical thickness, and the AMSR-E monthly SM products, the regional daily land surface SM was estimated over the eastern part of the Qinghai-Tibet Plateau. The results show that the estimated SM is lower than the ground measurements and the NCEP (American National Centers for Environmental Prediction reanalysis data at the Maqu Station (33.85° N, 102.57° E and the Tanglha Station (33.07° N, 91.94° E, but its regional distribution is reasonable and somewhat better than that from the daily AMSR-E SM product, and its temporal variation shows a quick response to the ground daily precipitations. Furthermore, in order to improve the simulating ability of the WRF (Weather Research and Forecasting model to land surface SM, the estimated SM was assimilated into the Noah land surface model by the Newtonian relaxation (NR method. The results indicate that, by fine tuning of the quality factor in NR method, the simulated SM values are improved most in desert area, followed by grassland, shrub and grass mixed zone. At temporal scale, Root Mean Square Error (RMSE values between simulated and observed SM are decreased 0.03 and 0.07 m3/m3 by using the NR method in the Maqu Station and the Tanglha Station, respectively.

  18. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  19. Heavy rainfall prediction applying satellite-based cloud data assimilation over land

    Science.gov (United States)

    Seto, Rie; Koike, Toshio; Rasmy, Mohamed

    2016-08-01

    To optimize flood management, it is crucial to determine whether rain will fall within a river basin. This requires very fine precision in prediction of rainfall areas. Cloud data assimilation has great potential to improve the prediction of precipitation area because it can directly obtain information on locations of rain systems. Clouds can be observed globally by satellite-based microwave remote sensing. Microwave observation also includes information of latent heat and water vapor associated with cloud amount, which enables the assimilation of not only cloud itself but also the cloud-affected atmosphere. However, it is difficult to observe clouds over land using satellite microwave remote sensing, because their emissivity is much lower than that of the land surface. To overcome this challenge, we need appropriate representation of heterogeneous land emissivity. We developed a coupled atmosphere and land data assimilation system with the Weather Research and Forecasting Model (CALDAS-WRF), which can assimilate soil moisture, vertically integrated cloud water content over land, and heat and moisture within clouds simultaneously. We applied this system to heavy rain events in Japan. Results show that the system effectively assimilated cloud signals and produced very accurate cloud and precipitation distributions. The system also accurately formed a consistent atmospheric field around the cloud. Precipitation intensity was also substantially improved by appropriately representing the local atmospheric field. Furthermore, combination of the method and operationally analyzed dynamical and moisture fields improved prediction of precipitation duration. The results demonstrate the method's promise in dramatically improving predictions of heavy rain and consequent flooding.

  20. Land Mobile Satellite Service (LMSS): A conceptual system design and identification of the critical technologies. Part 1: Executive summary

    Science.gov (United States)

    Naderi, F. (Editor)

    1982-01-01

    A system design for a satellite aided land mobile service is described. The advanced system is based on a geostationary satellite which employs a large UHF reflector to communicate with small user antennas on mobile vehicles. It is shown that the system through multiple beam antennas and frequency reuse provides for radiotelephone and dispatch channels. It is concluded that the system is technologically feasible to provide service to rural and remote regions.

  1. Discovery of Remote Globular Cluster Satellites of M87

    Science.gov (United States)

    Sparkman, Lea; Guo, Rachel; Toloba, Elisa; Guhathakurta, Puragra; Peng, Eric W.; Ferrarese, Laura; Cote, Patrick; NGVS Collaboration

    2016-01-01

    We present the discovery of several tens of globular clusters (GCs) in the outer regions of the giant elliptical M87, the brightest galaxy in the Virgo Cluster. These M87 GC satellites were discovered in the course of Keck/DEIMOS spectroscopic follow up of GC candidates that were identified in the Next Generation Virgo cluster Survey (NGVS). Specifically, the primary targets of this Keck spectroscopic campaign were GC satellites of early-type dwarf (dE) galaxies. However, we found that our sample contained a subset of GCs for which M87 is the most likely host. This subset is consistent with having an r^-1 power-law surface density distribution and a radial velocity distribution both centered on M87. The remote M87 GC satellites span the radial range 140 to 900 kpc, out to about a third of the Virgo Cluster's virial radius (for comparison, M87's effective radius is only 8 kpc). These M87 GC satellites are probably former satellites of other Virgo Cluster galaxies that have subsequently been cannibalized by M87.This research was supported by the National Science Foundation and the UC Santa Cruz Science Internship Program.

  2. Using satellite data to monitor land-use land-cover change in North-eastern Latvia.

    Science.gov (United States)

    Fonji, Simon Foteck; Taff, Gregory N

    2014-01-01

    Land-use and land-cover change (LULCC), especially those caused by human activities, is one of the most important components of global environmental change (Jessen 3(rd) edition: 1-526 2005). In this study the effects of geographic and demographic factors on LULCC are analyzed in northeastern Latvia using official estimates from census and vital statistics data, and using remotely sensed satellite imagery (Landsat Thematic Mapper) acquired from 1992 and 2007. The remote sensing images, elevation data, in-situ ground truth and ground control data (using GPS), census and vital statistics data were processed, integrated, and analyzed in a geographic information system (GIS). Changes in six categories of land-use and land-cover (wetland, water, agriculture, forest, bare field and urban/suburban) were studied to determine their relationship to demographic and geographic factors between 1992 and 2007. Supervised classifications were performed on the Landsat images. Analysis of land cover change based on "change-to" categories between the 1992 and 2007 images revealed that changes to forest were the most common type of change (17.1% of pixels), followed by changes to agriculture (8.6%) and the fewest were changes to urban/suburban (0.8%). Integration of population data and land-cover change data revealed key findings: areas near to roads underwent more LULCC and areas far away from Riga underwent less LULCC. Range in elevation was positively correlated with all LULCC categories. Population density was found to be associated with most LULCC categories but the direction of effect was scale dependent. This paper shows how socio-demographic data can be integrated with satellite image data and cartographic data to analyze drivers of LULCC at multiple spatial scales.

  3. Urban Land Use Change Detection Using Multisensor Satellite Images

    Institute of Scientific and Technical Information of China (English)

    DENG Jin-Song; WANG Ke; LI Jun; DENG Yan-Hua

    2009-01-01

    Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multiseusor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 muttispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into bnilt-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.

  4. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

  5. Analysis of Spatio-Temporal Changes of Land Usein Xuzhou City Based on Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-ling; DU Pei-jun; GUO Da-zhi

    2006-01-01

    Based on the satellite remote sensing TM/ETM images of Xuzhou city, basic data about land use of the city from 1994 to 2000 are obtained with the neural network classification module of PCI software, and the dynamic conversion matrix of land use is thus calculated. The areas of construction land and water body have increased by 1833.93hm2 and 804.87 hm2, respectively. On the contrary, the area of cropland has decreased by 3207.24 hm2. The area of cropland converted into construction land makes up 26.84%, and that converted into water body amounts for 8.17% of the total area of cropland in 1994. The variation index of land use degree and the dynamic degree index of land use computed are 1.38 and 57.81%, respectively, which demonstrate that land use in Xuzhou is in a development period and the changes are drastic. The frequency index and importance index of the form in which cropland converted into construction land are 29.91% and 68.93% respectively. The results indicate that the change is not only widespread in space but a major form of spatial change of land use in the area.

  6. Land mobile satellite propagation measurements in Japan using ETS-V satellite

    Science.gov (United States)

    Obara, Noriaki; Tanaka, Kenji; Yamamoto, Shin-Ichi; Wakana, Hiromitsu

    1993-01-01

    Propagation characteristics of land mobile satellite communications channels have been investigated actively in recent years. Information of propagation characteristics associated with multipath fading and shadowing is required to design commercial land mobile satellite communications systems, including protocol and error correction method. CRL (Communications Research Laboratory) has carried out propagation measurements using the Engineering Test Satellite-V (ETS-V) at L band (1.5 GHz) through main roads in Japan by a medium gain antenna with an autotracking capability. This paper presents the propagation statistics obtained in this campaign.

  7. Research on Differential Coding Method for Satellite Remote Sensing Data Compression

    Science.gov (United States)

    Lin, Z. J.; Yao, N.; Deng, B.; Wang, C. Z.; Wang, J. H.

    2012-07-01

    Data compression, in the process of Satellite Earth data transmission, is of great concern to improve the efficiency of data transmission. Information amounts inherent to remote sensing images provide a foundation for data compression in terms of information theory. In particular, distinct degrees of uncertainty inherent to distinct land covers result in the different information amounts. This paper first proposes a lossless differential encoding method to improve compression rates. Then a district forecast differential encoding method is proposed to further improve the compression rates. Considering the stereo measurements in modern photogrammetry are basically accomplished by means of automatic stereo image matching, an edge protection operator is finally utilized to appropriately filter out high frequency noises which could help magnify the signals and further improve the compression rates. The three steps were applied to a Landsat TM multispectral image and a set of SPOT-5 panchromatic images of four typical land cover types (i.e., urban areas, farm lands, mountain areas and water bodies). Results revealed that the average code lengths obtained by the differential encoding method, compared with Huffman encoding, were more close to the information amounts inherent to remote sensing images. And the compression rates were improved to some extent. Furthermore, the compression rates of the four land cover images obtained by the district forecast differential encoding method were nearly doubled. As for the images with the edge features preserved, the compression rates are average four times as large as those of the original images.

  8. Remote atomic clock synchronization via satellites and optical fibers

    CERN Document Server

    Piester, D; Fujieda, M; Feldmann, T; Bauch, A

    2011-01-01

    In the global network of institutions engaged with the realization of International Atomic Time (TAI), atomic clocks and time scales are compared by means of the Global Positioning System (GPS) and by employing telecommunication satellites for two-way satellite time and frequency transfer (TWSTFT). The frequencies of the state-of-the-art primary caesium fountain clocks can be compared at the level of 10e-15 (relative, 1 day averaging) and time scales can be synchronized with an uncertainty of one nanosecond. Future improvements of worldwide clock comparisons will require also an improvement of the local signal distribution systems. For example, the future ACES (atomic clock ensemble in space) mission shall demonstrate remote time scale comparisons at the uncertainty level of 100 ps. To ensure that the ACES ground instrument will be synchronized to the local time scale at PTB without a significant uncertainty contribution, we have developed a means for calibrated clock comparisons through optical fibers. An un...

  9. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  10. Measuring thermal budgets of active volcanoes by satellite remote sensing

    Science.gov (United States)

    Glaze, L.; Francis, P. W.; Rothery, D. A.

    1989-01-01

    Thematic Mapper measurements of the total radiant energy flux Q at Lascar volcano in north Chile for December 1984 are reported. The results are consistent with the earlier suggestion that a lava lake is the source of a reported thermal budget anomaly, and with values for 1985-1986 that are much lower, suggesting that fumarolic activity was then a more likely heat source. The results show that satellite remote sensing may be used to monitor the activity of a volcano quantitatively, in a way not possible by conventional ground studies, and may provide a method for predicting eruptions.

  11. An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2006-01-01

    Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

  12. Classification of forest land attributes using multi-source remotely sensed data

    Science.gov (United States)

    Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

    2016-02-01

    The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

  13. Satellite Data for All? Review of Google Earth Engine for Archaeological Remote Sensing

    Directory of Open Access Journals (Sweden)

    Omar A. Alcover Firpi

    2016-11-01

    Full Text Available A review of Google Earth Engine for archaeological remote sensing using satellite data. GEE is a freely accessible software option for processing remotely sensed data, part of the larger Google suite of products.

  14. Land mobile satellite services in Europe

    Science.gov (United States)

    Bartholome, P.; Rogard, R.; Berretta, G.

    1988-10-01

    The potential role of satellite communication as a complement to the pan-European cellular telephone network being developed to replace the current national or regional networks in the mid 1990s is discussed. The design concept and capabilities of the all-digital cellular network are reviewed; the requirements not covered by the network are listed; market-survey results indicating business interest in these additional services are summarized; and particular attention is given to the ESA demonstration system PRODAT. PRODAT uses the Marecs satellite to provide low-rate two-way data transmission for mobile terminals; the CDMA technique is used for the return links from mobile unit to hub station.

  15. Visual interpretation of ASTER satellite data, Part II: Land use mapping in Mpumalanga,South Africa

    Directory of Open Access Journals (Sweden)

    Elna van Niekerk

    2007-09-01

    Full Text Available Since the initiation in 1960 of the era of satellite remote sensing to detect the different characteristics of the earth, a powerful tool was created to aid researchers. Many land-use studies were undertaken using Landsat MSS, Landsat TM and ETM, as well as SPOT satellite data. The application of these data to the mapping of land use and land cover at smaller scales was constrained by the limited spectral and/or spatial resolution of the data provided by these satellite sensors. In view of the relatively high cost of SPOT data, and uncertainty regarding the future continuation of the Landsat series, alternative data sources need to be investigated. In the absence of published previous research on this issue in South Africa, the purpose of this article is to investigate the value of visual interpretation of ASTER satellite images for the identification and mapping of land-use in an area in South Africa. The study area is situated in Mpumalanga, in the area of Witbank, around the Witbank and Doorndraai dams. This area is characterised by a variety of urban, rural and industrial land uses. Digital image processing of one Landsat 5 TM, one Landsat 7 ETM and one ASTER satellite image was undertaken, including atmospheric correction and georeferencing, natural colour composites, photo infrared colour composites (or false colour satellite images, band ratios, Normalised Difference Indices, as well as the Brightness, Greenness and Wetness Indices. The efficacy with which land use could be identified through the visual interpretation of the processed Landsat 5 TM, Landsat 7 TM and ASTER satellite images was compared. The published 1:50 000 topographical maps of the area were used for the purpose of initial verification. Findings of the visual interpretation process were verified by field visits to the study area. The study found that the ASTER satellite data produced clearer results and therefore have a higher mapping ability and capacity than the

  16. The future of satellite remote sensing: A worldwide assessment and prediction

    Science.gov (United States)

    Spann, G. W.

    1984-01-01

    A frame-work in which to assess and predict the future prospects for satellite remote sensing markets is provided. The scope of the analysis is the satellite-related market for data, equipment, and services. It encompasses both domestic and international markets and contains an examination of the various market characteristics by market segment (e.g., Federal Government, State and Local Governments, Academic Organizations, Industrial Companies, and Individuals) and primary applications areas (e.g., Geology, Forestry, Land Resource Management, Agriculture and Cartography). The forecasts are derived from an analysis of both U.S. and foreign market data. The evolution and current status of U.S. and Foreign markets to arrive at market growth rates is evaluated. Circumstances and events which are likely to affect the future market development are examined. A market growth scenario is presented that is consistent with past data sales trends and takes into account the dynamic nature of the future satellite remote sensing market. Several areas of current and future business opportunities available in this market are discussed. Specific worldwide forecasts are presented in three market sectors for the period 1980 to 1990.

  17. Satellite remote sensing for urban growth assessment in Shaoxing City, Zhejiang Province

    Institute of Scientific and Technical Information of China (English)

    RAMADAN Elnazir; FENG Xue-zhi (冯学智); CHENG Zheng (程征)

    2004-01-01

    Urban growth represents specific response to economic, demographic and environmental conditions. Rapid urbanization and industrializations have resulted in sharp land cover changes. The present investigation was carried out from Shaoxing City to quantify satellite-derived estimates of urban growth using a three-epoch time series Landsat TM data for the years 1984, 1997 and ETM 2000. The methodology used was based on post classification comparison. The use of GIS allowed spatial analysis of the data derived from remotely sensed images. Results showed that the built-up area surrounding Shaoxing City has expanded at an annual average of 7 km2. Analysis of the classified map showed that the physical growth of urban area is upsetting the other land cover classes such as farming, water resources, etc. The study conclusion mainly emphasized the need for sustainable urban capacity.

  18. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  19. Determination of atmospheric aerosol properties over land using satellite measurements

    NARCIS (Netherlands)

    Kokhanovsky, A.A.; Leeuw, G. de

    2009-01-01

    Mostly, aerosol properties are poorly understood because the aerosol properties are very sparse. The first workshop on the determination of atmospheric aerosol properties over land using satellite measurements is convened in Bremen, Germany. In this workshop, the topics of discussions included a var

  20. Polarimetric remote sensing of the Earth from satellites: a perspective

    Science.gov (United States)

    Mishchenko, M. I.; Glory APS Science Team

    2011-12-01

    attempt to launch a more accurate aerosol-cloud polarimeter, called APS, as part of the NASA Glory Mission failed on 4 March 2011. However, much useful information has been obtained with the air-borne version of APS called RSP. In this talk I will briefly summarize the main results obtained with POLDER and RSP and discuss the prospects of polarimetric remote sensing from Earth-orbiting satellites.

  1. Research on Coal Exploration Technology Based on Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xiao

    2016-01-01

    Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.

  2. Spatio-temporal analysis of changes in land use through remotely sensed imagery

    Science.gov (United States)

    Rodríguez-Galiano, Víctor; Chica-Olmo, Mario; Garcia-Soldado, Maria José

    Over the last decades Spanish rural and littoral areas have undergone a significant transformation. This process, affecting the use of land mainly, is even more obvious in periurban areas. It is along these areas where the process of urban expansion makes it difficult to combine the use of land in these regions, which, being basically agricultural in nature, become deeply influenced by neighbouring urban spaces. Remote sensing appears as an invaluable resource in this context of territory transformation processes. Monitoring techniques based on multispectral satellite-acquired data have demonstrated potential as a means to detect, identify, and map changes in land use. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) data in the are of Granada for 1998 and 2002. Various types of techniques have been used, both quantitative and of image comparison: difference between images, multitemporal quotients, main component analysis (MCA), multitemporal vectors, and multitemporal analysis of classified images. The results quantify the land cover change patterns in the metropolitan area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.

  3. Polarimetric Remote Sensing of Aerosols over Land

    Energy Technology Data Exchange (ETDEWEB)

    Waquet, F.; Cairns, Brian; Knobelspiesse, Kirk D.; Chowdhary, J.; Travis, Larry D.; Schmid, Beat; Mishchenko, M.

    2009-01-26

    The sensitivity of accurate polarized reflectance measurements over a broad spectral (410 -2250 nm) and angular (±60° from nadir) range to the presence of aerosols over land is analyzed and the consequent ability to retrieve the aerosol burden and microphysical model is assessed. Here we present a new approach to the correction of polarization observations for the effects of the surface that uses longer wavelength observations to provide a direct estimate of the surface polarized reflectance. This approach to surface modeling is incorporated into an optimal estimation framework for retrieving the particle number density and a detailed aerosol microphysical model: effective radius, effective variance and complex refractive index of aerosols. A sensitivity analysis shows that the uncertainties in aerosol optical thickness (AOT) increase with AOT while the uncertainties in the microphysical model decrease. Of particular note is that the uncertainty in the single scattering albedo is less than 0.05 by the time the AOT is greater than 0.2. We also find that calibration is the major source of uncertainty and that perfect angular and spectral correlation of calibration errors reduces the uncertainties in retrieved quantities compared with the case of uncorrelated errors. Finally, in terms of required spectral range, we observe that shorter wavelength (< 500 nm) observations are crucial for determining the vertical extent and imaginary refractive index of aerosols from polarized reflectance observations. The optimal estimation scheme is then tested on observations made by the Research Scanning Polarimeter during the Aerosol Lidar Validation experiment and over Southern California wild fires. These two sets of observations test the retrieval scheme under pristine and polluted conditions respectively. In both cases we find that the retrievals are within the combined uncertainties of the retrieval and the Aerosol Robotic Network Cimel products and Total Ozone Mapping

  4. Laser remote sensing calibration of ocean color satellite data

    Directory of Open Access Journals (Sweden)

    N. V. Kolodnikova

    2006-06-01

    Full Text Available world ocean: in fact, those processes dramatically affect the climatic equilibrium of our planet. For this reason, many advanced active and passive remote sensors have been used to study phytoplankton dynamics, since such phenomena are thought to be responsible for the sequestration of atmospheric carbon dioxide, one of the most important greenhouse gases. In this paper, one laser system and three satellite radiometers routinely used for the study of the phytoplankton dynamics will be briefly reviewed. Satellite sensors have been preferred to airborne sensors because, to our knowledge, ocean color airborne radiometers have not been operated in Antarctica, at least not throughout the whole lapse of time examined in this study. Particular focus was on the laser system (ELF and on a specific satellite radiometer (SeaWiFS. ELF is based on the laser-induced fluorescence of phytoplankton pigments and was conceived for the Italian expeditions to Antarctica. The goal of SeaWiFS is to provide the Earth science community with quantitative data on the global ocean bio-optical properties. Such satellite radiometer has been calibrated with in situ data mainly acquired in non polar regions. This is why a comparison between ELF and SeaWiFS measurements of chlorophyll-a surface concentrations in the Southern Ocean during the austral summer 1997-1998 was believed to be significant. Our results indicate that SeaWiFS overestimates high concentrations and underestimates low concentrations. In order to correct this behavior, the chlorophyll- a bio-optical algorithm of SeaWiFS has been recalibrated according to the measurements of ELF, thus providing a new estimation of the primary production in the Southern Ocean.

  5. Implementation of space satellite remote sensing programs in developing countries (Ecuador)

    Science.gov (United States)

    Segovia, A.

    1982-01-01

    The current state of space satellite remote sensing programs in developing countries is discussed. Sensors being utilized and results obtained are described. Requirements are presented for the research of resources in developing countries. It is recommended that a work procedure be developed for the use of satellite remote sensing data tailored to the necessities of the different countries.

  6. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  7. Aircraft and satellite remote sensing of desert soils and landscapes

    Science.gov (United States)

    Petersen, G. W.; Connors, K. F.; Miller, D. A.; Day, R. L.; Gardner, T. W.

    1987-01-01

    Remote sensing data on desert soils and landscapes, obtained by the Landsat TM, Heat Capacity Mapping Mission (HCMM), Simulated SPOT, and Thermal IR Multispectral Scanner (TIMS) aboard an aircraft, are discussed together with the analytical techniques used in the studies. The TM data for southwestern Nevada were used to discriminate among the alluvial fan deposits with different degrees of desert pavement and varnish, and different vegetation cover. Thermal-IR data acquired from the HCMM satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures in central Utah. Simulated SPOT data for northwestern New Mexico identified geomorphic features, such as differences in eolian sand cover and fluvial incision, while the TIMS data depicted surface geologic features of the Saline Valley in California.

  8. Remote Synchronization Experiments for Quasi-Senith Satellite System Using Current Geostationary Satellites

    Directory of Open Access Journals (Sweden)

    Toshiaki Iwata

    2010-01-01

    Full Text Available The remote synchronization system for the onboard crystal oscillator (RESSOX realizes accurate synchronization between an atomic clock at a ground station and the QZSS onboard crystal oscillator, reduces overall cost and satellite power consumption, as well as onboard weight and volume, and is expected to have a longer lifetime than a system with onboard atomic clocks. Since a QZSS does not yet exist, we have been conducting synchronization experiments using geostationary earth orbit satellites (JCSAT-1B or Intelsat-4 to confirm that RESSOX is an excellent system for timing synchronization. JCSAT-1B, the elevation angle of which is 46.5 degrees at our institute, is little affected by tropospheric delay, whereas Intelsat-4, the elevation angle of which is 7.9 degrees, is significantly affected. The experimental setup and the results of uplink experiments and feedback experiments using mainly Intelsat-4 are presented. The results show that synchronization within 10 ns is realized.

  9. Study of Remote Globular Cluster Satellites of M87

    Science.gov (United States)

    Sahai, Arushi; Shao, Andrew; Toloba, Elisa; Guhathakurta, Puragra; Peng, Eric W.; Zhang, Hao

    2017-01-01

    We present a sample of “orphan” globular clusters (GCs) with previously unknown parent galaxies, which we determine to be remote satellites of M87, a massive elliptical galaxy at the center of the Virgo Cluster of Galaxies. Because GCs were formed in the early universe along with their original parent galaxies, which were cannibalized by massive galaxies such as M87, they share similar age and chemical properties. In this study, we first confirm that M87 is the adoptive parent galaxy of our orphan GCs using photometric and spectroscopic data to analyze spatial and velocity distributions. Next, we increase the signal-to-noise ratio of our samples’ spectra through a process known as coaddition. We utilize spectroscopic absorption lines to determine the age and metallicity of our orphan GCs through comparison to stellar population synthesis models, which we then relate to the GCs’ original parent galaxies using a mass-metallicity relation. Our finding that remote GCs of M87 likely developed in galaxies with ~1010 solar masses implies that M87’s outer halo is formed of relatively massive galaxies, serving as important parameters for developing theories about the formation and evolution of massive galaxies.This research was funded in part by NASA/STScI and the National Science Foundation. Most of this work was carried out by high school students working under the auspices of the Science Internship Program at UC Santa Cruz.

  10. Hierarchical resource analysis for land use planning through remote sensing

    Science.gov (United States)

    Byrnes, B. H.; Frazee, C. J.; Cox, T. L.

    1976-01-01

    A hierarchical resource analysis was applied to remote sensing data to provide maps at Planning Levels I and III (Anderson et al., U.S. Geological Survey Circular 671) for Meade County, S. Dak. Level I land use and general soil maps were prepared by visual interpretation of imagery from a false color composite of Landsat MSS bands 4, 5, and 7 and single bands (5 and 7). A modified Level III land use map was prepared for the Black Hills area from RB-57 photography enlarged to a scale of 1:24,000. Level III land use data were used together with computer-generated interpretive soil maps to analyze relationships between developed and developing areas and soil criteria.

  11. The experience of land cover change detection by satellite data

    Institute of Scientific and Technical Information of China (English)

    Lev SPIVAK; Irina VITKOVSKAYA; Madina BATYRBAYEVA; Alexey TEREKHOV

    2012-01-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan.As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan.The major process of desertification takes place in the arid and semi-arid areas.To allocate spots of stable degradation of vegetation,the transition zone was first identified.Productivity of vegetation in transfer zone is slightly dependent on climate conditions.Multi-year digital maps of vegetation index were generated with NOAA satellite images.According to the result,the territory of the republic was zoned by means of vegetation productivity criterion.All the arable lands in Kazakhstan are in the risky agriculture zone.Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture,where natural factors,such as wind and water erosion,can significantly change land quality in a relatively short time period.We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from lowresolution satellite data for all of Kazakhstan.This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  12. Modelling the water balance of a mesoscale catchment basin using remotely sensed land cover data

    Science.gov (United States)

    Montzka, Carsten; Canty, Morton; Kunkel, Ralf; Menz, Gunter; Vereecken, Harry; Wendland, Frank

    2008-05-01

    SummaryHydrological modelling of mesoscale catchments is often adversely affected by a lack of adequate information about specific site conditions. In particular, digital land cover data are available from data sets which were acquired on a European or a national scale. These data sets do not only exhibit a restricted spatial resolution but also a differentiation of crops and impervious areas which is not appropriate to the needs of mesoscale hydrological models. In this paper, the impact of remote sensing data on the reliability of a water balance model is investigated and compared to model results determined on the basis of CORINE (Coordination of Information on the Environment) Land Cover as a reference. The aim is to quantify the improved model performance achieved by an enhanced land cover representation and corresponding model modifications. Making use of medium resolution satellite imagery from SPOT, LANDSAT ETM+ and ASTER, detailed information on land cover, especially agricultural crops and impervious surfaces, was extracted over a 5-year period (2000-2004). Crop-specific evapotranspiration coefficients were derived by using remote sensing data to replace grass reference evapotranspiration necessitated by the use of CORINE land cover for rural areas. For regions classified as settlement or industrial areas, degrees of imperviousness were derived. The data were incorporated into the hydrological model GROWA (large-scale water balance model), which uses an empirical approach combining distributed meteorological data with distributed site parameters to calculate the annual runoff components. Using satellite imagery in combination with runoff data from gauging stations for the years 2000-2004, the actual evapotranspiration calculation in GROWA was methodologically extended by including empirical crop coefficients for actual evapotranspiration calculations. While GROWA originally treated agricultural areas as homogeneous, now a consideration and differentiation

  13. Detecting land use changes affected by human activities using remote sensing (Case study: Karkheh River Basin

    Directory of Open Access Journals (Sweden)

    Saeid Maddah

    2015-08-01

    Full Text Available Population growth and abundant activities in order to achieve maximum well-being has forced human to make a lot of changes in the nature. These changes will be cost-effective when they have the minimum damage on the landscape. One of the activities that human did for obtaining the water and preventing flood was making the dam in the track of running water. Since the dam is established until its impoundment and after impoundment, the condition of ecosystem and the appearance of the upstream and downstream of the dam will undergo changes. In this study, using satellite data and remote sensing, these changes have been studied and the landuse changes in vegetation, arid land, water level and residential and non-residential lands is measured in 1998 and 2014 using Maximum Likelihood method and support vector machine.

  14. The long-term Global LAnd Surface Satellite (GLASS) product suite and applications

    Science.gov (United States)

    Liang, S.

    2015-12-01

    Our Earth's environment is experiencing rapid changes due to natural variability and human activities. To monitor, understand and predict environment changes to meet the economic, social and environmental needs, use of long-term high-quality satellite data products is critical. The Global LAnd Surface Satellite (GLASS) product suite, generated at Beijing Normal University, currently includes 12 products, including leaf area index (LAI), broadband shortwave albedo, broadband longwave emissivity, downwelling shortwave radiation and photosynthetically active radiation, land surface skin temperature, longwave net radiation, daytime all-wave net radiation, fraction of absorbed photosynetically active radiation absorbed by green vegetation (FAPAR), fraction of green vegetation coverage, gross primary productivity (GPP), and evapotranspiration (ET). Most products span from 1981-2014. The algorithms for producing these products have been published in the top remote sensing related journals and books. More and more applications have being reported in the scientific literature. The GLASS products are freely available at the Center for Global Change Data Processing and Analysis of Beijing Normal University (http://www.bnu-datacenter.com/), and the University of Maryland Global Land Cover Facility (http://glcf.umd.edu). After briefly introducing the basic characteristics of GLASS products, we will present some applications on the long-term environmental changes detected from GLASS products at both global and local scales. Detailed analysis of regional hotspots, such as Greenland, Tibetan plateau, and northern China, will be emphasized, where environmental changes have been mainly associated with climate warming, drought, land-atmosphere interactions, and human activities.

  15. Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa; Reichl, Rolf; Harrison, Kenneth; Santanello, Joseph

    2010-01-01

    Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

  16. Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture

    Directory of Open Access Journals (Sweden)

    Alejandro Egido

    2012-08-01

    Full Text Available The use of Global Navigation Satellite Systems (GNSS signals for remote sensing applications, generally referred to as GNSS-Reflectometry (GNSS-R, is gaining increasing interest among the scientific community as a remote sensing tool for land applications. This paper describes a long term experimental campaign in which an extensive dataset of GNSS-R polarimetric measurements was acquired over a crop field from a ground-based stationary platform. Ground truth ancillary data were also continuously recorded during the whole experimental campaign. The duration of the campaign allowed to cover a full crop growing season, and as a consequence of seasonal rains on the experimental area, data could be recorded over a wide variety of soil conditions. This enabled a study on the effects of different land bio-geophysical parameters on GNSS scattered signals. It is shown that significant power variations in the measured GNSS reflected signals can be detected for different soil moisture and vegetation development conditions. In this work we also propose a technique based on the combination of the reflected signal’s polarizations in order to improve the integrity of the observables with respect to nuisance parameters such as soil roughness.

  17. A simple method to detect land changes sourcing from overgrazing using remote sensing

    Science.gov (United States)

    Papadavid, G.; Themistocleous, K.; Christoforou, M.; Carmen, B.; Tsaltas, D.; Hadjimitsis, D.

    2013-08-01

    This is a technical paper, in the context of CASCADE project, describing an overgrazed area in Cyprus and how remote sensing techniques can assist the procedure for detecting land degradation sourcing from animal overgrazing. Remote sensing is a tool recently introduced to such studies but indeed very useful and vital. Using satellite images it is possible to retrieve consecutive vegetation indices which can identify if there is any further land-vegetation degradation in a specific area of interest. This is crucial in the procedure for monitoring semi or highly overgrazed areas since this change detection can inform policy makers regarding the status of an area, in terms of degradation. In this paper remotely sensed data is analyzed to detect, in specific areas which are known as overgrazed, to detect if there is a change using three main vegetation indices, namely WDVI, NDVI and SAVI. Change detection techniques are applied on these three vegetation indices maps in order to detect any further areas overgrazing.

  18. Tools and Services for Working with Multiple Land Remote Sensing Data Products

    Science.gov (United States)

    Krehbiel, C.; Friesz, A.; Harriman, L.; Quenzer, R.; Impecoven, K.; Maiersperger, T.

    2016-12-01

    The availability of increasingly large and diverse satellite remote sensing datasets provides both an opportunity and a challenge across broad Earth science research communities. On one hand, the extensive assortment of available data offer unprecedented opportunities to improve our understanding of Earth science and enable data use across a multitude of science disciplines. On the other hand, increasingly complex formats, data structures, and metadata can be an obstacle to data use for the broad user community that is interested in incorporating remote sensing Earth science data into their research. NASA's Land Processes Distributed Active Archive Center (LP DAAC) provides easy to use Python notebook tutorials for services such as accessing land remote sensing data from the LP DAAC Data Pool and interpreting data quality information from MODIS. We use examples to demonstrate the capabilities of the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), such as spatially and spectrally subsetting data, decoding valuable quality information, and exploring initial analysis results within the user interface. We also show data recipes for R and Python scripts that help users process ASTER L1T and ASTER Global Emissivity Datasets.

  19. Integrated use of satellite images, DEMs, soil and substrate data in studying mountainous lands

    Science.gov (United States)

    Giannetti, Fabio; Montanarella, Luca; Salandin, Roberto

    A method based on the integration into a GIS of satellite images of different spatial resolution (Landsat TM and SPOT), Digital Elevation Models, geo-lithological maps and some soil-landscape data was developed and applied to a test area on a sector of the Italian northwestern Alps in the Piemonte region (Pellice, Po, Varaita and Maira valleys southwest of Torino). The main working steps performed (using GIS software) in this area were: (1) acquisition of geo-lithological and geomorphological maps available and a first definition of homogeneous zones obtained by joining different classes with pedogenic criteria; (2) processing and classification of satellite images to define homogeneous areas with reference to prevailing land cover, land use pattern, relief shape and spectral characters; (3) integration of the previous two layers to obtain a first set of cartographic units showing a distinctive and often repetitive pattern of land form, land cover and parent material; and (4) processing DEMs (slope and aspect), soil or soil-landscape data in order to refine data and characterise the units. The resulting cartographic units were superimposed on a soil-landscape map realised by means of stereoscopic interpretation of aerial photographs by IPLA at the same scale (1:250,000). This comparison was used to verify the correctness of the satellite image processing steps and consistency with the map scale used. A larger scale application was also developed for grassland at 1:50,000 scale to demonstrate the practical use of remote sensing and GIS data in assisting mountainous land development.

  20. Higher resolution satellite remote sensing and the impact on image mapping

    Science.gov (United States)

    Watkins, Allen H.; Thormodsgard, June M.

    1987-01-01

    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented. 

  1. Higher resolution satellite remote sensing and the impact on image mapping

    Science.gov (United States)

    Watkins, Allen H.; Thormodsgard, June M.

    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

  2. Satellite remote sensing of Asian aerosols: a case study of clean, polluted and dust storm days

    Directory of Open Access Journals (Sweden)

    K. H. Lee

    2010-06-01

    Full Text Available Satellite-based aerosol observation is a useful tool for the estimation of microphysical and optical characteristics of aerosol during more than three decades. Until now, a lot of satellite remote sensing techniques have been developed for aerosol detection. In East Asian region, the role of satellite observation is quite important because aerosols originating from natural and man-made pollution in this region have been recognized as an important source for regional and global scale air pollution. However, it is still difficult to retrieve aerosol over land because of the complexity of the surface reflection and complex aerosol composition, in particular, aerosol absorption. In this study, aerosol retrievals using Look-up Table (LUT based method was applied to MODerate Resolution Imaging Spectroradiometer (MODIS Level 1 (L1 calibrated reflectance data to retrieve aerosol optical thickness (AOT over East Asia. Three case studies show how the methodology works to identify those differences to obtain a better AOT retrieval. The comparison between the MODIS and Aerosol Robotic Network (AERONET shows better results when the suggested methodology using the cluster based LUTs is applied (linear slope=0.94, R=0.92 than when operational MODIS aerosol products are used (linear slope=0.78, R=0.87. In conclusion, the suggested methodology is shown to work well with aerosol models acquired by statistical clustering the observation data in East Asia.

  3. THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    A. H. Ahrari

    2017-09-01

    Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

  4. Spatial Aggregation of Land Surface Characteristics: Impact of resolution of remote sensing data on land surface modelling

    NARCIS (Netherlands)

    Pelgrum, H.

    2000-01-01

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo, surface te

  5. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  6. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

  7. Indian remote sensing satellites: Planned missions and future applications

    Science.gov (United States)

    Chandrasekhar, M. G.; Jayaraman, V.; Rao, Mukund

    1996-02-01

    To cater the enhanced user demands, Indian Space Research Organisation is stepping a giant leap forward towards development of the state-of-the-art second generation Indian Remote Sensing Satellites, IRS-1C/1D following the successful design, launch and in-orbit performance of the first generation satellites, IRS-1A/1B. Characterised by improved spatial resolution, extended spectral bands, stereo-viewing and more frequent revisit capability, IRS-1C/1D are expected for launch during the timeframe of 1995-96/8. The IRS-1C and ID, which are identical, will have three major payloads. The Linear Imaging Spectral Scanner (LISS-III) in four spectral bands covering from 0.52 to 1.70 microns will have a spatial resolution of 23m along with a swath of 142 km in the visible and NIR spectral bands and a spatial resolution of 70m along with a swath of 148 km in the SWIR spectral band. The Panchromatic Camera (PAN) with a spectral band of 0.50 to 0.75 microns will have a spatial resolution of information on water stress, pest infestation and vegetation indices to arrive at better agricultural management practices, besides providing enhanced capabilities for arriving solutions for micro-level resource development and generation of digital terrain models. Having marked by the successful launch of IRS-P2 in 1994 through the indigenous development flight of PSLV, India is now poised to launch IRS-P3 satellite with unique payloads in the timeframe of 1995-1996 The IRS-P3 will carry three operational payloads viz., Wide Field Sensor (WiFS), Modular Opto-electronic Scanner (MOS) imaging spectrometer and an X-ray Astronomy payload. These payload mix of sensors will provide further capabilities for application studies related to vegetation dynamics, oceanography and X-ray astronomy. With the launch of these payloads, India will provide more effective and assured data services to the user community beyond the 90's.

