WorldWideScience

Sample records for remote-sensing time series

  1. Remote Sensing Time Series Product Tool

    Science.gov (United States)

    Predos, Don; Ryan, Robert E.; Ross, Kenton W.

    2006-01-01

    programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

  2. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

    2008-01-01

    The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

  3. 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.

  4. Remote sensing-based time-series analysis of cheatgrass (Bromus tectorum L.) phenology.

    Science.gov (United States)

    Clinton, Nicholas E; Potter, Christopher; Crabtree, Bob; Genovese, Vanessa; Gross, Peggy; Gong, Peng

    2010-01-01

    The western United States is under invasion from cheatgrass (Bromus tectorum L.), an annual grass that alters the pattern of phenology in the ecosystems it infests. This study was conducted to investigate methods for monitoring this invasion. As a result of its annual phenology, cheatgrass is not only an extremely competitive invader, it is also detectible from time series of remotely sensed data. Using the MODerate resolution imaging spectro-radiometer (MODIS) normalized difference vegetation index (NDVI) and spatially interpolated precipitation data, we fit splines to monthly observations to generate time series of NDVI and precipitation from 2001 to 2005 in the state of Utah. We generated a variety of existing metrics of phenology and developed several metrics to describe the relationship between the NDVI and the precipitation time series. These metrics not only describe the pattern of response to precipitation in ecosystems of various infestation levels, but they are predictive of cheatgrass infestation. We tested several popular data mining algorithms to investigate the predictive ability of the time series-based metrics. Our results show that presence-absence can be predicted with 90% accuracy, and four categorical levels of infestation can be predicted with 71% accuracy. The results show that time series-based metrics are effective in prediction of cheatgrass abundance levels, are more effective than metrics based only on NDVI, and provide more information that existing approaches to cheatgrass mapping using phenology. These results are important for designing strategies to monitor ecosystem health over long periods of time at a landscape scale.

  5. Monitoring and modeling of wetland environment using time-series bi-sensor remotely sensed data

    Science.gov (United States)

    Michishita, Ryo

    More than half of the wetlands in the world have been lost in the last century mainly due to human activities. Since natural wetlands receive a significant amount of untreated runoff from urban and agricultural areas, it is necessary to account for other landscapes adjacent to wetlands, such as water bodies, agricultural areas, and urban areas, in the protection and restoration of the wetlands. The goal of this dissertation is to monitor and model land cover changes using the time-series Landsat-5 TM and Terra MODIS data in the Poyang Lake area of China from two perspectives: wetland cover changes and urbanization. A bi-scale monitoring approach was adopted in the monitoring and modeling of wetland cover changes to examine the similarities and differences derived from remotely sensed imagery with different spatial resolutions. The effect of different modeling settings of multiple endmember spectral mixture analysis (MESMA) were examined utilizing a single pair of TM and MODIS scenes. MESMA applied to nine pairs of TM and MODIS scenes acquired from July 2004 to October 2005 captured phenological and hydrological trends of land cover fractions (LCFs) and LCF agreement between the image pairs. Ground surface reflectance, rather than LCFs, was chosen as the key parameter in the blending of bi-scale remotely sensed data that utilized the spatial details of one data type and temporal details of the other. This research customized an existing fusion model to overcome the problem with the unobserved pixels in MODIS data acquired on TM data acquisition dates. It is interesting that the input data combination considering water level change achieved higher accuracy. In the monitoring of urbanization, this research investigated the relationship between urban land cover and human activities, and detected the areas of new urban development and redevelopment of built-up areas. Different urbanization processes largely influenced by the economic reforms of China were demonstrated

  6. Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

    Science.gov (United States)

    Diao, Chunyuan

    In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of

  7. Spatiotemporal Mining of Time-Series Remote Sensing Images Based on Sequential Pattern Mining

    Science.gov (United States)

    Liu, H. C.; He, G. J.; Zhang, X. M.; Jiang, W.; Ling, S. G.

    2015-07-01

    With the continuous development of satellite techniques, it is now possible to acquire a regular series of images concerning a given geographical zone with both high accuracy and low cost. Research on how best to effectively process huge volumes of observational data obtained on different dates for a specific geographical zone, and to exploit the valuable information regarding land cover contained in these images has received increasing interest from the remote sensing community. In contrast to traditional land cover change measures using pair-wise comparisons that emphasize the compositional or configurational changes between dates, this research focuses on the analysis of the temporal sequence of land cover dynamics, which refers to the succession of land cover types for a given area over more than two observational periods. Using a time series of classified Landsat images, ranging from 2006 to 2011, a sequential pattern mining method was extended to this spatiotemporal context to extract sets of connected pixels sharing similar temporal evolutions. The resultant sequential patterns could be selected (or not) based on the range of support values. These selected patterns were used to explore the spatial compositions and temporal evolutions of land cover change within the study region. Experimental results showed that continuous patterns that represent consistent land cover over time appeared as quite homogeneous zones, which agreed with our domain knowledge. Discontinuous patterns that represent land cover change trajectories were dominated by the transition from vegetation to bare land, especially during 2009-2010. This approach quantified land cover changes in terms of the percentage area affected and mapped the spatial distribution of these changes. Sequential pattern mining has been used for string mining or itemset mining in transactions analysis. The expected novel significance of this study is the generalization of the application of the sequential pattern

  8. Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

    Science.gov (United States)

    Sawant, S. A.; Chakraborty, M.; Suradhaniwar, S.; Adinarayana, J.; Durbha, S. S.

    2016-06-01

    Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (http://earthexplorer.usgs.gov/). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system observed relevant weather parameters for crop ET estimation. The

  9. Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

    Science.gov (United States)

    Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

    2017-04-01

    As a consequence of environmental changes surface waters are undergoing changes in time and space. A better knowledge of the spatial and temporal distribution of surface waters resources becomes essential to support sustainable policies and development activities. Especially because surface waters, are not only a vital sweet water resource, but can also pose hazards to human settlements and infrastructures through flooding. Floods are a highly frequent disaster in the world and can caused huge material losses. Detecting and mapping their spatial distribution is fundamental to ascertain damages and for relief efforts. Spaceborne Synthetic Aperture Radar (SAR) is an effective way to monitor surface waters bodies over large areas since it provides excellent temporal coverage and, all-weather day-and-night imaging capabilities. However, emergent vegetation, trees, wind or flow turbulence can increase radar back-scatter returns and pose problems for the delineation of inundated areas. In such areas, passive remote sensing data can be used to identify vegetated areas and support the interpretation of SAR data. The availability of new Earth Observation products, for example Sentinel-1 (active) and Sentinel-2 (passive) imageries, with both high spatial and temporal resolution, have the potential to facilitate flood detection and monitoring of surface waters changes which are very dynamic in space and time. In this context, the research consists of two parts. In the first part, the objective is to propose generic and reproducible methodologies for the analysis of Sentinel-1 time series data for floods detection and surface waters mapping. The processing chain comprises a series of pre-processing steps and the statistical modeling of the pixel value distribution to produce probabilistic maps for the presence of surface waters. Images pre-processing for all Sentinel-1 images comprise the reduction SAR effect like orbit errors, speckle noise, and geometric effects. A modified

  10. Remote sensing time series analysis for crop monitoring with the SPIRITS software: new functionalities and use examples

    Directory of Open Access Journals (Sweden)

    Felix eRembold

    2015-07-01

    Full Text Available Monitoring crop and natural vegetation conditions is highly relevant, particularly in the food insecure areas of the world. Data from remote sensing image time series at high temporal and medium to low spatial resolution can assist this monitoring as they provide key information about vegetation status in near real-time over large areas. The Software for the Processing and Interpretation of Remotely sensed Image Time Series (SPIRITS is a stand-alone flexible analysis environment created to facilitate the processing and analysis of large image time series and ultimately for providing clear information about vegetation status in various graphical formats to crop production analysts and decision makers. In this paper we present the latest functional developments of SPIRITS and we illustrate recent applications. The main new developments include: HDF5 importer, Image re-projection, additional options for temporal Smoothing and Periodicity conversion, computation of a rainfall-based probability index (Standardized Precipitation Index for drought detection and extension of the Graph composer functionalities.In particular,. The examples of operational analyses are taken from several recent agriculture and food security monitoring reports and bulletins. We conclude with considerations on future SPIRITS developments also in view of the data processing requirements imposed by the coming generation of remote sensing products at high spatial and temporal resolution, such as those provided by the Sentinel sensors of the European Copernicus programme.

  11. Remote Sensing observations of Cecropia communities along Amazonian rivers: Mapping and monitoring habitat dynamics with time series datasets

    Science.gov (United States)

    Quinteros Casaverde, N. L.; McDonald, K.

    2016-12-01

    Riverine habitats host more than 14% of non-aquatic birds in the Amazon basin, some of them considered vulnerable by the UICN due to habitat destruction. Plant species of the genus Cecropia are known for being a late pioneer species in these riverine habitats creating monospecific stands along the Amazonian rivers. Cecropia biomes are thought to have significant impacts on the avifauna communities and their diversity. Nowadays, these habitats are threatened by the on-going development in the Amazonian countries. There are plans to build hydroelectric facilities, damming important tributaries of the Amazon river. Such large scale land cover change threatens Cecropia communities and the habitats they support and associated biodiversity. Thus, it is imperative to understand the fragility of these ecosystems, their extent and spatial distribution, and seasonal influences to their environments. We employ multiple sources of remote sensing data to assess the ability to use high resolution imagery to map Cecropia communities and multi-temporal observations to assess their seasonal dynamics. This research aims to facilitate the understanding of these communities through time series analyses using remote sensing products such as high resolution images from Synthetic Aperture Radar (SAR) and Landsat to identify the Cecropia stands along the rivers and lower resolution products such as satellite-borne radiometers and scatterometers to assess seasonality. Our goal is to employ combined remote sensing data sources at map and monitor these important habitats.