  8. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  9. Towards Jointly Validation of Land Remote Sensing Products In China

    Science.gov (United States)

    Li, X.; Jin, R.; Ma, M.; Xiao, Q.; Zhao, K.; Che, T.

    2015-12-01

    To assess the accuracy of remote sensing product (RSP) requires well designed and carefully implemented validation effort. However, validation is not a straightforward task. On the contrary, it is generally recognized as a challenging issue due to the inconsistence of resolutions and extents associated with various products, strong spatial and temporal variations of surface parameters and, the essential heterogeneity of land surfaces. Thus, to develop, design and conduct reasonable validation schemes and activities to acquire ground truth at pixel scale over heterogeneous land surfaces is urgently needed. This contains, from the perspective of measurement, to integrate various ground observations collected at multi-scale, in order to validating different RSPs from site to network, especially for those land surface variables with strong spatial-temporal variations. To this end, a dedicated validation initiative has been launched in China since 2011. The main scientific objectives and research contents of this project are to develop mathematical approaches for in situ sampling design to acquire ground truth at pixel scale over heterogeneous land surfaces, to form a series of recognized and practicable technical specifications to guide users to validate various RSPs, and to establish a prototype of national validation network and a RSP evaluation system. Specific validation activities, such as the HiWATER, were conducted from site to network, through multi-scale observations collected from multi-platform and multi-source, to experimentally examine those proposed methodologies and guidelines. Corresponding research outcomes on the development of sampling design, scale method and validation of land surface variables have already yielded. This enables validation efforts to be more effective for heterogeneous land surfaces and applicable for other validation tasks beyond local and regional scale. Following the experience of these validation exercises, we are coordinating

  10. Land and Forest Management by Land Use/ Land Cover Analysis and Change Detection Using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    Ankana

    2016-01-01

    Full Text Available Remote sensing and Geographical Information System (GIS are the most effective tools in spatial data analysis. Natural resources like land, forest and water, these techniques have proved a valuable source of information generation as well as in the management and planning purposes. This study aims to suggest possible land and forest management strategies in Chakia tahsil based on land use and land cover analysis and the changing pattern observed during the last ten years. The population of Chakia tahsil is mainly rural in nature. The study has revealed that the northern part of the region, which offers for the settlement and all the agricultural practices constitutes nearly 23.48% and is a dead level plain, whereas the southern part, which constitute nearly 76.6% of the region is characterized by plateau and is covered with forest. The southern plateau rises abruptly from the northern alluvial plain with a number of escarpments. The contour line of 100 m mainly demarcates the boundary between plateau and plain. The plateau zone is deeply dissected and highly rugged terrain. The resultant topography comprises of a number of mesas and isolated hillocks showing elevation differences from 150 m to 385 m above mean sea level. Being rugged terrain in the southern part, nowadays human encroachment are taking place for more land for the cultivation. The changes were well observed in the land use and land cover in the study region. A large part of fallow land and open forest were converted into cultivated land.

  11. Remote sensing of land degradation: experiences from Latin America and the Caribbean.

    Science.gov (United States)

    Metternicht, G; Zinck, J A; Blanco, P D; del Valle, H F

    2010-01-01

    Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

  12. MEaSUREs Land Surface Temperature from GOES Satellites

    Science.gov (United States)

    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  13. A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

    Science.gov (United States)

    Caradonna, Grazia; Novelli, Antonio; Tarantino, Eufemia; Cefalo, Raffaela; Fratino, Umberto

    2016-06-01

    Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

  14. Remote Sensing Parameterization of Land Surface Heat Fluxes over Arid and Semi-arid Areas

    Institute of Scientific and Technical Information of China (English)

    马耀明; 王介民; 黄荣辉; 卫国安; MassimoMENENTI; 苏中波; 胡泽勇; 高峰; 文军

    2003-01-01

    Dealing with the regional land surfaces heat fluxes over inhomogeneous land surfaces in arid and semi-arid areas is an important but not an easy issue. In this study, one parameterization method based on satellite remote sensing and field observations is proposed and tested for deriving the regional land surface heat fluxes over inhomogeneous landscapes. As a case study, the method is applied to the Dunhuang experimental area and the HEIFE (Heihe River Field Experiment, 1988-1994) area. The Dunhuang area is selected as a basic experimental area for the Chinese National Key Programme for Developing Basic Sciences: Research on the Formation Mecbanism and Prediction Theory of Severe Climate Disaster in China (G1998040900, 1999-2003). The four scenes of Landsat TM data used in this study are 3 June 2000,22 August 2000, and 29 January 2001 for the Dunhuang area and 9 July 1991 for the HEIFE area. The regional distributions of land surface variables, vegetation variables, and heat fluxes over inhomogeneous landscapes in arid and semi-arid areas are obtained in this study.

  15. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2015-11-01

    Full Text Available This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  16. Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

    Science.gov (United States)

    Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

    2013-01-01

    Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary

  17. Sampling design for an integrated socioeconomic and ecological survey by using satellite remote sensing and ordination.

    Science.gov (United States)

    Binford, Michael W; Lee, Tae Jeong; Townsend, Robert M

    2004-08-03

    Environmental variability is an important risk factor in rural agricultural communities. Testing models requires empirical sampling that generates data that are representative in both economic and ecological domains. Detrended correspondence analysis of satellite remote sensing data were used to design an effective low-cost sampling protocol for a field study to create an integrated socioeconomic and ecological database when no prior information on ecology of the survey area existed. We stratified the sample for the selection of tambons from various preselected provinces in Thailand based on factor analysis of spectral land-cover classes derived from satellite data. We conducted the survey for the sampled villages in the chosen tambons. The resulting data capture interesting variations in soil productivity and in the timing of good and bad years, which a purely random sample would likely have missed. Thus, this database will allow tests of hypotheses concerning the effect of credit on productivity, the sharing of idiosyncratic risks, and the economic influence of environmental variability.

  18. Remote sensing for greenhouse detection from stereo pairs of WorldView-2 satellite

    Directory of Open Access Journals (Sweden)

    M.A. Aguilar

    2014-05-01

    Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.

  19. Forest Condition Monitoring Using Very-High-Resolution Satellite Imagery in a Remote Mountain Watershed in Nepal

    Directory of Open Access Journals (Sweden)

    Kabir Uddin

    2015-08-01

    Full Text Available Satellite imagery has proven extremely useful for repetitive timeline-based data collection, because it offers a synoptic view and enables fast processing of large quantities of data. The changes in tree crown number and land cover in a very remote watershed (area 1305 ha in Nepal were analyzed using a QuickBird image from 2006 and an IKONOS image from 2011. A geographic object-based image analysis (GEOBIA was carried out using the region-growing technique for tree crown detection, delineation, and change assessment, and a multiresolution technique was used for land cover mapping and change analysis. The coefficient of determination for tree crown detection and delineation was 0.97 for QuickBird and 0.99 for IKONOS, calculated using a line-intercept transect method with 10 randomly selected windows (1×1 ha. The number of tree crowns decreased from 47,121 in 2006 to 41,689 in 2011, a loss of approximately 90 trees per month on average; the area of needle-leaved forest was reduced by 140 ha (23% over the same period. Analysis of widely available very-high-resolution satellite images using GEOBIA techniques offers a cost-effective method for detecting changes in tree crown number and land cover in remote mountain valleys; the results provide the information needed to support improved local-level planning and forest management in such areas.

  20. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    Science.gov (United States)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

  1. On the use of Satellite Remote Sensing and GIS to detect NO2 in the Troposphere

    DEFF Research Database (Denmark)

    Nielsen, Søren Zebitz

    2012-01-01

    This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...

  2. Satellite Remote Sensing Analysis to Monitor Desertification Processes in Central Plateau of Mexico

    Science.gov (United States)

    Becerril, R.; González Sosa, E.; Diaz-Delgado, C.; Mastachi-Loza, C. A.; Hernández-Tellez, M.

    2013-05-01

    Desertification is defined as land degradation in arid, semi-arid and sub-humid areas due to climatic variations and human activities. Therefore there is a need to monitor the desertification process in the spatiotemporal scale in order to develop strategies to fight against desertification (Wu and Ci, 2002). In this sense, data provided by remote sensing is an important source for spatial and temporal information, which allows monitoring changes in the environment at low cost and high effectiveness. In Mexico, drylands hold 65% of the area, with about 1,280,494 km2 (UNESCO, 2010), where is located 46% of the national population (SEMARNAT, 2008). Given these facts, there is interest in monitoring the degradation of these lands, especially in Mexico because no specific studies have identified trends and progress of desertification in the country so far. However, it has been considered land degradation as an indicator of desertification process. Thus, it has been determined that 42% of soils in Mexico present some degradation degree. The aim of this study was to evaluate the spatial and temporal dynamics of desertification for 1993, 2000 and 2011 in the semiarid central plateau in Mexico based on demographic, climatic and satellite data. It took into consideration: 1) the Anthropogenic Impact Index (HII), based on the spatial population distribution and its influence on the use of resources and 2) the Aridity Index (AI), calculated with meteorological station records for annual rainfall and potential evapotranspiration. Mosaics were made with Landsat TM scenes; considering they are a data source that allows evaluate surface processes regionally and with high spectral resolution. With satellite information five indices were estimated to assess the vegetation and soil conditions: Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Weighted Difference Vegetation Index (WDVI), Grain Size Index (GSI) and Bare Soil Index (BSI). The rates

  3. Potential association of dengue hemorrhagic fever incidence and remote senses land surface temperature, Thailand, 1998.

    Science.gov (United States)

    Nitatpattana, Narong; Singhasivanon, Pratap; Kiyoshi, Honda; Andrianasolo, Haja; Yoksan, Sutee; Gonzalez, Jean-Paul; Barbazan, Philippe

    2007-05-01

    A pilot study was designed to analyze a potential association between dengue hemorrhagic fever (DHF) incidence and, temperature computed by satellite. DHF is a mosquito transmitted disease, and water vapor and humidity are known to have a positive effect on mosquito life by increasing survival time and shortening the development cycle. Among other available satellite data, Land Surface Temperature (LST) was chosen as an indicator that combined radiated earth temperature and atmospheric water vapor concentration. Monthly DHF incidence was recorded by province during the 1998 epidemic and obtained as a weekly combined report available from the National Ministry of Public Health. Conversely, LST was calculated using remotely sensed data obtained from thermal infrared sensors of NOAA satellites and computed on a provincial scale. Out of nine selected study provinces, five (58.3%) exhibited an LST with a significant positive correlation with rainfall (p < 0.05). In four out of nineteen surveyed provinces (21.3%), LST showed a significant positive correlation with DHF incidence (p < 0.05). Positive association between LST and DHF incidence was significantly correlated in 75% of the cases during non-epidemic months, while no correlation was found during epidemic months. Non-climatic factors are supposed to be at the origin of this discrepancy between seasonality in climate (LST) and DHF incidence during epidemics.

  4. Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques

    Science.gov (United States)

    Nampak, Haleh; Pradhan, Biswajeet

    2016-07-01

    Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

  5. Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2015-12-01

    Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  6. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  7. Land Desertification Monitoring on Tibetan Plateau Using Remote Sensing Technology

    Science.gov (United States)

    Liu, Z.; Zou, X.; Liu, H.

    2012-12-01

    As one of the serious ecological environmental problems of the Tibetan plateau, desertification has critically hampered the economic and social development in Tibet, so it is imperative to monitoring the desertification in Tibet area. Due to its 200 thousand km2 vast area and steep terrain, this paper uses multi-source remote sensing image to survey the current situation of land desertification in Tibetan plateau, and study dynamic desertification change on the 10 km2 land between Namucuo lake and Selincuo lake. Data of the 250 meters time-series MODIS-NDVI images, 30 m resolution Landsat TM images and 90 m SRTM DEM data were used. Through the analysis of the relationship between MODIS-NDVI, vegetation growth characteristics and vegetation vertical distribution, this paper chooses the MODIS-NDVI time series data and principal component analysis of the first band (PC1), vegetation coverage(VC), DEM and its derived slope data as indicators for desertification monitoring. Visual interpretation based on 30 m TM image is also used to classify each type of desertification. Using the high temporal resolution data, we can quickly obtain desertification hot spot areas then accurately distinguish each degree of desertification with high spatial resolution images. The results are: (1) The desertification area in Tibetan plateau in 2008 is 218,286 km2, which is 18.91% of the total area, and mainly distributed in the Ali region, next by Nagqu and Xigaze. The severe desertification land area is 8,866 km2 ( 4.06% of the desertified land), of which the mobile dune area is 3224 km2, heavy saline area is 5641 km2. Moderate desertified land area is 110,915 km2( 50.81% of the desertified land), of which semi-fixed sand dune area is 10,075 km2 and the bare sand area is 100,839 km2. Mild desertified land area is 98,504 km2 ( 45.12% of the desertified land), of which the fixed dune area is 4,177 km2 and the half bare gravel area is 94,326 km2. (2) By using GIS spatial analysis, westudied

  8. Satellite remote sensing outputs of the certain glaciers on the territory of East Georgia

    Directory of Open Access Journals (Sweden)

    G. Kordzakhia

    2015-10-01

    With the launch of the Earth’s satellites it was determined that satellite remote sensing is the best technology allowing to receive data with needed regularity in terms of both time and space resolution. Some uncertainties remain in the data as the observational tool is too far away from the Earth’s surface. So, the necessity for the strong quality assessment/quality control (QA/QC remains. A lot of studies showed that the best method for investigation of glaciers is application of satellite remote sensing combined with terrestrial observations and expert knowledge of separate glaciers.

  9. A role for AVIRIS in the Landsat and Advanced Land Remote Sensing Systems program

    Science.gov (United States)

    Green, Robert O.; Simmonds, John J.

    1993-01-01

    As a calibrated imaging spectrometer flying at a 20 km altitude, AVIRIS may contribute to the Landsat and the Advanced Land Remote Sensing System efforts. These contributions come in the areas of: (1) on-orbit calibration, (2) specification of new spectral bands, (3) validation of algorithms, and (4) investigation of an imaging spectrometer of the Advanced Land Remote Sensing System.

  10. Mapping land slide occurrence zones using Remote Sensing and GIS techniques in Kelantan state, Malaysia

    Science.gov (United States)

    Hashim, M.; Pour, A. B.; Misbari, S.

    2017-05-01

    Integration of satellite remote sensing data and Geographic Information System (GIS) techniques is one of the most applicable approach for landslide mapping and identification of high potential risk and susceptible zones in tropical environments. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) remote sensing data sets were integrated with GIS analysis for detect, map and characterize landslide occurrences during December 2014 flooding period in the Kelantan river basin. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after December 2014 flooding for the study area. The PALSAR-2 data were used for mapping of major geological structures and detailed characterizations of lineaments in the state of Kelantan. Analytical Hierarchy Process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, Normalized Difference Vegetation Index (NDVI), land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from remote sensing satellite data and fieldwork to apply AHP approach. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire the Kelantan state. Modelled/predicted landslides with susceptible map generated prior and post flood episode, confirmed that intense rainfall in the Kelantan have contributed to weightage of numerous landslides with various sizes. It is concluded that precipitation is the most influential factor that bare to landslide event.

  11. A Global Record of Daily Landscape Freeze-Thaw Status from Satellite Microwave Remote Sensing

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; Colliander, A.; McDonald, K. C.

    2011-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, seasonal vegetation growth dynamics and terrestrial carbon budgets. A global Earth System Data Record (ESDR) of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The product is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier product validation is applied using in situ temperature and tower carbon flux measurements, and other satellite FT retrievals. The FT-ESDR record shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to surface air temperature measurements from global weather stations. Other comparisons against spatially dense temperature observations from an Alaska ecological transect reveal satellite sensor frequency dependence and variable FT sensitivity to surface air, vegetation, soil and snow properties. Other satellite sensor retrievals, including AMSR-E and SMOS show similar FT classification accuracies, but variable sensitivity to different landscape elements. Sensor FT classification differences reflect differences in microwave frequency, footprint resolution and satellite

  12. Application of Satellite remote sensing for detailed landslide inventories using Frequency ratio model and GIS

    Directory of Open Access Journals (Sweden)

    Himan Shahabi

    2012-07-01

    Full Text Available This paper presents landslide susceptibility analysis in central Zab basin in the southwest mountainsides of West-Azerbaijan province in Iran using remotely sensed data and Geographic Information System. Landslide database was generated using satellite imagery and aerial photographs accompanied by field investigations using Differential Global Positioning System to generate a landslide inventory map. Digital elevation model (DEM was first constructed using GIS software. Nine landslide inducing factors were used for landslide vulnerability analysis: slope, slope aspect, distance to road, distance to drainage network, distance to fault, land use, Precipitation, Elevation, and geological factors. This study demonstrates the synergistic use of medium resolution, multitemporal Satellite pour lObservation de la Terre (SPOT, for prepare of landslide-inventory map and Landsat ETM+ for prepare of Land use. The post-classification comparison method using the Maximum Likelihood classifier with SPOT images was able to detect approximately 70% of landslides. Frequency ratio of each factor was computed using the above thematic factors with past landslide locations. It employs the landslide events as dependant variable and data layers as independent variable, and makes use of the correlation between these two factors in landslide zonation. Given the employed model and the variables, signification tests were implemented on each independent variable, and the degree of fitness of zonation map was estimated Landslide susceptibility map was produced using raster analysis. The landslide susceptibility map was classified into four classes: low, moderate, high and very high. The model is validated using the Relative landslide density index (R-index method. The final, landslide low hazard susceptibility map was drawn using frequency ratio. As a result, showed that the identified landslides were located in the class (51.37%, moderate (29.35%, high (11.10% and very high

  13. The potential of remote sensing for monitoring land cover changes and effects on physical geography in the area of Kayisdagi Mountain and its surroundings (Istanbul).

    Science.gov (United States)

    Geymen, Abdurrahman; Baz, Ibrahim

    2008-05-01

    The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation.

  14. Validating a Satellite Microwave Remote Sensing Based Global Record of Daily Landscape Freeze-Thaw Dynamics

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; McDonald, K. C.

    2012-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, vegetation growth, terrestrial carbon budgets and land-atmosphere trace gas exchange. A global Earth System Data Record of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of overlapping 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The FT-ESDR is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier validation scheme was applied using in situ temperature measurements, other satellite FT retrievals and synergistic biophysical data. These results are incorporated into the product metadata structure, including mean daily spatial classification accuracies and annual quality assessment (QA) maps accounting for landscape heterogeneity, algorithm limitations and sensor retrieval gaps. The resulting FT-ESDR shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals. Accuracy is reduced during seasonal transition periods when FT heterogeneity is maximized within the relatively coarse (~25-km) satellite footprint. The QA rankings range from low (estimated accuracy 90%) categories; mean annual QA results for the 1979-2011 period show relative proportions of

  15. Towards a protocol for validating satellite-based Land Surface Temperature: Application to AATSR data

    Science.gov (United States)

    Ghent, Darren; Schneider, Philipp; Remedios, John

    2013-04-01

    , 2008); further insights are provided through intercomparison with retrievals from other satellite sensors; with time-series analysis performed to identify artefacts on an interannual time-scale. Specifically, we evaluate data from the AATSR instrument which until recently had been providing satellite observations of LST. Both the standard ESA LST product, and an enhanced offline LST product utilising high resolution auxiliary data produced by the University of Leicester (Ghent et al., in prep.) and in the process of being implanted in the Data Processing Model for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3, are assessed. This is a timely undertaking since it enables evaluation of the data record from AATSR - the predecessor to SLSTR, and it provides insights on the effectiveness of the validation protocol in preparation for the launch of Sentinel-3. References Ghent, D., Corlett, G., and Remedios, J. Advancing the AATSR land surface temperature retrieval with higher resolution auxiliary datasets, in prep. Schneider, P., Ghent, D., Corlett, G., Prata, F., and Remedios, J. Land Surface Temperature Validation Protocol, Report to ESA: Report No. UL-NILU-ESA-LST-LVP, 2012 Wan, Z., and Li, Z.-L. Radiance-based validation of the V5 MODIS land-surface temperature product, International Journal of Remote Sensing, 29, 5373-5395, 2008

  16. Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

    Science.gov (United States)

    Chuang, Ting-Wu; Henebry, Geoffrey M.; Kimball, John S.; VanRoekel-Patton, Denise L.; Hildreth, Michael B.; Wimberly, Michael C.

    2012-01-01

    Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems. PMID:23049143

  17. A New Fusion Technique of Remote Sensing Images for Land Use/Cover

    Institute of Scientific and Technical Information of China (English)

    WU Lian-Xi; SUN Bo; ZHOU Sheng-Lu; HUANG Shu-E; ZHAO Qi-Guo

    2004-01-01

    In China,accelerating industrialization and urbanization following high-speed economic development and population increases have greatly impacted land use/cover changes,making it imperative to obtain accurate and up to date information on changes so as to evaluate their environmental effects. The major purpose of this study was to develop a new method to fuse lower spatial resolution multispectral satellite images with higher spatial resolution panchromatic ones to assist in land use/cover mapping. An algorithm of a new fusion method known as edge enhancement intensity modulation (EEIM) was proposed to merge two optical image data sets of different spectral ranges. The results showed that the EEIM image was quite similar in color to lower resolution multispectral images,and the fused product was better able to preserve spectral information. Thus,compared to conventional approaches,the spectral distortion of the fused images was markedly reduced. Therefore,the EEIM fusion method could be utilized to fuse remote sensing data from the same or different sensors,including TM images and SPOT5 panchromatic images,providing high quality land use/cover images.

  18. Passive remote sensing of the atmospheric water vapour content above land surfaces

    Science.gov (United States)

    Bartsch, B.; Bakan, S.; Fischer, J.

    The global distribution of the atmospheric water vapour content plays an important role in the weather forecast and climate research. Nowadays there exist various methods dealing with remote sensing of the atmospheric water vapour content. Unfortunately, most of them are restricted to ocean areas, since, in general, the emission of land surfaces is not known well enough. Therefore, a new method is developed which allows the detection of the atmospheric total water vapour content from aircraft or satellite with the aid of backscattered solar radiation in the near infrared above land surfaces. The Matrix-Operator-Method has been used to simulate backscattered solar radiances, including various atmospheric profiles of temperature, pressure, water vapour, and aerosols of various types, several sun zenith angles, and different types of land surfaces. From these calculations it can be concluded, that the detection of water vapour content in cloudless atmospheres is possible with an error of < 10 % even for higher aerosol contents. In addition to the theoretical results first comparisons with aircraft measurements of the backscattered solar radiances are shown. These measurements have been carried out with the aid of OVID (Optical Visible and near Infrared Detector), a new multichannel array spectrometer, in 1993.

  19. Land Use Changes of Mata Lake Using Multi-temporal Satellite Imageries

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Land use and protection has become a global hotspot. How to use land resources is an important topic for the future socio-economic sustainable development. This paper analyzes the land use changes of Mata lake of Shandong province in China, from 1985's to 2000's using multi-temporal remotely sensed data including TM in the 1985s, ETM+ in the 2000s and ancillary data such as soil use map, water map etc. The remote sensing imageries were calibrated, registered and geo-referenced, then classified by multi-source information data and remote sensing image interpretation expert system based on knowledge base. Five land use types were extracted from remote sensing imageries, that is, water body, agriculture land, rural settlement, bare land and none use land. The total precision is 80.7% and Kappa index is 0.825. The analysis result of the remote sensing showsthat during the past 15 years, water resource dropped off very promptly from 51.77 km2 to 16. 65 km2 and bare land reduced greatly more than 60% in Mata lake region. With the development of the economy and agriculture areas, more and more water body and bare land converted to agriculture land use and rural settlement areas. Since last years, the Mata lake has been affected by natural factor, human activity and increasing population. So its land use pattern greatly changed from 1985 to 2000.The information of land use changes provided scientific supports for land planning and environmental protection.

  20. Remote Observation of Volcanos by Small Satellite Formations

    Science.gov (United States)

    Schilling, Klaus; Zakšek, Klemen

    2016-07-01

    Volcanic eruptions, severe storms, or desert dust can seriously jeopardize the safety of the air traffic. To prevent encounters of airplanes with such clouds it is necessary to accurately monitor the cloud top heights, which is impossible using currently operational satellites. The most commonly used method for satellite cloud height estimation compares brightness temperature of the cloud with the atmospheric temperature profile. Because of its many uncertainties we propose to exploit the formation of four satellites providing images for photogrammetric analysis. Simultaneous observations from multiple satellites is necessary, because clouds can move with velocities over several m/s. With the proposed mission, we propose a formation of nano-satellites that simultaneously observe the clouds from different positions and orientations. The proposed formation of four satellites will fly in the same orbit with a distance between each satellite of 100 km on the height of 600 km. There are autonomous reaction capabilities realized to focus all satellites on the same surface point for joint observations, enabling by postprocessing 3D surface images. Each satellite will carry a camera operating in visible spectrum providing data with 35 m spatial resolution. Such data will make possible to monitor multilayer clouds with a vertical accuracy of 200 m.

  1. Statistical analysis of land surface temperature-vegetation indexes relationship through thermal remote sensing.

    Science.gov (United States)

    Kumar, Deepak; Shekhar, Sulochana

    2015-11-01

    Vegetation coverage has a significant influence on the land surface temperature (LST) distribution. In the field of urban heat islands (UHIs) based on remote sensing, vegetation indexes are widely used to estimate the LST-vegetation relationship. This paper devises two objectives. The first analyzes the correlation between vegetation parameters/indicators and LST. The subsequent computes the occurrence of vegetation parameter, which defines the distribution of LST (for quantitative analysis of urban heat island) in Kalaburagi (formerly Gulbarga) City. However, estimation work has been done on the valuation of the relationship between different vegetation indexes and LST. In addition to the correlation between LST and the normalized difference vegetation index (NDVI), the normalized difference build-up index (NDBI) is attempted to explore the impacts of the green land to the build-up land on the urban heat island by calculating the evaluation index of sub-urban areas. The results indicated that the effect of urban heat island in Kalaburagi city is mainly located in the sub-urban areas or Rurban area especially in the South-Eastern and North-Western part of the city. The correlation between LST and NDVI, indicates the negative correlation. The NDVI suggests that the green land can weaken the effect on urban heat island, while we perceived the positive correlation between LST and NDBI, which infers that the built-up land can strengthen the effect of urban heat island in our case study. Although satellite data (e.g., Landsat TM thermal bands data) has been applied to test the distribution of urban heat islands, but the method still needs to be refined with in situ measurements of LST in future studies.

  2. CBERS-2B Brazilian remote sensing satellite to help to monitor the Bolivia-Brazil gas pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)

    2009-07-01

    This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)

  3. Analysis of spatio-temporal pattern and driving force of land cover change using multi-temporal remote sensing images

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Landuse and land cover change is regarded as a good indicator that represents the impact of human activities on earth’s environment.When the large collection of multi-temporal satellite images has become available,it is possible to study a long-term historical process of land cover change.This study aims to investigate the spatio-temporal pattern and driving force of land cover change in the Pearl River Delta region in southern China,where the rapid development has been witnessed since 1980s.The fast economic growth has been associated with an accelerated expansion of urban landuse,which has been recorded by historical remote sensing images.This paper reports the method and outcome of the research that attempts to model spatio-temporal pattern of land cover change using multi-temporal satellite images.The classified satellite images were compared to detect the change from various landuse types to built-up areas.The trajectories of land cover change have then been established based on the time-series of the classified land cover classes.The correlation between the expansion of built-up areas and selected economic data has also been analysed for better understanding on the driving force of the rapid urbanisation process.The result shows that,since early 1990s,the dominant trend of land cover change has been from farmland to urban landuse.The relationship between economic growth indicator(measured by GDP)and built-up area can well fit into a linear regression model with correlation coefficients greater than 0.9.It is quite clear that cities or towns have been sprawling in general,demonstrating two growth models that were closely related to the economic development stages.

  4. Regional adaptation of a dynamic global vegetation model using a remote sensing data derived land cover map of Russia

    Science.gov (United States)

    Khvostikov, S.; Venevsky, S.; Bartalev, S.

    2015-12-01

    The dynamic global vegetation model (DGVM) SEVER has been regionally adapted using a remote sensing data-derived land cover map in order to improve the reconstruction conformity of the distribution of vegetation functional types over Russia. The SEVER model was modified to address noticeable divergences between modelling results and the land cover map. The model modification included a light competition method elaboration and the introduction of a tundra class into the model. The rigorous optimisation of key model parameters was performed using a two-step procedure. First, an approximate global optimum was found using the efficient global optimisation (EGO) algorithm, and afterwards a local search in the vicinity of the approximate optimum was performed using the quasi-Newton algorithm BFGS. The regionally adapted model shows a significant improvement of the vegetation distribution reconstruction over Russia with better matching with the satellite-derived land cover map, which was confirmed by both a visual comparison and a formal conformity criterion.

  5. Interfacing geographic information systems and remote sensing for rural land-use analysis

    Science.gov (United States)

    Nellis, M. Duane; Lulla, Kamlesh; Jensen, John

    1990-01-01

    Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

  6. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    Science.gov (United States)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  7. Remote sensing of land processes: Sponsored programs of study by the National Aeronautics and Space Administration

    Science.gov (United States)

    Asrar, G.; Wickland, D. E.; Baltuck, M.; Ruzek, M. J.; Murphy, R. E.

    1988-01-01

    The NASA Land Processes Program consists of four interrelated disciplines which support studying the terrestrial geology, ecology, hydrology, and remote sensing science. The first three represent the space based components of classical science disciplines, while the last discipline is the study of the physics, biology, and chemistry of the land surface as it relates to the interaction of electromagnetic energy with the land surface.

  8. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    Science.gov (United States)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  9. Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

  10. MITRA Virtual laboratory for operative application of satellite time series for land degradation risk estimation

    Science.gov (United States)

    Nole, Gabriele; Scorza, Francesco; Lanorte, Antonio; Manzi, Teresa; Lasaponara, Rosa

    2015-04-01

    This paper aims to present the development of a tool to integrate time series from active and passive satellite sensors (such as of MODIS, Vegetation, Landsat, ASTER, COSMO, Sentinel) into a virtual laboratory to support studies on landscape and archaeological landscape, investigation on environmental changes, estimation and monitoring of natural and anthropogenic risks. The virtual laboratory is composed by both data and open source tools specifically developed for the above mentioned applications. Results obtained for investigations carried out using the implemented tools for monitoring land degradation issues and subtle changes ongoing on forestry and natural areas are herein presented. In detail MODIS, SPOT Vegetation and Landsat time series were analyzed comparing results of different statistical analyses and the results integrated with ancillary data and evaluated with field survey. The comparison of the outputs we obtained for the Basilicata Region from satellite data analyses and independent data sets clearly pointed out the reliability for the diverse change analyses we performed, at the pixel level, using MODIS, SPOT Vegetation and Landsat TM data. Next steps are going to be implemented to further advance the current Virtual Laboratory tools, by extending current facilities adding new computational algorithms and applying to other geographic regions. Acknowledgement This research was performed within the framework of the project PO FESR Basilicata 2007/2013 - Progetto di cooperazione internazionale MITRA "Remote Sensing tecnologies for Natural and Cultural heritage Degradation Monitoring for Preservation and valorization" funded by Basilicata Region Reference 1. A. Lanorte, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbance International Journal of Applied Earth Observation and

  11. The Utility of Remotely-Sensed Land Surface Temperature from Multiple Platforms For Testing Distributed Hydrologic Models over Complex Terrain

    Science.gov (United States)

    Xiang, T.; Vivoni, E. R.; Gochis, D. J.

    2011-12-01

    Land surface temperature (LST) is a key parameter in watershed energy and water budgets that is relatively unexplored as a validation metric for distributed hydrologic models. Ground-based or remotely-sensed LST datasets can provide insights into a model's ability in reproducing water and energy fluxes across a large range of terrain, vegetation, soil and meteorological conditions. As a result, spatiotemporal LST observations can serve as a strong constraint for distributed simulations and can augment other available in-situ data. LST fields are particular useful in mountainous areas where temperature varies with terrain properties and time-variable surface conditions. In this study, we collect and process remotely-sensed fields from several satellite platforms - Landsat 5/7, MODIS and ASTER - to capture spatiotemporal LST dynamics at multiple resolutions and with frequent repeat visits. We focus our analysis of these fields over the Sierra Los Locos basin (~100 km2) in Sonora, Mexico, for a period encompassing the Soil Moisture Experiment in 2004 and the North American Monsoon Experiment (SMEX04-NAME). Satellite observations are verified using a limited set of ground data from manual sampling at 30 locations and continuous measurements at 2 sites. First, we utilize the remotely-sensed fields to understand the summer seasonal evolution of LST in the basin in response to the arrival of summer storms and the vigorous ecosystem greening organized along elevation bands. Then, we utilize the ground and remote-sensing datasets to test the distributed predictions of the TIN-based Real-time Integrated Basin Simulator (tRIBS) under conditions accounting static and dynamic vegetation patterns. Basin-averaged and distributed comparisons are carried out for two different terrain products (INEGI aerial photogrammetry and ASTER stereo processing) used to derive the distributed model domain. Results from the comparisons are discussed in light of the utility of remotely-sensed LST

  12. Satellite Remote Sensing of Inundated Wetlands: Global Data Record Assembly and Planned Uncertainty Analysis

    Science.gov (United States)

    McDonald, K. C.; Chapman, B. D.; Podest, E.; Schröder, R.; Hess, L. L.; Jones, L. A.; Kimball, J. S.; Moghaddam, M.; Whitcomb, J.

    2011-12-01

    Wetlands cover less than 5% of Earth's ice-free land surface but exert major impacts on global biogeochemistry, hydrology, and biological diversity. Despite the importance of these environments in the global cycling of carbon and water, there is a scarcity of suitable regional-to-global remote-sensing data for characterizing their distribution and dynamics. We are assembling a global-scale Earth System Data Record (ESDR) of natural Inundated Wetlands to facilitate investigations on their role in climate, biogeochemistry, hydrology, and biodiversity. The ESDR comprises (1) Fine-resolution (100 meter) maps, delineating wetland extent, vegetation type, and seasonal inundation dynamics for regional to continental-scale areas covering crucial wetland regions, and (2) global coarse-resolution (~25 km), multi-temporal mappings of inundated area fraction (Fw) across multiple years. The fine-scale ESDR component is constructed from L-band synthetic aperture radar (SAR) data. The global maps of inundated area fraction are obtained by combining coarse-resolution (~25 km) remote sensing observations from passive and active microwave instruments. We present details of ESDR assembly and a comparative analysis of the high-resolution SAR-based data sets with the coarse resolution inundation data sets for wetlands ecosystems. We compare information content and accuracy of the coarse resolution data sets relative to the SAR-based data sets. We discuss issues which contribute to uncertainty in the ESDR data sets. Error sources include radiometric inconsistency of the remote sensing data sources, paucity of ground validation datasets available for implementation of classification algorithms, temporal undersampling relative to hydrologic variability, and ambiguities associated with implementation of coarse-resolution mixture models. We discuss plans for conducting systematic analyses of error sources related to aspects of ESDR assembly, including uncertainties associated with remote

  13. Satellite remote sensing of ultraviolet irradiance on the ocean surface

    Institute of Scientific and Technical Information of China (English)

    LI Teng; PAN Delu; BAI Yan; LI Gang; HE Xianqiang; CHEN Chen-Tung Arthur; GAO Kunshan; LIU Dong; LEI Hui

    2015-01-01

    Ultraviolet (UV) radiation has a significant influence on marine biological processes and primary productivity;however, the existing ocean color satellite sensors seldom contain UV bands. A look-up table of wavelength-integrated UV irradiance (280–400 nm) on the sea surface is established using the coupled ocean atmosphere radiative transfer (COART) model. On the basis of the look-up table, the distributions of the UV irradiance at middle and low latitudes are inversed by using the satellite-derived atmospheric products from the Aqua satellite, including aerosol optical thickness at 550 nm, ozone content, liquid water path, and the total precipitable water. The validation results show that the mean relative difference of the 10 d rolling averaged UV irradiance between the satellite retrieval and field observations is 8.20% at the time of satellite passing and 13.95% for the daily dose of UV. The monthly-averaged UV irradiance and daily dose of UV retrieved by satellite data show a good correlation with thein situ data, with mean relative differences of 6.87% and 8.43%, respectively. The sensitivity analysis of satellite inputs is conducted. The liquid water path representing the condition of cloud has the highest effect on the retrieval of the UV irradiance, while ozone and aerosol have relatively lesser effect. The influence of the total precipitable water is not significant. On the basis of the satellite-derived UV irradiance on the sea surface, a preliminary simple estimation of ultraviolet radiation’s effects on the global marine primary productivity is presented, and the results reveal that ultraviolet radiation has a non-negligible effect on the estimation of the marine primary productivity.

  14. The Design and Implementation of a Remote Fault Reasoning Diagnosis System for Meteorological Satellites Data Acquisition

    Directory of Open Access Journals (Sweden)

    Zhu Jie

    2017-01-01

    Full Text Available Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3 meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations,triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.

  15. Advances in the application of remote sensing and GIS for surveying mountainous land

    NARCIS (Netherlands)

    Mulders, M.A.

    2001-01-01

    Satellite remote sensing has been practised since 1972, starting with broad channels and moderate ground resolution (Landsat MSS). In the 1980s, Landsat TM and SPOT provided for improved spatial and spectral resolutions. Many satellite images were produced in these two decades, offering a synoptic v

  16. Use of Satellite Data to Study the Impact of Land-Cover/Land-Use Change in Madison County Alabama

    Directory of Open Access Journals (Sweden)

    Tomas Ayala-Silva

    2009-01-01

    Full Text Available The monitoring of land/use land cover changes along the northern part of Madison County Alabama are essential for the developers, planners, policy makers and management of government, public and private organizations. Remote sensing was used to analyze and study land-use/land-cover use changes impact on the environment of Madison County Alabama. This study area was selected because it is one of the fastest growing areas in the state of Alabama. The study used data sets obtained from several sources. Remote sensing images, land-use/land-cover use maps, global positioning data. The remote sensing images were LANDSAT Thematic Mapper (TM images acquired during April 1987 and May 1997. The data was processed and analyzed using MAP-X/RS and ERDAS. Six classes or categories of land-use/land-cover were analyzed to determine changes and the relationship to suburban sprawl. Each method used was assessed and checked in field. Six land use/land cover classes are produced. The overall accuracy for the 1987 image is (78.92% and for the 1997 image is (85.44% Analysis of the images for 1987 and 1997 showed a (26 and 15% increase in the urbanization and industrial development respectively and a decrease in all other classes. The most significant decrease (25% was in the pastures class, however, less significant changes were observed for the water resources and forest. The results from this study could be beneficial to state/county planners, researchers and policy makers.