  12. Time-Series Analysis of Remotely-Sensed SeaWiFS Chlorophyll in River-Influenced Coastal Regions

    Science.gov (United States)

    Acker, James G.; McMahon, Erin; Shen, Suhung; Hearty, Thomas; Casey, Nancy

    2009-01-01

    The availability of a nearly-continuous record of remotely-sensed chlorophyll a data (chl a) from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission, now longer than ten years, enables examination of time-series trends for multiple global locations. Innovative data analysis technology available on the World Wide Web facilitates such analyses. In coastal regions influenced by river outflows, chl a is not always indicative of actual trends in phytoplankton chlorophyll due to the interference of colored dissolved organic matter and suspended sediments; significant chl a timeseries trends for coastal regions influenced by river outflows may nonetheless be indicative of important alterations of the hydrologic and coastal environment. Chl a time-series analysis of nine marine regions influenced by river outflows demonstrates the simplicity and usefulness of this technique. The analyses indicate that coastal time-series are significantly influenced by unusual flood events. Major river systems in regions with relatively low human impact did not exhibit significant trends. Most river systems with demonstrated human impact exhibited significant negative trends, with the noteworthy exception of the Pearl River in China, which has a positive trend.

  13. Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

    Directory of Open Access Journals (Sweden)

    Stuart E. Marsh

    2010-01-01

    Full Text Available Climate change and variability are expected to impact the synchronicity and interactions between the Sonoran Desert and the forested sky islands which represent steep biological and environmental gradients. The main objectives were to examine how well satellite greenness time series data and derived phenological metrics (e.g., season start, peak greenness can characterize specific vegetation communities across an elevation gradient, and to examine the interactions between climate and phenological metrics for each vegetation community. We found that representative vegetation types (11, varying between desert scrub, mesquite, grassland, mixed oak, juniper and pine, often had unique seasonal and interannual phenological trajectories and spatial patterns. Satellite derived land surface phenometrics (11 for each of the vegetation communities along the cline showed numerous distinct significant relationships in response to temperature (4 and precipitation (7 metrics. Satellite-derived sky island vegetation phenology can help assess and monitor vegetation dynamics and provide unique indicators of climate variability and patterns of change.

  14. Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

    Science.gov (United States)

    Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

    2015-01-01

    Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

  15. Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

    Directory of Open Access Journals (Sweden)

    Zhen Zhou

    Full Text Available Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM and data mining (DM. In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

  16. Remote Sensing Time Series to Evaluate Direct Land Use Change of Recent Expanded Sugarcane Crop in Brazil

    Directory of Open Access Journals (Sweden)

    Marcio Pupin Mello

    2012-04-01

    Full Text Available The use of biofuels to mitigate global carbon emissions is highly dependent on direct and indirect land use changes (LUC. The direct LUC (dLUC can be accurately evaluated using remote sensing images. In this work we evaluated the dLUC of about 4 million hectares of sugarcane expanded from 2005 to 2010 in the South-central region of Brazil. This region has a favorable climate for rain-fed sugarcane, a great potential for agriculture expansion without deforestation, and is currently responsible for almost 90% of Brazilian’s sugarcane production. An available thematic map of sugarcane along with MODIS and Landast images, acquired from 2000 to 2009, were used to evaluate the land use prior to the conversion to sugarcane. A systematic sampling procedure was adopted and the land use identification prior to sugarcane, for each sample, was performed using a web tool developed to visualize both the MODIS time series and the multitemporal Landsat images. Considering 2000 as reference year, it was observed that sugarcane expanded: 69.7% on pasture land; 25.0% on annual crops; 0.6% on forest; while 3.4% was sugarcane land under crop rotation. The results clearly show that the dLUC of recent sugarcane expansion has occurred on more than 99% of either pasture or agriculture land.

  17. Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series

    Directory of Open Access Journals (Sweden)

    Claudia Kuenzer

    2015-07-01

    Full Text Available River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China, the Mekong Delta (Vietnam, the Irrawaddy Delta (Myanmar, and the Ganges-Brahmaputra (Bangladesh, India—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013. A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid

  18. Estimating sediment and caesium-137 fluxes in the Ribble Estuary through time-series airborne remote sensing.

    Science.gov (United States)

    Wakefield, R; Tyler, A N; McDonald, P; Atkin, P A; Gleizon, P; Gilvear, D

    2011-03-01

    High spatial and temporal resolution airborne imagery were acquired for the Ribble Estuary, North West England in 1997 and 2003, to assess the application of time-series airborne remote sensing to quantify total suspended sediment and radionuclide fluxes during a flood and ebb tide sequence. Concomitant measurements of suspended particulate matter (SPM) and water column turbidity were obtained during the time-series image acquisition for the flood and ebb tide sequence on the 17th July 2003 to verify the assumption of a vertically well mixed estuary and thus justifying the vertical extrapolation of spatially integrated estimate of surface SPM. The ¹³⁷Cs activity concentrations were calculated from a relatively stable relationship between SPM and ¹³⁷Cs for the Ribble Estuary. Total estuary wide budgets of sediment and ¹³⁷Cs were obtained by combining the image-derived estimates of surface SPM and ¹³⁷Cs with estimates of water volume from a two-dimensional hydrodynamic model (VERSE) developed for the Ribble Estuary. These indicate that around 10,000 tons of sediment and 2.72 GBq of ¹³⁷Cs were deposited over the tidal sequence monitored in July 2003. This compared favourably with bed height elevation change estimated from field work. An uncertainty analysis on the total sediment and ¹³⁷Cs flux yielded a total budget of the order of 40% on the final estimate. The results represent a novel approach to providing a spatially integrated estimate of the total net sediment and radionuclide flux in an intertidal environment over a flood and ebb tide sequence.

  19. Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

    Science.gov (United States)

    Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

    2014-05-01

    Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross

  20. Remote Sensing Monitoring of Tobacco Field Based on Phenological Characteristics and Time Series Image——A Case Study of Chengjiang County, Yunnan Province, China

    Institute of Scientific and Technical Information of China (English)

    PENG Guangxiong; DENG Lei; CUI Weihong; MING Tao; SHEN Wei

    2009-01-01

    Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpretation map based on the fusion image of TM and CBERS02B's High-Resolution (HR) camera image was used as standard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Likelihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accuracy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

  1. Estimating sediment and caesium-137 fluxes in the Ribble Estuary through time-series airborne remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Wakefield, R. [Atkins Limited, 200 Broomielaw, Glasgow, G1 4RU (United Kingdom); Tyler, A.N., E-mail: a.n.tyler@stir.ac.u [School of Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA (United Kingdom); McDonald, P. [Environmental Sciences Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3LN (United Kingdom); Atkin, P.A. [Atkins Limited, Wastwater Pavillion Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3JZ (United Kingdom); Gleizon, P. [Environmental Sciences Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3LN (United Kingdom); Gilvear, D. [School of Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA (United Kingdom)

    2011-03-15

    High spatial and temporal resolution airborne imagery were acquired for the Ribble Estuary, North West England in 1997 and 2003, to assess the application of time-series airborne remote sensing to quantify total suspended sediment and radionuclide fluxes during a flood and ebb tide sequence. Concomitant measurements of suspended particulate matter (SPM) and water column turbidity were obtained during the time-series image acquisition for the flood and ebb tide sequence on the 17th July 2003 to verify the assumption of a vertically well mixed estuary and thus justifying the vertical extrapolation of spatially integrated estimate of surface SPM. The {sup 137}Cs activity concentrations were calculated from a relatively stable relationship between SPM and {sup 137}Cs for the Ribble Estuary. Total estuary wide budgets of sediment and {sup 137}Cs were obtained by combining the image-derived estimates of surface SPM and {sup 137}Cs with estimates of water volume from a two-dimensional hydrodynamic model (VERSE) developed for the Ribble Estuary. These indicate that around 10,000 tonnes of sediment and 2.72 GBq of {sup 137}Cs were deposited over the tidal sequence monitored in July 2003. This compared favourably with bed height elevation change estimated from field work. An uncertainty analysis on the total sediment and {sup 137}Cs flux yielded a total budget of the order of 40% on the final estimate. The results represent a novel approach to providing a spatially integrated estimate of the total net sediment and radionuclide flux in an intertidal environment over a flood and ebb tide sequence. - Research highlights: {yields} This paper provides a rare insight into the next flux of sediment and associated radionuclide loading into an estuary over and ebb and flood tide sequence. {yields} The paper uses high temporal resolution airborne imagery coupled with concomitant sampling to convert total suspended sediment flux to {sup 137}Cs loading. {yields} For the estuary and date

  2. Monitoring Effects of Climatic stresses on a Papyrus Wetland System in Eastern Uganda Using Times Series of Remotely Sensed Data

    Science.gov (United States)

    Kayendeke, Ellen; French, Helen K.; Kansiime, Frank; Bamutaze, Yazidhi

    2017-04-01

    Papyrus wetlands predominant in southern, central and eastern Africa; are important in supporting community livelihoods since they provide land for agriculture, materials for building and craft making, as well as services of water purification and water storage. Papyrus wetlands are dominated by a sedge Cyperus papyrus, which is rooted at wetland edges but floats in open water with the help of a root mat composed of intermingled roots and rhizomes. The hypothesis is that the papyrus mat structure reduces flow velocity and increases storage volume during storm events, which not only helps to mitigate flood events but aids in storage of excess water that can be utilised during the dry seasons. However, due to sparse gauging there is inadequate meteorological and hydrological data for continuous monitoring of the hydrological functioning of papyrus systems. The objective of this study was to assess the potential of utilising freely available remote sensing data (MODIS, Landsat, and Sentinel-1) for cost effective monitoring of papyrus wetland systems, and their response to climatic stresses. This was done through segmentation of MODIS NDVI and Landsat derived NDWI datasets; as well as classification of Sentinel-1 images taken in wet and dry seasons of 2015 and 2016. The classified maps were used as proxies for changes in hydrological conditions with time. The preliminary results show that it is possible to monitor changes in biomass, wetland inundation extent, flooded areas, as well as changes in moisture content in surrounding agricultural areas in the different seasons. Therefore, we propose that remote sensing data, when complemented with available meteorological data, is a useful resource for monitoring changes in the papyrus wetland systems as a result of climatic and human induced stresses.

  3. Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

    Science.gov (United States)

    Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

    2016-09-01

    For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

  4. Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series.

    Science.gov (United States)

    Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

    2016-04-19

    Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.

  5. Multi-sensor time series of remote sensing data indicate rapid warming trend for lakes in California and Nevada

    Science.gov (United States)

    Schneider, P.; Hook, S. J.; Radocinski, R. R.; Corlett, G. K.; Hulley, G. C.; Schladow, S. G.; Steissberg, T. E.

    2009-12-01

    The temperature of large lakes is a potential indicator of climate change. However, its usefulness is limited by the paucity of in situ measurements and lack of long-term data records. Thermal infrared (TIR) satellite imagery can be used to obtain frequent and accurate remote observations of lake surface temperatures. The archive of TIR imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), the series of Along-Track Scanning Radiometers (ATSR/ATSR-2/AATSR) sensors, as well as from the series of Advanced Very High Resolution Radiometers (AVHRR), now spans nearly three decades and together these data sets can provide continuous time series of global lake surface temperatures. As part of an ongoing project involving the construction of 30-year time series of lake temperatures for 164 large lakes worldwide, we present the results of a case study for six lakes in California and Nevada. Seventeen years of data from the ATSR series was processed in combination with nine years of MODIS data in order to obtain time series of lake skin temperature. The accuracy of the skin temperature retrievals was tested against automated in situ measurements from buoys at the Lake Tahoe test site. The results indicate that nighttime skin temperatures can be estimated with mean errors as low as 0.2 °C. An analysis of average summer lake temperatures retrieved from the ATSR sensors shows that the six case study sites have exhibited average warming trends of 0.11 ± 0.026 °C yr-1 (p < 0.002) since 1992. The magnitude of the trend is confirmed by the shorter time series of MODIS data as well as by in situ measurements at Lake Tahoe. A comparison with air temperature observations suggests that the lake surface is warming more rapidly than the surface air temperature.

  6. Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands

    Science.gov (United States)

    Quan, Jinling; Zhan, Wenfeng; Chen, Yunhao; Wang, Mengjie; Wang, Jinfei

    2016-03-01

    Previous time series methods have difficulties in simultaneous characterization of seasonal, gradual, and abrupt changes of remotely sensed land surface temperature (LST). This study proposed a model to decompose LST time series into trend, seasonal, and noise components. The trend component indicates long-term climate change and land development and is described as a piecewise linear function with iterative breakpoint detection. The seasonal component illustrates annual insolation variations and is modeled as a sinusoidal function on the detrended data. This model is able to separate the seasonal variation in LST from the long-term (including gradual and abrupt) change. Model application to nighttime Moderate Resolution Imaging Spectroradiometer (MODIS)/LST time series during 2000-2012 over Beijing yielded an overall root-mean-square error of 1.62 K between the combination of the decomposed trend and seasonal components and the actual MODIS/LSTs. LST decreased (~ -0.086 K/yr, p sixth ring roads. The decreasing trend was stronger over croplands than over urban lands (p < 0.05), resulting in an increasing trend in surface urban heat island intensity (SUHII, 0.022 ± 0.006 K/yr). This was mainly attributed to the trends in urban-rural differences in rainfall and albedo. The SUHII demonstrated a concave seasonal variation primarily due to the seasonal variations of urban-rural differences in temperature cooling rate (related to canyon structure, vegetation, and soil moisture) and surface heat dissipation (affected by humidity and wind).

  7. Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time-series of remote sensing data

    DEFF Research Database (Denmark)

    Tøttrup, Christian; Rasmussen, Michael Schultz

    2004-01-01

    Remote sensing, NDVI, trend analysis, environmental change, rainfall, land cover change, Senegal......Remote sensing, NDVI, trend analysis, environmental change, rainfall, land cover change, Senegal...

  8. Monitoring soil erosion features using a time series of airborne remote sensing data: a case study Wild Coast, South Africa

    CSIR Research Space (South Africa)

    Singh, RG

    2014-10-01

    Full Text Available on historical conditions can be extracted. This paper examines the first results of the erosional feature detection using a time- series of high resolution aerial photography captured between 1937 and 2009. The erosional history of the area is considered... photography and satellite imagery using visual interpretation is a common approach. For example, visual interpretation of SPOT data was used for the creation of a national gully location map of South Africa (Mararakanye and Le Roux, 2012). The analysis...

  9. Using a curve-fitting methodology on remotely sensed time series to detect subtle patterns of land surface phenology

    Science.gov (United States)

    Bradley, B.; Mustard, J.; Jacob, R.; Hermance, J.

    2005-12-01

    Annual, inter-annual, and long-term trends in Land Surface Phenology (LSP) using NDVI time series from AVHRR and MODIS can be used to distinguish between natural ecosystem dynamics and land cover change. However, the full potential of long-term NDVI time series is often hampered by poor quality data caused by instrumentation problems, atmospheric conditions (e.g. clouds or haze), ground conditions (e.g. snow), and inter-annual variability of land cover. These effects make LSP difficult to identify, and may mask subtle shifts in inter-annual ecosystem response resulting from land use or other anthropogenic forcing. In order to maximize LSP detection, we use a curve fitting methodology useful for long-term time series across a range of phenologies. This approach is minimally affected by sensor error, clouds, and snow, and requires neither spatial nor temporal averaging to reduce noise. This methodology employs a spline-based curve, which is fit iteratively so that positive residuals are upweighted to capture the upper envelope of NDVI values. Here, we apply the curve fitting methodology to weekly AVHRR NDVI data (1990-2000) and biweekly MODIS NDVI data (2000-2005) at 1 km pixel resolution for the Great Basin desert of the western U.S. The spatial and temporal patterns of known ecosystems may then be assessed in order to identify anomalous trends in regional LSP. We compare both spatial and temporal variability of four known ecosystem types surveyed in 2004: sagebrush steppe, cheatgrass grassland, pinyon-juniper woodland, and montane shrubland. Average onset of greenness (using a timing of half max technique) occurred on Apr 14 (+/- 6 days; sagebrush), Apr 9 (+/- 8 days; cheatgrass), Apr 17 (+/- 8 days; pinyon-juniper) and May 24 (+/- 5 days; montane). The small standard deviation observed in similar ecosystems distributed throughout the Great Basin indicates that the phenologies are spatially robust in any individual year. However, there is considerable temporal

  10. Land-cover change and its time-series reconstructed using remotely sensed imageries in the Zhoushan islands

    Science.gov (United States)

    Chen, Jianyu; Zhan, Yuanzeng; Mao, Zhihua

    2009-09-01

    Coastal islands are located in transitional environments where land and sea interact. It is main frontier to develop oceanic economy and to utilize oceanic resources. Insular environment is isolated and its ecosystem is also vulnerable. The exploitation and development of islands make result on its land-cover and land-use transition and the trace of the landcover change indicates the impact on it conversely. Many changes have taken place in coastal area of East China within past four decades, especially in rapidly developing large islands. For monitoring environmental changes in such area, this paper, taking Zhoushan Island and its surrounding islands as an example, explored the temporal composition and spatial configuration of the land-cover trajectories. The recent land-cover data derived from both SPOT5 imageries and the last land-use data which came from investigation department. The historical distribution in 1980 was obtained from visual interpretation of CORONA photograph. Then the land-cover changed map could be derived through previous and last land-cover map. And the following time-series of land-cover was acquired from the supervised classification results of TM/ETM imageries which ranged from 1986 to 2000. The classification result was improved by limitation the sample selection in unchanged area in land-cover changed map in classification procedure. All these used satellite imageries were registered to the SPOT5 panchromatic imagery which was rectified using DGPS data in advance. Therefore, the temporal-spatial distributions of land-cover have been examined, reconstructed and analyzed with the support of GIS software. Based on those work, we revealed that the land-cover had changed rapidly in Zhoushan Island.

  11. A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Sofia Siachalou

    2015-03-01

    Full Text Available Vegetation monitoring and mapping based on multi-temporal imagery has recently received much attention due to the plethora of medium-high spatial resolution satellites and the improved classification accuracies attained compared to uni-temporal approaches. Efficient image processing strategies are needed to exploit the phenological information present in temporal image sequences and to limit data redundancy and computational complexity. Within this framework, we implement the theory of Hidden Markov Models in crop classification, based on the time-series analysis of phenological states, inferred by a sequence of remote sensing observations. More specifically, we model the dynamics of vegetation over an agricultural area of Greece, characterized by spatio-temporal heterogeneity and small-sized fields, using RapidEye and Landsat ETM+ imagery. In addition, the classification performance of image sequences with variable spatial and temporal characteristics is evaluated and compared. The classification model considering one RapidEye and four pan-sharpened Landsat ETM+ images was found superior, resulting in a conditional kappa from 0.77 to 0.94 per class and an overall accuracy of 89.7%. The results highlight the potential of the method for operational crop mapping in Euro-Mediterranean areas and provide some hints for optimal image acquisition windows regarding major crop types in Greece.

  12. Investigating the causality of changes in the landscape pattern of Lake Urmia basin, Iran using remote sensing and time series analysis.

    Science.gov (United States)

    Mehrian, Majid Ramezani; Hernandez, Raul Ponce; Yavari, Ahmad Reza; Faryadi, Shahrzad; Salehi, Esmaeil

    2016-08-01

    Lake Urmia is the second largest hypersaline lake in the world in terms of surface area. In recent decades, the drop in water level of the lake has been one of the most important environmental issues in Iran. At present, the entire basin is threatened due to abrupt decline of the lake's water level and the consequent increase in salinity. Despite the numerous studies, there is still an ambiguity about the main cause of this environmental crisis. This paper is an attempt to detect the changes in the landscape structure of the main elements of the whole basin using remote sensing techniques and analyze the results against climate data with time series analysis for the purpose of achieving a more clarified illustration of processes and trends. Trend analysis of the different affecting factors indicates that the main cause of the drastic dry out of the lake is the huge expansion of irrigated agriculture in the basin between 1999 and 2014. The climatological parameters including precipitation and temperature cannot be the main reasons for reduced water level in the lake. The results show how the increase in irrigated agricultural area without considering the water resources limits can lead to a regional disaster. The approach used in this study can be a useful tool to monitor and assess the causality of environmental disaster.

  13. Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index.

    Science.gov (United States)

    Löw, Fabian; Waldner, François; Latchininsky, Alexandre; Biradar, Chandrashekhar; Bolkart, Maximilian; Colditz, René R

    2016-12-01

    The Asian Migratory locust (Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km(2) (28% of the observed area) was flagged as potential locust habitat and 5% represents a permanent high risk of locust infestation. Results are instrumental for predicting potential locust outbreaks and developing well-targeted management plans. The method offers positive perspectives for locust management and treatment of infested sites because it is able to deliver risk maps in near real time, with an accuracy of 80% in April-May which coincides with both locust hatching and the first control surveys. Such maps could help in rapid decision-making regarding control interventions against the initial locust congregations, and thus the efficiency of survey teams and the chemical treatments could be increased, thus potentially reducing environmental pollution

  14. Integration of Multisensor Remote Sensing Data for the Retrieval of Consistent Times Series of High-Resolution NDVI Images for Crop Monitoring in Landscapes Dominated By Small-Scale Farming Agricultural

    Science.gov (United States)

    Sedano, F.; Kempeneers, P.