  17. New satellite project Aerosol-UA: Remote sensing of aerosols in the terrestrial atmosphere

    Science.gov (United States)

    Milinevsky, G.; Yatskiv, Ya.; Degtyaryov, O.; Syniavskyi, I.; Mishchenko, M.; Rosenbush, V.; Ivanov, Yu.; Makarov, A.; Bovchaliuk, A.; Danylevsky, V.; Sosonkin, M.; Moskalov, S.; Bovchaliuk, V.; Lukenyuk, A.; Shymkiv, A.; Udodov, E.

    2016-06-01

    We discuss the development of the Ukrainian space project Aerosol-UA which has the following three main objectives: (1) to monitor the spatial distribution of key characteristics of terrestrial tropospheric and stratospheric aerosols; (2) to provide a comprehensive observational database enabling accurate quantitative estimates of the aerosol contribution to the energy budget of the climate system; and (3) quantify the contribution of anthropogenic aerosols to climate and ecological processes. The remote sensing concept of the project is based on precise orbital measurements of the intensity and polarization of sunlight scattered by the atmosphere and the surface with a scanning polarimeter accompanied by a wide-angle multispectral imager-polarimeter. Preparations have already been made for the development of the instrument suite for the Aerosol-UA project, in particular, of the multi-channel scanning polarimeter (ScanPol) designed for remote sensing studies of the global distribution of aerosol and cloud properties (such as particle size, morphology, and composition) in the terrestrial atmosphere by polarimetric and spectrophotometric measurements of the scattered sunlight in a wide range of wavelengths and viewing directions from which a scene location is observed. ScanPol is accompanied by multispectral wide-angle imager-polarimeter (MSIP) that serves to collect information on cloud conditions and Earth's surface image. Various components of the polarimeter ScanPol have been prototyped, including the opto-mechanical and electronic assemblies and the scanning mirror controller. Preliminary synthetic data simulations for the retrieval of aerosol parameters over land surfaces have been performed using the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm. Methods for the validation of satellite data using ground-based observations of aerosol properties are also discussed. We assume that designing, building, and launching into orbit a multi

  18. New Satellite Project Aerosol-UA: Remote Sensing of Aerosols in the Terrestrial Atmosphere

    Science.gov (United States)

    Milinevsky, G.; Yatskiv, Ya.; Degtyaryov, O.; Syniavskyi, I.; Mishchenko, Michael I.; Rosenbush, V.; Ivanov, Yu.; Makarov, A.; Bovchaliuk, A.; Danylevsky, V.; Sosonkin, M.; Moskalov, S.; Bovchaliuk, V; Lukenyuk, A.; Shymkiv, A.

    2016-01-01

    We discuss the development of the Ukrainian space project Aerosol-UA which has the following three main objectives: (1) to monitor the spatial distribution of key characteristics of terrestrial tropospheric and stratospheric aerosols; (2) to provide a comprehensive observational database enabling accurate quantitative estimates of the aerosol contribution to the energy budget of the climate system; and (3) quantify the contribution of anthropogenic aerosols to climate and ecological processes. The remote sensing concept of the project is based on precise orbital measurements of the intensity and polarization of sunlight scattered by the atmosphere and the surface with a scanning polarimeter accompanied by a wide-angle multispectral imager-polarimeter. Preparations have already been made for the development of the instrument suite for the Aerosol-UA project, in particular, of the multi-channel scanning polarimeter (ScanPol) designed for remote sensing studies of the global distribution of aerosol and cloud properties (such as particle size, morphology, and composition) in the terrestrial atmosphere by polarimetric and spectrophotometric measurements of the scattered sunlight in a wide range of wavelengths and viewing directions from which a scene location is observed. ScanPol is accompanied by multispectral wide-angle imager-polarimeter (MSIP) that serves to collect information on cloud conditions and Earths surface image. Various components of the polarimeter ScanPol have been prototyped, including the opto-mechanical and electronic assemblies and the scanning mirror controller. Preliminary synthetic data simulations for the retrieval of aerosol parameters over land surfaces have been performed using the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm. Methods for the validation of satellite data using ground-based observations of aerosol properties are also discussed. We assume that designing, building, and launching into orbit a multi

  19. Philosophy and key features of 'Hodoyoshi' concept for optical remote sensing using 50kg class satellites

    Science.gov (United States)

    Enokuchi, A.; Takeyama, N.; Nakamura, Y.; Nojiri, Y.; Miyamura, N.; Iwasaki, A.; Nakasuka, S.

    2010-10-01

    Remote sensing missions have been conventionally performed by using satellite-onboard optical sensors with extraordinarily high reliability, on huge satellites. On the other hand, small satellites for remote-sensing missions have recently been developed intensely and operated all over the world. This paper gives a Japanese concept of the development of nano-satellites(10kg to 50kg) based on "Hodoyoshi" (Japanese word for "reasonable") reliability engineering aiming at cost-effective design of optical sensors, buses and satellites. The concept is named as "Hodoyoshi" concept. We focus on the philosophy and the key features of the concept. These are conveniently applicable to the development of optical sensors on nano-satellites. As major advantages, the optical sensors based on the "Hodoyoshi" concept are "flexible" in terms of selectability of wavelength bands, adaptability to the required ground sample distance, and optimal performance under a wide range of environmental temperatures. The first and second features mentioned above can be realized by dividing the functions of the optical sensor into modularized functional groups reasonably. The third feature becomes possible by adopting the athermal and apochromatic optics design. By utilizing these features, the development of the optical sensors become possible without exact information on the launcher or the orbit. Furthermore, this philosophy leads to truly quick delivery of nano-satellites for remote-sensing missions. On the basis of the concept, we are now developing nano-satellite technologies and five nano-satellites to realize the concept in a four-year-long governmentally funded project. In this paper, the specification of the optical sensor on the first satellite is also reported.

  20. Parameterizing atmosphere-land surface exchange for climate models with satellite data: A case study for the Southern Great Plains CART site

    Science.gov (United States)

    Gao, W.

    High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, researchers examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surface contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 x 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy's Atmospheric Radiation Measurement (ARM) Program.

  1. Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

    Science.gov (United States)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2013-10-01

    In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

  2. Radiative transfer model for satellite remote sensing of ocean color in coastal zones

    Science.gov (United States)

    Kobayashi, Hiroshi; Ohta, Sachio; Murao, Naoto; Tachibana, Harukuni; Yamagata, Sadamu

    2001-01-01

    A radiative transfer model for a coupled atmosphere-ocean system was developed for satellite remote sensing of costal pollution to estimate water-leaving radiance from polluted sea surfaces. The optical properties of suspended substances in the ocean such as phytoplankton (Skeletonema costatum and Heterosigma akashiwo), detritus, submicron particles, and inorganic particles were measured or estimated. The equation of radiative transfer in the coupled atmosphere-ocean system was solved by using the invariance imbedding method. The water-leaving radiance in clear and Case II waters, turbid waters with soil particles, and red tide waters, were calculated. It was possible to estimate the soil particle concentration of water by using the ratio of the upward radiance at different wavelengths with a high resolution sensor for the land like the Landsat TM. However, estimating the red tide phytoplankton concentration using Landsat TM was difficult, because the water-leaving radiance varies little with phytoplankton concentration, and is affected by assumed amounts of detritus.

  3. Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area: Jameson Land, East Greenland

    DEFF Research Database (Denmark)

    Hansen, Birger Ulf; Mosbech, Anders

    1994-01-01

    Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland......Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland...

  4. Satellite remote sensing of harmful algal blooms (HABs) and a potential synthesized framework.

    Science.gov (United States)

    Shen, Li; Xu, Huiping; Guo, Xulin

    2012-01-01

    Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives.

  5. Investigation of remote sensing to detect near-surface groundwater on irrigated lands

    Science.gov (United States)

    Ryland, D. W.; Schmer, F. A.; Moore, D. G.

    1975-01-01

    The application of remote sensing techniques was studied for detecting areas with high water tables in irrigated agricultural lands. Aerial data were collected by the LANDSAT-1 satellite and aircraft over the Kansas/Bostwick Irrigation District in Republic and Jewell Counties, Kansas. LANDSAT-1 data for May 12 and August 10, 1973, and aircraft flights (midday and predawn) on August 10 and 11, 1973, and June 25 and 26, 1974, were obtained. Surface and water table contour maps and active observation well hydrographs were obtained from the Bureau of Reclamation for use in the analysis. Results of the study reveal that LANDSAT-1 data (May MSS band 6 and August MSS band 7) correlate significantly (0.01 level) with water table depth for 144 active observation wells located throughout the Kansas/Bostwick Irrigation District. However, a map of water table depths of less than 1.83 meters prepared from the LANDSAT-1 data did not compare favorably with a map of seeped lands of less than 1.22 m (4 feet) to the water table. Field evaluation of the map is necessary for a complete analysis. Analysis of three fields on a within or single-field basis for the 1973 LANDSAT-1 data also showed significant correlation results.

  6. Remotely-sensed land use patterns and the presence of Anopheles larvae (Diptera: Culicidae) in Sukabumi, West Java, Indonesia.

    Science.gov (United States)

    Stoops, Craig A; Gionar, Yoyo R; Shinta; Sismadi, Priyanto; Rachmat, Agus; Elyazar, Iqbal F; Sukowati, Supratman

    2008-06-01

    Land use patterns and the occurrence of Anopheles species larvae were studied in Sukabumi District, West Java, Indonesia, from October 2004 to September 2005. Two land use maps derived using remote sensing were used. One map derived from Quickbird satellite images of 150 km2 of the Simpenan and Ciemas subdistricts (106 degrees 27' 53"-106 degrees 38' 38" E and 6 degrees 59' 59"-7 degrees 8' 46" S) in Sukabumi and one using ASTER images covering 4,000 km2 of Sukabumi District from 106 degrees 22' 15"-107 degrees 4' 1" E and 6 degrees 42' 50" - 7 degrees 26' 13" S. There was a total of 11 Anopheles spp. collected from 209 sampling locations in the area covered by the Quickbird image and a total of 15 Anopheles spp. collected from 1,600 sampling locations in the area covered by the ASTER map. For the area covered by the land use maps, ten species were found to have statistically positive relationships between land use class and species presence: Anopheles aconitus, An. annularis, An. barbirostris. An. flavirostris, An. insulaeflorum, An. kochi, An. maculatus, An. subpictus, An. sundaicus, and An. vagus. Quickbird and ASTER satellite images both produced land maps that were adequate for predicting species presence in an area. The land use classes associated with malaria vector breeding were rice paddy (An. aconitus, An. subpictus), plantation located near or adjacent to human settlements (An. maculatus), bush/shrub (An. aconitus, An. maculatus, An. sundaicus), bare land, and water body land use on the coast located < or = 250 m of the beach (An. sundaicus). Understanding the associations of habitat and species in one area, predictions of species presence or absence can be made prior to a ground survey allowing for accurate vector survey and control planning.

  7. A satellite constellation optimization for a regional GNSS remote sensing mission

    Science.gov (United States)

    Gavili Kilaneh, Narin; Mashhadi Hossainali, Masoud

    2017-04-01

    Due to the recent advances in the Global Navigation Satellite System Remote sensing (GNSS¬R) applications, optimization of a satellite orbit to investigate the Earth's properties seems significant. The comparison of the GNSS direct and reflected signals received by a Low Earth Orbit (LEO) satellite introduces a new technique to remotely sense the Earth. Several GNSS¬R missions including Cyclone Global Navigation Satellite System (CYGNSS) have been proposed for different applications such as the ocean wind speed and height monitoring. The geometric optimization of the satellite orbit before starting the mission is a key step for every space mission. Since satellite constellation design varies depending on the application, we have focused on the required geometric criteria for oceanography applications in a specified region. Here, the total number of specular points, their spatial distribution and the accuracy of their position are assumed to be sufficient for oceanography applications. Gleason's method is used to determine the position of specular points. We considered the 2-D lattice and 3-D lattice theory of flower constellation to survey whether a circular orbit or an elliptical one is suitable to improve the solution. Genetic algorithm is implemented to solve the problem. To check the visibility condition between the LEO and GPS satellites, the satellite initial state is propagated by a variable step size numerical integration method. Constellation orbit parameters achieved by optimization provide a better resolution and precession for the specular points in the study area of this research.

  8. Remote sensing application system for water environments developed for Environment Satellite 1

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Remote sensing data collected by the Environment Satellite I are characterized by high temporal resolution,high spectral resolution and mid-high spatial resolution.We designed the Remote Sensing Application System for Water Environments(RSASWE) to create an integrated platform for remote sensing data processing,parameter information extraction and thematic mapping using both remote sensing and GIS technologies.This system provides support for regional water environmental monitoring,and prediction and warning of water pollution.Developed to process and apply data collected by Environment Satellite I,this system has automated procedures including clipping,observation geometry computation,radiometric calibration,6S atmospheric correction and water quality parameter inversion.RSASWE consists of six subsystems:remote sensing image processing,basic parameter inversion,water environment remote sensing thematic outputs,application outputs,automated water environment outputs and a non-point source pollution monitoring subsystem.At present RSASWE plays an important role in operations at the Satellite Environment Center.

  9. Satellite ocean remote sensing at NOAA/NESDIS

    Science.gov (United States)

    Bayler, Eric J.

    2004-10-01

    Satellite oceanography within the Center for Satellite Applications and Research (STAR) in National Oceanic and Atmospheric Administration"s (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) focuses on observation retrievals and applications to address the NOAA missions of environmental assessment, prediction, and stewardship. Satellite oceanography within NOAA/NESDIS is an end-to-end process, addressing user requirements, sensor design support, observation retrieval research and development, calibration, applications and product research and development, the transition of research to operations, continuing product validation, and operational user support. The breadth of scientific investigation encompasses three functional areas: satellite ocean sensors, ocean dynamics/data assimilation, and marine ecosystems/climate. A cross-cutting science team from these functional areas has been established for each core subject: sea-surface temperature, sea-surface height, sea-surface roughness, ocean color, ocean surface winds, and sea ice. These science teams pursue the science and issues end to end within the core subject, with the primary objective being the transition of research to operations. Data fusion opportunities between science teams are also pursued. Each science team area addresses the common themes of calibration/validation, data assimilation, climate, and operational oceanography. Experimental and operational products, as well as user support, are provided to the user community via the NOAA OceanWatch/CoastWatch program.

  10. GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia.

    Science.gov (United States)

    Nigatu Wondrade; Dick, Øystein B; Tveite, Havard

    2014-03-01

    Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very

  11. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  12. Satellite monitoring of land-use and land-cover changes in northern Togo protected areas

    Institute of Scientific and Technical Information of China (English)

    Fousseni Folega; Chun-yu Zhang; Xiu-hai Zhao; Kperkouma Wala; Komlan Batawila; Hua-guo Huang; Marra Dourma; Koffi Akpagana

    2014-01-01

    Remote-sensing data for protected areas in northern Togo, obtained in three different years (2007, 2000, and 1987), were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index (NDVI) was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images. Maximum likelihood classification was applied to the 2007 image (ETM+2007) using a supervised classification process. Seven vegetation classes were defined from training data sets. The seven classes included the following biomes:riparian forest, dry forest, flooded vegetation, wooded savanna, fallows, parkland, and water. For these classes, the overall accuracy and the overall kappa statistic for the classi-fied map were 72.5% and 0.67, respectively. Data analyses indicated a great change in land resources;especially between 1987 and 2000 proba-bly due to the impact of democratization process social, economic, and political disorder from 1990. Wide-scale loss of vegetation occurred during this period. However, areas of vegetation clearing and regrowth were more visible between 2000 and 2007. The main source of confusion in the contingency matrix was due to heterogeneity within certain classes. It could also be due to spectral homogeneity among the classes. This research provides a baseline for future ecological landscape research and for the next management program in the area.

  13. An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

    Directory of Open Access Journals (Sweden)

    Chuli Hu

    2014-01-01

    Full Text Available In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.

  14. Urban Land Use and Land Cover Classification Using Remotely Sensed SAR Data through Deep Belief Networks

    Directory of Open Access Journals (Sweden)

    Qi Lv

    2015-01-01

    Full Text Available Land use and land cover (LULC mapping in urban areas is one of the core applications in remote sensing, and it plays an important role in modern urban planning and management. Deep learning is springing up in the field of machine learning recently. By mimicking the hierarchical structure of the human brain, deep learning can gradually extract features from lower level to higher level. The Deep Belief Networks (DBN model is a widely investigated and deployed deep learning architecture. It combines the advantages of unsupervised and supervised learning and can archive good classification performance. This study proposes a classification approach based on the DBN model for detailed urban mapping using polarimetric synthetic aperture radar (PolSAR data. Through the DBN model, effective contextual mapping features can be automatically extracted from the PolSAR data to improve the classification performance. Two-date high-resolution RADARSAT-2 PolSAR data over the Great Toronto Area were used for evaluation. Comparisons with the support vector machine (SVM, conventional neural networks (NN, and stochastic Expectation-Maximization (SEM were conducted to assess the potential of the DBN-based classification approach. Experimental results show that the DBN-based method outperforms three other approaches and produces homogenous mapping results with preserved shape details.

  15. Inexpensive land-use maps extracted from satellite data

    Science.gov (United States)

    Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.

    1979-01-01

    Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.

  16. Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

    Science.gov (United States)

    Brown, Molly E.; Essam, Timothy; Leonard, Kenneth

    2011-01-01

    Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

  17. Recent advances in remote sensing and geoinformation processing for land degradation assessment

    CERN Document Server

    Roeder, Achim

    2009-01-01

    Acknowledgements Contributors Achim Röder & Joachim Hill, Remote sensing and geoinformation processing in land degradation assessment-an introduction Part 1 Setting the scene: principles in remote sensing and spatial scene modelling for land degradation assessmentEric F. Lambin, Helmut Geist, James F. Reynolds & D. Mark Stafford-Smith, Coupled human-environment system approaches to desertification: Linking people to pixels Susan L. Ustin, Alacia Palacios-Orueta, Michael L. Whiting, Stéphane Jacquemoud & Lin Li, Remote sensing based assessm

  18. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

  19. An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems.

    Science.gov (United States)

    Emadi, Mostafa; Baghernejad, Majid; Pakparvar, Mojtaba; Kowsar, Sayyed Ahang

    2010-05-01

    This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0-30, 30-60, and 60-90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0-30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 x 150 m(2)) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.

  20. Cooling tower and plume modeling for satellite remote sensing applications

    Energy Technology Data Exchange (ETDEWEB)

    Powers, B.J.

    1995-05-01

    It is often useful in nonproliferation studies to be able to remotely estimate the power generated by a power plant. Such information is indirectly available through an examination of the power dissipated by the plant. Power dissipation is generally accomplished either by transferring the excess heat generated into the atmosphere or into bodies of water. It is the former method with which we are exclusively concerned in this report. We discuss in this report the difficulties associated with such a task. In particular, we primarily address the remote detection of the temperature associated with the condensed water plume emitted from the cooling tower. We find that the effective emissivity of the plume is of fundamental importance for this task. Having examined the dependence of the plume emissivity in several IR bands and with varying liquid water content and droplet size distributions, we conclude that the plume emissivity, and consequently the plume brightness temperature, is dependent upon not only the liquid water content and band, but also upon the droplet size distribution. Finally, we discuss models dependent upon a detailed point-by-point description of the hydrodynamics and thermodynamics of the plume dynamics and those based upon spatially integrated models. We describe in detail a new integral model, the LANL Plume Model, which accounts for the evolution of the droplet size distribution. Some typical results obtained from this model are discussed.

  1. The Application of GeoRSC Based on Domestic Satellite in Field Remote Sensing Anomaly Verification

    Science.gov (United States)

    Gao, Ting; Yang, Min; Han, Haihui; Li, Jianqiang; Yi, Huan

    2016-11-01

    The Geo REC is the digital remote sensing survey system which based on domestic satellites, and by means of it, the thesis carriedy out a remote sensing anomaly verification field application test in Nachitai area of Qinghai. Field test checks the system installation, the stability of the system operation, the efficiency of reading and show the romoate image or vector data, the security of the data management system and the accuracy of BeiDou navigation; through the test data, the author indicated that the hardware and software system could satisfy the remote sensing anomaly verification work in field, which could also could make it convenient forconvenient the workflow of remote sense survey and, improve the work efficiency,. Aat the same time, in the course of the experiment, we also found some shortcomings of the system, and give some suggestions for improvement combineding with the practical work for the system.

  2. L band microwave remote sensing and land data assimilation improve the representation of prestorm soil moisture conditions for hydrologic forecasting

    Science.gov (United States)

    Crow, W. T.; Chen, F.; Reichle, R. H.; Liu, Q.

    2017-06-01

    Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total streamflow divided by total rainfall accumulation in depth units) and prestorm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting streamflow response to future rainfall events.type="synopsis">type="main">Plain Language SummaryForecasting streamflow conditions is important for minimizing loss of life and property during flooding and adequately planning for low streamflow conditions accompanying drought. One way to improve these forecasts is measuring the amount of water in the soil—since soil moisture conditions determine what fraction of rainfall will run off horizontally into stream channels (versus vertically infiltrate into the soil column). Within the past 5 years, there have been important advances in our ability to monitor soil moisture over large scales using both satellite-based sensors and the application of new land data assimilation techniques. This paper illustrates that these advances have significantly improved our capacity to forecast how much streamflow will be generated by future precipitation events. These results may eventually be used by operational forecasters to improve flash flood forecasting and agricultural water use management.

  3. Attitude guidance and simulation with animation of a land-survey satellite motion

    Science.gov (United States)

    Somova, Tatyana

    2017-01-01

    We consider problems of synthesis of the vector spline attitude guidance laws for a land-survey satellite and an in-flight support of the satellite attitude control system with the use of computer animation of its motion. We have presented the results on the efficiency of the developed algorithms.

  4. Acoustic and satellite remote sensing of blue whale seasonality and habitat in the Northeast Pacific

    Science.gov (United States)

    Burtenshaw, Jessica C.; Oleson, Erin M.; Hildebrand, John A.; McDonald, Mark A.; Andrew, Rex K.; Howe, Bruce M.; Mercer, James A.

    2004-05-01

    Northeast Pacific blue whales seasonally migrate, ranging from the waters off Central America to the Gulf of Alaska. Using acoustic and satellite remote sensing, we have continuously monitored the acoustic activity and habitat of blue whales during 1994-2000. Calling blue whales primarily aggregate off the coast of southern and central California in the late summer, coinciding with the timing of the peak euphausiid biomass, their preferred prey. The northward bloom of primary production along the coast and subsequent northbound movements of the blue whales are apparent in the satellite and acoustic records, respectively, with the calling blue whales moving north along the Oregon and Washington coasts to a secondary foraging area with high primary productivity off Vancouver Island in the late fall. El Ni n˜o conditions, indicated by elevated sea-surface temperature and depressed regional chlorophyll- a concentrations, are apparent in the satellite records, particularly in the Southern California Bight during 1997/1998. These conditions disrupt biological production and alter the presence of calling blue whales in primary feeding locations. Remote sensing using acoustics is well suited to characterizing the seasonal movements and relative abundance of the northeast Pacific blue whales, and remote sensing using satellites allows for monitoring their habitat. These technologies are invaluable because of their ability to provide continuous large-scale spatial and temporal coverage of the blue whale migration.

  5. Design description report for a photovoltaic power system for a remote satellite earth terminal

    Science.gov (United States)

    Marshall, N. A.; Naff, G. J.

    1987-01-01

    A photovoltaic (PV) power system has been installed as an adjunct to an agricultural school at Wawatobi on the large northern island of the Republic of Indonesia. Its purpose is to provide power for a satellite earth station and a classroom. The renewable energy developed supports the video and audio teleconferencing systems as well as the facility at large. The ground station may later be used to provide telephone service. The installation was made in support of the Agency for International Development's Rural Satellite Program, whose purpose is to demonstrate the use of satellite communications for rural development assistance applications. The objective of this particular PV power system is to demonstrate the suitability of a hybrid PV engine-generator configuration for remote satellite earth stations.

  6. Emergency Response Damage Assessment using Satellite Remote Sensing Data

    Science.gov (United States)

    Clandillon, Stephen; Yésou, Hervé; Schneiderhan, Tobias; de Boissezon, Hélène; de Fraipont, Paul

    2013-04-01

    During disasters rescue and relief organisations need quick access to reliable and accurate information to be better equipped to do their job. It is increasingly felt that satellites offer a unique near real time (NRT) tool to aid disaster management. A short introduction to the International Charter 'Space and Major Disasters', in operation since 2000 promoting worldwide cooperation among member space agencies, will be given as it is the foundation on which satellite-based, emergency response, damage assessment has been built. Other complementary mechanisms will also be discussed. The user access, triggering mechanism, an essential component for this user-driven service, will be highlighted with its 24/7 single access point. Then, a clear distinction will be made between data provision and geo-information delivery mechanisms to underline the user need for geo-information that is easily integrated into their working environments. Briefly, the path to assured emergency response product quality will be presented beginning with user requirements, expressed early-on, for emergency response value-adding services. Initiatives were then established, supported by national and European institutions, to develop the sector, with SERTIT and DLR being key players, providing support to decision makers in headquarters and relief teams in the field. To consistently meet the high quality levels demanded by users, rapid mapping has been transformed via workflow and quality control standardisation to improve both speed and quality. As such, SERTIT located in Alsace, France, and DLR/ZKI from Bavaria, Germany, join their knowledge in this presentation to report about recent standards as both have ISO certified their rapid mapping services based on experienced, well-trained, 24/7 on-call teams and established systems providing the first crisis analysis product in 6 hours after satellite data reception. The three main product types provided are then outlined: up-to-date pre

  7. Remote sensing and GIS technology in the Global Land Ice Measurements from Space (GLIMS) Project

    Science.gov (United States)

    Raup, B.; Kääb, Andreas; Kargel, J.S.; Bishop, M.P.; Hamilton, G.; Lee, E.; Paul, F.; Rau, F.; Soltesz, D.; Khalsa, S.J.S.; Beedle, M.; Helm, C.

    2007-01-01

    Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyze them for glacier extent and changes, and to assess these change data in terms of forcings. The consortium is organized into a system of Regional Centers, each of which is responsible for glaciers in their region of expertise. Specialized needs for mapping glaciers in a distributed analysis environment require considerable work developing software tools: terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; change detection and analysis; visualization of images and derived data; interpretation and archival of derived data; and analysis to ensure consistency of results from different Regional Centers. A global glacier database has been designed and implemented at the National Snow and Ice Data Center (Boulder, CO); parameters have been expanded from those of the World Glacier Inventory (WGI), and the database has been structured to be compatible with (and to incorporate) WGI data. The project as a whole was originated, and has been coordinated by, the US Geological Survey (Flagstaff, AZ), which has also led the development of an interactive tool for automated analysis and manual editing of glacier images and derived data (GLIMSView). This article addresses remote sensing and Geographic Information Science techniques developed within the framework of GLIMS in order to fulfill the goals of this distributed project. Sample applications illustrating the developed techniques are also shown. ?? 2006 Elsevier Ltd. All rights reserved.

  8. The Use of Remote Sensing Satellites for Verification in International Law

    Science.gov (United States)

    Hettling, J. K.

    The contribution is a very sensitive topic which is currently about to gain significance and importance in the international community. It implies questions of international law as well as the contemplation of new developments and decisions in international politics. The paper will begin with the meaning and current status of verification in international law as well as the legal basis of satellite remote sensing in international treaties and resolutions. For the verification part, this implies giving a definition of verification and naming its fields of application and the different means of verification. For the remote sensing part, it involves the identification of relevant provisions in the Outer Space Treaty and the United Nations General Assembly Principles on Remote Sensing. Furthermore it shall be looked at practical examples: in how far have remote sensing satellites been used to verify international obligations? Are there treaties which would considerably profit from the use of remote sensing satellites? In this respect, there are various examples which can be contemplated, such as the ABM Treaty (even though out of force now), the SALT and START Agreements, the Chemical Weapons Convention and the Conventional Test Ban Treaty. It will be mentioned also that NGOs have started to verify international conventions, e.g. Landmine Monitor is verifying the Mine-Ban Convention. Apart from verifying arms control and disarmament treaties, satellites can also strengthen the negotiation of peace agreements (such as the Dayton Peace Talks) and the prevention of international conflicts from arising. Verification has played an increasingly prominent role in high-profile UN operations. Verification and monitoring can be applied to the whole range of elements that constitute a peace implementation process, ranging from the military aspects through electoral monitoring and human rights monitoring, from negotiating an accord to finally monitoring it. Last but not least the

  9. Geothermal Heat Flux Assessment Using Remote Sensing Land Surface Temperature and Simulated Data. Case Studies at the Kenyan Rift and Yellowstone Geothermal Areas

    Science.gov (United States)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C.; van der Meer, F. D.

    2015-12-01

    In this work we propose an innovative approach to assess the geothermal heat flux anomalies in the regions of the Kenyan Rift and the Yellowstone geothermal areas. The method is based on the land surface temperature (LST) differences obtained between remote sensing data and land surface model simulations. The hypothesis is that the model simulations do not account for the subsurface geothermal heat source in the formulation. Remote sensing of surface emitted radiances is able to detect at least the radiative portion of the geothermal signal that is not in the models. Two methods were proposed to assess the geothermal component of LST (LSTgt) based on the aforementioned hypothesis: a physical model and a data mining approach. The LST datasets were taken from the Land Surface Analysis Satellite Application Facilities products over Africa and the Copernicus Programme for North America, at a spatial resolution of 3-5 km. These correspond to Meteosat Second Generation and Geostationary Operational Environmental Satellite system satellites data respectively. The Weather Research and Forecasting model was used to simulate LST based on atmospheric and surface characteristics using the Noah land surface model. The analysis was carried out for a period of two months by using nighttime acquisitions. Higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data were also used on the Kenyan area to produce similar outputs employing existing methods. The comparison of the results from both methods and areas illustrated the potential of the data and methodologies for geothermal applications.

  10. Fusing Mobile In Situ Observations and Satellite Remote Sensing of Chemical Release Emissions to Improve Disaster Response

    Directory of Open Access Journals (Sweden)

    Ira Leifer

    2016-09-01

    Full Text Available Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and spacebased remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG Surveyor, a commuter car modified for science. Mobile surface in situ CH4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr-1. Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. This study demonstrated a novel application of satellite aerosol remote

  11. Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

    Science.gov (United States)

    Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

    2010-12-01

    The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture

  12. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    Science.gov (United States)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  13. Satellite remote sensing and spectroscopy: Joint ACE-Odin meeting, October 2015

    Science.gov (United States)

    Bernath, P. F.

    2017-01-01

    The Atmospheric Chemistry Experiment (ACE) and Odin satellite teams had a joint meeting in October, 2015 and it was decided to publish some of the papers presented as a special issue of this journal (JQSRT). ACE and Odin measure atmospheric composition by remote sensing from low Earth orbit. This Special Issue also includes papers about other space instruments and related ground-based observations. Remote sensing of the atmosphere relies entirely on spectroscopy so many of the papers report on spectroscopic measurements of atmospheric molecules and computer programs used for spectroscopic analysis.

  14. LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

    Science.gov (United States)

    Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

    2014-11-01

    The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

  15. DESERT ECOSYSTEMS: MAPPING, MONITORING & ASSESSMENT USING SATELLITE REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    A. S. Arya

    2012-09-01

    Full Text Available Desert ecosystems are unique but fragile ecosystems , mostly vulnerable to a variety of degradational processes like water erosion, vegetal degradation, salinity, wind erosion , water logging etc. Some researchers consider desertification to be a process of change, while others view it as the end result of a process of change. There is an urgent need to arrest the process of desertification and combat land degradation. Under the auspices of the United Nations Convention to Combat Desertification (UNCCD, Space Applications Centre, Ahmedabad has undertaken the task of mapping, monitoring and assessment of desertification carrying out pilot project in hot and cold desert regions in drylands on 1:50,000 scale followed by systematic Desertification Status Mappaing (DSM of India on 1:500,000 scale.

  16. The development of a land use inventory for regional planning using satellite imagery

    Science.gov (United States)

    Hessling, A. H.; Mara, T. G.

    1975-01-01

    Water quality planning in Ohio, Kentucky, and Indiana is reviewed in terms of use of land use data and satellite imagery. A land use inventory applicable to water quality planning and developed through computer processing of LANDSAT-1 imagery is described.

  17. Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

    Science.gov (United States)

    Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

    2016-04-01

    Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover

  18. Geographic Object-based Image Analysis for Developing Cryospheric Surface Mapping Application using Remotely Sensed High-Resolution Satellite Imagery

    Science.gov (United States)

    Jawak, S. D.; Luis, A. J.

    2015-12-01

    A novel semi-automated method was devised by coupling spectral index ratios (SIRs) and geographic object-based image analysis (GEOBIA) to extract cryospheric geoinformation from very high resolution WorldView 2 (WV-2) satellite imagery. The present study addresses development of multiple rule sets for GEOBIA-based classification of WV-2 imagery to accurately extract land cover features in the Larsemann Hills, Antarctica. Multi-level segmentation process was applied to WV-2 image to generate different sizes of geographic image objects corresponding to various land cover features w.r.t scale parameter. Several SIRs were applied to geographic objects at different segmentation levels to classify landmass, man-made features, snow/ice, and water bodies. A specific attention was paid to water body class to identify water areas at the image level, considering their uneven appearance on landmass and ice. The results illustrated that synergetic usage of SIRs and GEOBIA can provide accurate means to identify land cover classes with an overall classification accuracy of ≈97%. In conclusion, the results suggest that GEOBIA is a powerful tool for carrying out automatic and semiautomatic analysis for most cryospheric remote-sensing applications, and the synergetic coupling with pixel-based SIRs is found to be a superior method for mining geoinformation.

  19. Remote sensing satellite formation for bistatic synthetic aperture radar observation

    Science.gov (United States)

    D'Errico, Marco; Moccia, Antonio

    2001-12-01

    In recent years the Italian Space Agency has been proceeding to the definition and launch of small missions. In this ambit, the BISSAT mission was proposed and selected along with five other missions for a competitive Phase A study. BISSAT mission concept consists in flying a passive SAR on board a small satellite, which observes the area illuminated by an active SAR, operating on an already existing large platform. Several scientific applications of bistatic measurements can be envisaged: improvement of image classification and pattern recognition, derivation of medium-resolution digital elevation models, velocity measurements, measurements of sea-wave spectra. BISSAT payload is developed on the basis of the X-band SAR of the COSMO/SkyMed mission, while BISSAT bus is based on an upgrade of MITA. Orbit design has been performed, leading to the same orbit parameters apart from the ascending node right ascension (5.24 degree(s) shift) and the time of the passage on the ascending node (1.17s shift). A minimum distance at the passage of the orbit crossing point of about 42 km (5.7s) is computed. To maintain adequate swath overlap along the orbit, attitude maneuver or antenna electronic steering must be envisaged and traded-off taking into account radar performance and cost of hardware upgrade.

  20. Dealing with missing data in remote sensing images within land and crop classification

    Science.gov (United States)

    Skakun, Sergii; Kussul, Nataliia; Basarab, Ruslan

    Optical remote sensing images from space provide valuable data for environmental monitoring, disaster management [1], agriculture mapping [2], so forth. In many cases, a time-series of satellite images is used to discriminate or estimate particular land parameters. One of the factors that influence the efficiency of satellite imagery is the presence of clouds. This leads to the occurrence of missing data that need to be addressed. Numerous approaches have been proposed to fill in missing data (or gaps) and can be categorized into inpainting-based, multispectral-based, and multitemporal-based. In [3], ancillary MODIS data are utilized for filling gaps and predicting Landsat data. In this paper we propose to use self-organizing Kohonen maps (SOMs) for missing data restoration in time-series of satellite imagery. Such approach was previously used for MODIS data [4], but applying this approach for finer spatial resolution data such as Sentinel-2 and Landsat-8 represents a challenge. Moreover, data for training the SOMs are selected manually in [4] that complicates the use of the method in an automatic mode. SOM is a type of artificial neural network that is trained using unsupervised learning to produce a discretised representation of the input space of the training samples, called a map. The map seeks to preserve the topological properties of the input space. The reconstruction of satellite images is performed for each spectral band separately, i.e. a separate SOM is trained for each spectral band. Pixels that have no missing values in the time-series are selected for training. Selecting the number of training pixels represent a trade-off, in particular increasing the number of training samples will lead to the increased time of SOM training while increasing the quality of restoration. Also, training data sets should be selected automatically. As such, we propose to select training samples on a regular grid of pixels. Therefore, the SOM seeks to project a large number

  1. People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

    Directory of Open Access Journals (Sweden)

    Stefanie M. Herrmann

    2014-09-01

    Full Text Available Mounting evidence from satellite observations of a re-greening across much of the Sahel and Sudan zones over the past three decades has raised questions about the extent and reversibility of desertification. Historical ground data that could help in interpreting the re-greening are scarce. To fill that void, we tapped into the collective memories of local land users from central and western Senegal in 39 focus groups and assessed the spatial association between their perceptions of vegetation changes over time and remote sensing-derived trends. To provide context to the vegetation changes, we also explored the land users' perspective on the evolution of other environmental and human variables that are potentially related to the greening, using participatory research methods. While increases in vegetation were confirmed by the study participants for certain areas, which spatially corresponded to satellite-observed re-greening, vegetation degradation dominated their perceptions of change. This degradation, although spatially extensive according to land users, flies under the radar of coarse-resolution remote sensing data because it is not necessarily associated with a decrease in biomass but rather with undesired changes in species composition. Few significant differences were found in the perceived trends of population pressure, environmental, and livelihood variables between communities that have greened up according to satellite data and those that have not. Our findings challenge the prevailing chain of assumptions of the satellite-observed greening trend indicating an improvement of environmental conditions in the sense of a rehabilitation of the vegetation cover after the great droughts of the 1970s and 1980s, and the improvement of environmental conditions possibly translating into more stable livelihoods and greater well-being of the populations. For monitoring desertification and rehabilitation, there is a need to develop remote sensing

  2. A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery

    Science.gov (United States)

    kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2013-12-01

    A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery Ugur ALGANCI1, Sinasi KAYA1,2, Elif SERTEL1,2,Berk USTUNDAG3 1 ITU, Center for Satellite Communication and Remote Sensing, 34469, Maslak-Istanbul,Turkey 2 ITU, Department of Geomatics, 34469, Maslak-Istanbul, Turkey 3 ITU, Agricultural and Environmental Informatics Research Center,34469, Maslak-Istanbul,Turkey alganci@itu.edu.tr, kayasina@itu.edu.tr, sertele@itu.edu.tr, berk@berk.tc ABSTRACT Cultivated land determination and their area estimation are important tasks for agricultural management. Derived information is mostly used in agricultural policies and precision agriculture, in specifically; yield estimation, irrigation and fertilization management and farmers declaration verification etc. The use of satellite image in crop type identification and area estimate is common for two decades due to its capability of monitoring large areas, rapid data acquisition and spectral response to crop properties. With launch of high and very high spatial resolution optical satellites in the last decade, such kind of analysis have gained importance as they provide information at big scale. With increasing spatial resolution of satellite images, image classification methods to derive the information form them have become important with increase of the spectral heterogeneity within land objects. In this research, pixel based classification with maximum likelihood algorithm and object based classification with nearest neighbor algorithm were applied to 2012 dated 2.5 m resolution SPOT 5 satellite images in order to investigate the accuracy of these methods in determination of cotton and corn planted lands and their area estimation. Study area was selected in Sanliurfa Province located on Southeastern Turkey that contributes to Turkey's agricultural production in a major way. Classification results were compared in terms of crop type identification using

  3. Design of motion compensation mechanism of satellite remote sensing camera

    Science.gov (United States)

    Gu, Song; Yan, Yong; Xu, Kai; Jin, Guang

    2011-08-01

    With the development of aerospace remote sensing technology, the ground resolution of remote sensing camera enhances continuously. Since there is relative motion between camera and ground target when taking pictures, the target image recorded in recording media is moved and blurred. In order to enhance the imaging quality and resolution of the camera, the image motion had to be compensated. In order to abate the effect of image motion to image quality of space camera and improve the resolution of the camera, the compensation method of image motion to space camera is researched. First, the reason of producing drift angle and adjustment principle are analyzed in this paper. This paper introduce the composition and transmission principle of image motion compensation mechanism. Second, the system adopts 80C31 as controller of drift angle, and adopts stepping motor for actuators, and adopts absolute photoelectric encoder as the drift Angle measuring element. Then the control mathematical model of the image motion compensation mechanism are deduced, and it achieve the closed-loop control of the drift angle position. At the last, this paper analyses the transmission precision of the mechanism. Through the experiment, we measured the actual precision of the image motion compensation mechanism, and compared with the theoretical analysis.There are two major contributions in this paper. First, the traditional image motion compensation mechanism is big volume and quality heavy. This has not fit for the development trend of space camera miniaturization and lightweight. But if reduce the volume and quality of mechanism, it will bring adverse effects for the precision and stiffness of mechanism. For this problem, This paper designed a image motion compensation that have some advantages such as small size, light weight at the same time, high precision, stiffness and so on. This image motion compensation can be applicable to the small optics cameras with high resolution. Second

  4. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale

    Directory of Open Access Journals (Sweden)

    Christiane Schmullius

    2013-05-01

    Full Text Available Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Very High Resolution Radiometer (AVHRR and (Advanced Along Track Scanning Radiometer ((AATSR are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude. Within this study, we compared land surface temperature products from (AATSR, MODIS and AVHRR with an in situ air temperature (Tair database provided by the National Climate Data Center (NCDC. Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST and air temperature for the overlapping time period of the remote sensing data (2000–2005. In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (AATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

  5. Regional assessment of lake water clarity using satellite remote sensing

    Directory of Open Access Journals (Sweden)

    David L. SKOLE

    2003-09-01

    Full Text Available Lake water clarity as measured by Secchi disk transparency (SDT is a cost-effective measure of water quality. However, in regions where there are thousands of lakes, sampling even a small proportion of those lakes for SDT year after year is cost prohibitive. Remote sensing has the potential to be a powerful tool for assessing lake clarity over large spatial scales. The overall objective of our study was to examine whether Landsat-7 ETM+ could be used to measure water clarity across a large range of lakes. Our specific objectives were to: 1 develop a regression model to estimate SDT from Landsat data calibrated using 93 lakes in Michigan, U.S.A., and to 2 examine how the distribution of SDT across the 93 calibration lakes influenced the model. Our calibration dataset included a large number of lakes with a wide range of SDT values that captured the summer statewide distribution of SDT values in Michigan. Our regression model had a much lower r2 value than previously published studies conducted on smaller datasets. To examine the importance of the distribution of calibration data, we simulated a calibration dataset with a different SDT distribution by sub-sampling the original dataset to match the distribution of previous studies. The sub-sampled dataset had a much higher percentage of lakes with shallow water clarity, and the resulting regression model had a much higher r2 value than our original model. Our study shows that the use of Landsat to measure water clarity is sensitive to the distribution of water clarity used in the calibration set.

  6. Mapping land cover from satellite images: A basic, low cost approach

    Science.gov (United States)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

    1978-01-01

    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  7. Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Peter Corke

    2009-05-01

    Full Text Available Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs. We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

  8. Land cover for Ukraine: the harmonization of remote sensing and ground-based data

    Science.gov (United States)

    Lesiv, M.; Shchepashchenko, D.; Shvidenko, A.; See, L. M.; Bun, R.

    2012-12-01

    This study focuses on the development of a land cover map of the Ukraine through harmonization of remote sensing and ground-based data. At present there is no land cover map of the Ukraine available that is of sufficient accuracy for use in environmental modeling. The existing remote sensing data are not enough accurate. In this study we compare the territory of the Ukraine from three global remote sensing products (GlobCover 2009, MODIS Land Cover and GLC-2000) using a fuzzy logic methodology in order to capture the uncertainty in the classification of land cover. The results for the Ukraine show that GlobCover 2009, MODIS Land Cover and GLC-2000 have a fuzzy agreement of 65%. We developed a weighted algorithm for the creation of a land cover map based on an integration of a number of global land cover and remote sensing products including the GLC-2000, GlobCover 2009, MODIS Land Cover, the Vegetation Continuous Fields product, digital map of administrative units and forest account data at the local level. This weighted algorithm is based on the results of comparing these products and an analysis of a dataset of validation points for different land cover types in the Ukraine. We applied this algorithm to generate a forest land cover type map. This raster map contains a forest expectation index that was calculated for each pixel. Forest land was then allocated based on forest statistics at the local level. Areas with a higher forest expectation index were allocated with forest first until the results matched the forest statistics. The result is the first digital map of forest (with a spatial resolution of 300m) for the Ukraine, which consistent with forest and land accounts, remote sensing datasets and GIS products. The forest land was well defined in forest rich areas (i.e. in the northern part of the Ukraine, the Carpathians and the Crimea); well less accurate areas were identified in the steppe due to heterogeneous land cover. Acknowledgements. This research was

  9. Need for, and financial feasibility of, satellite-aided land mobile communications

    Science.gov (United States)

    Castruccio, P. A.; Marantz, C. S.; Freibaum, J.

    Questions regarding the role of a mobile-satellite system in augmenting the terrestrial communications system are considered, and a market assessment study is discussed. Aspects of an investment analysis are examined, taking into account a three phase financial study of four postulated land Mobile Satellite Service (LMSS) systems, project profitability evaluation methods, risk analysis methods, financial projections, potential investor acceptance standards, and a risk analysis. It is concluded that a satellite augmented terrestrial mobile service appears to be economically and technically superior to a service depending exclusively on terrestrial systems. The interest in the Mobile Satellite Service is found to be worldwide, and the ground equipment market is potentially large.

  10. Reflectance properties of selected arctic-boreal land cover types: field measurements and their application in remote sensing

    Directory of Open Access Journals (Sweden)

    J. I. Peltoniemi

    2008-03-01

    Full Text Available We developed a mobile remote sensing measurement facility for spectral and anisotropic reflectance measurements. We measured reflection properties (BRF of over 100 samples from most common land cover types in boreal and subarctic regions. This extensive data set serves as a unique reference opportunity for developing interpretation algorithms for remotely sensed materials as well as for modelling climatic effects in the boreal and subarctic zones.

    Our goniometric measurements show that the reflectances of the most common land cover types in the boreal and subarctic region can differ from each other by a factor of 100. Some types are strong forward scatterers, some backward scatterers, some reflect specularly, some have strong colours, some are bright in visual, some in infrared. We noted that spatial variations in reflectance, even among the same type of vegetation, can be well over 20%, diurnal variations of the same order and seasonal variation often over a factor of 10. This has significant consequences on the interpretation of satellite and airborne images and on the development of radiation regime models in both optical remote sensing and climate change research.

    We propose that the accuracy of optical remote sensing can be improved by an order of magnitude, if better physical reflectance models can be introduced. Further improvements can be reached by more optimised design of sensors and orbits/flight lines, by the effective combining of several data sources and better processing of atmospheric effects. We conclude that more extensive and systematic laboratory experiments and field measurements are needed, with more modelling effort.

  11. The current and potential role of satellite remote sensing in the campaign against malaria

    Science.gov (United States)

    Kazansky, Yaniv; Wood, Danielle; Sutherlun, Jacob

    2016-04-01

    Malaria and other vector borne diseases claim lives and cause illness, especially in less developed countries. Although well understood methods, such as spraying and insecticidal nets, are identified as effective deterrents to malaria transmission by mosquitoes, the nations that have the greatest burden from the disease also struggle to deploy such measures sufficiently. More targeted and up to date information is needed to identify which regions of malaria-endemic countries are most likely to be at risk of malaria in the near future. This will allow national governments, local officials and public health workers to deploy protective equipment and personnel where they are most needed. This paper explores the role of environmental data generated via satellite remote sensing as an ingredient to a Malaria Early Warning System. Data from remote sensing satellites can cover broad geographical areas frequently and consistently. Much of the relevant data may be accessed by malaria-endemic countries at minimal cost via international data sharing polices. While previous research studies have demonstrated the potential to assign malaria risk to a geographic region based on indicators from satellites and other sources, there is still a need to deploy such tools in a broader and more operational manner to inform decision making on malaria management. This paper describes current research on the use of satellite-based environmental data to predict malaria risk and examines the barriers and opportunities for implementing Malaria Early Warning Systems enabled by satellite remote sensing. A Systems Architecture Framework analyses the components of a Malaria Early Warning System and highlights the need for effective coordination across public and private sector organizations.

  12. Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices

    Directory of Open Access Journals (Sweden)

    D. G. Hadjimitsis

    2010-01-01

    Full Text Available Solar radiation reflected by the Earth's surface to satellite sensors is modified by its interaction with the atmosphere. The objective of applying an atmospheric correction is to determine true surface reflectance values and to retrieve physical parameters of the Earth's surface, including surface reflectance, by removing atmospheric effects from satellite images. Atmospheric correction is arguably the most important part of the pre-processing of satellite remotely sensed data. Such a correction is especially important in cases where multi-temporal images are to be compared and analyzed. For agricultural applications, in which several vegetation indices are applied for monitoring purposes, multi-temporal images are used. The integration of vegetation indices from remotely sensed images with other hydro-meteorological data is widely used for monitoring natural hazards such as droughts. Indeed, the most important task is to retrieve the true values of the vegetation status from the satellite-remotely sensed data. Any omission of considering the effects of the atmosphere when vegetation indices from satellite images are used, may lead to major discrepancies in the final outcomes. This paper highlights the importance of considering atmospheric effects when vegetation indices, such as DVI, NDVI, SAVI, MSAVI and SARVI, are used (or considered and presents the results obtained by applying the darkest-pixel atmospheric correction method on ten Landsat TM/ETM+ images of Cyprus acquired from July to December 2008. Finally, in this analysis, an attempt is made to determine evapotranspiration and to examine its dependence on the consideration of atmospheric effects when multi-temporal image data are used. It was found that, without applying any atmospheric correction, the real daily evapotranspiration was less than the one found after applying the darkest pixel atmospheric correction method.

  13. .A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

    Science.gov (United States)

    Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

  14. Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

    Science.gov (United States)

    Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

    2010-05-01

    Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection

  15. an assessment of the land use and land cover changes in shurugwi ...

    African Journals Online (AJOL)

    Dr Osondu

    Geographic Information System and remote sensing techniques. Three satellite ... degraded land covers 26.6% with the rest shared between vegetation (18.1%) and water (2%). There has ... decision support system employing land cover.

  16. AN ASSESSMENT OF LAND USE CHANGES IN FUQING COUNTY OF CHINA USING REMOTE SENSING TECHNOLOGY

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Fuqing County of southeast China has witnessed significant land use changes during the last decade. Remote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monitor land use changes in the county. Two TM scenes from 1991 and 1996 were used to cover the county and a five-year time period. Digital image processing was carried out for the remotely sensed data to produce classified images. The images were further processed using GIS software to generate GIS databases so that the data could be further spatially analyzed taking the advantages of the software. Land use change areas were determined by using the change detection technique. The comparison of the two classified TM images using the above technologies reveals that during the five study years, a large area of arable lands in the county has been lost and deforestation has taken place largely because of the dramatic increase in built-up land and orchard. The conclusive statistical information is useful to understand the processes, causes and impacts of the land use changes in the county. The major driving force to the land use changes in the county appeared to be the rapid economic development. The decision makers of the county have to pay more attention to the land use changes for the county′ s sustainable development.

  17. Considerations and techniques for incorporating remotely sensed imagery into the land resource management process.

    Science.gov (United States)

    Brooner, W. G.; Nichols, D. A.

    1972-01-01

    Development of a scheme for utilizing remote sensing technology in an operational program for regional land use planning and land resource management program applications. The scheme utilizes remote sensing imagery as one of several potential inputs to derive desired and necessary data, and considers several alternative approaches to the expansion and/or reduction and analysis of data, using automated data handling techniques. Within this scheme is a five-stage program development which includes: (1) preliminary coordination, (2) interpretation and encoding, (3) creation of data base files, (4) data analysis and generation of desired products, and (5) applications.

  18. Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

    Science.gov (United States)

    Olokeogun, O. S.; Iyiola, K.; Iyiola, O. F.

    2014-11-01

    Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

  19. Long-Term Monitoring of Desert Land and Natural Resources and Application of Remote Sensing Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Hamada, Yuki [Argonne National Lab. (ANL), Argonne, IL (United States); Rollins, Katherine E. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-11-01

    Monitoring environmental impacts over large, remote desert regions for long periods of time can be very costly. Remote sensing technologies present a promising monitoring tool because they entail the collection of spatially contiguous data, automated processing, and streamlined data analysis. This report provides a summary of remote sensing products and refinement of remote sensing data interpretation methodologies that were generated as part of the U.S. Department of the Interior Bureau of Land Management Solar Energy Program. In March 2015, a team of researchers from Argonne National Laboratory (Argonne) collected field data of vegetation and surface types from more than 5,000 survey points within the eastern part of the Riverside East Solar Energy Zone (SEZ). Using the field data, remote sensing products that were generated in 2014 using very high spatial resolution (VHSR; 15 cm) multispectral aerial images were validated in order to evaluate potential refinements to the previous methodologies to improve the information extraction accuracy.

  20. Urban land use extraction from Very High Resolution remote sensing imagery using a Bayesian network

    Science.gov (United States)

    Li, Mengmeng; Stein, Alfred; Bijker, Wietske; Zhan, Qingming

    2016-12-01

    Urban land use extraction from Very High Resolution (VHR) remote sensing images is important in many applications. This study explores a novel way to characterize the spatial arrangement of land cover features, and to integrate it with commonly used land use indicators. Characterization is done based upon building objects, taking their functional properties into account. We categorize the objects to a set of building types according to their geometrical, morphological, and contextual attributes. The spatial arrangement is characterized by quantifying the distribution of building types within a land use unit. Moreover, a set of existing land use indicators primarily based upon the coverage ratio and density of land cover features is investigated. A Bayesian network integrates the spatial arrangement and land use indicators, by which the urban land use is inferred. We applied urban land use extraction to a Pléiades VHR image over the city of Wuhan, China. Our results showed that integrating the spatial arrangement significantly improved the accuracy of urban land use extraction as compared with using land use indicators alone. Moreover, the Bayesian network method produced results comparable to other commonly used classifiers. We concluded that the proposed characterization of spatial arrangement and Bayesian network integration was effective for urban land use extraction from VHR images.

  1. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    Science.gov (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  2. Intelligent remote sensing satellite system%智能遥感卫星系统

    Institute of Scientific and Technical Information of China (English)

    张兵

    2011-01-01

    分析了当前遥感卫星系统存在的一些不足,论述了新一代"智能遥感卫星系统"的概念及其主要特点,对其中自适应遥感成像和星上数据实时处理两个核心部分进行重点介绍,并对其涉及的关键科学问题和关键技术进行阐述.设计了一套具有自适应成像和应用模式优化能力的智能高光谱卫星有效载荷系统.该系统由用于区域背景信息获取的前视预判遥感器、用于地表详细观测的主遥感器以及星上数据实时处理和分析3部分组成.对智能高光谱卫星的工作原理和流程进行介绍,并呼吁中国尽快围绕智能遥感卫星系统开展一些前沿性的科学理论和关键技术研究,以实现中国在卫星遥感领域的跨越式发展.%This paper analyzes the disadvantages of the current remote sensing satellite systems, and describes the concept of the latest generation "intelligent remote sensing satellite system" and its main characteristics which mainly includes: (1) the adaptive remote sensor system; (2) the onboard real-time data processing system; and also introduces the key scientific issues and the key technologies involved. This paper presents the design of an intelligent hyperspectral sateUite payload system with adaptive imaging and application mode optimization capacity, which consists of three parts: (1) a fore-field pfe-judgment sensor for regional background information acquisition; (2) a main sensor for detailed surface observations; (3) an onboard real-time data processing and analysis subsystem. It also introduces the working principles and processes of intelligent hyperspectral satellite,and calls for the research on some frontier scientific theories and key technologies related to the intelligent remote sensing satelLite system in an early stage to realize the leap-forward development in the field of remote sensing satellite in China.

  3. Continuous evaluation of land cover restoration of tsunami struck plains in Japan by using several kinds of optical satellite image in time series

    Science.gov (United States)

    Hashiba, H.

    2015-09-01

    The Mw 9.0 earthquake that struck Japan in 2011 was followed by a large-scale tsunami in the Tohoku region. The damage in the coastal plane was extensively displayed through many satellite images. Furthermore, satellite imaging is requested for the ongoing evaluation of the restoration process. The reconstruction of the urban structure, farmlands, grassland, and coastal forest that collapsed under the large tsunami requires effective long-term monitoring. Moreover, the post-tsunami land cover dynamics can be effectively modeled using time-constrained satellite data to establish a prognosis method for the mitigation of future tsunami impact. However, the remote satellite capture of a long-term restoration process is compromised by accumulating spatial resolution effects and seasonal influences. Therefore, it is necessary to devise a method for data selection and dataset structure. In the present study, the restoration processes were investigated in four years following the disaster in a part of the Sendai plain, northeast Japan, from same-season satellite images acquired by different optical sensors. Coastal plains struck by the tsunami are evaluated through land-cover classification processing using the clustering method. The changes in land cover are analyzed from time-series optical images acquired by Landsat-5/TM, 7/ETM+, 8/OLI, EO-1/ALI, and ALOS-1/AVNIR-2. The study reveals several characteristics of the change in the inundation area and signs of artificial and natural restoration.

  4. Linking Satellite Remote Sensing Based Environmental Predictors to Disease: AN Application to the Spatiotemporal Modelling of Schistosomiasis in Ghana

    Science.gov (United States)

    Wrable, M.; Liss, A.; Kulinkina, A.; Koch, M.; Biritwum, N. K.; Ofosu, A.; Kosinski, K. C.; Gute, D. M.; Naumova, E. N.

    2016-06-01

    90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

  5. LINKING SATELLITE REMOTE SENSING BASED ENVIRONMENTAL PREDICTORS TO DISEASE: AN APPLICATION TO THE SPATIOTEMPORAL MODELLING OF SCHISTOSOMIASIS IN GHANA

    Directory of Open Access Journals (Sweden)

    M. Wrable

    2016-06-01

    Full Text Available 90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

  6. Optimal link budget to maximize data receiving from remote sensing satellite at different ground stations

    Science.gov (United States)

    Godse, Vinay V.; Rukmini, B.

    2016-10-01

    Earth observation satellite plays a significant role for global situation awareness. The earth observation satellite uses imaging payloads in RF and IR bands, which carry huge amount of data, needs to be transferred during visibility of satellite over the ground station. Location of ground station plays a very important role in communication with LEO satellites, as orbital speed of LEO satellite is much higher than earth rotation speed. It will be accessible for particular equatorial ground station for a very short duration. In this paper we want to maximize data receiving by optimizing link budget and receiving data at higher elevation links. Data receiving at multiple ground stations is preferred to counter less pass duration due to higher elevation links. Our approach is to calculate link budget for remote sensing satellite with a fixed power input and varying different minimum elevation angles to obtain maximum data. The minimum pass duration should be above 3 minutes for effective communication. We are proposing to start process of command handling as soon as satellite is visible to particular ground station with low elevation angle up to 5 degree and start receiving data at higher elevation angles to receive data with higher speed. Cartosat-2B LEO earth observation satellite is taken for the case study. Cartosat-2B will complete around 14 passes over equator in a day, out of which only 4-5 passes will be useful for near equator ground stations. Our aim is to receive data at higher elevation angles at higher speed and increase amount of data download, criteria being minimum pass duration of 3 minutes, which has been set for selecting minimum elevation angle.

  7. Remote Sensing and Synchronous Land Surface Measurements of Soil Moisture and Soil Temperature in the Field

    Science.gov (United States)

    Kolev, N. V.; Penev, K. P.; Kirkova, Y. M.; Krustanov, B. S.; Nazarsky, T. G.; Dimitrov, G. K.; Levchev, C. P.; Prodanov, H. I.; Kraleva, L. H.

    1998-01-01

    The paper presents the results of remote sensing and synchronous land surface measurements for estimation of soil (surface and profile) water content and soil temperature for different soil types in Bulgaria. The relationship between radiometric temperature and soil surface water content is shown. The research is illustrated by some results from aircraft and land surface measurements carried out over three test areas near Pleven, Sofia and Plovdiv, respectively, during the period 1988-1990.

  8. A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions

    OpenAIRE

    Li, Xiaodong; Ling, Feng; Giles M. Foody; Du, Yun

    2016-01-01

    The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD)is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the ...

  9. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

    Directory of Open Access Journals (Sweden)

    Xueke Li

    2016-05-01

    Full Text Available The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1 opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m to EO-1 Hyperion (with a spatial resolution of 30 m. The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC, pixel-based support vector machine (PSVM, hybrid maximum likelihood classifier (HMLC, and hybrid support vector machine (HSVM were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the

  10. Detection of Seagrass Distribution Changes from 1991 to 2006 in Xincun Bay, Hainan, with Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chaoyu Yang

    2009-02-01

    Full Text Available Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides,Thalassia hemperichii distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI. Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.

  11. Detection of seagrass distribution changes from 1991 to 2006 in xincun bay, hainan, with satellite remote sensing.

    Science.gov (United States)

    Yang, Dingtian; Yang, Chaoyu

    2009-01-01

    Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.

  12. Remote Sensing by Satellite for Environmental Education: A Survey and a Proposal for Teaching at Upper Secondary and University Level.

    Science.gov (United States)

    Bosler, Ulrich

    Knowledge of the environment has grown to such an extent that information technology (IT) is essential to make sense of the available data. An example of this is remote sensing by satellite. In recent years this field has grown in importance and remote sensing is used for a range of uses including the automatic survey of wheat yields in North…

  13. INTEGRATED TECHNOLOGY OF DATA REMOTE SENSING AND GIS TECHNIQUES ASSESS THE LAND USE AND LAND COVER CHANGES OF MADURAI CITY BETWEEN THE YEAR 2003-2013

    Directory of Open Access Journals (Sweden)

    P.Venkataraman

    2016-03-01

    Full Text Available The present study focuses on the nature and pattern of urban expansion of Madurai city over its surrounding region during the period from 2003 to 2013. Based on Its proximity to the Madurai city, Preparation of various thematic data such Land use and Land cover using Land sat data. Create a land use land cover map from satellite imagery using supervised classification. Find out the areas from the classified data. The study is Based on secondary data, the satellite imagery has downloaded from GLCF (Global Land Cover Facility web site, for the study area (path101 row 67, the downloaded imagery Subset using Imagery software to clip the study area. The clipped satellite imagery has Send to prepare the land use and land cover map using supervised classification.

  14. An Estimation of Land Surface Temperatures from Landsat ETM+ ...

    African Journals Online (AJOL)

    Dr-Adeline

    2 National Authority for Remote Sensing and Space Sciences, Cairo, Egypt. 3University of ... Keywords: Urban growth, urban heat Island, land surface temperatures, satellite remote sensing .... observed target includes green vegetation or not.

  15. THE DYNAMIC MONITORING OF HORQIN SAND LAND USING REMOTE SENSING

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Horqin Sand Land is regarded as the typical region for studying the problem of desertification. The integration of 3S(GIS, GPS and RS) techniques offer a most helpful method to study and monitor the dynamics of desertification.Based on the data derived from 3 periods' mulfitemporal Landsat TM imagery of the 1990s, the regional land use and dynamics of desertification in Horqin Sand L and were studied. The main results revealed that: 1 ) as long as the general changetendency was concerned, the desertification of Horqin Sand Land would continue to spread; 2) there was a gradual decrease in the area of both moving sand dunes and semi-stabilized ones, which meant that fruitful progress had been madeto control the desertification during the 1990s; 3) as a result of unreasonable cultivation, the total area of stabilized sanddunes and grassland in the middle and western region decreased obviously. It suggested that the increasing damagecaused by human was leading to the hazard of further desertitication. So in the future, it is necessary to take more effective measures to control the spread of desertification and restore the degraded ecosystems for the purpose of optimizing theglobal eco-environment in Horqin Sand Land.

  16. Approach and status for a unified national plan for satellite remote sensing research and development

    Science.gov (United States)

    Butera, Kristine; Okerson, David J.

    1987-01-01

    Public Law 98-365, the Land Remote-Sensing Commercialization Act of 1984, requires that the Secretary of the Department of Commerce and the Administrator of the National Aeronautics and Space Administration 'shall, within one year after the date of the Law's enactment and biennially thereafter, jointly develop and transmit to the Congress a report that includes (1) a unified national plan for remote-sensing research and development applied to the earth and its atmosphere; (2) a compilation of progress in the relevant on-going research and development activities of Federal agencies; and (3) an assessment of the state of our knowledge of the Earth and its atmosphere, the needs for additional research (including research related to operational Federal remote-sensing space programs), and opportunities available for further progress'. NASA and NOAA have organized a series of public forums to encourage interest and discussion of the national plan.

  17. Determination of wetland ecosystem boundaries and validation of land use maps using remote sensing: Fuente de Piedra case study (Spain)

    Science.gov (United States)

    Sánchez, Antonio; Malak, Dania Abdul; Schröder, Christoph; Martinez-Murillo, Juan F.

    2016-04-01

    Remote sensing techniques (SRS) are valid tools for wetland monitoring that could support wetland managers in assessing the spatial and temporal changes in wetland ecosystems as well as in understanding their condition and the ecosystem services they provide. This study focuses on the one hand, on drawing hydro-ecological guidelines for the delimitation of wetland ecosystems; and on the other hand, to assess the reliability of widely available satellite images (Landsat) in estimating the land use/ land cover types covering wetlands. This research develops comprehensive guidelines to determine the boundaries of the Fuente de Piedra wetland ecosystem located in Andalusia, Spain and defines the main land use/ land cover classes covering this ecosystem using Landsat 8 images. An accuracy of the SRS results delivered is tested using the regional inventory of land use produced by the regional government of Andalusia in 2011. By using the ecological and hydrological settings of the area, the boundaries of the Fuente de Piedra wetland ecosystem are determined as an alternative to improve the current delimitations methodology (the Ramsar and Natura 2000 delineations), used by the local authorities so far and based mainly on administrative reasoning. In terms of the land use land cover definition in the area, Fuente de Piedra wetland ecosystem shows to cover a total area of 195 km2 composed mainly by agricultural areas (81.46%): olive groves, non-irrigated arable land and pastures, being 54.82%, 25.71% and 0.93% of the surface respectively. Wetland related land covers (water surface, wetland vegetation) represent 6.85% while natural vegetation is distributed in forest, 1.67%, and shrub areas, 4.14%, being 5.81% in total. 4.58% of the area corresponds to urban and other artificial surfaces. The rest, 1.30%, is composed of different areas without vegetation (sands, bare rock, dumps, etc.). The classification of the Landsat images made with the newly developed SWOS toolbox

  18. Global mobile satellite communications theory for maritime, land and aeronautical applications

    CERN Document Server

    Ilčev, Stojče Dimov

    2017-01-01

    This book discusses current theory regarding global mobile satellite communications (GMSC) for maritime, land (road and rail), and aeronautical applications. It covers how these can enable connections between moving objects such as ships, road and rail vehicles and aircrafts on one hand, and on the other ground telecommunications subscribers through the medium of communications satellites, ground earth stations, Terrestrial Telecommunication Networks (TTN), Internet Service Providers (ISP) and other wireless and landline telecommunications providers. This new edition covers new developments and initiatives that have resulted in land and aeronautical applications and the introduction of new satellite constellations in non-geostationary orbits and projects of new hybrid satellite constellations. The book presents current GMSC trends, mobile system concepts and network architecture using a simple mode of style with understandable technical information, characteristics, graphics, illustrations and mathematics equ...

  19. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  20. Improvement of NCEP Numerical Weather Prediction with Use of Satellite Land Measurements

    Science.gov (United States)

    Zheng, W.; Ek, M. B.; Wei, H.; Meng, J.; Dong, J.; Wu, Y.; Zhan, X.; Liu, J.; Jiang, Z.; Vargas, M.

    2014-12-01

    Over the past two decades, satellite measurements are being increasingly used in weather and climate prediction systems and have made a considerable progress in accurate numerical weather and climate predictions. However, it is noticed that the utilization of satellite measurements over land is far less than over ocean, because of the high land surface inhomogeneity and the high emissivity variabilities in time and space of surface characteristics. In this presentation, we will discuss the application efforts of satellite land observations in the National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS) in order to improve the global numerical weather prediction (NWP). Our study focuses on use of satellite data sets such as vegetation type and green vegetation fraction, assimilation of satellite products such as soil moisture retrieval, and direct radiance assimilation. Global soil moisture data products could be used for initialization of soil moisture state variables in numerical weather, climate and hydrological forecast models. A global Soil Moisture Operational Product System (SMOPS) has been developed at NOAA-NESDIS to continuously provide global soil moisture data products to meet NOAA-NCEP's soil moisture data needs. The impact of the soil moisture data products on numerical weather forecast is assessed using the NCEP GFS in which the Ensemble Kalman Filter (EnKF) data assimilation algorithm has been implemented. In terms of radiance assimilation, satellite radiance measurements in various spectral channels are assimilated through the JCSDA Community Radiative Transfer Model (CRTM) on the NCEP Gridpoint Statistical Interpolation (GSI) system, which requires the CRTM to calculate model brightness temperature (Tb) with input of model atmosphere profiles and surface parameters. Particularly, for surface sensitive channels (window channels), Tb largely depends on surface parameters such as land surface skin temperature, soil

  1. Systematic evaluation of satellite remote sensing for identifying uranium mines and mills.

    Energy Technology Data Exchange (ETDEWEB)

    Blair, Dianna Sue; Stork, Christopher Lyle; Smartt, Heidi Anne; Smith, Jody Lynn

    2006-01-01

    In this report, we systematically evaluate the ability of current-generation, satellite-based spectroscopic sensors to distinguish uranium mines and mills from other mineral mining and milling operations. We perform this systematic evaluation by (1) outlining the remote, spectroscopic signal generation process, (2) documenting the capabilities of current commercial satellite systems, (3) systematically comparing the uranium mining and milling process to other mineral mining and milling operations, and (4) identifying the most promising observables associated with uranium mining and milling that can be identified using satellite remote sensing. The Ranger uranium mine and mill in Australia serves as a case study where we apply and test the techniques developed in this systematic analysis. Based on literature research of mineral mining and milling practices, we develop a decision tree which utilizes the information contained in one or more observables to determine whether uranium is possibly being mined and/or milled at a given site. Promising observables associated with uranium mining and milling at the Ranger site included in the decision tree are uranium ore, sulfur, the uranium pregnant leach liquor, ammonia, and uranyl compounds and sulfate ion disposed of in the tailings pond. Based on the size, concentration, and spectral characteristics of these promising observables, we then determine whether these observables can be identified using current commercial satellite systems, namely Hyperion, ASTER, and Quickbird. We conclude that the only promising observables at Ranger that can be uniquely identified using a current commercial satellite system (notably Hyperion) are magnesium chlorite in the open pit mine and the sulfur stockpile. Based on the identified magnesium chlorite and sulfur observables, the decision tree narrows the possible mineral candidates at Ranger to uranium, copper, zinc, manganese, vanadium, the rare earths, and phosphorus, all of which are

  2. A dynamic analysis of regional land use and cover changing (LUCC) by remote sensing and GIS: taking Fuzhou area as example

    Science.gov (United States)

    Yu, Ming; Chen, Dawei; Huang, Ruihong; Ai, Tinghua

    2010-04-01

    Regional difference of environmental evolvements is one of important aspects in world change research program. Changes in land cover and in the way people use the land have become recognized as important global environmental change in many areas. Land-use and cover changing (LUCC) is one of the major studies of global changing lately. Land-use is the term which covers the condition of used-land, the method, extent, structure, regional distributing and benefits in the land-use. It is affected by the natural condition or is enslaved to the conditions in society, economy and technology, and social production mode plays a decisive role in land-use; land-cover is the state of covering which is formed on account of the earth's surface or contrived by human being, is the summary of vegetation and artificially covering on the earth's surface. So land-use and cover changing is connecting closely. Land-use and cover changing information points that information on the position, distributing, range, and size of land-use and cover changing in the certain time. Motivated by a global concern for sustainability and environmental quality in city, a considerable number of studies have utilized satellite sensor data in the analysis of urban morphological change .some studies focused on the physical and socioeconomic drivers of change in urban land cover and implications on land use practices and resource management. Other studies went beyond the characterization of change and its causes and attempted to integrate remotely sensed data with models of urban growth to project future change. GIS and RS technologies are widely applied for LUCC studies providing a powerful tool for capturing, storing, checking manipulating, merging, analyzing and displaying data. Especially RS technology are also widely used for LUCC studies such as automatic discovery changing, automatic extraction changing area, confirmation changing type, using interactive explanation accessorily to extract the changing

  3. Multi-sensor remote sensing parameterization of heat fluxes over heterogeneous land surfaces

    NARCIS (Netherlands)

    Faivre, R.D.

    2014-01-01

    The parameterization of heat transfer by remote sensing, and based on SEBS scheme for turbulent heat fluxes retrieval, already proved to be very convenient for estimating evapotranspiration (ET) over homogeneous land surfaces. However, the use of such a method over heterogeneous landscapes (e.g. sem

  4. Method of interpretation of remotely sensed data and applications to land use

    Science.gov (United States)

    Parada, N. D. J. (Principal Investigator); Dossantos, A. P.; Foresti, C.; Demoraesnovo, E. M. L.; Niero, M.; Lombardo, M. A.

    1981-01-01

    Instructional material describing a methodology of remote sensing data interpretation and examples of applicatons to land use survey are presented. The image interpretation elements are discussed for different types of sensor systems: aerial photographs, radar, and MSS/LANDSAT. Visual and automatic LANDSAT image interpretation is emphasized.

  5. Land Cover Change and Remote Sensing in the Classroom: An Exercise to Study Urban Growth

    Science.gov (United States)

    Delahunty, Tina; Lewis-Gonzales, Sarah; Phelps, Jack; Sawicki, Ben; Roberts, Charles; Carpenter, Penny

    2012-01-01

    The processes and implications of urban growth are studied in a variety of disciplines as urban growth affects both the physical and human landscape. Remote sensing methods provide ways to visualize and mathematically represent urban growth; and resultant land cover change data enable both quantitative and qualitative analysis. This article helps…

  6. Land Cover Change and Remote Sensing in the Classroom: An Exercise to Study Urban Growth

    Science.gov (United States)

    Delahunty, Tina; Lewis-Gonzales, Sarah; Phelps, Jack; Sawicki, Ben; Roberts, Charles; Carpenter, Penny

    2012-01-01

    The processes and implications of urban growth are studied in a variety of disciplines as urban growth affects both the physical and human landscape. Remote sensing methods provide ways to visualize and mathematically represent urban growth; and resultant land cover change data enable both quantitative and qualitative analysis. This article helps…

  7. Land capability classification of some western desert Oases, Egypt, using remote sensing and GIS

    Directory of Open Access Journals (Sweden)

    Abd-Alla Gad

    2015-10-01

    It could be concluded that the desert Oases are sustainable areas, which might have potential importance supporting the national development programs. Integrating remote sensing data with digital soil map, using GIS, led to the elaboration of successful land capability classification mapping.

  8. Desertification and land degradation investigations in the Mediterranean basin based on hydrological and remote sensing data interpretation.

    Science.gov (United States)

    Kallioras, A.; Rokos, E.; Charou, E.; Perrakis, A.; Vasileiou, E.; Markantonis, K.