    2014-12-01

    There is a need for timely and accurate information of food supply and early warnings of production shortfalls. Crop growth models commonly rely on information on vegetation dynamics from low and moderate spatial resolution remote sensing imagery. While the short revisit period of these sensors captures the temporal dynamics of crops, they are not able to monitor small-scale farming areas where environmental factors, crop type and management practices often vary at subpixel level. Although better suited to retrieve fine spatial structure, time series of higher resolution imagery (circa 30 m) are often incomplete due to larger revisit periods and persistent cloud coverage. However, as the Landsat archive expands and more fine resolution Earth observation sensors become available, the possibilities of multisensor integration to monitor crop dynamics with higher level of spatial detail are expanding. We have integrated remote sensing imagery from two moderate resolution sensors (MODIS and PROBA-V) and three medium resolution platforms (Landsat 7- 8; and DMC) to improve the characterization of vegetation dynamics in agricultural landscapes dominated by small-scale farms. We applied a data assimilation method to produce complete temporal sequences of synthetic medium-resolution NDVI images. The method implements a Kalman filter recursive algorithm that incorporates models, observations and their respective uncertainties to generate medium-resolution images at time steps for which only moderate-resolution imagery is available. The results for the study sites show that the time series of synthetic NDVI images captured seasonal vegetation dynamics and maintained the spatial structure of the landscape at higher spatial resolution. A more detailed characterization of spatiotemporal dynamics of vegetation in agricultural systems has the potential to improve the estimates of crop growth models and allow a more precise monitoring and forecasting of crop productivity.

  15. Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China

    Directory of Open Access Journals (Sweden)

    Jiyan Wang

    2016-02-01

    Full Text Available Measuring the impact of livestock grazing on grassland above-ground net primary production (ANPP is essential for grass yield estimation and pasture management. However, since there is a lack of accurate and repeatable techniques to obtain the details of grazing locations and stocking rates at the regional scale, it is an extremely challenging task to study the influence of regional grazing on the grassland ANPP. Taking Zoige County as a case, this paper proposes an approach to quantify the spatial and temporal variation of grazing intensity and grazing period through time-series remote sensing data, simulated grassland ANPP through the denitrification and decomposition (DNDC model, and then explores the impact of grazing on grassland ANPP. The result showed that the model-estimated ANPP while considering grazing had a significant relationship with the field-observed ANPP, with the coefficient of determination (R2 of 0.75, root mean square error (RMSE of 122.86 kgC/ha, and average relative error (RE of 8.77%. On the contrary, if grazing activity was not considered in simulation, a large uncertainty was found when the model-estimated ANPP was compared with the field observation, showing R2 of 0.4, RMSE of 211.51 kgC/ha, and average RE of 32.5%. For the whole area of Zoige County in 2012, the statistics of the estimation showed that the total regional ANPP was up to 3.815 × 105 tC, while the total regional ANPP, without considering grazing, would be overestimated by 44.4%, up to 5.51 × 105 tC. This indicates that the grazing parameters derived in this study could effectively improve the accuracy of ANPP simulation results. Therefore, it is feasible to combine time-series remote sensing data with the process model to simulate the grazing effects on grassland ANPP. However, some issues, such as selecting proper remote sensing data, improving the quality of model input parameters, collecting more field data, and exploring the data assimilation

  16. HiTempo: a platform for time-series analysis of remote-sensing satellite data in a high-performance computing environment

    CSIR Research Space (South Africa)

    Van den Bergh, F

    2012-08-01

    Full Text Available Course resolution earth observation satellites offer large data sets with daily observations at global scales. These data sets represent a rich resource that, because of the high acquisition rate, allows the application of time-series analysis...

  17. Space-Time Data fusion for Remote Sensing Applications

    Science.gov (United States)

    Braverman, Amy; Nguyen, H.; Cressie, N.

    2011-01-01

    NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

  18. Land use and land cover change dynamics across the Brazilian Amazon: insights from extensive time-series analysis of remote sensing data.

    Science.gov (United States)

    Carreiras, João M B; Jones, Joshua; Lucas, Richard M; Gabriel, Cristina

    2014-01-01

    Throughout the Amazon region, the age of forests regenerating on previously deforested land is determined, in part, by the periods of active land use prior to abandonment and the frequency of reclearance of regrowth, both of which can be quantified by comparing time-series of Landsat sensor data. Using these time-series of near annual data from 1973-2011 for an area north of Manaus (in Amazonas state), from 1984-2010 for south of Santarém (Pará state) and 1984-2011 near Machadinho d'Oeste (Rondônia state), the changes in the area of primary forest, non-forest and secondary forest were documented from which the age of regenerating forests, periods of active land use and the frequency of forest reclearance were derived. At Manaus, and at the end of the time-series, over 50% of regenerating forests were older than 16 years, whilst at Santarém and Machadinho d'Oeste, 57% and 41% of forests respectively were aged 6-15 years, with the remainder being mostly younger forests. These differences were attributed to the time since deforestation commenced but also the greater frequencies of reclearance of forests at the latter two sites with short periods of use in the intervening periods. The majority of clearance for agriculture was also found outside of protected areas. The study suggested that a) the history of clearance and land use should be taken into account when protecting deforested land for the purpose of restoring both tree species diversity and biomass through natural regeneration and b) a greater proportion of the forested landscape should be placed under protection, including areas of regrowth.

  19. Land use and land cover change dynamics across the Brazilian Amazon: insights from extensive time-series analysis of remote sensing data.

    Directory of Open Access Journals (Sweden)

    João M B Carreiras

    Full Text Available Throughout the Amazon region, the age of forests regenerating on previously deforested land is determined, in part, by the periods of active land use prior to abandonment and the frequency of reclearance of regrowth, both of which can be quantified by comparing time-series of Landsat sensor data. Using these time-series of near annual data from 1973-2011 for an area north of Manaus (in Amazonas state, from 1984-2010 for south of Santarém (Pará state and 1984-2011 near Machadinho d'Oeste (Rondônia state, the changes in the area of primary forest, non-forest and secondary forest were documented from which the age of regenerating forests, periods of active land use and the frequency of forest reclearance were derived. At Manaus, and at the end of the time-series, over 50% of regenerating forests were older than 16 years, whilst at Santarém and Machadinho d'Oeste, 57% and 41% of forests respectively were aged 6-15 years, with the remainder being mostly younger forests. These differences were attributed to the time since deforestation commenced but also the greater frequencies of reclearance of forests at the latter two sites with short periods of use in the intervening periods. The majority of clearance for agriculture was also found outside of protected areas. The study suggested that a the history of clearance and land use should be taken into account when protecting deforested land for the purpose of restoring both tree species diversity and biomass through natural regeneration and b a greater proportion of the forested landscape should be placed under protection, including areas of regrowth.

  20. How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems.

    Science.gov (United States)

    De Keersmaecker, Wanda; Lhermitte, Stef; Honnay, Olivier; Farifteh, Jamshid; Somers, Ben; Coppin, Pol

    2014-07-01

    Increasing frequency of extreme climate events is likely to impose increased stress on ecosystems and to jeopardize the services that ecosystems provide. Therefore, it is of major importance to assess the effects of extreme climate events on the temporal stability (i.e., the resistance, the resilience, and the variance) of ecosystem properties. Most time series of ecosystem properties are, however, affected by varying data characteristics, uncertainties, and noise, which complicate the comparison of ecosystem stability metrics (ESMs) between locations. Therefore, there is a strong need for a more comprehensive understanding regarding the reliability of stability metrics and how they can be used to compare ecosystem stability globally. The objective of this study was to evaluate the performance of temporal ESMs based on time series of the Moderate Resolution Imaging Spectroradiometer derived Normalized Difference Vegetation Index of 15 global land-cover types. We provide a framework (i) to assess the reliability of ESMs in function of data characteristics, uncertainties and noise and (ii) to integrate reliability estimates in future global ecosystem stability studies against climate disturbances. The performance of our framework was tested through (i) a global ecosystem comparison and (ii) an comparison of ecosystem stability in response to the 2003 drought. The results show the influence of data quality on the accuracy of ecosystem stability. White noise, biased noise, and trends have a stronger effect on the accuracy of stability metrics than the length of the time series, temporal resolution, or amount of missing values. Moreover, we demonstrate the importance of integrating reliability estimates to interpret stability metrics within confidence limits. Based on these confidence limits, other studies dealing with specific ecosystem types or locations can be put into context, and a more reliable assessment of ecosystem stability against environmental disturbances

  1. Monitoring of vegetation dynamics on the former military training area Königsbrücker Heide using remote sensing time series

    Science.gov (United States)

    Wessollek, Christine; Karrasch, Pierre

    2016-10-01

    In 1989 about 1.5 million soldiers were stationed in Germany. With the political changes in the early 1990s a substantial decline of the staff occurred on currently 200,000 employees in the armed forces and less than 60,000 soldiers of foreign forces. These processes entailed conversions of large areas not longer used for military purposes, especially in the new federal states in the eastern part of Germany. One of these conversion areas is the former military training area Konigsbruck in Saxony. For the analysis of vegetation and its development over time, the Normalized Difference Vegetation Index (NDVI) has established as one of the most important indicators. In this context, the questions arise whether MODIS NDVI products are suitable to determine conversion processes on former military territories like military training areas and what development processes occurred in the "Konigsbrucker Heide" in the past 15 years. First, a decomposition of each series in its trend component, seasonality and the remaining residuals is performed. For the trend component different regression models are tested. Statistical analysis of these trends can reveal different developments, for example in nature development zones (without human impact) and zones of controlled succession. The presented workflow is intended to show the opportunity to support a high temporal resolution monitoring of conversion areas such as former military training areas.

  2. Using remote sensing time series to model the impact of changing flooding regimes on riparian vegetation in Australia's most important river basin

    Science.gov (United States)

    Broich, M.; Tulbure, M. G.; Verbesselt, J.; Xin, Q.