    2012-04-01

    As concluded in the relevant UN Convention in 1994, desertification has affected large areas within the European Mediterranean coastal regions and is threatening even larger territories. Desertification as a means of land degradation can be resulted from a series of factors including climatic changes and anthropogenic activities; while appears more pronounced in arid and semi-arid areas. With special reference to Greece, it is estimated that more than 35% of the country's surface area shows high risk of desertification; with the island of Crete having the highest potential for such environmental hazard. More specifically over 50% of the island is exposed to high desertification potential, especially in areas located at the south-eastern part. Desertification in the island of Crete takes place as a consequence of: (i) climate conditions and (ii) anthropogenic activities causing intrusion of seawater into the mainland aquifers. The climate is semi-arid, with ephemeral rainfall events which are unevenly distributed in spatial as well as time extent. The average precipitation (P) is approximately 477.1mm and the evaporation is 350 mm (73%) -average temperature is 18.7oC- while the sum of runoff and percolation is app. 127.1mm (27%). On the other hand, the majority of the coastal aquifers are subjected to overexploitation -groundwater used for irrigation purposes- conditions which has led to encroachment of seawater towards the coastal freshwater aquifers. As brackish groundwater is used for irrigation purposes, this consequently results in salt accumulation on the soil surface, fact which severely degrades the soil by increasing salinity. Remote Sensing techniques can be proved a useful tool in various fields of environmental research, while satellite image processing can be used for assessment and monitoring of environmental analysis, land cover/use changes, landscape mapping and soil analysis. In the case of Eastern Crete, remote sensing digital image analysis can be

  9. Monitoring the frozen duration of Qinshai Lake using satellite passive microwave remote sensing low frequency data

    Institute of Scientific and Technical Information of China (English)

    CHE Tao; LI Xin; JIN Rui

    2009-01-01

    The Qinghai Lake is the largest inland lake in China.The significant difference of dielectric properties between water and ice suggests that a simple method of monitoring the Qinghai lake freeze-up and break-up dates using satellite passive microwave remote sensing data could be used.The freeze-up and break-up dates from the Qinghai Lake hydrological station and the MODIS L1B reflectance data were used to validate the passive microwave remote sensing results.The validation shows that passive microwave remote sensing data can accurately monitor the lake ice.Some uncertainty comes mainly from the revisit frequency of satellite overpass.The data from 1978 to 2006 show that lake ice duration is reduced by about 14-15 days.The freeze-up dates are about 4 days later and break-up dates about 10 days earlier.The regression analyses show that,at the 0.05 significance level,the correlations are 0.83,0.66 and 0.89 between monthly mean air temperature (MMAT) and lake ice duration days,freeze-up dates,break-up dates,respectively.Therefore,inter-annual variations of the Qinghai Lake ice duration days can significantly reflect the regional climate variation.

  10. Land use change detection and impact assessment in Anzali international coastal wetland using multi-temporal satellite images.

    Science.gov (United States)

    Mousazadeh, Roya; Ghaffarzadeh, Hamidreza; Nouri, Jafar; Gharagozlou, Alireza; Farahpour, Mehdi

    2015-12-01

    Anzali is one of the 18 Iranian wetlands of international importance listed in Ramsar Convention. This unique ecosystem in the world with high ecological diversity is highly threatened by various factors such as pollutants, sedimentation, unauthorized development of urban infrastructure, over-harvesting of wetland resources, land use changes, and invasive species. Among which, one of the most challenging destructive factors, land use change, was scrutinized in this study. For this, remotely sensed data and Geographical Information System (GIS) were used to detect land changes and corresponding impacts on the study area over a 38-year period from 1975 to 2013.. Changes in the study area were traced in five dominant land-use classes at four time intervals of 1975, 1989, 2007, and 2013. Accordingly, changes in different categories were quantified using satellite images. The methodology adopted in this study includes an integrated approach of supervised classification, zonal and object-oriented image analyses. According to the Kappa coefficient of 0.84 for the land use map of 2013, the overall accuracy of the method was estimated at 89%, which indicated that this method can be useful for monitoring and behavior analysis of other Iranian wetlands. The obtained results revealed extensive land use changes over the study period. As the results suggest, between the years 1975 to 2013, approximately 6500 ha (∼69%) rangeland area degraded. Further, urban and agricultural areas have been extended by 2982 ha (∼74%) and 2228 ha (∼6%), respectively. This could leave a negative impact on water quality of the wetland.

  11. An Autonomous Satellite Time Synchronization System Using Remotely Disciplined VC-OCXOs

    Directory of Open Access Journals (Sweden)

    Xiaobo Gu

    2015-07-01

    Full Text Available An autonomous remote clock control system is proposed to provide time synchronization and frequency syntonization for satellite to satellite or ground to satellite time transfer, with the system comprising on-board voltage controlled oven controlled crystal oscillators (VC-OCXOs that are disciplined to a remote master atomic clock or oscillator. The synchronization loop aims to provide autonomous operation over extended periods, be widely applicable to a variety of scenarios and robust. A new architecture comprising the use of frequency division duplex (FDD, synchronous time division (STDD duplex and code division multiple access (CDMA with a centralized topology is employed. This new design utilizes dual one-way ranging methods to precisely measure the clock error, adopts least square (LS methods to predict the clock error and employs a third-order phase lock loop (PLL to generate the voltage control signal. A general functional model for this system is proposed and the error sources and delays that affect the time synchronization are discussed. Related algorithms for estimating and correcting these errors are also proposed. The performance of the proposed system is simulated and guidance for selecting the clock is provided.

  12. An assessment of soil productivity loss caused by expanding urban land use using remote sensing and soil productivity models

    Science.gov (United States)

    Nizeyimana, Egide; Petersen, Gary W.; Warner, Eric D.; Shi, Xuenzheng; Imhoff, Marc L.; Lawrence, William T.; Russo, Joseph M.

    1997-01-01

    An EOS IDS project has been recently designed to assess the loss of soil productivity resulting from expanding urbanization in the U.S. and selected regions in Mexico and the Middle East using remotely sensed data and soil productivity models. The extent of urbanization will be determined by generating urban land cover layers from DMSP/OLS (Defense Meteorological Satellite Program's Operational Linescan System) nighttime imagery. This imagery will be calibrated using Landsat Thematic Mapper (TM) and population/housing census data. A range of soil/land productivity models will be evaluated using soil factors computed from the State Soil Geographic Database (STATSGO) and FAO soil databases, terrain models, climate and vegetation to rank soil mapping units based on their productivity potential. Examples of these models are the Net Primary Productivity (NPP) and FAO Fertility Capability Classification (FCC) system. The magnitude of soil productivity loss due to urbanization will finally be determined by analysis of data obtained from GIS overlays of urban land use and soil productivity layers.

  13. Monitoring Land Use Dynamics in Chanthaburi Province of Thailand Using Digital Remotely Sensed Images

    Institute of Scientific and Technical Information of China (English)

    SHEN RUNPING; I. KHEORUENROMNE

    2003-01-01

    A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.

  14. Monitoring crop land greening and degradation using remotely sensed MODIS time-series data

    Science.gov (United States)

    Subhash Palmate, Santosh; Pandey, Ashish

    2017-04-01

    The management of crop land is crucial to sustain the food productivity in developing country like India. Manual monitoring of crop condition is difficult and time consuming in a large river basin. The phenological study is essential to understand changes in crop growth stages. This study is an attempt to monitor land greening and degradation, and to derive phenological parameters of crop land area using remotely sensed MODIS Normalized Difference Vegetation Index (NDVI) time-series data of the years 2001-2013 for the Betwa river basin, Central India. Savitzky Golay filtering method was employed to de-noise NDVI time-series data using TIMESAT software. Seven phenological parameters (start of the season, end of the season, length of the season, base value, peak time, peak value and amplitude) were obtained for the crop land area. Furthermore, spatial analysis was carried out to identify changes in crop land areas. Result shows that more land greening and degradation have been occurred for crop land and natural vegetation area respectively. This study revealed that remote sensing data based analysis will help to secure the food productivity in a large agricultural river basin.

  15. Ship detection in high spatial resolution remote sensing image based on improved sea-land segmentation

    Science.gov (United States)

    Li, Na; Zhang, Qiaochu; Zhao, Huijie; Dong, Chao; Meng, Lingjie

    2016-10-01

    A new method to detect ship target at sea based on improved segmentation algorithm is proposed in this paper, in which the improved segmentation algorithm is applied to precisely segment land and sea. Firstly, mean value is replaced instead of average variance value in Otsu method in order to improve the adaptability. Secondly, Mean Shift algorithm is performed to separate the original high spatial resolution remote sensing image into several homogeneous regions. At last, the final sea-land segmentation result can be located combined with the regions in preliminary sea-land segmentation result. The proposed segmentation algorithm performs well on the segment between water and land with affluent texture features and background noise, and produces a result that can be well used in shape and context analyses. Ships are detected with settled shape characteristics, including width, length and its compactness. Mean Shift algorithm can smooth the background noise, utilize the wave's texture features and helps highlight offshore ships. Mean shift algorithm is combined with improved Otsu threshold method in order to maximizes their advantages. Experimental results show that the improved sea-land segmentation algorithm on high spatial resolution remote sensing image with complex texture and background noise performs well in sea-land segmentation, not only enhances the accuracy of land and sea boarder, but also preserves detail characteristic of ships. Compared with traditional methods, this method can achieve accuracy over 90 percent. Experiments on Worldview images show the superior, robustness and precision of the proposed method.

  16. Land-mobile-satellite fade measurements in Australia

    Science.gov (United States)

    Vogel, Wolfhard J.; Goldhirsh, Julius; Hase, Yoshihiro

    1992-01-01

    Attenuation measurements were implemented at L-band (1.5 GHz) in southeastern Australia during an 11-day period in October 1988 as part of a continuing examination of the propagation effects due to roadside trees and terrain for mobile-satellite service. Beacon transmissions from the geostationary ETS-V and IPORS satellites were observed. The Australian campaign expanded to another continent our Mobile Satellite Service data base of measurements executed in the eastern and southwestern United States regions. An empirical fade distribution model based on U.S. data predicted the Australian results with errors generally less than 1 dB in the 1-20 percent probability region. Directive antennas are shown to suffer deeper fades under severe shadowing conditions (3 dB excess at 4 percent), the equal-probability isolation between co- and cross-polarized transmissions deteriorated to 10 dB at the 5 dB fade level, and antenna diversity reception may reduce unavailability of the system by a factor of 2-8.

  17. Integration between terrestrial-based and satellite-based land mobile communications systems

    Science.gov (United States)

    Arcidiancono, Antonio

    A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

  18. Integration between terrestrial-based and satellite-based land mobile communications systems

    Science.gov (United States)

    Arcidiancono, Antonio

    1990-01-01

    A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

  19. 土地利用的遥感信息变化提取研究%Research on the Land Use of Remote Sensing Information Change Extraction

    Institute of Scientific and Technical Information of China (English)

    张莹; 陈圣波; 王明常; 张庸; 郭鹏举

    2012-01-01

    利用卫星遥感影像进行土地利用类型分类和动态变化监测是遥感应用中的一个重要课题.选择不同时相的ETM+和SPOT-5卫星遥感影像数据.对两期影像进行监督分类.快速提取不同时期的土地利用数据.然后进行动态变化监测,获得土地利用情况的变化特征和信息.最后对其分类精度进行评价分析.研究表明,两期影像中耕地、居民用地和未利用地这三个类别的变化面积较大.ETM+影像进行监督分类的精度为90.1692%;Kappa系数值为0.8268.SPOT-5影像进行监督分类的精度为95.1477%,Kappa系数值为0.9361.由于SPOT-5影像的分辨率较高,分类效果更优于ETM+影像,更能准确的反映土地类型的信息和.特征.%By making use of satellite remote sensing image of types of land use classification and dynamic changes in the applications of remote sensing monitoring is an important issue. At present, with the tense situation of land is getting worse and land use pattern changes constantly, so using remote sensing technology to land in the use of resources and planning has important social value and practical significance. Based on different periods of ETM + and SPOT-5 remote sensing satellite image data, carried out supervised classification, land use data of two periods were extracted, and dynamic monitoring of the study area land use were completed, then summarized the information and characteristics of the land use changes. Finally, the classification precision evaluation was analysed. Establish by establish Interpretion marks and analyzing the study area can get the data of land use type change and extract rapidly the land use type change information. The study area Jinxi City located in the western Liaoning Province. The altitude is generally (20 ~ 500) m. The mountain toward the north-east, the terrain is generally high in the northwest to southeast. The area has many types of vegetation including the the type of the forest, bush

  20. Remote sensing and GIS analyses for emergency manouvering and forced landing areas definition as a support for general aviation flights

    Science.gov (United States)

    Skocki, Krzysztof

    2016-08-01

    This paper summarizes the preliminary analyses of using existing remote sensing data, medium and high-resolution satellite and airborne data to define safe emergency landing and maneuvering areas to be used by small aircrafts operating from small airports and airfields in Poland. The pilots need to know such places in the interest of safe flight operations. In common practice, flying instructors typically show the student pilot fields around the airfield supposed to be suitable for emergency or precautionary landing (or ditching) in the initial phase of the training. Although it looks to cover the most basic needs, the problem still exists in relation to guest pilots. To fill this gap, the unified safety map document covering the safe emergency areas around the airfields is proposed in this research. Use of satellite high resolution data, as well as aerial photos, infrastructure information, with use of GIS tools (like buffer zones, distance, equal-time circles or position lines) enable to check the terrain around selected airfields and define possible areas suitable for emergency operations. In the second phase of work, selected areas will be described in terms of easy navigation, possible infrastructure around them, rescue possibilities, radio signal coverage, and others. The selected areas should be also checked for typical cover and surface hardness and stability (eg. with use of moisture estimation on the base of middle-resolution satellite data). Its planned to prepare one combined and separate sheets of the final map for various aircraft characteristics (`classes' of small Cessna-related, big Cessna-related, fast low-wing Diamond-like, two-engine Piper-like). The presented concept should highly increase the safety operations for small aviation in secondary airports and airfields, where the information available is limited. There is also a possibility to make a similar maps for `cruise', which means the areas with dense traffic between the airports/airfields.

  1. Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

    Science.gov (United States)

    Lo, C. P.; Quattrochi, Dale A.

    2003-01-01

    Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

  2. NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne remote sensing

    Science.gov (United States)

    Robert E. Davis; Thomas H. Painter; Don Cline; Richard Armstrong; Terry Haran; Kyle McDonald; Rick Forster; Kelly Elder

    2008-01-01

    This paper describes satellite data collected as part of the 2002/03 Cold Land Processes Experiment (CLPX). These data include multispectral and hyperspectral optical imaging, and passive and active microwave observations of the test areas. The CLPX multispectral optical data include the Advanced Very High Resolution Radiometer (AVHRR), the Landsat Thematic Mapper/...

  3. ANALYZING THE SHAPE CHARACTERISTICS OF LAND USE CLASSES IN REMOTE SENSING IMAGERY

    Directory of Open Access Journals (Sweden)

    L. Jiao

    2012-07-01

    Full Text Available Shape is an important aspect of spatial attributes of land use segments in remotely sensed imagery, but it is still rarely used as a component in land use classification or image-based land use analysis. This study aims to quantitatively characterize land use classes using shape metrics. The study is conducted in a case area located in south China, covering twelve scenes of SPOT-5 images. There were total ten metrics selected for the analysis, namely, Convexity (CONV, Solidity (SOLI, Elongation (ELONG, Roundness (ROUND, Rectangular Fitting (RECT, Compact (COMP, Form Factor (FORM, Square pixel metric (SqP, Fractal Dimension (FD, and Shape Index (SI. The last five metrics were used to measure the complexity of shape. Eight land use classes were investigated in the case area, namely, roads, cultivated lands, settlement places, rivers, ponds, forest and grass lands, reservoirs, and dams. The results show that all typical shape properties of land use segments can be well measured by shape metrics. We identified the land use classes whose values are significantly differentiated from most classes for each metric. Two of the five complexity metrics, FORM and SqP, were identified to be more effective in characterizing the complexity of land use classes. We finally selected six shape metrics and deduced the "Shape Metric Signatures" (SMS of different land use classes. SMS can serve as accurate and predictive discriminators of land use classes within the study area. Our results show that SMS can clearly distinguish spectrally similar land use classes. The results will help to build a more accurate and intelligent object-oriented classification system for land use classes.

  4. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented.Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively,the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model.A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper.The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  5. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    WEN JianGuang; LIU QinHuo; XIAO Qing; LIU Qiang; LI XiaoWen

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented. Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively, the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model. A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper. The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  6. Remote sensing and GIS for land use/cover mapping and integrated land management: case from the middle Ganga plain

    Institute of Scientific and Technical Information of China (English)

    R B SINGH; Dilip KUMAR

    2012-01-01

    In India,land resources have reached a critical stage due to the rapidly growing population.This challenge requires an integrated approach toward hamessing land resources,while taking into account the vulnerable environmental conditions.Remote sensing and Geographical Information System (GIS) based technologies may be applied to an area in order to generate a sustainable development plan that is optimally suited to the terrain and to the productive potential of the local resources.The present study area is a part of the middle Ganga plain,known as Son-Karamnasa interfluve,in India.Alternative land use systems and the integration of livestock enterprises with the agricultural system have been suggested for land resources management.The objective of this paper is to prepare a land resource development plan in order to increase the productivity of land for sustainable development.The present study will contribute necessary input for policy makers to improve the socio-economic and environmental conditions of the region.

  7. ENVIRONMENTAL IMPACT ASSESSMENT OF LAND USE PLANING AROUND THE LEASED LIMESTONE MINE USING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    P. Ranade

    2007-01-01

    Full Text Available Mining activities and the waste products produced can have significant impact on the surrounding environment - ranging from localized surface and ground water contamination to the damaging effects of airborne pollutants on the regional ecosystem. The long term monitoring of environmental impacts requires a cost effective method to characterize land cover and land cover changes over time. As per the guidelines of Ministry of Environment and Forest, Govt. of India, it is mandatory to study and analyze the impacts of mining on its surroundings. The use of remote sensing technology to generate reliable land cover maps is a valuable asset to completing environmental assessments over mining affected areas. In this paper, a case study has been discussed to study the land use – land cover status around 10 Km radius of open cast limestone mine area and the subsequent impacts on environmental as well as social surroundings.

  8. Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

    Science.gov (United States)

    Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

    2014-12-01

    Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to

  9. Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

    Science.gov (United States)

    Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

    2016-12-01

    Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

  10. Satellite remote sensing - An integral tool in acquiring global crop production information

    Science.gov (United States)

    Hall, F. G.

    1982-01-01

    Since NASA's program of research concerning remote sensing was initiated in the 1960s, one of its major objectives has been to advance the state-of-the-art in machine processing of satellite acquired multispectral data. Possibilities have been studied regarding a use of these data to identify type, to monitor condition, and to estimate the ontogenetic stage of cultural vegetation. The present investigation provides a review of the state-of-the-art of the technology used to make remote sensing crop production estimates in foreign regions. Attention is given to Landsat data acquisition, aspects of registration and preprocessing, questions of data transformation, data modeling, proportion estimation, labeling, development stage models, crop condition models, and an outlook regarding future developments.

  11. The application of GIS in land satellite data management and service

    Science.gov (United States)

    Zhang, Zhenhua; Liu, Defeng

    2015-12-01

    In recent years, with the rapid development of China's satellite remote sensing technology, ZY-1 02C, ZY-3 and TH-1 satellites have been successfully launched, ZY-3 satellite is China's first autonomous civilian high-resolution stereo mapping satellite, achieved a breakthrough in the field of civil high resolution mapping satellite[1]. Its successful applications have become a new milestone in the history of Chinese satellite surveying and mapping, undertake to build database of remote sensing information, promote the development of geographic space information industry. This paper, based on data distribution service subsystem of the construction of ZY-3 ground processing as an example, introduces GIS in the subsystem which plays an important role. This sub-system is the window of the ground system of information collection and product distribution, whose task is to provide ZY-3, ZY-1 02C a variety of sensor data distribution service at all levels of products, to provide users with a unified search, browse, order and download services, and has a certain capacity expansion upgrade, which provides a technical basis and guarantee for subsequent satellite distribution service. With ZY-3 satellite in orbit, the amount of data is increasing, how to efficiently manage multi-source image data becomes the system to be solved. In this paper, ArcGIS mosaic datasets is used to manage large-scale image data to solve the many problems that exist in the traditional image management and shared services to complete data distribution. At present, the distribution system has been stabilized, and serves the masses of users.

  12. Satellite Remote Sensing Atmospheric Compositions and their Application in Air Quality Monitoring in China

    Science.gov (United States)

    Zhang, P.; Zhang, X. Y.; Bai, W. G.; Wang, W. H.; Huang, F. X.; Li, X. J.; Sun, L.; Wang, G.; Qi, J.; Qiu, H.; Zhang, Y.; van der A, R. J.; Mijling, B.

    2013-01-01

    This paper summarizes the achievements related to atmospheric compositions remote sensing from the bilateral cooperation under the framework of MOST-ESA Dragon Programme. The algorithms to retrieve Aerosol, ozone amount and profile, NO2, SO2, CH4, CO2, etc. have been developed since 2004. Such algorithms are used to process FY-3 series (Chinese second generation polar orbit satellites) observation and ground based FTIR observation. The results are validated with in-situ measurements. Aerosol, total ozone amount shows the very good consistent with the ground measurements. The temporal and spatial characteristics of the important atmospheric compositions, such as aerosol, O3, NO2, SO2, CH4, CO etc., have been analysed from satellite derived products. These works demonstrate the satellite’s capacity on atmospheric composition monitoring, as well as the possible application in the air quality monitoring and climate change research.

  13. Application of remote sensing to thermal pollution analysis. [satellite sea surface temperature measurement assessment

    Science.gov (United States)

    Hiser, H. W.; Lee, S. S.; Veziroglu, T. N.; Sengupta, S.

    1975-01-01

    A comprehensive numerical model development program for near-field thermal plume discharge and far field general circulation in coastal regions is being carried on at the University of Miami Clean Energy Research Institute. The objective of the program is to develop a generalized, three-dimensional, predictive model for thermal pollution studies. Two regions of specific application of the model are the power plants sites at the Biscayne Bay and Hutchinson Island area along the Florida coastline. Remote sensing from aircraft as well as satellites are used in parallel with in situ measurements to provide information needed for the development and verification of the mathematical model. This paper describes the efforts that have been made to identify problems and limitations of the presently available satellite data and to develop methods for enhancing and enlarging thermal infrared displays for mesoscale sea surface temperature measurements.

  14. On the use of Satellite Remote Sensing and GIS to detect NO2 in the Troposphere

    DEFF Research Database (Denmark)

    Nielsen, Søren Zebitz

    2012-01-01

    This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...... are conducted, and it is shown that plumes from major Danish source areas can be detected in all wind directions, and that pollution transported from Europe is seen when the wind has a southern component. Examples of day to day tracking of transport of NO2 are also given to explain two pollution episodes...... stations in the Danish Air Quality Measurement network to find correlation between the two datasets. Clear weekly and annual cycles are found in both datasets and they are shown to be significantly correlated, though with a low correlation coefficient. Analyses of the patterns in different wind directions...

  15. SOME KEY ISSUES ON THE APPLICATION OF SATELLITE REMOTE SENSING TO MINING AREAS

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    In order to apply Satellite Remote Sensing (RS) to mining areas, some key issues should be solved. Based on an introduction to relative studying background, related key issues are proposed and analyzed oriented to the development of RS information science and demands of mining areas. Band selection and combination optimization of Landsat TM is discussed firstly, and it proved that the combination of Band 3, Band 4 and Band 5 has the largest information amount in all three-band combination schemes by both N-dimensional entropy method and Genetic Algorithm (GA). After that the filtering of Radarsat image is discussed. Different filtering methods are experimented and compared, and adaptive methods are more efficient than others. Finally the classification of satellite RS image is studied, and some new methods including classification by improved BPNN(Back Propagation Neural Network) and classification based on GIS and knowledge are proposed.

  16. Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model

    Science.gov (United States)

    Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.

    2017-03-01

    This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.

  17. National Satellite Land Monitoring Systems for REDD+ : the UN-REDD support to countries

    Science.gov (United States)

    Jonckheere, I. G. C.

    2015-12-01

    REDD+, which stands for 'Reducing Emissions from Deforestation and Forest Degradation in Developing Countries' - is a climate mitigation effort and aims to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. The UN-REDD Programme, a collaborative partnership between FAO, UNDP and UNEP launched in September 2008, supports nationally-led REDD+ processes and promotes the imeaningful involvement of all stakeholders, including Indigenous Peoples and other forest-dependent communities, in national and international REDD+ implementation.The Programme supports national REDD+ readiness efforts in partner countries spanning Africa, Asia-Pacific and Latin America, in two ways: (i) direct support to the design and implementation of UN-REDD National Programmes; and (ii) complementary support to national REDD+ action through common approaches, analyses, methodologies, tools, data and best practices. The UN-REDD Programme currently supports 62 partner countries. The UN-REDD Programme gathers technical teams from around the world to develop common approaches, analyses and guidelines on issues such as measurement, reporting and verification (MRV) of carbon emissions and flows, remote sensing, and greenhouse gas inventories. Within the partnership, FAO supports countries on technical issues related to forestry and the development of cost effective and credible MRV processes for emission reductions. While at the international level, it fosters improved guidance on MRV approaches, including consensus on principles and guidelines for MRV and training programmes. It provides guidance on how best to design and implement REDD, to ensure that forests continue to provide multiple benefits for livelihoods and biodiversity to societies while storing carbon at the same time. Other areas of work include national forest assessments and monitoring

  18. AN ASSESSMENT OF LAND USE CHANGES IN FUQING COUNTY OF CHINA USING REMOTE SENSING TECHNOLOGY

    Institute of Scientific and Technical Information of China (English)

    XUHan-qin

    2002-01-01

    Fuqing County of southeast Chian has witnessed significant land use changes during the last decade.Re-mote sensing technology using multitemporal Landsat TM images was used to characterize land use types and to monitor land use changes in the county.Two TM scenes from 1991and 1996 were used to cover the county and a five-year time period.Digital image processing was carried out for the remotely sensed data to produce classified images.The images were further processed using GIS software to generate GIS databases so that the data could be further spatially analyzed taking the advantages of the software.Land use change areas were determined by using the change detection technique.The comparison of the two classified TM images using the above technologies reveals that during the five study years,a large area of arable lands in the county has been lost and deforestation has taken place largely because of the dramatic in-crease in built-up land and orchard.The conclusive statistical information is useful to understand the processes,causes and impacts of the land use changes in the county.The major driving force to the land use changes in the county ap-peared to be the rapid economic development.The decision makers of the county have to pay more attention to the land use changes for the county's sustainable development.

  19. Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China

    Directory of Open Access Journals (Sweden)

    Shanyu Huang

    2015-08-01

    Full Text Available Rice farming in Northeast China is crucially important for China’s food security and sustainable development. A key challenge is how to optimize nitrogen (N management to ensure high yield production while improving N use efficiency and protecting the environment. Handheld chlorophyll meter (CM and active crop canopy sensors have been used to improve rice N management in this region. However, these technologies are still time consuming for large-scale applications. Satellite remote sensing provides a promising technology for large-scale crop growth monitoring and precision management. The objective of this study was to evaluate the potential of using FORMOSAT-2 satellite images to diagnose rice N status for guiding topdressing N application at the stem elongation stage in Northeast China. Five farmers’ fields (three in 2011 and two in 2012 were selected from the Qixing Farm in Heilongjiang Province of Northeast China. FORMOSAT-2 satellite images were collected in late June. Simultaneously, 92 field samples were collected and six agronomic variables, including aboveground biomass, leaf area index (LAI, plant N concentration (PNC, plant N uptake (PNU, CM readings and N nutrition index (NNI defined as the ratio of actual PNC and critical PNC, were determined. Based on the FORMOSAT-2 imagery, a total of 50 vegetation indices (VIs were computed and correlated with the field-based agronomic variables. Results indicated that 45% of NNI variability could be explained using Ratio Vegetation Index 3 (RVI3 directly across years. A more practical and promising approach was proposed by using satellite remote sensing to estimate aboveground biomass and PNU at the panicle initiation stage and then using these two variables to estimate NNI indirectly (R2 = 0.52 across years. Further, the difference between the estimated PNU and the critical PNU can be used to guide the topdressing N application rate adjustments.

  20. Remote Mine Detection Technologies for Land and Water Environments

    Energy Technology Data Exchange (ETDEWEB)

    Hoover, Eddie R.

    1999-05-11

    The detection of mines, both during and after hostilities, is a growing international problem. It limits military operations during wartime and unrecovered mines create tragic consequences for civilians. From a purely humanitarian standpoint an estimated 100 million or more unrecovered mines are located in over 60 countries worldwide. This paper presents an overview of some of the technologies currently being investigated by Sandia National Laboratories for the detection and monitoring of minefields in land and water environments. The three technical areas described in this paper are: 1) the development of new mathematical techniques for combining or fusing the data from multiple sources for enhanced decision-making; 2) an environmental fate and transport (EF&T) analysis approach that is central to improving trace chemical sensing technique; and 3) the investigation of an underwater range imaging device to aid in locating and characterizing mines and other obstacles in coastal waters.

  1. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; Velde, van der R.; Vekerdy, Z.; Su, Z.

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  2. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park

  3. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  4. A data mining approach for sharpening satellite thermal imagery over land

    Science.gov (United States)

    Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

  5. Optical and Radar Satellite Remote Sensing for Large Area Analysis of Landslide Activity in Southern Kyrgyzstan, Central Asia

    Science.gov (United States)

    Roessner, S.; Behling, R.; Teshebaeva, K. O.; Motagh, M.; Wetzel, H. U.

    2014-12-01

    The presented work has been investigating the potential of optical and radar satellite remote sensing for the spatio-temporal analysis of landslide activity at a regional scale along the eastern rim of the Fergana Basin representing the area of highest landslide activity in Kyrgyzstan. For this purpose a multi-temporal satellite remote sensing database has been established for a 12.000 km2 study area in Southern Kyrgyzstan containing a multitude of optical data acquired during the last 28 years as well as TerraSAR-X and ALOS-PALSAR acquired since 2007. The optical data have been mainly used for creating a multi-temporal inventory of backdated landslide activity. For this purpose an automated approach for object-oriented multi-temporal landslide detection has been developed which is based on the analysis of temporal NDVI-trajectories complemented by relief information to separate landslide-related surface changes from other land cover changes. Applying the approach to the whole study area using temporal high resolution RapidEye time series data has resulted in the automated detection of 612 landslide objects covering a total area of approx. 7.3 km². Currently, the approach is extended to the whole multi-sensor time-series database for systematic analysis of longer-term landslide occurrence at a regional scale. Radar remote sensing has been focussing on SAR Interferometry (InSAR) to detect landslide related surface deformation. InSAR data were processed by repeat-pass interferometry using the DORIS and SARScape software. To better assess ground deformation related to individual landslide objects, InSAR time-series analysis has been applied using the Small Baseline Subset (SBAS) method. Analysis of the results in combination with optical data and DEM information has revealed that most of the derived deformations are caused by slow movements in areas of already existing landslides indicating the reactivation of older slope failures. This way, InSAR analysis can

  6. The determinations of remote sensing satellite data delivery service quality: A positivistic case study in Chinese context

    Science.gov (United States)

    Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun

    2014-03-01

    With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice.

  7. Use of satellite land surface temperatures in the EUSTACE global surface air temperature analysis

    Science.gov (United States)

    Ghent, D.; Good, E.; Rayner, N. A.

    2015-12-01

    EUSTACE (EU Surface Temperatures for All Corners of Earth) is a Horizon2020 project that will produce a spatially complete, near-surface air temperature (NSAT) analysis for the globe for every day since 1850. The analysis will be based on both satellite and in situ surface temperature observations over land, sea, ice and lakes, which will be combined using state-of-the-art statistical methods. The use of satellite data will enable the EUSTACE analysis to offer improved estimates of NSAT in regions that are poorly observed in situ, compared with existing in-situ based analyses. This presentation illustrates how satellite land surface temperature (LST) data - sourced from the European Space Agency (ESA) Data User Element (DUE) GlobTemperature project - will be used in EUSTACE. Satellite LSTs represent the temperature of the Earth's skin, which can differ from the corresponding NSAT by several degrees or more, particularly during the hottest part of the day. Therefore the first challenge is to develop an approach to estimate global NSAT from satellite observations. Two methods will be trialled in EUSTACE, both of which are summarised here: an established empirical regression-based approach for predicting NSAT from satellite data, and a new method whereby NSAT is calculated from LST and other parameters using a physics-based model. The second challenge is in estimating the uncertainties for the satellite NSAT estimates, which will determine how these data are used in the final blended satellite-in situ analysis. This is also important as a key component of EUSTACE is in delivering accurate uncertainty information to users. An overview of the methods to estimate the satellite NSATs is also included in this presentation.

  8. SYNOPTIC GLOBAL REMOTE SENSING OF LAND SURFACE VEGETATION: OVERVIEW OF DAILY DATA QUALITY, CHALLENGES, AND OPPORTUNITIES

    Science.gov (United States)

    Barreto-Munoz, A.; Didan, K.

    2009-12-01

    Continuous acquisition of global satellite imagery over the years has contributed to the creation of a long data record from AVHRR, MODIS, TM, SPOT VGT, and other sensors. These records account now for 30+ years, and as the archive grows, it becomes an invaluable source of data for many environmental related studies dealing with trends and changes from local to global scale. Synoptic global remote sensing provides a multitude of land surface state variables and serves as a major foundation for global change research. However, these records are inhibited with problems that need to be accounted for in order to understand the limits and improve the science results derived from these records. The presence of clouds, aerosols, spatial gaps, variable viewing geometry, inconsistent atmosphere corrections, multiple reprocessing, and different sensors characteristics, makes it difficult to obtain frequently high quality data everywhere and every time. Moreover, these issues are location and season dependent making it even more difficult to construct the consistent time series required to study change over time. To evaluate these records, we analyzed 30+ years (1981 to 1999 and 2000 to 2009) of daily global land surface measurements (CMG resolution) from AVHRR (N07, N09, N11 and N14) and MODIS (AQUA and TERRA, Collection 5, C5). We stratified the data based on land cover, latitudinal zone, and season and we examined the daily data quality, including cloud persistence, aerosol loads, data gaps, and an index of reliability that measures how likely an observation is acceptable for research. The aim was to generate aggregate maps of cloud distribution, aerosol levels distribution, and data reliability distribution in both time and space. This information was then converted into an uncertainty measure at the pixel level that indicates how suspect or significant a result could potentially be, depending on its location and season and consequently what geographic locations and times

  9. Determination of Agriculture Land Use and Land Cover Change Using Remote Sensing and GIS in TROIA National Park

    Directory of Open Access Journals (Sweden)

    Y. B. Bostanci

    2007-01-01

    Full Text Available The area selected for land use land cover (LULC dynamics, TROIA national park, is located in the city of Çanakkale, TURKEY. The national park covers an area of about 13600 ha. Remote sensing studies especially multi-temporal analysis of changes provides sufficient information about the dynamics of historic landscape. Tasseled Cap Indexes and Normalized Difference Vegetation Index (NDVI were used to create the new images from Landsat TM 1987 and Landsat TM 2006 images for classification. Supervised classification was applied with ground truth data and auxiliary data collected from different sources such as air photo, cadastral information and others.Four classes of changed and unchanged multi-temporal raster were discriminated from created new images as followed: Active Agriculture, Grassland, Forestry, and Water. Classification accuracy was determined for 1987 image and 2006 image as 81% and 87% respectively. It was found that LULC change was dynamic between classes because of the land consolidation in the region. Grassland was changed to active agriculture area by 75% and to forestry class by 5%. Forested area also converted to active agriculture by 46% and to grassland by 9%. It was concluded that land consolidation project in the study area was the main force to change land cover.

  10. Rayleigh radiance computations for satellite remote sensing: accounting for the effect of sensor spectral response function.

    Science.gov (United States)

    Wang, Menghua

    2016-05-30

    To understand and assess the effect of the sensor spectral response function (SRF) on the accuracy of the top of the atmosphere (TOA) Rayleigh-scattering radiance computation, new TOA Rayleigh radiance lookup tables (LUTs) over global oceans and inland waters have been generated. The new Rayleigh LUTs include spectral coverage of 335-2555 nm, all possible solar-sensor geometries, and surface wind speeds of 0-30 m/s. Using the new Rayleigh LUTs, the sensor SRF effect on the accuracy of the TOA Rayleigh radiance computation has been evaluated for spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS)-1, showing some important uncertainties for VIIRS-SNPP particularly for large solar- and/or sensor-zenith angles as well as for large Rayleigh optical thicknesses (i.e., short wavelengths) and bands with broad spectral bandwidths. To accurately account for the sensor SRF effect, a new correction algorithm has been developed for VIIRS spectral bands, which improves the TOA Rayleigh radiance accuracy to ~0.01% even for the large solar-zenith angles of 70°-80°, compared with the error of ~0.7% without applying the correction for the VIIRS-SNPP 410 nm band. The same methodology that accounts for the sensor SRF effect on the Rayleigh radiance computation can be used for other satellite sensors. In addition, with the new Rayleigh LUTs, the effect of surface atmospheric pressure variation on the TOA Rayleigh radiance computation can be calculated precisely, and no specific atmospheric pressure correction algorithm is needed. There are some other important applications and advantages to using the new Rayleigh LUTs for satellite remote sensing, including an efficient and accurate TOA Rayleigh radiance computation for hyperspectral satellite remote sensing, detector-based TOA Rayleigh radiance computation, Rayleigh radiance calculations for high altitude

  11. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  12. Land use change detection based on multi-date imagery from different satellite sensor systems

    Science.gov (United States)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  13. Resultant Land Use and Land Cover Change from Oil Spillage using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    E.O. Omodanisi

    2013-07-01

    Full Text Available The spill of oil into the environment threatens the existence of vegetation. This study identified the coastal area of Lagos impacted by oil spill, explosion and fire; using Landsat ETM+2005 and Ikonos 2007 and evaluated the effect. Subsequently, geo-spatial database was created for monitoring of oil pipelines Right of Way (ROW in the area. The biggest land use land cover changes were the high forest and the light forest classes of mangrove vegetation by 22.2 and 15.5% respectively. The control quadrat sampled had the highest species diversity index of 0.6758 compared to the others. The study concluded that oil spill had affected the land use land cover as well as provided oil spill emergency response centres sites as a Spatial Decision Support System (SDSS for oil pipeline management.

  14. Examining the Satellite-Detected Urban Land Use Spatial Patterns Using Multidimensional Fractal Dimension Indices

    Directory of Open Access Journals (Sweden)

    Dongjie Fu

    2013-10-01

    Full Text Available Understanding the spatial patterns of urban land use at both the macro and the micro levels is a central issue in global change studies. Due to the nonlinear features associated with land use spatial patterns, it is currently necessary to provide some distinct analysis methods to analyze them across a range of remote sensing imagery resolutions. The objective of our study is to quantify urban land use patterns from various perspectives using multidimensional fractal methods. Three commonly used fractal dimensions, i.e., the boundary dimension, the radius dimension, and the information entropy dimension, are introduced as the typical indices to examine the complexity, centrality and balance of land use spatial patterns, respectively. Moreover, a new lacunarity dimension for describing the degree of self-organization of urban land use at the macro level is presented. A cloud-free Landsat ETM+ image acquired on 17 September 2010 was used to extract land use information in Wuhan, China. The results show that there are significant linear relationships represented by good statistical fitness related to these four indices. The results indicate that rapid urbanization has substantially affected the urban landscape pattern, and different land use types show different spatial patterns in response. This analysis reveals that multiple fractal/nonfractal indices provides a more comprehensive understanding of the spatial heterogeneity of urban land use spatial patterns than any single fractal dimension index. These findings can help us to gain deeper insight into the complex spatial patterns of urban land use.

  15. THE IMPACT OF SHADOWS IN THE RECENT INDIAN REMOTE SENSING SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    Mrs. G.Devi

    2011-08-01

    Full Text Available Remote sensing technology is emerging as a strong tool to extract information about the earth resources from the satellite imagery. However, shadow in fine resolution imagery affects this information. The fine resolution images from recent Indian Remote Sensing (IRS satellites are compared for the pixel values in shadow and non-shadow areas using histogram occupy large shadow area compared to Cartosat-1 of resolution 2.5m. The solar elevation angle is 41degree for which long shadows are formed in case of Cartosat-2 images. The solarelevation angle is 59 degree for which short shadows are formed in case of Cartosat-1 images. The shadows in an image are a function of the solar elevation angle, azimuth angle and spatial resolution etc. The fine resolution image (Cartosat-2 building and their shadow pixel values are analysed by bimodal histogram splitting technique. The shadow boundaries are extracted. Finally Gamma filtering applied and with the Gaussian enhancement technique the shadows are eliminated from Cartosat-2 image. The building shadow under objectcan be identified in this method. The main application in shadow elimination is used for urban map preparation and the object oriented classification.

  16. Remote, mobile telemedicine: the satellite transmission of medical data from Mount Logan.

    Science.gov (United States)

    Otto, C; Pipe, A

    1997-01-01

    The purpose of this investigation was to demonstrate the potential of remote, mobile telemedicine during a four-week, high-altitude mountaineering expedition to Mount Logan, Canada's highest summit. Using a mobile satellite terminal and a laptop computer (both powered by a photovoltaic solar panel), ECG tracings and blood pressure measurements, in addition to colour images, short-segment video and audio clips were transmitted during the course of the ascent. The data were transmitted via a mobile communications satellite to a ground station in Ottawa, a distance of over 4000 km. The data were then transferred to the public switched data network and delivered to the University of Ottawa Heart Institute for analysis. Similarly, data were transmitted from the ground station to the expedition team on Mount Logan throughout the ascent. Using this technique, medical diagnosis and emergency care can be facilitated in extreme and isolated locations lacking a telecommunications infrastructure. Such technology has applications in developing countries, disaster response efforts, remote civilian and military operations, and in space operations.

  17. Using satellite remote sensing to monitor the total suspended solids (TSS) over Penang Island, Malaysia

    Science.gov (United States)

    Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Mohd. Saleh, N.

    2008-10-01

    Total suspended solid (TSS) is a major factor affecting water quality in aquatic ecosystem. An investigation has been conducted to test the feasibility of using SPOT 5 data for estimating TSS in the coastal waters of Penang Island, Malaysia. Atmospheric correction of the satellite measurements is critical for aquatic remote sensing. Atmospheric correction of the remotely sensed image was performed using the ENVI FLAASH. Water samples were collected simultaneously with the satellite image acquisition and later analyzed in the laboratory. The digital numbers for each band corresponding to the sea-truth locations were extracted and then converted into reflectance values. The variables of the reflectance were used for calibration of the water quality algorithm. Regression technique was employed to calibrate the algorithm using the SPOT multispectral signals. An algorithm was developed based on the reflectance model, which is a function of the inherent optical properties of water that can be related to the concentration of its constituents. Spatial distribution map of the water quality parameter was produced using the calibrated algorithm. The efficiency of the present algorithm, in comparison to other forms of algorithm, was also investigated. Finally, the TSS map was generated using the proposed algorithm.

  18. Land use changes in Pak Phanang Basin using satellite images and geographic information system

    Directory of Open Access Journals (Sweden)

    Yongchalermchai, C.

    2004-01-01

    Full Text Available This study defined major changes in land use in Pak Phanang Basin, Nakhon Si Thammarat Province by using remote sensing and geographic information system techniques. The land use map conducted by Department of Land Development in 1988 was compared with the land use map interpreted from satelliteimages of Landsat-5 TM acquired in 1995 and 1999. The results revealed that between 1988 to 1999, forest area in the basin decreased by a total of 98.08 km2, a drastic decline of 60% that was changed to rubber plantation area. The rubber area increased about 181.7 km2 or 41%. Shrimp farm area increased by 184.87 km2, equivalent to a high increase of 886% while paddy field area decreased by 248.7 km2, or 16% that was converted to shrimp farm and rubber land. A decline in forest area caused soil erosion. The severe expansion of shrimp farm area caused the salinity and affected nearby paddy field and water source areas, that resulted in degradation of the environment. Application of remote sensing and geographic information system was utilized as a tool for monitoring the land use change and planning proper resource utilization for sustainable development in Pak Phanang Basin.

  19. Parameterization of aerodynamic roughness of China's land surface vegetation from remote sensing data

    Science.gov (United States)

    Hu, Deyong; Xing, Liwei; Huang, Shengli; Deng, Lei; Xu, Yingjun

    2014-01-01

    Aerodynamic roughness length (z0) is one of the important parameters that influence energy exchange at the land-atmosphere interface in numerical models, so it is of significance to accurately parameterize the land surface. To parameterize the z0 values of China's land surface vegetation using remote sensing data, we parameterized the vegetation canopy area index using the leaf area index and land cover products of moderate resolution imaging spectroradiometer data. Then we mapped the z0 values of different land cover types based on canopy area index and vegetation canopy height data. Finally, we analyzed the intra-annual monthly z0 values. The conclusions are: (1) This approach has been developed to parameterize large scale regional z0 values from multisource remote sensing data, allowing one to better model the land-atmosphere flux exchange based on this feasible and operational scheme. (2) The variation of z0 values in the parametric model is affected by the vegetation canopy area index and its threshold had been calculated to quantify different vegetation types. In general, the z0 value will increase during the growing season. When the threshold in the dense vegetation area or in the growing season is exceeded, the z0 values will decrease but the zero-plane displacement heights will increase. This technical scheme to parameterize the z0 can be applied to large-scale regions at a spatial resolution of 1 km, and the dynamic products of z0 can be used in high resolution land or atmospheric models to provide a useful scheme for land surface parameterization.

  20. Remote sensing monitoring land use change in Donglutian coal mine, Shuozhou City

    Science.gov (United States)

    Ye, Baoying; Liu, Ling

    2017-01-01

    This paper monitored the coal mine exploitation in Donglutian coal mine, Shuozhou city, Shanxi Province. Landsat satellite images from 2008 to 2016 were selected, and then 15m color composite images were obtained through data processing and image fusion. On this basis, the land use map from 2008 to 2016 was obtained using visual interpretation method. Results showed that the main land use type in this area was cropland, unused land and coalmine. Area of cropland and unused land kept decreasing year by year, while coal mine expanded rapidly. The expansion of coal mine concentrated on two time periods: from 2009 to 2010 and from 2012 to 2013. During these two time periods, topsoil stripping was the main exploitation type, while deep mining was the main type for other times. Results also presented that the exploitation number of small coals kept increasing year by year, from the initial number of 26 at 2008 to 42 at 2016.

  1. Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

    Science.gov (United States)

    Morris, Mary

    Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD's observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD's observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating

  2. Combining forest inventory, satellite remote sensing, and geospatial data for mapping forest attributes of the conterminous United States

    Science.gov (United States)

    Mark Nelson; Greg Liknes; Charles H. Perry

    2009-01-01

    Analysis and display of forest composition, structure, and pattern provides information for a variety of assessments and management decision support. The objective of this study was to produce geospatial datasets and maps of conterminous United States forest land ownership, forest site productivity, timberland, and reserved forest land. Satellite image-based maps of...

  3. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  4. Satellite remote sensing of water turbidity in Alqueva reservoir and implications on lake modelling

    Directory of Open Access Journals (Sweden)

    M. Potes

    2012-06-01

    Full Text Available The quality control and monitoring of surface freshwaters is crucial, since some of these water masses constitute essential renewable water resources for a variety of purposes. In addition, changes in the surface water composition may affect the physical properties of lake water, such as temperature, which in turn may impact the interactions of the water surface with the lower atmosphere.

    The use of satellite remote sensing to estimate the water turbidity of Alqueva reservoir, located in the south of Portugal, is explored. A validation study of the satellite derived water leaving spectral reflectance is firstly presented, using data taken during three field campaigns carried out during 2010 and early 2011. Secondly, an empirical algorithm to estimate lake water surface turbidity from the combination of in situ and satellite measurements is proposed. Finally, the importance of water turbidity on the surface energy balance is tested in the form of a study of the sensitivity of a lake model to the extinction coefficient of water (estimated from turbidity, showing that this is an important parameter that affects the lake surface temperature.

  5. Application of NASA's modern era retrospective-analysis in Global Wetlands Mappings Derived from Coarse-Resolution Satellite Microwave Remote Sensing

    Science.gov (United States)

    Schröder, R.; McDonald, K. C.; Podest, E.; Jones, L. A.; Kimball, J. S.; Pinto, N.; Zimmermann, R.; Küppers, M.

    2011-12-01

    The sensitivity of Earth's wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. Global methane emissions are typically estimated via process-based models calibrated to individual wetland sites. Regardless of the complexity of these process-based models, accurate geographical distribution and seasonality of recent global wetland extent are typically not accounted for in such an approach, which may explain the large variations in estimated global methane emissions as well as the significant interannual variations in the observed atmospheric growth rate of methane. Spatially comprehensive ground observation networks of large-scale inundation patterns are very sparse because they require large fiscal, technological and human resources. Satellite remote sensing of global inundation dynamics thus can support the ability for a complete synoptic view of past and current inundation dynamics over large areas that otherwise could not be assessed. Coarse-resolution (~25km) satellite data from passive and active microwave instruments are well suited for the global observation of large-scale inundation patterns because they are primarily sensitive to the associated dielectric properties of the landscape and cover large areas within a relatively short amount of time (up to daily repeat in high latitudes). This study summarizes a new remote sensing technique for quantifying global daily surface water fractions based on combined passive-active microwave remote sensing data sets from the AMSR-E and QuikSCAT instruments over a 7 year period (July 2002 - July 2009). We apply these data with ancillary land cover maps from MODIS to: 1) define the potential global domain of surface water impacted land; 2) establish land cover driven predictive equations for implementing a dynamic mixture model adjusted to total column water vapor obtained from NASA's modern era

  6. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

    Science.gov (United States)

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

    2014-12-01

    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  7. Multi-source remotely sensed data fusion for improving land cover classification

    Science.gov (United States)

    Chen, Bin; Huang, Bo; Xu, Bing

    2017-02-01

    Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

  8. EvaluationofLandCoverChangesRemoteSensingTechnique (Case Study: Hableh Rood Subwatershed of ShahrabadBasin)

    OpenAIRE

    Khadijeh Abolfathi; Marzieh Alikhah-Asl; Mohammad Rezvani; Mohammad Namdar

    2016-01-01

    The growing population and increasing socio-economic necessities creates a pressure on land use/land cover. Nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. This study investigates the land use changes in part of Hableh Rood Watershed of Iran using Landsat 7 and 8 (Sensor ETM+ and OLI) images between 2001 and 2013. Supervised classification was used for classifica...

  9. Classification of Forest Land Information Using Environment Satellite (HJ-1 Data

    Directory of Open Access Journals (Sweden)

    Yanxia Wang

    2011-06-01

    Full Text Available For researching properties of HJ-1A CCD camera multi-spectral data in performance on extraction of land features information, this paper selected the east area of NiLeke forest farm in the western Tianshan mountain as the study area, and analyzed different accuracies for HJ-1A CCD data in identifying forest land categories using various classification methods. Firstly, maximum-likelihood classifier, Mahalanobis distance classifier, minimum distance classifier and K-means classifier were used to category land use types with two different scales on HJ-1A CCD1 and Landsat5 TM images, and analyzed separately with confusion matrix. Secondly, forest land types were distinguished by texture information and the smallest polygon size using K-NN method based on clustering algorithm. The comparing results show: at first, different classification system have different accuracy. In the first land use classification system, the accuracy of HJ-1A CCD1 images are lower than TM images, but higher in the second land use classification system. Secondly, accuracy result of maximum-likelihood classification is the best method to classify land use types. In the first land use classification system, TM total accuracy is up to 85.1% and Kappa coefficient is 0.8. In the second land use classification system, the result is up to 85.4% and kappa coefficient is 0.74.Thirdly, judgment both from the view of visual interpretation and quantitative accuracy testes, non-supervised method with K-means classifier has low qualities where many land features have characters of scattered distribution and small different spectrum information. Finally, the experiment proved that there were good vector results on HJ-1A remote sensing image in the view of visual judgment, and extracted deferent forest land by the overall accuracy 87% with the supports by those variables’ distribution knowledge, such as conifer, mixed forest, broadleaf, shrubby.

  10. Constraints from atmospheric CO2 and satellite-based vegetation activity observations on current land carbon cycle trends

    Directory of Open Access Journals (Sweden)

    S. Zaehle

    2012-11-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely-sensed vegetation activity to provide a firm set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration has to pass, to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI-Earth system model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite based vegetation activity data allows to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations.

  11. Analysis of Landsat8 satellite remote sensing data preprocessing%Landsat8卫星遥感数据预处理方法

    Institute of Scientific and Technical Information of China (English)

    祝佳

    2016-01-01

    Landsat系列卫星是由美国航空航天局和美国地质调查局共同管理的资源遥感系列卫星,40多a来为地球遥感探测活动提供了大量清晰而稳定的图像数据。卫星遥感数据预处理是获取优质遥感基础图像的第一步,对后续各级卫星遥感产品的质量有着很重要的影响。针对Landsat8卫星原始数据,对卫星下传所采用的空间数据传输协议和数据传输格式进行了详细的解析,分析了原始数据从解同步、数据帧解析、任务数据包解析、图像数据获取直到生成0级图像产品的步骤;特别针对存在无损数据压缩的陆地成像仪( operational land imager,OLI)数据,讨论了基于空间数据系统咨询委员会( consultative committee for space data systems,CCSDS)相关标准进行无损数据解压缩处理的方法和过程。经数据预处理得到的Landsat8卫星0级图像产品,可为Landsat8卫星数据应用提供优质的基础图像。%The Landsat series satellites are the remote sensing resource series satellites, which are jointly managed by National Aeronautics and Space Administration and United States Geological Survey. Large quantities of high-resolution and stable image data provided by the Landsat series satellites have created good opportunities for the earth remote sensing exploration activities in the past forty years. Satellite remote sensing data preprocessing is the first step for obtaining remote sensing image, and has an important impact on the quality of the satellite remote sensing product. Aimed at tackling the Landsat8 raw data, the authors dealt in detail with the space data transmission protocol and data transmission format for Landsat8 data downlink. The preprocessing steps for raw data were analyzed, which included synchronization, transfer frame analyzing, unpack, mission data extracting, etc. In addition, the procedure of 0 - level image product acquisition was described. Specifically, based on CCSDS

  12. Responses to satellite remote sensing opportunities in East and Southern Africa

    Science.gov (United States)

    Falconer, Allan; Odenyo, Victor A. O.

    Since 1978 the U.S. Agency for International Development (USAID) has funded a regional remote sensing project for East and Southern Africa. The project, hosted by the Regional Centre for Services in Surveying Mapping and Remote Sensing, has provided a programme of training courses, user services and project support. This included the equipping and establishment of a photo-laboratory complex for processing Landsat images and the provision of advice and support for agencies undertaking natural resources analysis. Response to the training programme has been very good. Courses are usually over subscribed and there is a continued demand for training. Assessments of the courses by participants are highly positive and the courses have featured consultants of international calibre. Requests for follow-up courses, and for specialist group training indicate a strong response to this training activity. User services are active, consultations with staff, use of the browse file and interpretation equipment and the purchase of data for project work all produce an average demand of 12 active enquiries per working week. The photo-laboratory is particularly active and demand for products exceeds available capacity. Project work is now being supported but limited resources restrict the range and amount of project activity. Response to the opportunities offered for projects has been favourable and this activity is ripe for expansion. The difficulty in expanding to meet the expressed demand is primarily financial. The east and southern Africa region is not economically strong and has a great need for natural resources data for development work and planning. The responses to satellite remote sensing opportunities will be limited by these financial constraints which effectively means by the level of international aid directed to this activity. For such aid to be effective it must be coordinated and firmly attached to the region. Such coordinated aid programmes would avoid fragmentation

  13. Assessment of the Impact of Reservoirs in the Upper Mekong River Using Satellite Radar Altimetry and Remote Sensing Imageries

    Directory of Open Access Journals (Sweden)

    Kuan-Ting Liu

    2016-04-01

    Full Text Available Water level (WL and water volume (WV of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2 and Landsat-5/-7/-8 Thematic Mapper (TM/Enhanced Thematic Mapper plus (ETM+/Operational  Land Imager (OLI optical remote sensing (RS imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE is at 2–5 m level. The estimated WV variations derived from combined RA

  14. Surface Properties and Characteristics of Mars Landing Sites from Remote Sensing Data and Ground Truth

    Science.gov (United States)

    Golombek, M. P.; Haldemann, A. F.; Simpson, R. A.; Furgason, R. L.; Putzig, N. E.; Huertas, A.; Arvidson, R. E.; Heet, T.; Bell, J. F.; Mellon, M. T.; McEwen, A. S.

    2008-12-01

    Surface characteristics at the six sites where spacecraft have successfully landed on Mars can be related favorably to their signatures in remotely sensed data from orbit and from the Earth. Comparisons of the rock abundance, types and coverage of soils (and their physical properties), thermal inertia, albedo, and topographic slope all agree with orbital remote sensing estimates and show that the materials at the landing sites can be used as ground truth for the materials that make up most of the equatorial and mid- to moderately high-latitude regions of Mars. The six landing sites sample two of the three dominant global thermal inertia and albedo units that cover ~80% of the surface of Mars. The Viking, Spirit, Mars Pathfinder, and Phoenix landing sites are representative of the moderate to high thermal inertia and intermediate to high albedo unit that is dominated by crusty, cloddy, blocky or frozen soils (duricrust that may be layered) with various abundances of rocks and bright dust. The Opportunity landing site is representative of the moderate to high thermal inertia and low albedo surface unit that is relatively dust free and composed of dark eolian sand and/or increased abundance of rocks. Rock abundance derived from orbital thermal differencing techniques in the equatorial regions agrees with that determined from rock counts at the surface and varies from ~3-20% at the landing sites. The size-frequency distributions of rocks >1.5 m diameter fully resolvable in HiRISE images of the landing sites follow exponential models developed from lander measurements of smaller rocks and are continuous with these rock distributions indicating both are part of the same population. Interpretation of radar data confirms the presence of load bearing, relatively dense surfaces controlled by the soil type at the landing sites, regional rock populations from diffuse scattering similar to those observed directly at the sites, and root-mean-squared slopes that compare favorably

  15. Hydroclimatology of Lake Victoria region using hydrologic model and satellite remote sensing data

    Directory of Open Access Journals (Sweden)

    S. I. Khan

    2011-01-01

    Full Text Available Study of hydro-climatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data over the last two decades combined with the recently available multiple-years satellite remote sensing data, we analyzed and simulated, with a distributed hydrologic model, the hydro-climatology in Nzoia, one of the major contributing sub-basins of Lake Victoria in the East African highlands. The basin, with a semi arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the prime cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990's have had high peak discharges despite having relatively less annual rain. The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6 is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to

  16. An advanced generation land mobile satellite system and its critical technologies

    Science.gov (United States)

    Naderi, F.

    1982-01-01

    A conceptual design for a Land Mobile Satellite System (LMSS) for the 1990s is presented. LMSS involves small tranceivers accessing satellites directly, with ground reception through small car-top antennas. The satellite would have a large antenna and blanket coverage areas in the UHF. The call may originate from a home, be carried by wire to a gateway, transmitted to satellite on the S-band, converted to UHF on the satellite, and transmitted to the vehicle. The system design is constrained by the number of users in an area during the busiest hours, Shuttle storage, controllability factors, and the total area served. A 55-m antenna has been selected, with 87 spot beams and two 10 MHz UHF bands in the 806-890 MHz band. A 17 dB interbeam isolation level is required, implying that sufficient sub-bands can be generated to assure 8265 total channels. The mobile satellite (MSAT) would have an 83 m mast lower segment, a 34 m upper segment, and a second, 10 m antenna made of a deployable mesh. Various antenna function modes are considered.

  17. Land resources assessment of El-Galaba basin, South Egypt for the potentiality of agriculture expansion using remote sensing and GIS techniques

    Directory of Open Access Journals (Sweden)

    A.M. Saleh

    2015-10-01

    Full Text Available The socio-economic development in Egypt is based on land resources. Recently, the Egyptian government is interested in developing low desert zone areas which are located between the recent Nile flood plain and the limestone plateau, from the east and west sides, and represent an important source of aggregate materials. Therefore, this study was carried out to investigate the potentiality of El-Galaba basin soils which are located in the western part of the Aswan Governorate and are characterized by Wadi El-Kubbaniya for the horizontal agricultural expansion and their optimum agricultural use. The investigated area was remotely sensed to identify the landscape and its land resources. Terrain units were identified using draped Landsat 8 satellite image over Digital Terrain Model (DTM to express the landscape and the associated soil mapping units. Fifteen mapping units were identified and grouped. Land capability evaluation was performed using Cervatana capability model. The results of capability modeling revealed about 3.33% of land with good use capability, 76.06% land with moderate use capability, and 0.08% marginal or non-productive land. The main capability limitations were soil and erosion risks. The Almagra model was used to produce the optimum cropping pattern and limitations of soil units. Matching the crop requirements with soil characteristics, optimum cropping pattern was obtained for wheat, corn, melon, potatoes, sunflower, sugar beet, Alfalfa, peach, citrus, and olive. The results of the study revealed the potentiality of El-Galaba basin for agricultural uses.

  18. Monitoring and Evaluation of Cultivated Land Irrigation Guarantee Capability with Remote Sensing

    Science.gov (United States)

    Zhang, C., Sr.; Huang, J.; Li, L.; Wang, H.; Zhu, D.

    2015-12-01

    Abstract: Cultivated Land Quality Grade monitoring and evaluation is an important way to improve the land production capability and ensure the country food safety. Irrigation guarantee capability is one of important aspects in the cultivated land quality monitoring and evaluation. In the current cultivated land quality monitoring processing based on field survey, the irrigation rate need much human resources investment in long investigation process. This study choses Beijing-Tianjin-Hebei as study region, taking the 1 km × 1 km grid size of cultivated land unit with a winter wheat-summer maize double cropping system as study object. A new irrigation capacity evaluation index based on the ratio of the annual irrigation requirement retrieved from MODIS data and the actual quantity of irrigation was proposed. With the years of monitoring results the irrigation guarantee capability of study area was evaluated comprehensively. The change trend of the irrigation guarantee capability index (IGCI) with the agricultural drought disaster area in rural statistical yearbook of Beijing-Tianjin-Hebei area was generally consistent. The average of IGCI value, the probability of irrigation-guaranteed year and the weighted average which controlled by the irrigation demand index were used and compared in this paper. The experiment results indicate that the classification result from the present method was close to that from irrigation probability in the gradation on agriculture land quality in 2012, with overlap of 73% similar units. The method of monitoring and evaluation of cultivated land IGCI proposed in this paper has a potential in cultivated land quality level monitoring and evaluation in China. Key words: remote sensing, evapotranspiration, MODIS cultivated land quality, irrigation guarantee capability Authors: Chao Zhang, Jianxi Huang, Li Li, Hongshuo Wang, Dehai Zhu China Agricultural University zhangchaobj@gmail.com

  19. Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery

    Science.gov (United States)

    Pervez, Wasim; Uddin, Vali; Khan, Shoab Ahmad; Khan, Junaid Aziz

    2016-04-01

    Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

  20. System architecture and market aspects of an European Land Mobile Satellite System via EMS

    Science.gov (United States)

    Ananasso, F.; Mistretta, I.

    1992-03-01

    The paper describes an implementation scenario of a Land Mobile Satellite System via the EMS (European Mobile System) payload embarked on Italsat F-2. Some emphasis is given on market issues aiming at singling out business niches of Land Mobile Satellite Services (LMSS) in Europe. Other crucial issues exist such as: the alternate/competitive systems, the problems of interworking with other existing and/or planned systems, the definition of network architecture that better fits the user requirements, the marketing strategy and, last but not least, the financial evaluation of the project. The paper, on the basis of a study performed by Telespazio on behalf of ESA, discusses some of these issues with emphasis on competitive market aspects.

  1. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  2. Bridging Epidemiology and Remote Sensing: A Case Study of Dengue Fever and Land Use and Land Cover Change in Roatán, Honduras

    Science.gov (United States)

    Tuholske, C.; Brooks, T.

    2015-12-01

    Dengue fever is one of the fastest spreading infectious diseases in Latin America and the Caribbean. As part of a yearlong epidemiological study of dengue, this paper takes the first step to model the relationship between the urban/built environment and incidents of dengue fever in Roatán, Honduras. Roatán has experienced an 80-fold increase in annual tourists since the 1990s, with over 1.2 million people now visiting the island yearly. In tandem, the Caribbean island's population has exploded from fewer than 13,000 people in the 1970s to over 100,000 people today. Using broadband remote sensed satellite imagery, this paper maps and measures how this massive influx of tourists and population has altered the island's landscape. Results from a decision tree classifying technique applied to a Landsat 5 Thematic Mapper (TM) image from 1985 and Landsat 8 Operational Land Imager (OLI) image from 2014 suggest a rapid pace of urbanization; built and impervious surface has increased over 300% in the last 30 years. Emerging research suggests, similar to other mosquito-borne diseases, a correlation between built environment and risk to dengue because of the increase in stagnate water that serve as disease-host reservoirs. This remote sensing analysis will be integrated with georeferenced household level data of cases of dengue collected during a year-long cross-sectional study of dengue patients in Roatán. The result will be to model the relationship between dengue fever and urban/built environment.

  3. Decision tree approach for classification of remotely sensed satellite data using open source support

    Indian Academy of Sciences (India)

    Richa Sharma; Aniruddha Ghosh; P K Joshi

    2013-10-01

    In this study, an attempt has been made to develop a decision tree classification (DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source data mining software. The classified image is compared with the image classified using classical ISODATA clustering and Maximum Likelihood Classifier (MLC) algorithms. Classification result based on DTC method provided better visual depiction than results produced by ISODATA clustering or by MLC algorithms. The overall accuracy was found to be 90% (kappa = 0.88) using the DTC, 76.67% (kappa = 0.72) using the Maximum Likelihood and 57.5% (kappa = 0.49) using ISODATA clustering method. Based on the overall accuracy and kappa statistics, DTC was found to be more preferred classification approach than others.

  4. Integrating TWES and Satellite-based remote sensing: Lessons learned from the Honshu 2011 Tsunami

    Science.gov (United States)

    Löwe, Peter; Wächter, Joachim

    2013-04-01

    The Boxing Day Tsunami killed 240,000 people and inundated the affected shorelines with waves reaching heights up to 30m. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Honshu 2011 tsunami demonstrate that the key challenge for TEWS research still lies in the timely issuing of reliable early warning messages to areas at risk, but also to other stakeholders professionally involved in the unfolding event. Until now remote sensing products for Tsunami events, including crisis maps and change detection products, are exclusively linked to those phases of the disaster life cycle, which follow after the early warning stage: Response, recovery and mitigation. The International Charter for Space and Major Disasters has been initiated by the European Space Agency (ESA) and the Centre National d'Etudes Spatiales (CNES) in 1999. It coordinates a voluntary group of governmental space agencies and industry partners, to provide rapid crisis imaging and mapping to disaster and relief organisations to mitigate the effects of disasters on human life, property and the environment. The efficiency of this approach has been demonstrated in the field of Tsunami early warning by Charter activations following the Boxing Day Tsunami 2004, the Chile Tsunami 2010 and the Honshu Tsunami 2011. Traditional single-satellite operations allow at best bimonthly repeat rates over a given Area of Interest (AOI). This allows a lot of time for image acquisition campaign planning between imaging windows for the same AOI. The advent of constellations of identical remote sensing satellites in the early 21st century resulted both in daily AOI revisit capabilities and drastically reduced time frames for acquisition planning. However, the image acquisition planning for optical remote sensing satellite constellations is constrained by orbital and communication

  5. Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

    Full Text Available The Microwave Infrared Combined Rainfall Algorithm (MICRA consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN based technique is briefly illustrated.

  6. Dynamic land cover information: bridging the gap between remote sensing and natural resource management

    Directory of Open Access Journals (Sweden)

    Richard Thackway

    2013-03-01

    Full Text Available Environmental decision-makers are increasingly demanding detailed spatial coverages with high temporal frequency to assess trends and changes in the extent and condition of wetlands, species habitats, farmlands, forests, rangelands, soil, water, and vegetation. Dynamic land cover information can substantially meet these requirements. Access to satellite-based time series information provides an unprecedented opportunity to better focus natural resource management (NRM in Australia. Opportunities include assessing the extent and condition of key assets, prioritizing investment in key localities and time periods, improving targeting of scarce public funding, and monitoring and evaluating the outcome of this investment to assist land managers in improving land management practices to meet wider community social, economic, and environmental goals. We illustrate how these key “decision points” can be enhanced by linking dynamic land cover information to a stepped “cycle” model. We use the stepped cycle model to present two case studies, the management of fire and soil erosion, which demonstrate the application of dynamic land cover information to improve NRM decision-making across three broad stakeholder groups (national, regional, local. We use the case studies to highlight how accurate dynamic land cover information has been used to improve the design and reporting of national NRM programs.

  7. Handover aspects for a Low Earth Orbit (LEO) CDMA Land Mobile Satellite (LMS) system

    Science.gov (United States)

    Carter, P.; Beach, M. A.

    1993-01-01

    This paper addresses the problem of handoff in a land mobile satellite (LMS) system between adjacent satellites in a low earth orbit (LEO) constellation. In particular, emphasis is placed on the application of soft handoff in a direct sequence code division multiple access (DS-CDMA) LMS system. Soft handoff is explained in terms of terrestrial macroscopic diversity, in which signals transmitted via several independent fading paths are combined to enhance the link quality. This concept is then reconsidered in the context of a LEO LMS system. A two-state Markov channel model is used to simulate the effects of shadowing on the communications path from the mobile to each satellite during handoff. The results of the channel simulation form a platform for discussion regarding soft handoff, highlighting the potential merits of the scheme when applied in a LEO LMS environment.

  8. Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw

    uxes, such as sensible heat ux, ground heat ux and net radiation, are also necessary. While it is possible to measure those uxes with ground-based instruments at local scales, at region scales they usually need to be modelled or estimated with the help of satellite remote sensing data. Even though....... The performance of the DTD model was improved in forested ecosystems and during senescence, by taking into account the fraction of the vegetation that is green, as well as during dry conditions and in temperate climates, by modifying certain model formulations. A disaggregation algorithm was also developed...

  9. Remote Synchronization Experiments for Quasi-Zenith Satellite System Using Multiple Navigation Signals as Feedback Control

    Directory of Open Access Journals (Sweden)

    Toshiaki Iwata

    2011-01-01

    Full Text Available The remote synchronization system for the onboard crystal oscillator (RESSOX is a remote control method that permits synchronization between a ground station atomic clock and Japanese quasi-zenith satellite system (QZSS crystal oscillators. To realize the RESSOX of the QZSS, the utilization of navigation signals of QZSS for feedback control is an important issue. Since QZSS transmits seven navigation signals (L1C/A, L1CP, L1CD, L2CM, L2CL, L5Q, and L5I, all combinations of these signals should be evaluated. First, the RESSOX algorithm will be introduced. Next, experimental performance will be demonstrated. If only a single signal is available, ionospheric delay should be input from external measurements. If multiple frequency signals are available, any combination, except for L2 and L5, gives good performance with synchronization error being within two nanoseconds that of RESSOX. The combination of L1CD and L5Q gives the best synchronization performance (synchronization error within 1.14 ns. Finally, in the discussion, comparisons of long-duration performance, computer simulation, and sampling number used in feedback control are considered. Although experimental results do not correspond to the simulation results, the tendencies are similar. For the overlapping Allan deviation of long duration, the stability of 1.23×10−14 at 100,160 s is obtained.

  10. Assessment of nutrient distributions in Lake Champlain using satellite remote sensing.

    Science.gov (United States)

    Isenstein, Elizabeth M; Park, Mi-Hyun

    2014-09-01

    The introduction of nutrients to lakes causing eutrophic conditions is a major problem around the world. Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R(2)=0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. This approach can be applicable to other lakes experiencing eutrophication assisting decision making when implementing Best Management Practices and other mitigation techniques to lakes. Copyright © 2014. Published by Elsevier B.V.

  11. Potential of high resolution satellite imagery, remote weather data and 1D hydraulic modeling to evaluate flood areas in Gonaives, Haiti

    Science.gov (United States)

    Bozza, Andrea; Durand, Arnaud; Allenbach, Bernard; Confortola, Gabriele; Bocchiola, Daniele

    2013-04-01

    We present a feasibility study to explore potential of high-resolution imagery, coupled with hydraulic flood modeling to predict flooding risks, applied to the case study of Gonaives basins (585 km²), Haiti. We propose a methodology working at different scales, providing accurate results and a faster intervention during extreme flood events. The 'Hispaniola' island, in the Caribbean tropical zone, is often affected by extreme floods events. Floods are caused by tropical springs and hurricanes, and may lead to several damages, including cholera epidemics, as recently occurred, in the wake of the earthquake upon January 12th 2010 (magnitude 7.0). Floods studies based upon hydrological and hydraulic modeling are hampered by almost complete lack of ground data. Thenceforth, and given the noticeable cost involved in the organization of field measurement campaigns, the need for exploitation of remote sensing images data. HEC-RAS 1D modeling is carried out under different scenarios of available Digital Elevation Models. The DEMs are generated using optical remote sensing satellite (WorldView-1) and SRTM, combined with information from an open source database (Open Street Map). We study two recent flood episodes, where flood maps from remote sensing were available. Flood extent and land use have been assessed by way of data from SPOT-5 satellite, after hurricane Jeanne in 2004 and hurricane Hanna in 2008. A semi-distributed, DEM based hydrological model is used to simulate flood flows during the hurricanes. Precipitation input is taken from daily rainfall data derived from TRMM satellite, plus proper downscaling. The hydraulic model is calibrated using floodplain friction as tuning parameters against the observed flooded area. We compare different scenarios of flood simulation, and the predictive power of model calibration. The method provide acceptable results in depicting flooded areas, especially considering the tremendous lack of ground data, and show the potential of

  12. A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

    Science.gov (United States)

    Shen, Xin; Zhang, Jing; Yao, Huang

    2015-12-01

    Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

  13. Variability of Yellow River turbid plume detected with satellite remote sensing during water-sediment regulation

    Science.gov (United States)

    Guo, Kai; Zou, Tao; Jiang, Dejuan; Tang, Cheng; Zhang, Hua

    2017-03-01

    Water Sediment Regulations (WSRs) of the Yellow River (YR) have fundamentally altered the dynamics of freshwater and sediment transport in YR estuary and might profoundly affect water quality and ecosystem of the adjacent Bohai Sea. In this study, empirical algorithms were established to infer sea surface salinity and turbidity of YR plume using on surface reflectance products of MODIS and GOCI satellites in combination with observations from hydrographic surveys during the 2014 WSR event. Inter- and intraday variability of salinity and turbidity were quantitatively assessed and correlated with external forces including river discharge, tides, Coriolis force, and wind-driven circulation. The results revealed the enhanced offshore extension of turbid plume as WSR drastically increased freshwater and sediment discharge to river mouth. During WSR event, the area of low salinity plume (0.12sr-1) occupied a maximum area of 162 km2. Intraday variation observed from geostationary GOCI data clearly illustrated the dominance of tidal current on short term dispersal pattern of freshwater and sediment plume. In comparison, wind field dominated the seasonal variation in flume transport but had insignificant impact on short term river plume dynamic during WSR. Overall, this study demonstrated that the spatial and temporal dynamic of YR plume was successfully captured by satellite remote sensing, which provided an effective tool for evaluating the environmental and ecological impact of WSRs.

  14. A peculiar faint satellite in the remote outer halo of M31

    CERN Document Server

    Mackey, Dougal; Martin, Nicolas; Ferguson, Annette; Dotter, Aaron; McConnachie, Alan; Ibata, Rodrigo; Irwin, Mike; Lewis, Geraint; Sakari, Charli; Tanvir, Nial; Venn, Kim

    2013-01-01

    We present Hubble Space Telescope imaging of a newly-discovered faint stellar system, PAndAS-48, in the outskirts of the M31 halo. Our photometry reveals this object to be comprised of an ancient and very metal-poor stellar population with age > 10 Gyr and [Fe/H] < -2.3. Our inferred distance modulus of 24.57 +/- 0.11 confirms that PAndAS-48 is most likely a remote M31 satellite with a 3D galactocentric radius of 149 (+19 -8) kpc. We observe an apparent spread in color on the upper red giant branch that is larger than the photometric uncertainties should allow, and briefly explore the implications of this. Structurally, PAndAS-48 is diffuse, faint, and moderately flattened, with a half-light radius rh = 26 (+4 -3) pc, integrated luminosity Mv = -4.8 +/- 0.5, and ellipticity = 0.30 (+0.08 -0.15). On the size-luminosity plane it falls between the extended globular clusters seen in several nearby galaxies, and the recently-discovered faint dwarf satellites of the Milky Way; however, its characteristics do not...