    2016-12-01

    Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M km2, as a case study. The MDB is the country's primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999-2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a `boom' and `bust' cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the

  3. Remote Sensing

    CERN Document Server

    Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F

    2012-01-01

    Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.

  4. Timing constraints on remote sensing of wildland fire burned area in the southeastern US

    Science.gov (United States)

    Picotte, Joshua J.; Robertson, Kevin

    2011-01-01

    Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.

  5. Remote Sensing.

    Science.gov (United States)

    Williams, Richard S., Jr.; Southworth, C. Scott

    1983-01-01

    The Landsat Program became the major event of 1982 in geological remote sensing with the successful launch of Landsat 4. Other 1982 remote sensing accomplishments, research, publications, (including a set of Landsat worldwide reference system index maps), and conferences are highlighted. (JN)

  6. Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

    Science.gov (United States)

    Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

    2013-01-01

    The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

  7. Estimating Urban Heat Island Effects on the Temperature Series of Uccle (Brussels, Belgium Using Remote Sensing Data and a Land Surface Scheme

    Directory of Open Access Journals (Sweden)

    Rafiq Hamdi

    2010-12-01

    Full Text Available In this letter, the urban heat island effects on the temperature time series of Uccle (Brussels, Belgium during the summers months 1960–1999 was estimated using both ground-based weather stations and remote sensing imagery, combined with a numerical land surface scheme including state-of-the-art urban parameterization, the Town Energy Balance Scheme. Analysis of urban warming based on remote sensing method reveals that the urban bias on minimum temperature is rising at a higher rate, 2.5 times (2.85 ground-based observed more, than on maximum temperature, with a linear trend of 0.15 °C (0.19 °C ground-based observed and 0.06 °C (0.06 °C ground-based observed per decade respectively. The results based on remote sensing imagery are compatible with estimates of urban warming based on weather stations. Therefore, the technique presented in this work is a useful tool in estimating the urban heat island contamination in long time series, countering the drawbacks of a ground-observational approach.

  8. Remote Sensing Information Gateway

    Science.gov (United States)

    Remote Sensing Information Gateway, a tool that allows scientists, researchers and decision makers to access a variety of multi-terabyte, environmental datasets and to subset the data and obtain only needed variables, greatly improving the download time.

  9. Identifying Thermally Challenging Landscapes and Time Periods for Wildlife Using Remote Sensing

    Science.gov (United States)

    Albright, T. P.; Pidgeon, A.; Radeloff, V.; Wardlow, B.

    2011-12-01

    Recent events and climate model outputs indicate an increase in the occurrence and magnitude of heat waves and other high temperature events in many locations. Temperatures at the land surface may be much higher than air temperatures making this a particularly relevant consideration for animals that nest, forage, or seek refuge at or near the ground. Often associated with heat waves are prolonged and/or rapid onset drought events, which can combine to place stress on vegetation and animals. In order to assess the influence of heat waves and drought on communities of birds, we developed statistical models between avian abundance and species richness data collected by volunteer observers as part of the North American Breeding Bird Survey and a suite of precipitation and temperature metrics. We used station data, gridded standardized precipitation indices, and remotely sensed vegetation indices, and developed an index of accumulated temperature exceedance using time series MODIS land surface temperature (LST) products. Mixed effects models accounting for nuisance factors and temporal autocorrelation revealed that LST was among the strongest predictors of same year and following-year avian abundance. In particular, declines in abundance were largest and most common among ground-nesting birds and long-distance migrants in the US Southwest. In cooler regions, high LST exceedances were sometimes associated with increases in abundance. Because these results do not indicate whether dispersal, reproductive effort, or mortality explain the changes, one area of current research focuses on identifying demographic mechanisms and population consequences of such responses. A second area of active research focuses on using LST data in conjunction with digital elevation models and derivatives and dense networks of ground-level observations to produce physiologically-relevant indicators of thermally stressful conditions for birds and other animals.

  10. Real-time progressive hyperspectral remote sensing detection methods for crop pest and diseases

    Science.gov (United States)

    Wu, Taixia; Zhang, Lifu; Peng, Bo; Zhang, Hongming; Chen, Zhengfu; Gao, Min

    2016-05-01

    Crop pests and diseases is one of major agricultural disasters, which have caused heavy losses in agricultural production each year. Hyperspectral remote sensing technology is one of the most advanced and effective method for monitoring crop pests and diseases. However, Hyperspectral facing serial problems such as low degree of automation of data processing and poor timeliness of information extraction. It resulting we cannot respond quickly to crop pests and diseases in a critical period, and missed the best time for quantitative spraying control on a fixed point. In this study, we take the crop pests and diseases as research point and breakthrough, using a self-development line scanning VNIR field imaging spectrometer. Take the advantage of the progressive obtain image characteristics of the push-broom hyperspectral remote sensor, a synchronous real-time progressive hyperspectral algorithms and models will development. Namely, the object's information will get row by row just after the data obtained. It will greatly improve operating time and efficiency under the same detection accuracy. This may solve the poor timeliness problem when we using hyperspectral remote sensing for crop pests and diseases detection. Furthermore, this method will provide a common way for time-sensitive industrial applications, such as environment, disaster. It may providing methods and technical reserves for the development of real-time detection satellite technology.

  11. Near real-time landslide hazard assessment using remotely sensed data

    Science.gov (United States)

    Kirschbaum, D.; Stanley, T.; Cappelaere, P. G.; Simmons, J. M. D.

    2015-12-01

    Remote sensing data offers the unique perspective to provide situational awareness of hydrometeorological hazards over large areas in a way that is impossible to achieve with in situ data. Recent work has shown that rainfall-triggered landslides, while typically local hazards that occupy small spatial areas, can be approximated over regional scales in near real-time. By leveraging data from the Global Precipitation Measurement (GPM) mission, topographic data from the Shuttle Radar Topography Mission (SRTM) and other remote and in situ sources, we can represent the conditions for landslide triggering over broad regions. The landslide hazard assessment for situational awareness (LHASA) model integrates satellite precipitation data, a modeled and satellite-based soil moisture product and susceptibility information to improve the characterization of areas that may experience landslide activity at regional and global scales. The goal of LHASA is to better inform decision-making and disaster response agencies on landslide hazards at the regional and global scale. This system outputs straightforward landslide hazard assessment products available in near real-time that can be used to identify landslide-prone areas and the general timing of landslide initiation. This presentation summarizes the results of this modeling framework, discusses the utility of remote sensing products for landslide hazard characterization, and outlines the path forward for this modeling approach.

  12. Remote sensing of temperature and wind using acoustic travel-time measurements

    Directory of Open Access Journals (Sweden)

    Manuela Barth

    2013-04-01

    Full Text Available A remote sensing technique to detect area-averaged temperature and flow properties within an area under investigation, utilizing acoustic travel-time measurements, is introduced. This technique uses the dependency of the speed of acoustic signals on the meteorological parameters temperature and wind along the propagation path. The method itself is scalable: It is applicable for investigation areas with an extent of some hundred square metres as well as for small-scale areas in the range of one square metre. Moreover, an arrangement of the acoustic transducers at several height levels makes it possible to determine profiles and gradients of the meteorological quantities. With the help of two examples the potential of this remote sensing technique for simultaneously measuring averaged temperature and flow fields is demonstrated. A comparison of time histories of temperature and wind values derived from acoustic travel-time measurements with point measurements shows a qualitative agreement whereas calculated root-mean-square errors differ for the two example applications. They amount to 1.4 K and 0.3 m/s for transducer distances of 60 m and 0.4 K and 0.2 m/s for transducer distances in the range of one metre.

  13. Integrating SAR with Optical and Thermal Remote Sensing for Operational Near Real-Time Volcano Monitoring

    Science.gov (United States)

    Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.

    2013-12-01

    Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing techniques have become established in operational forecasting, monitoring, and managing of volcanic hazards. Monitoring organizations, like the Alaska Volcano Observatory (AVO), are nowadays heavily relying on remote sensing data from a variety of optical and thermal sensors to provide time-critical hazard information. Despite the high utilization of these remote sensing data to detect and monitor volcanic eruptions, the presence of clouds and a dependence on solar illumination often limit their impact on decision making processes. Synthetic Aperture Radar (SAR) systems are widely believed to be superior to optical sensors in operational monitoring situations, due to the weather and illumination independence of their observations and the sensitivity of SAR to surface changes and deformation. Despite these benefits, the contributions of SAR to operational volcano monitoring have been limited in the past due to (1) high SAR data costs, (2) traditionally long data processing times, and (3) the low temporal sampling frequencies inherent to most SAR systems. In this study, we present improved data access, data processing, and data integration techniques that mitigate some of the above mentioned limitations and allow, for the first time, a meaningful integration of SAR into operational volcano monitoring systems. We will introduce a new database interface that was developed in cooperation with the Alaska Satellite Facility (ASF) and allows for rapid and seamless data access to all of ASF's SAR data holdings. We will also present processing techniques that improve the temporal frequency with which hazard-related products can be produced. These techniques take advantage of modern signal processing technology as well as new radiometric normalization schemes, both enabling the combination of

  14. Volcanic eruptions, hazardous ash clouds and visualization tools for accessing real-time infrared remote sensing data

    Science.gov (United States)

    Webley, P.; Dehn, J.; Dean, K. G.; Macfarlane, S.

    2010-12-01

    Volcanic eruptions are a global hazard, affecting local infrastructure, impacting airports and hindering the aviation community, as seen in Europe during Spring 2010 from the Eyjafjallajokull eruption in Iceland. Here, we show how remote sensing data is used through web-based interfaces for monitoring volcanic activity, both ground based thermal signals and airborne ash clouds. These ‘web tools’, http://avo.images.alaska.edu/, provide timely availability of polar orbiting and geostationary data from US National Aeronautics and Space Administration, National Oceanic and Atmosphere Administration and Japanese Meteorological Agency satellites for the North Pacific (NOPAC) region. This data is used operationally by the Alaska Volcano Observatory (AVO) for monitoring volcanic activity, especially at remote volcanoes and generates ‘alarms’ of any detected volcanic activity and ash clouds. The webtools allow the remote sensing team of AVO to easily perform their twice daily monitoring shifts. The web tools also assist the National Weather Service, Alaska and Kamchatkan Volcanic Emergency Response Team, Russia in their operational duties. Users are able to detect ash clouds, measure the distance from the source, area and signal strength. Within the web tools, there are 40 x 40 km datasets centered on each volcano and a searchable database of all acquired data from 1993 until present with the ability to produce time series data per volcano. Additionally, a data center illustrates the acquired data across the NOPAC within the last 48 hours, http://avo.images.alaska.edu/tools/datacenter/. We will illustrate new visualization tools allowing users to display the satellite imagery within Google Earth/Maps, and ArcGIS Explorer both as static maps and time-animated imagery. We will show these tools in real-time as well as examples of past large volcanic eruptions. In the future, we will develop the tools to produce real-time ash retrievals, run volcanic ash dispersion

  15. Confronting remote sensing product with ground base measurements across time and scale

    Science.gov (United States)

    Pourmokhtarian, A.; Dietze, M.

    2015-12-01

    Ecosystem models are essential tools in forecasting ecosystem responses to global climate change. One of the most challenging issues in ecosystem modeling is scaling while preserving landscape characteristics and minimizing loss of information, when moving from point observation to regional scale. There is a keen interest in providing accurate inputs for ecosystem models which represent ecosystem initial state conditions. Remote sensing land cover products, such as Landsat NLCD and MODIS MCD12Q1, provide extensive spatio-temporal coverage but do not capture forest composition and structure. Lidar and hyperspectral have the potential to meet this need but lack sufficient spatial and historical coverage. Forest inventory measurements provide detailed information on the landscape but in a very small footprint. Combining inventory and land cover could improve estimates of ecosystem state and characteristic across time and space. This study focuses on the challenges associated with fusing and scaling the US Forest Service FIA database and NLCD across regional scales to quantify ecosystem characteristics and reduce associated uncertainties. Across Southeast of U.S. 400 stratified random samples of 10x10 km2 landscapes were selected. Data on plant density, species, age, and DBH of trees in FIA plots within each site were extracted. Using allometry equations, the canopy cover of different plant functional types (PFTs) was estimated using a PPA-style canopy model and used to assign each inventory plot to a land cover class. Inventory and land cover were fused in a Bayesian model that adjusts the fractional coverage of inventory plots while accounting for multiple sources of uncertainty. Results were compared to estimates derived from inventory alone, land cover alone, and model spin-up alone. Our findings create a framework of data assimilation to better interpret remote sensing data using ground-based measurements.

  16. 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.

  17. Up Close from Afar: Using Remote Sensing To Teach the American Landscape. Pathways in Geography Series, Title No. 8.

    Science.gov (United States)

    Baumann, Paul R., Ed.

    This teaching guide offers educators glimpses into the value of remote sensing, the process of observing and analyzing the earth from a distance. Remote sensing provides information in forms to see spatial patterns over large areas in a more realistic way than thematic maps and allows a macro-scale look at global problems. The six instructional…

  18. Earth Observation for Ecosystems Monitoring in Space and Time: A Special Issue in Remote Sensing

    OpenAIRE

    Duccio Rocchini

    2015-01-01

    This Editorial introduces the papers published in the special issue “Earth Observation for Ecosystems Monitoring in Space and Time” which includes the most important researchers in the field and the most challenging aspects of the application of remote sensing to study ecosystems.

  19. SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data

    Science.gov (United States)

    Crétaux, J.-F.; Jelinski, W.; Calmant, S.; Kouraev, A.; Vuglinski, V.; Bergé-Nguyen, M.; Gennero, M.-C.; Nino, F.; Abarca Del Rio, R.; Cazenave, A.; Maisongrande, P.

    2011-05-01

    An accurate and continuous monitoring of lakes and inland seas is available since 1993 thanks to the satellite altimetry missions (Topex-Poseidon, GFO, ERS-2, Jason-1, Jason-2 and Envisat). Global data processing of these satellites provides temporal and spatial time series of lakes surface height with a decimetre precision on the whole Earth. The response of water level to regional hydrology is particularly marked for lakes and inland seas in semi-arid regions. A lake data centre is under development at by LEGOS (Laboratoire d'Etude en Géophysique et Océanographie Spatiale) in Toulouse, in coordination with the HYDROLARE project (Headed by SHI: State Hydrological Institute of the Russian Academy of Science). It already provides level variations for about 150 lakes and reservoirs, freely available on the web site (HYDROWEB: http://www.LEGOS.obs-mip.fr/soa/hydrologie/HYDROWEB), and surface-volume variations of about 50 big lakes are also calculated through a combination of various satellite images (Modis, Asar, Landsat, Cbers) and radar altimetry. The final objective is to achieve in 2011 a fully operating data centre based on remote sensing technique and controlled by the in situ infrastructure for the Global Terrestrial Network for Lakes (GTN-L) under the supervision of WMO (World Meteorological Organization) and GCOS (Global Climate Observing System).

  20. Can remote sensing help citizen-science based phenological studies?

    Science.gov (United States)

    Delbart, Nicolas; Elisabeth, Beaubien; Laurent, Kergoat; Thuy, Le Toan

    2017-04-01

    Citizen science networks and remote sensing are both efficient to collect massive data related to phenology. However both differ in their advantages and drawbacks for this purpose. Contrarily to remote sensing, citizen science allows distinguishing species-specific phenological responses to climate variability. On the other hand, large portions of territory of a country like Canada are not covered by citizen science networks, and the time series are often incomplete. The main mode of interaction between both types of data consists in validating the maps showing the ecosystem foliage transition times, such as the green-up date, obtained from remote sensing data with field observations, and in particular those collected by citizen scientists. Thus the citizen science phenology data bring confidence to remote sensing based studies. However, one can merely find studies in which remote sensing is used to improve in any way citizen science based study. Here we present bi-directional interactions between both types of data. We first use phenological data from the PlantWatch citizen science network to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. In particular we analyze the interspecies differences in phenology at the scale of so-called "pheno-regions" delineated using remote sensing green-up maps.

  1. Near Real-Time Applications of Earth Remote Sensing for Response to Meteorological Disasters

    Science.gov (United States)

    Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Bell, Jordan R.

    2013-01-01

    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 area. 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. Other applications are being developed to refine light source detections with the VIIRS day-night band and to map hail during the growing season through combination of available satellite and radar imagery. The aforementioned products and support are not useful unless they are distributed in a timely manner and within an appropriate decision support system. This presentation will provide an update on ongoing activities to support inclusion of these data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing

  2. Real Time Estimation of the Calgary Floods Using Limited Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Emily Schnebele

    2014-02-01

    Full Text Available Every year, flood disasters are responsible for widespread destruction and loss of human life. Remote sensing data are capable of providing valuable, synoptic coverage of flood events but are not always available because of satellite revisit limitations, obstructions from cloud cover or vegetation canopy, or expense. In addition, knowledge of road accessibility is imperative during all phases of a flood event. In June 2013, the City of Calgary experienced sudden and extensive flooding but lacked comprehensive remote sensing coverage. Using this event as a case study, this work illustrates how data from non-authoritative sources are used to augment traditional data and methods to estimate flood extent and identify affected roads during a flood disaster. The application of these data, which may have varying resolutions and uncertainities, provide an estimation of flood extent when traditional data and methods are lacking or incomplete. When flooding occurs over multiple days, it is possible to construct an estimate of the advancement and recession of the flood event. Non-authoritative sources also provide flood information at the micro-level, which can be difficult to capture from remote sensing data; however, the distibution and quantity of data collected from these sources will affect the quality of the flood estimations.

  3. Real-time remote sensing driven river basin modeling using radar altimetry

    Directory of Open Access Journals (Sweden)

    S. J. Pereira-Cardenal

    2011-01-01

    Full Text Available Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models.

    In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA, temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat measurements of reservoir water levels. The modeling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is located in Central Asia and shared between 4 countries with conflicting water management interests.

    The modeling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean absolute error of the simulated reservoir water levels from 4.7 to 1.9 m, and

  4. Real-time remote sensing driven river basin modelling using radar altimetry

    Directory of Open Access Journals (Sweden)

    S. J. Pereira-Cardenal

    2010-10-01

    Full Text Available Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models.

    In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modelling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA, temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat measurements of reservoir water levels. The modelling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is shared between 4 countries with conflicting water management interests.

    The modelling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean error of the simulated reservoir water levels from 4.7 to 1.9 m, and overall model RMSE from 10.3 m to 6

  5. Spatial distribution of the timing of rainfall extremes derived by remote sensing and raingauges data assimilation

    Science.gov (United States)

    Libertino, Andrea; Claps, Pierluigi; Sharma, Ashish; Lakshmi, Venkat

    2016-04-01

    Severe rainfall events are quite common in the coastal areas of the Mediterranean basin during autumn season, despite its generally mild climate. Very often meteorological conditions responsible for these kinds of events are quasi-stationary convective systems, characterized by very localized development, hard to detect with traditional rain gauge networks. In order to improve prediction and management capabilities, progress must be made in understanding the mechanism that govern the development of these kind of precipitation systems at the different scales. Rainfall product from the Tropical Rainfall Measuring Mission (TRMM) are commonly adopted in different branches of the environmental sciences due to the high spatio-temporal resolution and to the quasi-global nature of the data. Building upon the success of TRMM, NASA and JAXA deployed the GPM Core Observatory that, after just two years of activity, seems to allow for great improvement in the accuracy of rainfall products. We developed a methodology aimed at exploiting the timing information derived from high-resolution remote sensing products to analyze the characteristic of severe rainfall systems in the Mediterranean basin. The spatial analysis from satellite, combined with the historical information from the rain gauge network, allows us deepening the knowledge of the spatial extension of extreme rainfall phenomena. All those information, merged together in a hierarchical framework, lead to the definition of Intensity-Duration-Frequency curves "informed" on the nature of the events for each location of the domain, without the need to adopt classical interpolation techniques, unable to represent the complexity of the rainfall systems. The case study refers to a database of daily rainfall measurements extracted from the NOAA GHCN-Daily dataset, recorded during the 20th century by 700 rain gauges distributed in the Mediterranean basin. TRMM and GPM images are used to calibrate the event timing over the

  6. Introduction to remote sensing

    CERN Document Server

    Cracknell, Arthur P

    2007-01-01

    Addressing the need for updated information in remote sensing, Introduction to Remote Sensing, Second Edition provides a full and authoritative introduction for scientists who need to know the scope, potential, and limitations in the field. The authors discuss the physical principles of common remote sensing systems and examine the processing, interpretation, and applications of data. This new edition features updated and expanded material, including greater coverage of applications from across earth, environmental, atmospheric, and oceanographic sciences. Illustrated with remotely sensed colo

  7. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing

    Directory of Open Access Journals (Sweden)

    Deqing Liu

    2016-08-01

    Full Text Available In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC. The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  8. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing.