  15. Remote sensing models using Landsat satellite data to monitor algal blooms in Lake Champlain.

    Science.gov (United States)

    Trescott, A; Park, M-H

    2013-01-01

    Lake Champlain is significantly impaired by excess phosphorus loading, requiring frequent lake-wide monitoring for eutrophic conditions and algal blooms. Satellite remote sensing provides regular, synoptic coverage of algal production over large areas with better spatial and temporal resolution compared with in situ monitoring. This study developed two algal production models using Landsat Enhanced Thematic Mapper Plus (ETM(+)) satellite imagery: a single band model and a band ratio model. The models predicted chlorophyll a concentrations to estimate algal cell densities throughout Lake Champlain. Each model was calibrated with in situ data compiled from summer 2006 (July 24 to September 10), and then validated with data for individual days in August 2007 and 2008. Validation results for the final single band and band ratio models produced Nash-Sutcliffe efficiency (NSE) coefficients of 0.65 and 0.66, respectively, confirming satisfactory model performance for both models. Because these models have been validated over multiple days and years, they can be applied for continuous monitoring of the lake.

  16. Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations

    Directory of Open Access Journals (Sweden)

    Miriam Pablos

    2016-07-01

    Full Text Available Soil moisture (SM is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST and evapotranspiration (ET. Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS and NASA’s Soil Moisture Active Passive (SMAP. LST is remotely sensed using thermal infrared (TIR sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014 of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R ≈ − 0.6 to −0.8, and between SMOS SM and MODIS LST Terra/Aqua day (R ≈ − 0.7. At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R ≈ − 0.5 to −0.7; satellite R ≈ − 0.4 to −0.7 indicating SM–LST coupling, than in winter (in situ R ≈ +0.3; satellite R ≈ − 0.3 indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ∼0

  17. 5 CFR Appendix A to Subpart C to... - Daily Transportation Allowance Schedule, Commuting Over Land by Private Motor Vehicle to Remote...

    Science.gov (United States)

    2010-01-01

    ..., Commuting Over Land by Private Motor Vehicle to Remote Duty Posts A Appendix A to Subpart C to Part 591... Allowance Based on Duty at Remote Worksites Pt. 591, Subpt. C, App. A Appendix A to Subpart C to Part 591—Daily Transportation Allowance Schedule, Commuting Over Land by Private Motor Vehicle to Remote...

  18. Watershed Land Cover/Land Use Mapping Using Remote Sensing and Data Mining in Gorganrood, Iran

    Directory of Open Access Journals (Sweden)

    Masoud Minaei

    2016-04-01

    Full Text Available The Gorganrood watershed (GW is experiencing considerable environmental change in the form of natural hazards and erosion, as well as deforestation, cultivation and development activities. As a result of this, different types of Land Cover/Land Use (LCLU change are taking place on an intensive level in the area. This research study investigates the LCLU conditions upstream of this watershed for the years 1972, 1986, 2000 and 2014, using Landsat MSS, TM, ETM+ and OLI/TIRS images. LCLU maps for 1972, 1986, and 2000 were produced using pixel-based classification methods. For the 2014 LCLU map, Geographic Object-Based Image Analysis (GEOBIA in combination with the data-mining capabilities of Gini and J48 machine-learning algorithms were used. The accuracy of the maps was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. The overall accuracy ranged from 89% to 95%, quantity disagreement from 2.1% to 6.6%, and allocation disagreement from 2.1% for 2014 to 2.7% for 2000. The results of this study indicate that a significant amount of change has occurred in the region, and that this has as a consequence affected ecosystem services and human activity. This knowledge of the LCLU status in the area will help managers and decision makers to develop plans and programs aimed at effectively managing the watershed into the future.

  19. Applications of Satellite Remote Sensing for Response to and Recovery from Meteorological Disasters

    Science.gov (United States)

    Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Camp, Parks; Leonardo, Dario; Bell, Jordan R.

    2014-01-01

    Numerous on-orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short-term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth-observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat-7 and Landsat-8 imagery help to identify the damaged areas. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. This presentation will provide an overview of near real-time data products developed for dissemination to SPoRT's partners in NOAA's National Weather Service, through collaboration with the USGS and other federal agencies. Specifically, it will focus on integration of various data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.

  20. A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

    NARCIS (Netherlands)

    Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Reiche, Johannes

    2016-01-01

    The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral

  1. The role of GIS and remote sensing in land degradation assessment and conservation mapping: some user experiences and expectations

    NARCIS (Netherlands)

    Lynden, van G.W.J.; Mantel, S.

    2001-01-01

    Planning strategies for sustainable land management require solid base line data on natural resources (soils, physiography, climate, vegetation, land use, etc.) and on socio-economic aspects. GIS and remote sensing have an important role in linkage and analysis of such data, in particular for detect

  2. Detection of land cover change using an Artificial Neural Network on a time-series of MODIS satellite data

    CSIR Research Space (South Africa)

    Olivier, JC

    2007-11-01

    Full Text Available An Artificial Neural Network (ANN) is proposed to detect human-induced land cover change using a sliding window through a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite surface reflectance pixel values. Training...

  3. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates.

    Science.gov (United States)

    Zheng, Daolan; Heath, Linda S; Ducey, Mark J

    2008-09-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg.ha(-1), dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg ha(-1) (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval.

  4. Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

    Science.gov (United States)

    Zin, M. H. M.; Ahmad, B.

    2014-02-01

    The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.

  5. Mapping forest plantations in Mainland China: combining remotely sensed land cover and census land use data in a land transition model

    Science.gov (United States)

    Ying, Q.; Hurtt, G. C.; Chini, L. P.; Fisk, J.; Liang, S.; Hansen, M.; Dolan, K. A.

    2013-12-01

    Forest plantations have played an important role in shaping the coverage and compositions of China's forests. Maps characterizing the spatial and temporal patterns of forest plantations in china are essential to both identifying and quantifying how forest plantations are driving changes to the countries ecosystem structure and terrestrial carbon cycle. At this time there are no detailed spatial maps of plantations in China accessible to public. Land transition model that employs Metropolis simulated annealing optimization has been demonstrated effective in land use mapping when land cover observations and land use census data are available. This study aims to map forest plantations in Mainland China by linking remote sensing observations of land cover and census statistics on land use in land transition model. Two models, a national model and a regional model were developed in the study. National model depicted a universal relationship between land cover and land use across the whole country. One of the land use data sources came from the 7th National Forest Inventory (NFI) that depicted forest plantation area in the period of 2004-2008 in each provincial jurisdictions of China (Data from Taiwan, Hongkong and Macau is not available). In accordance with land use data, MODIS yearly IGBP land cover product that contains sixteen-land cover types has been averaged upon the same time period and summarized for each province. The pairwise correlation coefficient between modeled value and reported value is 0.9996. In addition, the 95% confidence interval of true population correlation of these two variables is [0.9994, 0.9998]. Because the targeted forest plantations cover much less area compared to the other land use type of non-plantation, model precision on forest plantations was isolated to eliminate the dominance in area of non-plantation and the correlation coefficient is 0.8058. National model tends to underestimate plantation area. Due to distinct geographic and

  6. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  7. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  8. The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

    Science.gov (United States)

    Hogan, Christine A.

    1996-01-01

    A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

  9. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  10. Seasonal evaluation of the land surface sheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian regions in Hungary

    NARCIS (Netherlands)

    Wipfler, E.L.; Metselaar, K.; Dam, van J.C.; Feddes, R.A.; Meijgaard, van E.; Ulft, van L.H.; Hurk, van den B.; Zwart, S.J.; Bastiaanssen, W.G.M.

    2011-01-01

    The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of

  11. The Water Cycle from Space: Use of Satellite Data in Land Surface Hydrology and Water Resource Management

    Science.gov (United States)

    Laymon, Charles; Blankenship, Clay; Khan, Maudood; Limaye, Ashutosh; Hornbuckle, Brian; Rowlandson, Tracy

    2010-01-01

    This slide presentation reviews how our understanding of the water cycle is enhanced by our use of satellite data, and how this informs land surface hydrology and water resource management. It reviews how NASA's current and future satellite missions will provide Earth system data of unprecedented breadth, accuracy and utility for hydrologic analysis.

  12. Land Mobile Satellite Service (LMSS): A conceptual system design and identification of the critical technologies: Part 2: Technical report

    Science.gov (United States)

    Naderi, F. (Editor)

    1982-01-01

    A conceptual system design for a satellite-aided land mobile service is described. A geostationary satellite which employs a large (55-m) UHF reflector to communicate with small inexpensive user antennas on mobile vehicles is discussed. It is shown that such a satellite system through multiple beam antennas and frequency reuse can provide thousands of radiotelephone and dispatch channels serving hundreds of thousands of users throughout the U.S.

  13. Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data.

    Science.gov (United States)

    Fallati, Luca; Savini, Alessandra; Sterlacchini, Simone; Galli, Paolo

    2017-08-01

    The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe's WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product's overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.

  14. Estimation of the rice-planting field in Bangladesh by satellite remote sensing

    Science.gov (United States)

    Furuta, E.; Suzuki, G.; Yamassaki, M.; Teraoka, T.; Fujiwara, H.; Ogino, Y.; Akashi, M.; Lahrita, L.; Naruse, N.; Takahashi, Y.

    2016-12-01

    In Bangladesh, price of rice has been unstable due to a large increase in production. To control the price can become a political issue, because rice agriculture is one of the most important industries in Bangladesh, whereas the total area of the paddy field is accurately unknown, owing to unsustainable and on-site surveys for the area (1). Satellite remote sensing is an effective solution to research the all area of domestic paddy field. Microwave satellite imaging has a large merit to be observable regardless of the weather conditions, however, research institutions have been limited to observing continuously since the cost is high for developing countries, such as Bangladesh. This study aims to establish the way to grasp the paddy field using optical satellite images for free of charge (Landsat-8). We have focused on seasonal changes in the water and the vegetation indices obtained from paddy fields. We have performed image calculations of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) of the well-known paddy field in Bangladesh Rice Research Institute. We found that there are seasonal changes of NDVI and NDWI calculated from paddy field. The characteristics are as follows; the NDVI and the NDWI values varies by 0.17-0.25 up and 0.11-0.19 down, respectively, at the transition from the dry to the rainy season, on the other hand, the NDVI and the NDWI changes by 0.21-0.29 down and 0.09-0.17 up from the rainy to the dry season. These features make us to distinguish the paddy field from the other cultivated area. The decrease of NDVI means that rice bares, The increase of NDWI can be interpreted that the paddy field is covered with water for the preparation for planting it. Our estimated area of paddy field in Bangladesh (85,900km ) corresponds well with the previous reported value of 117,700km (1). We have established the way to grasp the paddy field using optical satellite images for free of charge, on the bases of the

  15. Visir-Sat - a Prospective Micro-Satellite Based Multi-Spectral Thermal Mission for Land Applications

    Science.gov (United States)

    Ruecker, G.; Menz, G.; Heinemann, S.; Hartmann, M.; Oertel, D.

    2015-04-01

    Current space-borne thermal infrared satellite systems aimed at land surface remote sensing retain some significant deficiencies, in particular in terms of spatial resolution, spectral coverage, number of imaging bands and temperature-emissivity separation. The proposed VISible-to-thermal IR micro-SATellite (VISIR-SAT) mission addresses many of these limitations, providing multi-spectral imaging data with medium-to-high spatial resolution (80m GSD from 800 km altitude) in the thermal infrared (up to 6 TIR bands, between 8 and 11μm) and in the mid infrared (1 or 2 MIR bands, at 4μm). These MIR/TIR bands will be co-registered with simultaneously acquired high spatial resolution (less than 30 m GSP) visible and near infrared multi-spectral imaging data. To enhance the spatial resolution of the MIR/TIR multi-spectral imagery during daytime, data fusion methods will be applied, such as the Multi-sensor Multi-resolution Technique (MMT), already successfully tested over agricultural terrain. This image processing technique will make generation of Land Surface Temperature (LST) EO products with a spatial resolution of 30 x 30 m2 possible. For high temperature phenomena such as vegetation- and peat-fires, the Fire Disturbance Essential Climate Variables (ECV) "Active fire location" and "Fire Radiative Power" will be retrieved with less than 100 m spatial resolution. Together with the effective fire temperature and the spatial extent even for small fire events the innovative system characteristics of VISIR-SAT go beyond existing and planned IR missions. The comprehensive and physically high-accuracy products from VISIR-SAT (e.g. for fire monitoring) may synergistically complement the high temperature observations of Sentinel-3 SLSTR in a unique way. Additionally, VISIR-SAT offers a very agile sensor system, which will be able to conduct intelligent and flexible pointing of the sensor's line-of-sight with the aim to provide global coverage of cloud free imagery every 5

  16. Integration of remotely sensed indices for land cover changes caused by the 2009 Victorian bushfires using Landsat TM imagery

    Institute of Scientific and Technical Information of China (English)

    GUO Li; LI Xiao-jing; XU Xian-lei; GE Lin-lin

    2010-01-01

    In order to minimise the bushfires negative impacts on society, an efficient and reliable bushfire detection system was proposed to assess the devastated effects of the 2009 Victorian bushfires. It is possible to utilise the repetitive capability of satellite remote sensing imagery to identify the location of change to the Earth's surface and integrate the different remotely sensed indices. The results confirm that the procedure can offer essential spatial information for bushfire assessment.

  17. Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets.

    Science.gov (United States)

    Vadrevu, Krishna Prasad; Lasko, Kristofer; Giglio, Louis; Justice, Chris

    2014-12-01

    In this study, we assess the intense pollution episode of June 2013, in Riau province, Indonesia from land clearing. We relied on satellite retrievals of aerosols and Carbon monoxide (CO) due to lack of ground measurements. We used both the yearly and daily data for aerosol optical depth (AOD), fine mode fraction (FMF), aerosol absorption optical depth (AAOD) and UV aerosol index (UVAI) for characterizing variations. We found significant enhancement in aerosols and CO during the pollution episode. Compared to mean (2008-2012) June AOD of 0.40, FMF-0.39, AAOD-0.45, UVAI-1.77 and CO of 200 ppbv, June 2013 values reached 0.8, 0.573, 0.672, 1.77 and 978 ppbv respectively. Correlations of fire counts with AAOD and UVAI were stronger compared to AOD and FMF. Results from a trajectory model suggested transport of air masses from Indonesia towards Malaysia, Singapore and southern Thailand. Our results highlight satellite-based mapping and monitoring of pollution episodes in Southeast Asia.

  18. Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

    2015-11-01

    Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

  19. Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

    2015-01-01

    Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

  20. Multi-Criteria Assessment of Land Cover Dynamic Changes in Halgurd Sakran National Park (HSNP, Kurdistan Region of Iraq, Using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    Rahel Hamad

    2017-03-01

    Full Text Available Halgurd Sakran National Park (HSNP is Iraq’s first designated national park, located in the Kurdistan Region, which has suffered multiple armed conflicts over the past decades. This study assesses how vegetation dynamics have affected the landscape structure and composition of the core zone of the park over the last 31 years. Spatio-temporal changes in land cover were mapped for three points in time using remote sensing, geographic information systems (GIS, and landscape metrics. Land cover changes were mapped using random forest classifications of satellite images from Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 LDCM acquired in 1984, 1998, and 2015. Five landscape pattern metrics were analysed at class and landscape levels in order to quantify landscape patterns arising from land use and land cover (LULC change in HSNP using FRAGSTATS 4.2. These landscape pattern metrics were patch metrics, area metrics, shape metrics interspersion/juxtaposition and contagion metrics and diversity metrics. Significant changes in cultivated areas after 1991 were observed, which indicate the role of anthropogenic activities in land cover change. Areas of bare surface and forest lands declined and became more fragmented in 1984 and 1998 while, at the same time, cultivated areas increased, with a continuing fragmentation of pasture land. Internal migration of people was one of the major drivers of LULC change. The results reveal that significant LULC changes in terms of composition and spatial structure over the 31-year period have occurred in the designated protected area. Landscape metrics were able to assess the trend of spatial patchiness over the studied period. A discussion of the significance of changes in land use systems for understanding the causes and consequences of change is provided.

  1. Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

    Science.gov (United States)

    Fearns, Peter

    2017-01-01

    The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

  2. "Using Satellite Remote Sensing to Derive Numeric Criteria in Coastal and Inland Waters of the United States"

    Science.gov (United States)

    Crawford, T. N.; Schaeffer, B. A.

    2016-12-01

    Anthropogenic nutrient pollution is a major stressor of aquatic ecosystems around the world. In the United States, states and tribes can adopt numeric water quality values (i.e. criteria) into their water quality management standards to protect aquatic life from eutrophication impacts. However, budget and resource constraints have limited the ability of many states and tribes to collect the water quality monitoring data needed to derive numeric criteria. Over the last few decades, satellite technology has provided water quality measurements on a global scale over long time periods. Water quality managers are finding the data provided by satellite technology useful in managing eutrophication impacts in coastal waters, estuaries, lakes, and reservoirs. In recent years EPA has worked with states and tribes to derive remotely sensed numeric Chl-a criteria for coastal waters with limited field-based data. This approach is now being expanded and used to derive Chl-a criteria in freshwater systems across the United States. This presentation will cover EPA's approach to derive numeric Chl-a criteria using satellite remote sensing, recommendations to improve satellite sensors to expand applications, potential areas of interest, and the challenges of using remote sensing to establish water quality management goals, as well as provide a case in which this approach has been applied.

  3. Towards a Quantitative Use of Satellite Remote Sensing in Crop Growth Models for Large Scale Agricultural Production Estimate (Invited)

    Science.gov (United States)

    Defourny, P.

    2013-12-01

    The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables

  4. Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

    Science.gov (United States)

    Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

    2016-08-01

    Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

  5. Studying bio-thermal effects at and around MSW dumps using Satellite Remote Sensing and GIS.

    Science.gov (United States)

    Mahmood, Khalid; Batool, Syeda Adila; Chaudhry, Muhammad Nawaz

    2016-09-01

    Estimating negative impacts of MSW dumps on its surrounding environment is the key requirement for any remedial measures. This study has been undertaken to map bio-thermal effects of MSW dumping at and around dumping facilities (non-engineered) using satellite imagery for Faisalabad, Pakistan. Thirty images of Landsat 8 have been selected after validation for the accuracy of their observational details from April 2013 to October 2015. Land Surface Temperature (LST), NDVI, SAVI and MSAVI have been derived from these images through Digital Image Processing (DIP) and have been subjected to spatio-temporal analysis in GIS environment. MSW dump has been found with average temperature elevation of 4.3K and 2.78K from nearby agriculture land and urban settlement respectively. Vegetation health has been used as the bio-indicator of MSW effects and is implemented through NDVI, SAVI, MSAVI. Spatial analyses have been used to mark boundary of bio-thermally affected zone around dumped MSW and measure 700m. Seasonal fluctuations of elevated temperatures and boundary of the bio-thermally affected zones have also been discussed. Based on the direct relation found between vegetation vigor and the level of deterioration within the bio-thermally affected region, use of crops with heavy vigor is recommended to study MSW hazard influence using bio-indicators of vegetation health.

  6. Comparing near-earth and satellite remote sensing based phenophase estimates: an analysis using multiple webcams and MODIS (Invited)

    Science.gov (United States)

    Hufkens, K.; Richardson, A. D.; Migliavacca, M.; Frolking, S. E.; Braswell, B. H.; Milliman, T.; Friedl, M. A.

    2010-12-01

    In recent years several studies have used digital cameras and webcams to monitor green leaf phenology. Such "near-surface" remote sensing has been shown to be a cost effective means of accurately capturing phenology. Specifically, it allows for accurate tracking of intra- and inter-annual phenological dynamics at high temporal frequency and over broad spatial scales compared to visual observations or tower-based fAPAR and broadband NDVI measurements. Near surface remote sensing measurements therefore show promise for bridging the gap between traditional in-situ measurements of phenology and satellite remote sensing data. For this work, we examined the relationship between phenophase estimates derived from satellite remote sensing (MODIS) and near-earth remote sensing derived from webcams for a select set of sites with high-quality webcam data. A logistic model was used to characterize phenophases for both the webcam and MODIS data. We documented model fit accuracy, phenophase estimates, and model biases for both data sources. Our results show that different vegetation indices (VI's) derived from MODIS produce significantly different phenophase estimates compared to corresponding estimates derived from webcam data. Different VI's showed markedly different radiometric properties, and as a result, influenced phenophase estimates. The study shows that phenophase estimates are not only highly dependent on the algorithm used but also depend on the VI used by the phenology retrieval algorithm. These results highlight the need for a better understanding of how near-earth and satellite remote data relate to eco-physiological and canopy changes during different parts of the growing season.

  7. Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Hasituya

    2017-03-01

    Full Text Available In recent years, the area of plastic-mulched farmland (PMF has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1 satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.

  8. Role of satellite remote sensing in the geographic information economics in France

    Science.gov (United States)

    Denégre, Jean

    In national and international economics, geographic information plays a role which is generally acknowledged to be important but which is however, difficult to assess quantitatively, its applications being rather miscellaneous and indirect. Computer graphics and telecommunications increae that importance still more and justify many investments and research into new cartographic forms. As part of its responsibility for participating in the promotion of those developments, by taking into account needs expressed by public or private users, the National Council for Geographic Information (C.N.I.G.) has undertaken a general evaluation of the economic and social utility of geographic information in France. The study involves an estimation of the cost of production and research activities, which are probably about 0.1% of the Cross National Product—similar to many other countries. It also devised a method of estimating "cost/advantage" ratios applicable to these "intangible" benefits. Within that framework, remote sensing emphasizes particular aspects related both to the increase of economic performances in cartographic production and to the advent of new products and new ways of utilization. A review of some significant sectors shows effective earnings of about 10-20%, or even 50% or 100% of the costs, and these are doubtless much greater for the efficacy in the exploitation of products. Finally, many applications, entirely new result from extensions in various fields which would have been impossible without remote sensing: here the "cost advantage" ratio cannot even be compared with previous processes. Studies were undertaken in parallel for defining different types of products derived from satellite imagery, as well as those domains where development effort is required in order to make new advances.

  9. Cross-validation of satellite products over France through their integration into a land surface model

    Science.gov (United States)

    Calvet, Jean-Christophe; Barbu, Alina; Carrer, Dominique; Meurey, Catherine

    2014-05-01

    Long (more than 30 years) time series of satellite-derived products over land are now available. They concern Essential Climate Variables (ECV) such as LAI, FAPAR, surface albedo, and soil moisture. The direct validation of such Climate Data Records (CDR) is not easy, as in situ observations are limited in space and time. Therefore, indirect validation has a key role. It consists in comparing the products with similar preexisting products derived from satellite observations or from land surface model (LSM) simulations. The most advanced indirect validation technique consists in integrating the products into a LSM using a data assimilation scheme. The obtained reanalysis accounts for the synergies of the various upstream products and provides statistics which can be used to monitor the quality of the assimilated observations. Meteo-France develops the ISBA-A-gs generic LSM able to represent the diurnal cycle of the surface fluxes together with the seasonal, interannual and decadal variability of the vegetation biomass. The LSM is embedded in the SURFEX modeling platform together with a simplified extended Kalman filter. These tools form a Land Data Assimilation System (LDAS). The current version of the LDAS assimilates SPOT-VGT LAI and ASCAT surface soil moisture (SSM) products over France (8km x 8km), and a passive monitoring of albedo, FAPAR and Land Surface temperature (LST) is performed (i.e., the simulated values are compared with the satellite products). The LDAS-France system is used in the European Copernicus Global Land Service (http://land.copernicus.eu/global/) to monitor the quality of upstream products. The LDAS generates statistics whose trends can be analyzed in order to detect possible drifts in the quality of the products: (1) for LAI and SSM, metrics derived from the active monitoring (i.e. assimilation) such as innovations (observations vs. model forecast), residuals (observations vs. analysis), and increments (analysis vs. model forecast) ; (2

  10. Remote Sensing Education and Development Countries: Multilateral Efforts through the Committee on Earth Observation Satellites (CEOS)

    Science.gov (United States)

    Charles, Leslie Bermann

    1998-01-01

    The Committee on Earth Observation Satellites (CEOS) is an international organization which coordinates space-based Earth observations world wide. Created in 1984, CEOS now comprises 38 national space agencies, regional organizations and international space-related and research groups. The aim of CEOS is to achieve international coordination in the planning of satellite missions for Earth observation and to maximize the utilization of data from these missions world-wide. With regard to developing countries, the fundamental aim of CEOS is to encourage the creation and maintenance of indigenous capability that is integrated into the local decision-making process, thereby enabling developing countries to obtain the maximum benefit from Earth observation. Obtaining adequate access to remote sensing information is difficult for developing countries and students and teachers alike. High unit data prices, the specialized nature of the technology , difficulty in locating specific data, complexities of copyright provisions, the emphasis on "leading edge" technology and research, and the lack of training materials relating to readily understood application are frequently noted obstacles. CEOS has developed an education CD-ROM which is aimed at increasing the integration of space-based data into school curricula, meeting the heretofore unsatisfied needs of developing countries for information about Earth observation application, data sources and future plans; and raising awareness around the world of the value of Earth observation data from space. The CD-ROM is designed to be used with an Internet web browser, increasing the information available to the user, but it can also be used on a stand-alone machine. It contains suggested lesson plans and additional resources for educators and users in developing countries.

  11. A PECULIAR FAINT SATELLITE IN THE REMOTE OUTER HALO OF M31

    Energy Technology Data Exchange (ETDEWEB)

    Mackey, A. D.; Dotter, A. [Research School of Astronomy and Astrophysics, Australian National University, Mount Stromlo Observatory, via Cotter Road, Weston, ACT 2611 (Australia); Huxor, A. P. [Astronomisches Rechen-Institut, Universitaet Heidelberg, Moenchhofstrasse 12-14, D-69120 Heidelberg (Germany); Martin, N. F.; Ibata, R. A. [Observatoire astronomique de Strasbourg, Universite de Strasbourg, CNRS, UMR 7550, 11 rue de l' Universite, F-67000 Strasbourg (France); Ferguson, A. M. N. [Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); McConnachie, A. W. [NRC Herzberg Institute for Astrophysics, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Irwin, M. J. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Lewis, G. F. [Sydney Institute for Astronomy, School of Physics, A28, University of Sydney, NSW 2006 (Australia); Sakari, C. M.; Venn, K. A. [Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 1A1 (Canada); Tanvir, N. R., E-mail: dougal@mso.anu.edu.au [Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH (United Kingdom)

    2013-06-20

    We present Hubble Space Telescope imaging of a newly discovered faint stellar system, PAndAS-48, in the outskirts of the M31 halo. Our photometry reveals this object to be comprised of an ancient and very metal-poor stellar population with age {approx}> 10 Gyr and [Fe/H] {approx}< -2.3. Our inferred distance modulus (m - M){sub 0} = 24.57 {+-} 0.11 confirms that PAndAS-48 is most likely a remote M31 satellite with a three-dimensional galactocentric radius of 149{sup +19}{sub -8} kpc. We observe an apparent spread in color on the upper red giant branch that is larger than the photometric uncertainties should allow, and briefly explore the implications of this. Structurally, PAndAS-48 is diffuse, faint, and moderately flattened, with a half-light radius r{sub h}=26{sup +4}{sub -3} pc, integrated luminosity M{sub V} = -4.8 {+-} 0.5, and ellipticity {epsilon}=0.30{sup +0.08}{sub -0.15}. On the size-luminosity plane it falls between the extended globular clusters seen in several nearby galaxies and the recently discovered faint dwarf satellites of the Milky Way; however, its characteristics do not allow us to unambiguously classify it as either type of system. If PAndAS-48 is a globular cluster then it is among the most elliptical, isolated, and metal-poor of any seen in the Local Group, extended or otherwise. Conversely, while its properties are generally consistent with those observed for the faint Milky Way dwarfs, it would be a factor of {approx}2-3 smaller in spatial extent than any known counterpart of comparable luminosity.

  12. Quantifying land-cover proportions for urban runoff prediction. The advantage of distributed remote sensing techniques.

    Science.gov (United States)

    Berezowski, T.; Chormanski, J.; Batelaan, O.; Canters, F.; Van de Voorde, T.

    2012-04-01

    The volume, intensity and contamination of runoff generated by rainfall events in catchments are strongly dependent on land-cover composition. This aspect is extremely important in urbanized catchments, where floods are dangerous for inhabitants and infrastructure; moreover, water contamination is an important issue. Parameterization of distributed models in urban land-use is difficult because impervious objects are mixed with other land-covers like: vegetation, bare soil and water. Many hydrological models do not account for this variability and parameterize urban land-use by focusing only on impervious proportions, assuming one proportion value per land-use class. This parameterization strategy may lead to decreasing physical meaning of other parameters calibrated in a model. This study aims to show how the method of estimation of land-cover proportions impacts discharge prediction of the distributed hydrological model - WetSpa. The study area is an urbanized catchment of the Biala River, situated in the northeastern part of Poland. The simulations were run in a summer period with peak discharge events. Three modeling scenarios of land-cover proportions were tested of which two assumed fully-distributed land-cover proportions in the study area: hard classification of an Ikonos scene and a subpixel classification of a Landsat 5 TM scene. The third scenario used a standard modeling approach in which one impervious proportion is assigned per land-use class. The best Nash-Sutcliffe efficiency (NS) result was obtained for the Landsat TM subpixel classification scenario (NS=0.63). A similar result was obtained for the Ikonos hard-classification scenario (NS=0.62). The standard modeling scenario resulted in the lowest simulation efficiency (NS=0.40). Comparison of the observed and simulated peak discharges showed the best match for the Ikonos hard-classification, while the Landsat TM subpixel had ~18% and the standard modeling approach ~36% underestimation. Based on

  13. Fuzzy nonlinear proximal support vector machine for land extraction based on remote sensing image.

    Directory of Open Access Journals (Sweden)

    Xiaomei Zhong

    Full Text Available Currently, remote sensing technologies were widely employed in the dynamic monitoring of the land. This paper presented an algorithm named fuzzy nonlinear proximal support vector machine (FNPSVM by basing on ETM(+ remote sensing image. This algorithm is applied to extract various types of lands of the city Da'an in northern China. Two multi-category strategies, namely "one-against-one" and "one-against-rest" for this algorithm were described in detail and then compared. A fuzzy membership function was presented to reduce the effects of noises or outliers on the data samples. The approaches of feature extraction, feature selection, and several key parameter settings were also given. Numerous experiments were carried out to evaluate its performances including various accuracies (overall accuracies and kappa coefficient, stability, training speed, and classification speed. The FNPSVM classifier was compared to the other three classifiers including the maximum likelihood classifier (MLC, back propagation neural network (BPN, and the proximal support vector machine (PSVM under different training conditions. The impacts of the selection of training samples, testing samples and features on the four classifiers were also evaluated in these experiments.

  14. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    Directory of Open Access Journals (Sweden)

    M. Marshall

    2013-03-01

    Full Text Available Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET, a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET, driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

  15. Concepts and cost trade-offs for land vehicle antennas in satellite mobile communications

    Science.gov (United States)

    Haddad, H. A.

    1948-01-01

    Several antenna design concepts, operating at UHF (821 to 825 MHz transmit and 866 to 870 MHz receive bands), with gain ranging between 6 and 12 dBic, that are suitable for land mobile vehicles are presented. The antennas may be used within CONUS and ALASKA to communicate to and from a geosynchronous satellite. Depending on the type of steering mechanism, the antennas are broken down into three categories; (1) electronically scanned arrays with phase shifters, (2) electronically switched arrays with switchable power dividers/combiners, and (3) mechanically steered arrays. The operating characteristics of two of these design concepts, one a conformal antenna with electronic beam steering and the other a nonconformal design with mechanical steering, were evaluated with regard to two and three satellite system. Cost estimates of various antenna concepts were made and plotted against their overall gain performance.

  16. Use of various remote sensing land cover products for PFT mapping over Siberia

    Directory of Open Access Journals (Sweden)

    C. Ottlé

    2013-06-01

    Full Text Available High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation. The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern

  17. Use of various remote sensing land cover products for PFT mapping over Siberia

    Science.gov (United States)

    Ottlé, C.; Lescure, J.; Maignan, F.; Poulter, B.; Wang, T.; Delbart, N.

    2013-06-01

    High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated

  18. Use of various remote sensing land cover products for plant functional type mapping over Siberia

    Science.gov (United States)

    Ottlé, C.; Lescure, J.; Maignan, F.; Poulter, B.; Wang, T.; Delbart, N.

    2013-11-01

    High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover

  19. Serving Satellite Remote Sensing Data to User Community through the OGC Interoperability Protocols

    Science.gov (United States)

    di, L.; Yang, W.; Bai, Y.

    2005-12-01

    Remote sensing is one of the major methods for collecting geospatial data. Hugh amount of remote sensing data has been collected by space agencies and private companies around the world. For example, NASA's Earth Observing System (EOS) is generating more than 3 Tb of remote sensing data per day. The data collected by EOS are processed, distributed, archived, and managed by the EOS Data and Information System (EOSDIS). Currently, EOSDIS is managing several petabytes of data. All of those data are not only valuable for global change research, but also useful for local and regional application and decision makings. How to make the data easily accessible to and usable by the user community is one of key issues for realizing the full potential of these valuable datasets. In the past several years, the Open Geospatial Consortium (OGC) has developed several interoperability protocols aiming at making geospatial data easily accessible to and usable by the user community through Internet. The protocols particularly relevant to the discovery, access, and integration of multi-source satellite remote sensing data are the Catalog Service for Web (CS/W) and Web Coverage Services (WCS) Specifications. The OGC CS/W specifies the interfaces, HTTP protocol bindings, and a framework for defining application profiles required to publish and access digital catalogues of metadata for geographic data, services, and related resource information. The OGC WCS specification defines the interfaces between web-based clients and servers for accessing on-line multi-dimensional, multi-temporal geospatial coverage in an interoperable way. Based on definitions by OGC and ISO 19123, coverage data include all remote sensing images as well as gridded model outputs. The Laboratory for Advanced Information Technology and Standards (LAITS), George Mason University, has been working on developing and implementing OGC specifications for better serving NASA Earth science data to the user community for many

  20. Water balance modelling in a semi-arid environment with limited in-situ data: remote sensing coupled with satellite gravimetry, Lake Manyara, East African Rift, Tanzania

    Directory of Open Access Journals (Sweden)

    D. Deus

    2011-09-01

    Full Text Available Accurate and up to date information on the status and trends of water balance is needed to develop strategies for conservation and the sustainable management of water resources. The purpose of this research is to estimate water balance in a semi-arid environment with limited in-situ data by using a remote sensing approach. We focus on the Lake Manyara catchment, located within the East African Rift of northern Tanzania. We use remote sensing and a semi-distributed hydrological model to study the spatial and temporal variability of water balance parameters within Manyara catchment. Satellite gravimetry GRACE data is used to verify the trend of the water balance result. The results show high spatial and temporal variations and characteristics of a semi-arid climate with high evaporation and low rainfall. We observe that the Lake Manyara water balance and GRACE equivalent water depth show comparable trends a decrease after 2002 followed by a sharp increase in 2006–2007. Despite the small size of Lake Manyara, GRACE data are useful and show great potential for hydrological research on smaller un-gauged lakes and catchments in semi-arid environments. Our modelling confirms the importance of the 2006–2007 Indian Ocean Dipole fluctuation in replenishing the groundwater reservoirs of East Africa. The water balance information can be used for further analysis of lake variations in relation to soil erosion, climate and land cover/land use change as well as different lake management and conservation scenarios. We demonstrate that water balance modelling can be performed accurately using remote sensing data even in complex climatic settings.

  1. Validation of Satellite-Derived Land Surface Temperature Products - Methods and Good Practice

    Science.gov (United States)

    Guillevic, P. C.; Hulley, G. C.; Hook, S. J.; Biard, J.; Ghent, D.

    2014-12-01

    Land Surface Temperature (LST) is a key variable for surface water and energy budget calculations that can be obtained globally and operationally from satellite observations. LST is used for many applications, including weather forecasting, short-term climate prediction, extreme weather monitoring, and irrigation and water resource management. In order to maximize the usefulness of LST for research and studies it is necessary to know the uncertainty in the LST measurement. Multiple validation methods and activities are necessary to assess LST compliance with the quality specifications of operational users. This work presents four different validation methods that have been widely used to determine the uncertainties in LST products derived from satellite measurements. 1) The temperature based validation method involves comparisons with ground-based measurements of LST. The method is strongly limited by the number and quality of available field stations. 2) Scene-based comparisons involve comparing a new satellite LST product with a heritage LST product. This method is not an absolute validation and satellite LST inter-comparisons alone do not provide an independent validation measurement. 3) The radiance-based validation method does not require ground-based measurements and is usually used for large scale validation effort or for LST products with coarser spatial resolution (> 1km). 4) Time series comparisons are used to detect problems that can occur during the instrument's life, e.g. calibration drift, or unrealistic outliers due to cloud coverage. This study enumerates the sources of errors associated with each method. The four different approaches are complementary and provide different levels of information about the quality of the retrieved LST. The challenges in retrieving the LST from satellite measurements are discussed using results obtained for MODIS and VIIRS. This work contributes to the objective of the Land Product Validation (LPV) sub-group of the

  2. Analysis on Effectiveness of SO2 Emission Reduction in Shanxi, China by Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Huaxiang Song

    2014-11-01

    Full Text Available The SO2 emissions from coal-fired power plants in China have been regulated since 2005 by a mandatory installation of flue gas desulfurization (FGD devices. In order to verify the effectiveness of FGD systems applied in power plants, Shanxi (a province well-known for the largest coal reserves in China was selected, and the characteristic and evolution of SO2 densities over 22 regions with large coal-fired power plants during 2005–2012 were investigated by using the satellite remote sensing data from the Ozone Monitoring Instrument (OMI. A unit-based inventory was also employed to study the trend of SO2 emissions from coal-fired power plants in Shanxi. The results show that the operation of FGD systems was successful in reducing SO2 emissions from power plants during 2005–2010: the mean SO2 densities satellite-observed over those regions with power plants operated before 2005 showed a notable decrease of approximate 0.4 DU; the mean SO2 densities over other regions with power plants newly built behind 2006 did not show a statistical increasing trend overall; the mean SO2 density over the whole Shanxi also showed a moderate decline from 2008 to 2010. However, the polluted conditions over Shanxi during 2011–2012 rebounded and the declining trend in mean SO2 density over the whole Shanxi disappeared again. In comparison of unit-based emission inventory, the emissions calculated show a similar trend with SO2 densities satellite-observed during 2005–2010 and still maintain at a lower volume during 2011–2012. By investigating the developments of other emission sources in Shanxi during 2005–2012, it is considered that the rapid expansion of industries with high coal-consumption has played an important role for the increment rise of SO2 emissions. Lack of an independent air quality monitoring network and the purposeful reduced operation rate of FGD systems occurring in some coal-fired power plants have reduced the effectiveness of SO2

  3. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  4. Advancing Coastal Climate Adaptation in Denmark by Land Subsidence Mapping using Sentinel-1 Satellite Imagery

    DEFF Research Database (Denmark)

    Sørensen, Carlo Sass; Broge, Niels H.; Mølgaard, Mads R.