    Science.gov (United States)

    Liu, Deqing; Luan, Xiaoning; Guo, Jinjia; Cui, Tingwei; An, Jubai; Zheng, Ronger

    2016-08-23

    In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC). The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA) has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  9. A virtual remote sensing observation network for continuous, near-real-time monitoring of atmospheric instability

    Science.gov (United States)

    Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco

    2017-04-01

    remote sensing (i.e. SEVIRI, AMSU) is used to complement observations from a virtual ground-based microwave radiometer network based on the reanalysis of the COSMO model for Europe. In this contribution, we present a synergetic retrieval algorithm of stability indices from satellite observations and ground-based microwave measurements based on the COSMO-DE reanalysis as truth. In order to make the approach feasible for data assimilation applications at national weather services, we simulate satellite observations with the standard RTTOV model and use the newly developed RTTOV-gb (ground-based) for the ground-based radiometers (De Angelis et al., 2016). For the detection of significant instabilities, we show the synergy benefit in terms of uncertainty reduction, probability of detection and other forecast skill scores. The overall goal of ARON is to quantify the impact of ground-based vertical profilers within an integrated forecasting system, which combines short-term and now-casting.

  10. Combining Citizen Science Phenological Observations with Remote Sensing Data

    Science.gov (United States)

    Delbart, Nicolas; Beaubien, Elisabeth; Kergoat, Laurent; Deront, Lise; Le Toan, Thuy

    2016-08-01

    Citizen science is efficient to collect data about plant phenology across large areas such as Canada and independently for each species. However, such time series are often discontinuous and observations are not evenly distributed. On the other hand, remote sensing provides a synoptic view on phenology but does not inform about inter-species differences in phenological response to climate variability.Existing interactions between the two types of data are so far essentially limited to the evaluation of remote sensing methods by citizen science data, which proved quite efficient. Here we first use such an approach to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. We analyze the interspecies differences in phenology at the scale of so- called "pheno-regions" delineated using remote sensing green-up maps.

  11. Evaluation of Harmonic Analysis of Time Series (HANTS): impact of gaps on time series reconstruction

    NARCIS (Netherlands)

    Zhou, J.Y.; Jia, L.; Hu, G.; Menenti, M.

    2012-01-01

    In recent decades, researchers have developed methods and models to reconstruct time series of irregularly spaced observations from satellite remote sensing, among which the widely used Harmonic Analysis of Time Series (HANTS) method. Many studies based on time series reconstructed with HANTS docume

  12. Evaluation of Harmonic Analysis of Time Series (HANTS): impact of gaps on time series reconstruction

    NARCIS (Netherlands)

    Zhou, J.Y.; Jia, L.; Hu, G.; Menenti, M.

    2012-01-01

    In recent decades, researchers have developed methods and models to reconstruct time series of irregularly spaced observations from satellite remote sensing, among which the widely used Harmonic Analysis of Time Series (HANTS) method. Many studies based on time series reconstructed with HANTS docume

  13. Evaluation of Harmonic Analysis of Time Series (HANTS): impact of gaps on time series reconstruction

    NARCIS (Netherlands)

    Zhou, J.Y.; Jia, L.; Hu, G.; Menenti, M.

    2012-01-01

    In recent decades, researchers have developed methods and models to reconstruct time series of irregularly spaced observations from satellite remote sensing, among which the widely used Harmonic Analysis of Time Series (HANTS) method. Many studies based on time series reconstructed with HANTS

  14. Remote sensing in precision farming: real-time monitoring of water and fertilizer requirements of agricultural crops

    Science.gov (United States)

    Zilberman, Arkadi; Ben Asher, Jiftah; Kopeika, Norman S.

    2016-10-01

    The advancements in remote sensing in combination with sensor technology (both passive and active) enable growers to analyze an entire crop field as well as its local features. In particular, changes of actual evapo-transpiration (ET) as a function of water availability can be measured remotely with infrared radiometers. Detection of crop water stress and ET and combining it with the soil water flow model enable rational irrigation timing and application amounts. Nutrient deficiency, and in particular nitrogen deficiency, causes substantial crop losses. This deficiency needs to be identified immediately. A faster the detection and correction, a lesser the damage to the crop yield. In the present work, to retrieve ET a novel deterministic approach was used which is based on the remote sensing data. The algorithm can automatically provide timely valuable information on plant and soil water status, which can improve the management of irrigated crops. The solution is capable of bridging between Penman-Monteith ET model and Richards soil water flow model. This bridging can serve as a preliminary tool for expert irrigation system. To support decisions regarding fertilizers the greenness of plant canopies is assessed and quantified by using the spectral reflectance sensors and digital color imaging. Fertilization management can be provided on the basis of sampling and monitoring of crop nitrogen conditions using RS technique and translating measured N concentration in crop to kg/ha N application in the field.

  15. Optical remote sensing

    CERN Document Server

    Prasad, Saurabh; Chanussot, Jocelyn

    2011-01-01

    Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data: challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, patter

  16. High time resolution boundary layer description using combined remote sensing instruments

    Directory of Open Access Journals (Sweden)

    C. Gaffard

    2008-09-01

    Full Text Available Ground based remote sensing systems for future observation operations will allow continuous monitoring of the lower troposphere at temporal resolutions much better than every 30 min. Observations which may be considered spurious from an individual instrument can be validated or eliminated when considered in conjunction with measurements from other instruments observing at the same location. Thus, improved quality control of atmospheric profiles from microwave radiometers and wind profilers should be sought by considering the measurements from different systems together rather than individually. In future test bed deployments for future operational observing systems, this should be aided by observations from laser ceilometers and cloud radars. Observations of changes in atmospheric profiles at high temporal resolution in the lower troposphere are presented from a 12 channel microwave radiometer and 1290 MHz UHF wind profiler deployed in southern England during the CSIP field experiment in July/August 2005. The observations chosen were from days when thunderstorms occurred in southern England. Rapid changes near the surface in dry layers are considered, both when rain/hail may be falling from above and where the dry air is associated with cold pools behind organised thunderstorms. Also, short term variations in atmospheric profiles and vertical stability are presented on a day with occasional low cloud, when thunderstorms triggered 50 km down wind of the observing site Improved quality control of the individual remote sensing systems need to be implemented, examining the basic quality of the underlying observations as well as the final outputs, and so for instance eliminating ground clutter as far as possible from the basic Doppler spectra measurements of the wind profiler. In this study, this was performed manually. The potential of incorporating these types of instruments in future upper air observational networks leads to the challenge to

  17. Optical Remote Sensing Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Optical Remote Sensing Laboratory deploys rugged, cutting-edge electro-optical instrumentation for the collection of various event signatures, with expertise in...

  18. Autofocus method for scanning remote sensing cameras.

    Science.gov (United States)

    Lv, Hengyi; Han, Chengshan; Xue, Xucheng; Hu, Changhong; Yao, Cheng

    2015-07-10

    Autofocus methods are conventionally based on capturing the same scene from a series of positions of the focal plane. As a result, it has been difficult to apply this technique to scanning remote sensing cameras where the scenes change continuously. In order to realize autofocus in scanning remote sensing cameras, a novel autofocus method is investigated in this paper. Instead of introducing additional mechanisms or optics, the overlapped pixels of the adjacent CCD sensors on the focal plane are employed. Two images, corresponding to the same scene on the ground, can be captured at different times. Further, one step of focusing is done during the time interval, so that the two images can be obtained at different focal plane positions. Subsequently, the direction of the next step of focusing is calculated based on the two images. The analysis shows that the method investigated operates without restriction of the time consumption of the algorithm and realizes a total projection for general focus measures and algorithms from digital still cameras to scanning remote sensing cameras. The experiment results show that the proposed method is applicable to the entire focus measure family, and the error ratio is, on average, no more than 0.2% and drops to 0% by reliability improvement, which is lower than that of prevalent approaches (12%). The proposed method is demonstrated to be effective and has potential in other scanning imaging applications.

  19. Hyperspectral remote sensing

    CERN Document Server

    Eismann, Michael

    2012-01-01

    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. This book provides a holistic treatment that captures its multidisciplinary nature, emphasizing the physical principles of hyperspectral remote sensing.

  20. Remote Sensing of Water Pollution

    Science.gov (United States)

    White, P. G.

    1971-01-01

    Remote sensing, as a tool to aid in the control of water pollution, offers a means of making rapid, economical surveys of areas that are relatively inaccessible on the ground. At the same time, it offers the only practical means of mapping pollution patterns that cover large areas. Detection of oil slicks, thermal pollution, sewage, and algae are discussed.

  1. REMOTE SENSING IN OCEANOGRAPHY.

    Science.gov (United States)

    remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

  2. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  3. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  4. Progress in the remote sensing of C3 and C4 grass species aboveground biomass over time and space

    Science.gov (United States)

    Shoko, Cletah; Mutanga, Onisimo; Dube, Timothy

    2016-10-01

    The remote sensing of grass aboveground biomass (AGB) has gained considerable attention, with substantial research being conducted in the past decades. Of significant importance is their photosynthetic pathways (C3 and C4), which epitomizes a fundamental eco-physiological distinction of grasses functional types. With advances in technology and the availability of remotely sensed data at different spatial, spectral, radiometric and temporal resolutions, coupled with the need for detailed information on vegetation condition, the monitoring of C3 and C4 grasses AGB has received renewed attention, especially in the light of global climate change, biodiversity and, most importantly, food security. This paper provides a detailed survey on the progress of remote sensing application in determining C3 and C4 grass species AGB. Importantly, the importance of species functional type is highlighted in conjunction with the availability and applicability of different remote sensing datasets, with refined resolutions, which provide an opportunity to monitor C3 and C4 grasses AGB. While some progress has been made, this review has revealed the need for further remote sensing studies to model the seasonal (cyclical) variability, as well as long-term AGB changes in C3 and C4 grasses, in the face of climate change and food security. Moreover, the findings of this study have shown the significance of shifting towards the application of advanced statistical models, to further improve C3 and C4 grasses AGB estimation accuracy.