    2016-01-01

    There are still large uncertainties in projections of climate change and sea level rise. Here, land subsidence is an additional factor that may adversely affect the vulnerability towards floods in low-lying coastal communities. The presented study performs an initial assessment of subsidence...... mapping using Sentinel-1 satellite imagery and leveling at two coastal locations in Denmark. Within both investigated areas current subsidence rates of 5-10 millimeters per year are found. This subsidence is related to the local geology, and challenges and potentials in bringing land subsidence mapping...... and geology into climate adaptation are discussed in relation to perspectives of a national subsidence monitoring system partly based on the findings from the two coastal locations. The current lack of subsidence data and a fragmentation of geotechnical information are considered as hindrances to optimal...

  5. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

    Directory of Open Access Journals (Sweden)

    Annett Bartsch

    2016-11-01

    Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

  6. Efficient approach to designing a Schmidt-Cassegrain objective for a remote sensing satellite.

    Science.gov (United States)

    Tawfik, Tamer M

    2009-12-10

    This paper presents an efficient approach to designing a Schmidt-Cassegrain objective for a remote sensing satellite. The objective is required to have multispectral operational bands, with three spectral channels distributed along the range (0.5 to 0.9 mum), as well as a panchromatic channel; 4 degrees field of view; distortion smaller than 0.3%; and a modulation transfer function, at 50 lines/mm spatial frequency, better than 0.5 and 0.35 at the center and edge of the field of view. The proposed design approach is based on Slyusarev's theory of aberrations and optical design. An image quality index is formulated as a function of optical system component powers and axial distances. For each combination of parameters, there exists a possible solution that can be realized into a thin lens system by solving Seidel sum equations. The final design is then reached by a simple and quick optimization step. The best three designs are compared in terms of initial values of optical system parameters and final design specifications. The best system image quality is thoroughly analyzed. All three presented designs meet and exceed the required design specifications.

  7. Diurnal Variability of Turbidity Fronts Observed by Geostationary Satellite Ocean Color Remote Sensing

    Directory of Open Access Journals (Sweden)

    Zifeng Hu

    2016-02-01

    Full Text Available Monitoring front dynamics is essential for studying the ocean’s physical and biogeochemical processes. However, the diurnal displacement of fronts remains unclear because of limited in situ observations. Using the hourly satellite imageries from the Geostationary Ocean Color Imager (GOCI with a spatial resolution of 500 m, we investigated the diurnal displacement of turbidity fronts in both the northern Jiangsu shoal water (NJSW and the southwestern Korean coastal water (SKCW in the Yellow Sea (YS. The hourly turbidity fronts were retrieved from the GOCI-derived total suspended matter using the entropy-based algorithm. The results showed that the entropy-based algorithm could provide fine structure and clearly temporal evolution of turbidity fronts. Moreover, the diurnal displacement of turbidity fronts in NJSW can be up to 10.3 km in response to the onshore-offshore movements of tidal currents, much larger than it is in SKCW (around 4.7 km. The discrepancy between NJSW and SKCW are mainly caused by tidal current direction relative to the coastlines. Our results revealed the significant diurnal displacement of turbidity fronts, and highlighted the feasibility of using geostationary ocean color remote sensing technique to monitor the short-term frontal variability, which may contribute to understanding of the sediment dynamics and the coupling physical-biogeochemical processes.

  8. Satellite Remote Sensing and Transportation Lifelines: Safety and Risk Analysis Along Rural Roads

    Science.gov (United States)

    Williamson, R.

    the application of satellite Earth Observation (EO) methods to the analysis of transportation networks. Other geospatial technologies, including geographic information systems (GIS) and the Global Positioning System (GPS), sharply enhance the utility of EO data in identifying potential road hazards and providing an objective basis for allocating resources to reduce their risks. In combination, these powerful information technologies provide substantial public benefits and increased business opportunities to remote sensing value-added firms. departments in rural jurisdictions improve the trafficability of the roads under their management during severe weather. We are developing and testing these methods in the U.S. Southwest, where thousands of kilometers of unimproved and graded dirt roads cross Native American reservations. This generally arid region is nevertheless subject to periodic summer rainstorms and winter snow and ice, creating hazardous conditions for the region's transportation lifelines. Arizona and Southeast Utah, as well as digital terrain models from the U.S. Geological Survey. We have analyzed several risk factors, such as slope, road curvature, and intersections, by means of multi-criteria evaluation (MCE) on both unimproved and improved roads. In partnership with the Hopi Indian Nation in Arizona, we have acquired and analyzed GPS road centerline data and accident data that validate our methodology. hazards along paved and unpaved roads of the American Southwest. They are also transferable to the international settings, particularly in similarly arid climates.

  9. A space-time stochastic model of rainfall for satellite remote-sensing studies

    Science.gov (United States)

    Bell, Thomas L.

    1987-01-01

    A model of the spatial and temporal distribution of rainfall is described that produces random spatial rainfall patterns with these characteristics: (1) the model is defined on a grid with each grid point representing the average rain rate over the surrounding grid box, (2) rain occurs at any one grid point, on average, a specified percentage of the time and has a lognormal probability distribution, (3) spatial correlation of the rainfall can be arbitrarily prescribed, and (4) time stepping is carried out so that large-scale features persist longer than small-scale features. Rain is generated in the model from the portion of a correlated Gaussian random field that exceeds a threshold. The portion of the field above the threshold is rescaled to have a lognormal probability distribution. Sample output of the model designed to mimic radar observations of rainfall during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), is shown. The model is intended for use in evaluating sampling strategies for satellite remote-sensing of rainfall and for development of algorithms for converting radiant intensity received by an instrument from its field of view into rainfall amount.

  10. Learning Oriented Region-based Convolutional Neural Networks for Building Detection in Satellite Remote Sensing Images

    Science.gov (United States)

    Chen, C.; Gong, W.; Hu, Y.; Chen, Y.; Ding, Y.

    2017-05-01

    The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based CNN model (R-CNN) for object detection is receiving an increasing attention. Despite the excellent performance in object detection, it is problematic to directly leverage the features of R-CNN model for building detection in single aerial image. As we know, the single aerial image is in vertical view and the buildings possess significant directional feature. However, in R-CNN model, direction of the building is ignored and the detection results are represented by horizontal rectangles. For this reason, the detection results with horizontal rectangle cannot describe the building precisely. To address this problem, in this paper, we proposed a novel model with a key feature related to orientation, namely, Oriented R-CNN (OR-CNN). Our contributions are mainly in the following two aspects: 1) Introducing a new oriented layer network for detecting the rotation angle of building on the basis of the successful VGG-net R-CNN model; 2) the oriented rectangle is proposed to leverage the powerful R-CNN for remote-sensing building detection. In experiments, we establish a complete and bran-new data set for training our oriented R-CNN model and comprehensively evaluate the proposed method on a publicly available building detection data set. We demonstrate State-of-the-art results compared with the previous baseline methods.

  11. Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

    Science.gov (United States)

    Quattrochi, D. A.; Jedlovec, G.; Meyer, P. J.

    2011-12-01

    potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

  12. Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

    Science.gov (United States)

    Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul

    2011-01-01

    potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

  13. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  14. Viewing marine bacteria, their activity and response to environmental drivers from orbit: satellite remote sensing of bacteria.

    Science.gov (United States)

    Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G

    2014-04-01

    Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.

  15. Supporting a Diverse Community of Undergraduate Researchers in Satellite and Ground-Based Remote Sensing

    Science.gov (United States)

    Blake, R.; Liou-Mark, J.

    2012-12-01

    The U.S. remains in grave danger of losing its global competitive edge in STEM. To find solutions to this problem, the Obama Administration proposed two new national initiatives: the Educate to Innovate Initiative and the $100 million government/private industry initiative to train 100,000 STEM teachers and graduate 1 million additional STEM students over the next decade. To assist in ameliorating the national STEM plight, the New York City College of Technology has designed its NSF Research Experience for Undergraduate (REU) program in satellite and ground-based remote sensing to target underrepresented minority students. Since the inception of the program in 2008, a total of 45 undergraduate students of which 38 (84%) are considered underrepresented minorities in STEM have finished or are continuing with their research or are pursuing their STEM endeavors. The program is comprised of the three primary components. The first component, Structured Learning Environments: Preparation and Mentorship, provides the REU Scholars with the skill sets necessary for proficiency in satellite and ground-based remote sensing research. The students are offered mini-courses in Geographic Information Systems, MATLAB, and Remote Sensing. They also participate in workshops on the Ethics of Research. Each REU student is a member of a team that consists of faculty mentors, post doctorate/graduate students, and high school students. The second component, Student Support and Safety Nets, provides undergraduates a learning environment that supports them in becoming successful researchers. Special networking and Brown Bag sessions, and an annual picnic with research scientists are organized so that REU Scholars are provided with opportunities to expand their professional community. Graduate school support is provided by offering free Graduate Record Examination preparation courses and workshops on the graduate school application process. Additionally, students are supported by college

  16. Land mobile satellite communication system. Volume 2: Traffic analysis and market demand for the land mobile communications system in the European scenario

    Science.gov (United States)

    Carnebianca, C.; Pavesi, B.; Tuozzi, A.; Capone, R.

    1986-06-01

    The socioeconomic desirability in terms of market demand, technical economic feasibility, and price-performance for a Land Mobile Communication system ground based and/or satellite aided, able to satisfy the request of the traffic demand, foreseable in the 1995-2005 time frame, for the Western European countries was assessed. The criterion of economic value of the mobile system is considered as the driving element. The presence of gaps in the terrestrial system and reasonable traffic extrapolations suggest a very attractive role for a land mobile satellite communications mission.

  17. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  18. Complementing geotechnical slope stability and land movement analysis using satellite DInSAR

    Science.gov (United States)

    Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Papadaki, Eirini; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis

    2014-03-01

    This paper explores the potential of using satellite radar inteferometry to monitor time-varying land movement prior to any visible tension crack signs. The idea was developed during dedicated geotechnical studies at a large open-pit lignite mine, where large slope movements (10-20 mm/day) were monitored and large fissures were observed in the immediate area outside the current pit limits. In this work, differential interferometry (DInSAR), using Synthetic Aperture Radar (SAR) ALOS images, was applied to monitor the progression of land movement that could potentially thwart mine operations. Early signs of land movements were captured by this technique well before their visual observation. Moreover, a qualitative comparison of DInSAR and ground geodetic measurements indicates that the technique can be used for the identification of high risk areas and, subsequently, for the optimization of the spatial distribution of the available ground monitoring equipment. Finally, quantitative land movement results from DInSAR are shown to be in accordance with simultaneous measurements obtained by ground means.

  19. LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

    Science.gov (United States)

    See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

    2016-04-01

    The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

  20. Management of land use land cover through the application of remote sensing, geographic information systems and simulation

    Science.gov (United States)

    Jha, Praveen

    Deforestation and degradation of forest areas, including those in the Protected Areas (PAs), are major concerns in India. There were 2 broad objectives of the study: the technological objective pertained to the development of state-of-art programs that could serve as Decision Support Systems while finalizing plans and policy interventions, while the other objective aimed at generating geo-spatial data in 2 PAs. A part of the Eastern Himalaya biodiversity hotspot, Manas Tiger Reserve (MTR), Assam, India having an area of 2837.12 sq km and an important part of Rajaji-Corbett Tiger Conservation Unit, Rajaji National Park (RNP), Uttarakhand, India, having an area of 820.42 sq km, were taken for the assessment of land use and land cover (LULC) change during 1990--2004. Simulation was undertaken in a smaller area of 1.2 km * 1.2 km right on the fringe of RNP. Three advanced geo-spatial programs---Multi-Algorithm Automation Program (MAAP), Data Automatic Modification Program (DAMP) and Multi-Stage Simulation Program (MUSSIP)---developed by the author were used extensively. Based on the satellite data, MAAP was used for the rapid assessments of LULC of 2004 and 1990; DAMP was used for the spectral modification of the satellite data of the adjacent scenes of 2004 and of 1990; and MUSSIP was used to simulate LULC maps for the future periods (till 2018). These programs produced very high accuracy levels: 91.12% in 2004 and 89.67% in 1990 were obtained for MTR; and 94.87% in 2004 and 94.10% in 1990 were obtained for RNP; 93.40% pixel-to-pixel accuracy and 0.7904 for kappa were achieved for simulation. The annual rate of loss of forests (0.41% in MTR and 1.20% in RNP) and loss of water (1.79% in MTR and 1.69% in RNP) during 1990-2004 is a matter of serious concern. The scenario analysis in the study area for simulation revealed that the deforestation rate of 1.27% per year during 2004--2018 would increase to 2.04% if the human population growth rate is enhanced by 10%. Hence

  1. Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

    Science.gov (United States)

    Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

    2017-08-30

    Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

  2. TOWARDS A REMOTE SENSING BASED ASSESSMENT OF LAND SUSCEPTIBILITY TO DEGRADATION: EXAMINING SEASONAL VARIATION IN LAND USE-LAND COVER FOR MODELLING LAND DEGRADATION IN A SEMI-ARID CONTEXT

    Directory of Open Access Journals (Sweden)

    G. Mashame

    2016-06-01

    Full Text Available Land degradation (LD is among the major environmental and anthropogenic problems driven by land use-land cover (LULC and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO International Organization of Standardization (ISO code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22% of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

  3. Towards a Remote Sensing Based Assessment of Land Susceptibility to Degradation: Examining Seasonal Variation in Land Use-Land Cover for Modelling Land Degradation in a Semi-Arid Context

    Science.gov (United States)

    Mashame, Gofamodimo; Akinyemi, Felicia

    2016-06-01

    Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

  4. Distributed land surface modeling with utilization of multi-sensor satellite data: application for the vast agricultural terrain in cold region

    Science.gov (United States)

    Muzylev, E.; Uspensky, A.; Gelfan, A.; Startseva, Z.; Volkova, E.; Kukharsky, A.; Romanov, P.; Alexandrovich, M.

    2012-04-01

    A technique for satellite-data-based modeling water and heat regimes of a large scale area has been developed and applied for the 227,300 km2 agricultural region in the European Russia. The core component of the technique is the physically based distributed Remote Sensing Based Land Surface Model (RSBLSM) intended for simulating transpiration by vegetation and evaporation from bare soil, vertical transfer of water and heat within soil and vegetation covers during a vegetation season as well as hydrothermal processes in soil and snow covers during a cold season, including snow accumulation and melt, dynamics of soil moisture and temperature during soil freezing and thawing, infiltration into frozen soil. Processes in the "atmosphere-snow-frozen soil" system are critical for cold region agriculture, as they control crop development in early spring before the vegetation season beginning. For assigning the model parameters as well as for preliminary calibrating and validating the model, available multi-year data sets of soil moisture/temperature profiles, evaporation, snow and soil freezing depth measured at the meteorological stations located within the study region have been utilized. To provide an appropriate parametrization of the model for the areas where ground-based measurements are unavailable, estimates have been utilized for vegetation, meteorological and snow characteristics derived from the multispectral measurements of AVHRR/NOAA (1999-2010), MODIS/EOS Terra & Aqua (2002-2010), AMSR-E/Aqua (2003-2004; 2008-2010), and SEVIRI/Meteosat-9 (2009-2010). The technologies of thematic processing the listed satellite data have been developed and applied to estimate the land surface and snow cover characteristics for the study area. The developed technologies of AVHRR data processing have been adapted to retrieve land surface temperature (LST) and emissivity (E), surface-air temperature at a level of vegetation cover (TA), normalized vegetation index (NDVI), leaf

  5. Development of monitoring method of coffee leaf rust fungus (Hemileia vastatrix) infected area using satellite remote sensing

    Science.gov (United States)

    Katsuhama, N.; Ikeda, K.; Imai, M.; Watanabe, K.; Marpaung, F.; Yoshii, T.; Naruse, N.; Takahashi, Y.

    2016-12-01

    Since 2008, coffee leaf rust fungus (Hemileia vastatrix) has expanded its infection in Latin America, and early trimming and burning infected trees have been only effective countermeasures to prevent spreading infection. Although some researchers reported a case about the monitoring of coffee leaf rust using satellite remote sensing in 1970s, the spatial resolution was unsatisfied, and therefore, further technological development has been required. The purpose of this research is to develop effective method of discovering coffee leaf rust infected areas using satellite remote sensing. Annual changes of vegetation indices, i.e. Normalized Difference Vegetation Index (NDVI) and Modified Structure Insensitive Pigment Index (MSIPI), around Cuchumatanes Mountains, Republic of Guatemala, were analyzed by Landsat 7 images. Study fields in the research were limited by the coffee farm areas based on a previous paper about on site surveys in different damage areas. As the result of the analysis, the annual change of NDVI at the coffee farm areas with damages tended to be lower than those without damages. Moreover, the decline of NDVI appear from 2008 before the damage was reported. On the other hand, the change of MSIPI had no significant difference. NDVI and MSIPI are mainly related to the amount of chlorophyll and carotenoid in the leaves respectively. This means that the infected coffee leaves turned yellow without defoliation. This situation well matches the symptom of coffee leaf rust. The research concluded that the property of infected leaves turning yellow is effective to monitoring of infection areas by satellite remote sensing.

  6. Mapping of land cover in northern California with simulated hyperspectral satellite imagery

    Science.gov (United States)

    Clark, Matthew L.; Kilham, Nina E.

    2016-09-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands

  7. Global land ice measurements from space (GLIMS): remote sensing and GIS investigations of the Earth's cryosphere

    Science.gov (United States)

    Bishop, Michael P.; Olsenholler, Jeffrey A.; Shroder, John F.; Barry, Roger G.; Rasup, Bruce H.; Bush, Andrew B. G.; Copland, Luke; Dwyer, John L.; Fountain, Andrew G.; Haeberli, Wilfried; Kaab, Andreas; Paul, Frank; Hall, Dorothy K.; Kargel, Jeffrey S.; Molnia, Bruce F.; Trabant, Dennis C.; Wessels, Rick L.

    2004-01-01

    Concerns over greenhouse‐gas forcing and global temperatures have initiated research into understanding climate forcing and associated Earth‐system responses. A significant component is the Earth's cryosphere, as glacier‐related, feedback mechanisms govern atmospheric, hydrospheric and lithospheric response. Predicting the human and natural dimensions of climate‐induced environmental change requires global, regional and local information about ice‐mass distribution, volumes, and fluctuations. The Global Land‐Ice Measurements from Space (GLIMS) project is specifically designed to produce and augment baseline information to facilitate glacier‐change studies. This requires addressing numerous issues, including the generation of topographic information, anisotropic‐reflectance correction of satellite imagery, data fusion and spatial analysis, and GIS‐based modeling. Field and satellite investigations indicate that many small glaciers and glaciers in temperate regions are downwasting and retreating, although detailed mapping and assessment are still required to ascertain regional and global patterns of ice‐mass variations. Such remote sensing/GIS studies, coupled with field investigations, are vital for producing baseline information on glacier changes, and improving our understanding of the complex linkages between atmospheric, lithospheric, and glaciological processes.

  8. Land Use Transformation Rule Analysis in Beijing-Tianjin-Tangshan Region Using Remote Sensing and GIS Technology

    Directory of Open Access Journals (Sweden)

    Shang-min Zhao

    2016-01-01

    Full Text Available Based on land use classification system, this paper acquires the land use distribution status at 2000, 2005, and 2010 in Beijing-Tianjin-Tangshan Region using remote sensing images, field survey data, images in Google Earth, and visual interpretation methods. Then, the land use transformation rules from 2000 to 2010 are achieved using GIS (geographic information system technology. The research results shows the following: (1 as to the distribution area of the land use types, dry field has the largest area, followed by forest land, building land, paddy field, water area, grassland, and unused land; (2 from 2000 to 2010, the area of building land has the largest increase, which is mainly transformed from cropland and sea reclamation area; the largest decreased land use type is paddy field, which mainly transforms to dry field and building land; (3 the high increase of building land and decrease of cropland suggest the land use transformation in the quick development process of economy; meanwhile, the total area of forestland and grassland changes little, so the ecological environment does not have apparent deterioration in the 1st decade of the new century.

  9. Fade measurements at L-band and UHF in mountainous terrain for land mobile satellite systems

    Science.gov (United States)

    Vogel, Wolfhard J.; Goldhirsh, Julius

    1988-01-01

    Fading results related to land mobile satellite communications at L-band (1502 MHz) and UHF (870 MHz) are described. These results were derived from an experiment performed in a series of canyon passes in the Boulder, Colorado region of the US. The experimental configuration involved a helicopter as the source platform, which maintained a relatively fixed geometry with a mobile van containing the receiver and data-acquisition system. An unobstructed line of sight between the radiating sources and the receiving van was, for the most part, also maintained. In this configuration, the dominant mechanism causing signal fading (or enhancement) is a result of multipath. The resulting fade distributions demonstrated that at the 1 percent and 5 percent levels, 5.5- and 2.6-dB fades were on the average exceeded at L-band and 4.8- and 2.4-dB at UHF, respectively, for a path elevation angle of 45 deg. The canyon results as compared with previous roadside-tree-shadowing results demonstrate that the deciding factor dictating fade margin for future land mobile satellite systems is tree shadowing rather than fades caused by multipath.

  10. Land Cover and Seasonality Effects on Biomass Burning Emissions and Air Quality Impacts Observed from Satellites

    Science.gov (United States)

    Zoogman, P.; Hoffman, A.; Gonzalez Abad, G.; Miller, C. E.; Nowlan, C. R.; Huang, G.; Liu, X.; Chance, K.

    2016-12-01

    Trace gas emissions from biomass burning can vary greatly both regionally and from event to event, but our current scientific understanding is unable to fully explain this variability. The large uncertainty in ozone formation resulting from fire emissions has posed a great challenge for assessing fire impacts on air quality and atmospheric composition. Satellite observations from OMI offer a powerful tool to observe biomass burning events by providing observations globally over a range of environmental conditions that effect emissions of NOx, formaldehyde, and glyoxal. We have investigated the seasonal relationship of biomass burning enhancements of these trace gases derived from OMI observations over tropical South America, Africa, and Indonesia. Land cover type (also derived from satellite observations) has a significant impact on formaldehyde and glyoxal enhancements from fire activity. We have found that the chemical ratio between formaldehyde and glyoxal is dependent on the burned land type and will present our current hypotheses for the spatial variation of this ratio in the tropics. Furthermore, in individual case studies we will investigate how these chemical ratios can inform our knowledge of the secondary formation of ozone, particularly during exceptional pollution events.

  11. Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa

    Directory of Open Access Journals (Sweden)

    Ronald A. Harris

    2014-12-01

    Full Text Available Wind farms (WFs are believed to have an impact on lower boundary layer meteorology. A recent study examined satellite-measured land surface temperature data (LST and found a local nighttime warming effect attributable to a group of four large WFs in Texas. This study furthers their work by investigating the impacts of five individual WFs in Iowa, where the land surface properties and climate conditions are different from those in Texas. Two methods are used to assess WF impacts: first, compare the spatial coupling between the LST changes (after turbine construction versus before and the geographic layouts of the WFs; second, quantify the LST difference between the WFs and their immediate surroundings (non-WF areas. Each WF shows an irrefutable nighttime warming signal relative to the surrounding areas after their turbines were installed, and these warming signals are generally coupled with the geographic layouts of the wind turbines, especially in summer. This study provides further observational evidence that WFs can cause surface warming at nighttime, and that such a signal can be detected by satellite-based sensors.

  12. Image interpretation for a multilevel land use classification system

    Science.gov (United States)

    1973-01-01

    The potential use is discussed of three remote sensors for developing a four level land use classification system. Three types of imagery for photointerpretation are presented: ERTS-1 satellite imagery, high altitude photography, and medium altitude photography. Suggestions are given as to which remote sensors and imagery scales may be most effectively employed to provide data on specific types of land use.

  13. Study of land surface temperature and spectral emissivity using multi-sensor satellite data

    Indian Academy of Sciences (India)

    P K Srivastava; T J Majumdar; Amit K Bhattacharya

    2010-02-01

    In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km2, is a part of Singhbhum–Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show

  14. The Evolution of Operational Satellite Based Remote Sensing in Support of Weather Analysis, Nowcasting, and Hazard Mitigation

    Science.gov (United States)

    Hughes, B. K.

    2010-12-01

    The mission of the National Oceanic and Atmospheric Administration (NOAA) National Environmental Data Information Service (NESDIS) is to provide timely access to global environmental data from satellites and other sources to promote, protect, and enhance America’s economy, security, environment, and quality of life. To fulfill its responsibilities, NESDIS acquires and manages America’s operational environmental satellites, operates the NOAA National Data Centers, provides data and information services including Earth system monitoring, performs official assessments of the environment, and conducts related research. The Nation’s fleet of operational environmental satellites has proven to be very critical in the detection, analysis, and forecast of natural or man-made phenomena. These assets have provided for the protection of people and property while safeguarding the Nation’s commerce and enabling safe and effective military operations. This presentation will take the audience through the evolution of operational satellite based remote sensing in support of weather forecasting, nowcasting, warning operations, hazard detection and mitigation. From the very first experiments involving radiation budget to today’s fleet of Geostationary and Polar Orbiting satellites to tomorrow’s constellation of high resolution imagers and hyperspectral sounders, environmental satellites sustain key observations for current and future generations.

  15. Land use/land cover changes around Rameshwaram Island, east coast of India

    Digital Repository Service at National Institute of Oceanography (India)

    Gowthaman, R.; Dwarakish, G.S.; Sanilkumar, V.

    Land-use/land cover changes are studied using the Indian Remote Sensing satellite (IRS-1C, IRS-6) Linear Image Self-scan Sensor (LISS) III data of 1998 and 2010 Coastal land use categories such as sand, vegetation, coral reef and water have been...

  16. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  17. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

    Science.gov (United States)

    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  18. A Comparative Analysis and Evaluation of Neka River Basin Deforested Land from 1977-2006 using MSS, TM and ETM Satellite Images

    Directory of Open Access Journals (Sweden)

    Hassan Ahmadi

    2013-07-01

    Full Text Available The main objective of this study is to find out the loss of forest area through analyzing it in different periods. In general, deforestation can be regarded as one of the most important elements in LULC and the scenario of global changes is taking place around the world. Therefore, it is worth assessing its trend and the rate at which it is taking place now. These changes will play a significant role in bringing about some changes in regional climate and accordingly on biodiversity. The loss of forest in Iran is going on since 1960 onwards in the Neka river Basin. The estimation of forest loss was not reported to be done by using Satellite data. The changes occurring in forest cover were reported by a series of four satellite images in different time intervals by using Remote Sensing (RS and GIS such as Land satMSS of 1977, Land satTM of1987, ETM 2001 and ETM+ 2006. The forest covers were analyzed and maps from four temporal satellite datasets were prepared. Based on 1977, 1987, 2001 and 2006 satellite data interpretation, the forest cover was converted to geospatial database. According to the results obtained from these images, there was a decrease in forest area (7096.63, productive forest area, as well as degraded forest area. However, the total forest area showed a decrease in the first period (1977-1987 although an increase was reported again during the second period (1987-2001 to 2418.82 hectares (3.5% of the study area, this trend continued even between 2001-2006 and the mixed forest cover increased by856.08 hectares (1.31%. This increase was due to few hectares of mixed forest area was converted into manmade forest.

  19. Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data.

    Science.gov (United States)

    Hadjimitsis, Diofantos G; Clayton, Chris

    2009-12-01

    Although there have been many studies conducted on the use of satellite remote sensing for water quality monitoring and assessment in inland water bodies, relatively few studies have considered the problem of atmospheric intervention of the satellite signal. The problem is especially significant when using time series multi-spectral satellite data to monitor water quality surveillance in inland waters such as reservoirs, lakes, and dams because atmospheric effects constitute the majority of the at-satellite reflectance over water. For the assessment of temporal variations of water quality, the use of multi-date satellite images is required so atmospheric corrected image data must be determined. The aim of this study is to provide a simple way of monitoring and assessing temporal variations of water quality in a set of inland water bodies using an earth observation- based approach. The proposed methodology is based on the development of an image-based algorithm which consists of a selection of sampling area on the image (outlet), application of masking and convolution image processing filter, and application of the darkest pixel atmospheric correction. The proposed method has been applied in two different geographical areas, in UK and Cyprus. Mainly, the method has been applied to a series of eight archived Landsat-5 TM images acquired from March 1985 up to November 1985 of the Lower Thames Valley area in the West London (UK) consisting of large water treatment reservoirs. Finally, the method is further tested to the Kourris Dam in Cyprus. It has been found that atmospheric correction is essential in water quality assessment studies using satellite remotely sensed imagery since it improves significantly the water reflectance enabling effective water quality assessment to be made.

  20. Observing Sea Level Change and its Causes with Satellite Remote Sensing

    Science.gov (United States)

    Boening, Carmen; Fu, Lee-Lueng; Landerer, Felix; Willis, Josh

    2016-07-01

    Sea level rise as a response to a changing climate is an imminent threat for coastal communities in the near future. Coastal zone management relies on most accurate predictions of sea level change over the coming decades for planning potential mitigation efforts. Hence, it is of high importance to accurately measure changes and understand physical processes behind them in great detail on a variety of time scales. Satellite observations of sea level height from altimetry have provided an unprecedented understanding of global changes and regional patterns for over two decades. With more and more missions providing now also observations of causes such as water mass changes due to ice melt and land hydrology as well as the ocean heat and salinity budget and local and regional wind patterns, we can now get a comprehensive understanding of the physical processes causing the short to long term changes in sea level. Here, we present an overview of sea level observations in combination with a suite of measurements looking at sea level contributions to provide insight into current and future challenges to understand the sea level budget and its impact on the accuracy of future projections.

  1. Sources of Divergence in Remote Sensing of Vegetation Phenology From Multiple Long Term Satellite Data Records

    Science.gov (United States)

    Barreto, A.; Didan, K.; Miura, T.

    2008-12-01

    Changes in vegetation phenology depict an integrated response to change in environmental factors and provide valuable information to global change research. Typically, remote sensing of vegetation phenology is based on the analysis of vegetation index temporal profiles, because of their simplicity, stability, and inherent resistant to noise. Most phenology estimates are, however, limited to using one sensor owing to the inter-sensor continuity challenges. Although, phenology is used for a variety of research and application topics, the central premise remains the study of vegetation dynamics change in response to change in climate and other factors. Consequently, the consistency and length of data records are key requirements. With satellite missions lasting few years only, long term phenology measures will have to be based on a mixture of satellite data records. In this study we compared phenology parameters from the AVHRR-GIMMS and MODIS NDVI records (1982- 2007). We analyzed both records globally using a cluster approach to abate noise and focus on the landscape level vegetation dynamic. The cluster approach, assumes that phenology is controlled by a complex set of factors that could be encapsulated by homogeneous climate, soil, elevational gradient, sun- shade exposure, and biophysical capacity. We applied this method to each of the sensors and examined three fundamental phenology parameters: the start and end of the growing season and the cumulative seasonal signal. These parameters are sensitive to, and are capable of capturing changes in the underlying environmental factors. Our results indicate that a large divergence exist over the dense forest of the tropics. This divergence was attributed to MODIS saturation rather than NDVI saturation. Boreal forests exhibited also large disagreement owing to snow cover and related differences in data processing. Furthermore, agricultural areas showed the most irregular phenological signals. This noise resulted from the

  2. Spatial-Temporal Analyses of Lightning Activities over Pakistan using Satellite Remote Sensing

    Science.gov (United States)

    Qaiser, Saddam; Imran Shahzad, Muhammad

    2016-07-01

    Lightning is a naturally occurring spectacular and powerful phenomenon often accompanied by thunder. Regardless, it's hazardous and responsible for thousands of deaths and property loss all over the globe.In Pakistan, this hazardous phenomenon mostly occurs in monsoon and pre-monsoon seasons. To prevent or at least minimize the unforeseen property damages and human casuality, we need to identify the vulnerable locations to lightning in Pakistan, but yet there have not been done any detailed study regarding the lightning hazards yet for Pakistan. In the present study for the years 2001 - 2014 lightning density mapping has been done by means of satellite Remote Sensing techniques. Lightning Image Sensor (LIS) datasets of locations and Time of Occurrence (TOA) are used to identify the lightning prone locations all over Pakistan. Efforts have been made to develop a technique that is helpful in generating the hazard maps of lighting in Pakistan on temporal basis by using spatio-temporal satellite images. These maps show frequency distribution trends of lightning in many regions of Pakistan that enable us to locate high, moderate and low lightning-susceptible areas. Results demonstrate that thunderstorm frequency is comparatively higher over the mountain and sub-mountain regions in the Punjab, Federally Administered Tribal Areas (FATA) and Khyber Pakhtoon Khwa (KPK) provinces. Interestingly lightning data showed a strong correlation between the FlashesYear and the El Niño and La Niña years. It is observed that about 40.1 % of lightning activities occurred during the monsoon followed by pre-monsoon with 39.7 %, which can possibly create synergistic and devastating effects in combination with heavy seasonal rainfall. A severe lightning event with 4559 flashes in just 3.08 seconds is also recorded on 8-Oct-2005 in Pakistan-India border near Azad Jammu Kashmir (AJK) and Jammu Kashmir. However, it is to be noted that on the same date Pakistan was hit by a major Earthquake

  3. Spatial and Quantitative Comparison of Satellite-Derived Land Cover Products over China

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gen-Suo

    2012-01-01

    Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer (MODIS), Global Land Cover 2000 (GLC2000), and the National Land Cover/Use Data- sets (NLCD) products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.

  4. Analysis of land use and land cover change in a coastal area of Rio de Janeiro using high-resolution remotely sensed data

    Science.gov (United States)

    Avelar, Silvania; Tokarczyk, Piotr

    2014-01-01

    Coastal areas offer great recreational and economic opportunities, but require intensive resource management and environmental protection. Land use and land cover information provides a rapid and cost-effective means for monitoring and planning coastal area development. This study quantitatively describes spatiotemporal changes of land use and land cover over the last four decades in a coastal area of the state of Rio de Janeiro, Brazil. Historical aerial photographs from 1976 and satellite images from 1990 and 2012 were classified and analyzed. We used supervised classification and machine learning techniques to classify the images. An accuracy assessment of results was performed. Land use change statistics for the period indicate that urban areas have increased to the detriment of dense vegetation, salines, and bare soil. The analysis provides a basis for better control of anthropogenic impacts and geoconservation activities in this coastal area of Rio de Janeiro.

  5. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  6. A global dataset of crowdsourced land cover and land use reference data.

    Science.gov (United States)

    Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F; Danylo, Olha; Sturn, Tobias; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael

    2017-06-13

    Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

  7. Datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates.

    Science.gov (United States)

    Carrea, Laura; Embury, Owen; Merchant, Christopher J

    2015-11-01

    Datasets containing information to locate and identify water bodies have been generated from data locating static-water-bodies with resolution of about 300 m (1/360(∘)) recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The LC CCI water-bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR on Envisat between 2005 and 2010. The new derived datasets provide coherently: distance to land, distance to water, water-body identifiers and lake-centre locations. The water-body identifier dataset locates the water bodies assigning the identifiers of the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). During the generation and validation of the datasets some limitations of the GLWD database and of the LC CCI water-bodies mask have been found. Some examples of the inaccuracies/limitations are presented and discussed. Temporal change in water-body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.

  8. Practical applicability and preliminary results of the Baltic Environmental Satellite Remote Sensing System (SatBaltic)

    Science.gov (United States)

    Wozniak, B.; Ostrowska, M.; Bradtke, K.; Darecki, M.; Dera, J.; Dudzinska-Nowak, J.; Dzierzbicka, L.; Ficek, D.; Furmanczyk, K.; Kowalewski, M.; Krezel, A.; Majchrowski, R.; Paszkuta, M.; Ston-Egiert, J.; Stramska, M.; Zapadka, T.

    2012-04-01

    SatBaltic (Satellite Monitoring of the Baltic Sea Environment) project is being realized in Poland by the SatBaltic Scientific Consortium, specifically appointed for this purpose, which associates four scientific institutions: the Institute of Oceanology PAN in Sopot - coordinator, the University of Gdańsk (Institute of Oceanography), the Pomeranian Academy in Słupsk (Institute of Physics) and the University of Szczecin (Institute of Marine Sciences). We present the first the results of the first year and a half of SatBaltic's implementation. The final result of the project is to be the creation and setting in motion of the SatBaltic Operational System (SBOS), the aim of which is to monitor effectively and comprehensively the state of the Baltic Sea environment using remote sensing techniques. Various aspects of the practical applicability of SBOS to the monitoring of the Baltic ecosystem are discussed. We present some examples of the maps of the various characteristics of the Baltic obtained using the current version of SBOS, including algorithms and models that are still in an unfinished state. At the current stage of research, these algorithms apply mainly to the characteristics of the solar energy influx and the distribution of this energy among the various processes taking place in the atmosphere-sea system, and also to the radiation balance of the sea surface, the irradiance conditions for photosynthesis and the condition of plant communities in the water, sea surface temperature distributions and some other marine phenomena correlated with this temperature. Also given are results of preliminary inspections of the accuracy of the magnitudes shown on the maps.

  9. Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography

    Science.gov (United States)

    Moore, Caitlin E.; Brown, Tim; Keenan, Trevor F.; Duursma, Remko A.; van Dijk, Albert I. J. M.; Beringer, Jason; Culvenor, Darius; Evans, Bradley; Huete, Alfredo; Hutley, Lindsay B.; Maier, Stefan; Restrepo-Coupe, Natalia; Sonnentag, Oliver; Specht, Alison; Taylor, Jeffrey R.; van Gorsel, Eva; Liddell, Michael J.

    2016-09-01

    Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that

  10. Impacts of a Changing Climate and Land Use on Reindeer Pastoralism: Indigenous Knowledge and Remote Sensing

    Science.gov (United States)

    Maynard, N. G.; Oskal, A.; Turi, A.; Mathiesen, J. M.; Eira, S. D.; Yurchak, I. M. G.; Etylin, B.; Gebelein, J.

    2009-01-01

    The Arctic is home to many indigenous peoples, including those who depend on reindeer herding for their livelihood, in one of the harshest environments in the world. For the largely nomadic peoples, reindeer not only form a substantial part of the Arcti