  5. Suitability Evaluation for Products Generation from Multisource Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Jining Yan

    2016-12-01

    Full Text Available With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-term series Earth observation, and have, in particular, made standard, automated product generation more popular. However, there is more than one type of data selection for producing a certain remote sensing product; no single remote sensor can cover such a large area at one time. Therefore, we should automatically select the best data source from redundant multisource remote sensing data, or select substitute data if data is lacking, during the generation of remote sensing products. However, the current data selection strategy mainly adopts the empirical model, and has a lack of theoretical support and quantitative analysis. Hence, comprehensively considering the spectral characteristics of ground objects and spectra differences of each remote sensor, by means of spectrum simulation and correlation analysis, we propose a suitability evaluation model for product generation. The model will enable us to obtain the Production Suitability Index (PSI of each remote sensing data. In order to validate the proposed model, two typical value-added information products, NDVI and NDWI, and two similar or complementary remote sensors, Landsat-OLI and HJ1A-CCD1, were chosen, and the verification experiments were performed. Through qualitative and quantitative analysis, the experimental results were consistent with our model calculation results, and strongly proved the validity of the suitability evaluation model. The proposed production suitability evaluation model could assist with standard, automated, serialized product generation. It will play an important role in one-station, value-added information services during the big data era of Earth observation.

  6. Experiment Design Regularization-Based Hardware/Software Codesign for Real-Time Enhanced Imaging in Uncertain Remote Sensing Environment

    Directory of Open Access Journals (Sweden)

    Castillo Atoche A

    2010-01-01

    Full Text Available A new aggregated Hardware/Software (HW/SW codesign approach to optimization of the digital signal processing techniques for enhanced imaging with real-world uncertain remote sensing (RS data based on the concept of descriptive experiment design regularization (DEDR is addressed. We consider the applications of the developed approach to typical single-look synthetic aperture radar (SAR imaging systems operating in the real-world uncertain RS scenarios. The software design is aimed at the algorithmic-level decrease of the computational load of the large-scale SAR image enhancement tasks. The innovative algorithmic idea is to incorporate into the DEDR-optimized fixed-point iterative reconstruction/enhancement procedure the convex convergence enforcement regularization via constructing the proper multilevel projections onto convex sets (POCS in the solution domain. The hardware design is performed via systolic array computing based on a Xilinx Field Programmable Gate Array (FPGA XC4VSX35-10ff668 and is aimed at implementing the unified DEDR-POCS image enhancement/reconstruction procedures in a computationally efficient multi-level parallel fashion that meets the (near real-time image processing requirements. Finally, we comment on the simulation results indicative of the significantly increased performance efficiency both in resolution enhancement and in computational complexity reduction metrics gained with the proposed aggregated HW/SW co-design approach.

  7. Fusion of hyperspectral remote sensing data for near real-time monitoring of microcystin distribution in Lake Erie

    Science.gov (United States)

    Vannah, Benjamin; Chang, Ni-Bin

    2013-09-01

    Urban growth and agricultural production have caused an influx of nutrients into Lake Erie, leading to eutrophic zones. These conditions result in the formation of algal blooms, some of which are toxic due to the presence of Microcystis (a cyanobacteria), which produces the hepatotoxin microcystin. Microcystis has a unique advantage over its competition as a result of the invasive zebra mussel population that filters algae out of the water column except for the toxic Microcystis. The toxin threatens human health and the ecosystem, and it is a concern for water treatment plants using the lake water as a tap water source. This presentation demonstrates the prototype of a near real-time early warning system using Integrated Data Fusion techniques with the aid of both hyperspectral remote sensing data to determine spatiotemporal microcystin concentrations. The temporal resolution of MODIS is fused with the higher spatial and spectral resolution of MERIS to create synthetic images on a daily basis. As a demonstration, the spatiotemporal distributions of microcystin within western Lake Erie are reconstructed using the band data from the fused products and applied machine-learning techniques. Analysis of the results through statistical indices confirmed that the this type of algorithm has better potential to accurately estimating microcystin concentrations in the lake, which is better than current two band models and other computational intelligence models.

  8. Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

    DEFF Research Database (Denmark)

    Ivits, Eva; Horion, Stéphanie Marie Anne F; Fensholt, Rasmus

    2014-01-01

    bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time-series of Normalized Difference Vegetation Index (NDVI). Drought spatio...

  9. Advanced laser remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, J.; Czuchlewski, S.; Karl, R. [and others

    1996-11-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory. Remote measurement of wind velocities is critical to a wide variety of applications such as environmental studies, weather prediction, aircraft safety, the accuracy of projectiles, bombs, parachute drops, prediction of the dispersal of chemical and biological warfare agents, and the debris from nuclear explosions. Major programs to develop remote sensors for these applications currently exist in the DoD and NASA. At present, however, there are no real-time, three-dimensional wind measurement techniques that are practical for many of these applications and we report on two new promising techniques. The first new technique uses an elastic backscatter lidar to track aerosol patterns in the atmosphere and to calculate three dimensional wind velocities from changes in the positions of the aerosol patterns. This was first done by Professor Ed Eloranta of the University of Wisconsin using post processing techniques and we are adapting Professor Eloranta`s algorithms to a real-time data processor and installing it in an existing elastic backscatter lidar system at Los Alamos (the XM94 helicopter lidar), which has a compatible data processing and control system. The second novel wind sensing technique is based on radio-frequency (RF) modulation and spatial filtering of elastic backscatter lidars. Because of their compactness and reliability, solid state lasers are the lasers of choice for many remote sensing applications, including wind sensing.

  10. 遥感卫星星上时间管理方法%On-board time management method of remote sensing satellate

    Institute of Scientific and Technical Information of China (English)

    田贺祥; 王同桓; 李璇; 徐浩

    2013-01-01

    Remote sensing satellite is important mode of the earth and space observation, and time management system is one of the most important part of remote sensing satellite. Remote sensing satellite is used as the application object. Time system designing and time management method are analyzed, unified time management model is established. Time management operating mechanism is analyzed, and error model which affects time management precision is given, that provides reference for time management system design of remote sensing satellite. The time management model is testified through experiment, and the result shows that the time management method and error model can meet the demand of high precision time synchronism design and analysis.%遥感卫星是地球和空间观测的重要方式,时间管理系统是其重要组成部分.以遥感卫星为应用对象,围绕星上时间系统设计和时间管理方法展开分析,建立了统一的星上时间管理模型,重点针对遥感卫星实用的时间管理运行机制进行了梳理与总结,给出了影响时间管理精度的误差模型,为遥感卫星时间管理系统的设计提供参考.进一步通过实验方式对时间管理模型进行了验证,结果表明:采用的时间管理方法和误差模型能够满足遥感卫星高精度时间同步的设计和分析需求.

  11. Remote sensing in biological oceanography

    Science.gov (United States)

    Esaias, W. E.

    1981-01-01

    The main attribute of remote sensing is seen as its ability to measure distributions over large areas on a synoptic basis and to repeat this coverage at required time periods. The way in which the Coastal Zone Color Scanner, by showing the distribution of chlorophyll a, can locate areas productive in both phytoplankton and fishes is described. Lidar techniques are discussed, and it is pointed out that lidar will increase the depth range for observations.

  12. Environmental impact prediction using remote sensing images

    Institute of Scientific and Technical Information of China (English)

    Pezhman ROUDGARMI; Masoud MONAVARI; Jahangir FEGHHI; Jafar NOURI; Nematollah KHORASANI

    2008-01-01

    Environmental impact prediction is an important step in many environmental studies. Awide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005~2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.

  13. Introduction to remote sensing

    CERN Document Server

    Campbell, James B

    2012-01-01

    A leading text for undergraduate- and graduate-level courses, this book introduces widely used forms of remote sensing imagery and their applications in plant sciences, hydrology, earth sciences, and land use analysis. The text provides comprehensive coverage of principal topics and serves as a framework for organizing the vast amount of remote sensing information available on the Web. Including case studies and review questions, the book's four sections and 21 chapters are carefully designed as independent units that instructors can select from as needed for their courses. Illustrations in

  14. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  15. Hyperspectral remote sensing for light pollution monitoring

    Directory of Open Access Journals (Sweden)

    P. Marcoionni

    2006-06-01

    Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.

  16. Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

    Science.gov (United States)

    Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

    2015-11-02

    This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

  17. Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time

    Directory of Open Access Journals (Sweden)

    Gustavo S. C. Avellar

    2015-11-01

    Full Text Available This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs equipped with image sensors. The solution is divided into two parts: (i the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

  18. Remote sensing of natural phenomena

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2014-06-01

    after the withdrawal of water, for the estimation of damage and flood recovery. Usage of satellite images in detectingearthquakes Remote sensing is widely used in the procedure of detecting and locating earthquakes. Earthquakes can be detected by the combination of geophysical methods with multispectral and radar images. By combining these nethods, we can monitor the conditions of seizmic areas. The obtained information can be computed and sent to information centres in stationary stations where the modelling of earthquake-affected terrains is carried out. Usage of satellite images in monitoring volcanos Remote sensing has been used ifor examining a large number of active vulcanos. Monitoring is performed several times, during and after eruptions. The modelling of volcanic areas enables the definition of lava-effusion zones,and  potentially dangerous zones, which is further used for  planning the protection of affected areas. Usage of satellite images in monitoring fire (blaze One of important methods of investigating, forecasting and monitoring forest fires is remote sensing. Satellite images are valuable in discovering fires and in mapping affected areas within the geographical-information system (GIS, as well as in the estimation of demage caused by fire. Satellite images can also be usedto estimate the temperature on the Earth surface. Conclusion Remote sensing becomes an increasingly important and unavoidable method of the acquisition of data on  geospacein general. The importance of thus obtained data  is invaluable in all phases of monitoring  catastrophic events, from detecting their onsets through monitoring their spreading and effects  to the phase of recovery. New generations of sensors enable systematic monitoring, recording and measuring different data important for detecting changes and processes in the sea, on the ground and in the atmosphere. The procedures of remote sensing enable surveying (recording and registration of different natural

  19. Inclusion of In-Situ Velocity Measurements into the UCSD Time-Dependent Tomography to Constrain and Better-Forecast Remote-Sensing Observations

    Science.gov (United States)

    Jackson, B. V.; Hick, P. P.; Bisi, M. M.; Clover, J. M.; Buffington, A.

    2010-08-01

    The University of California, San Diego (UCSD) three-dimensional (3-D) time-dependent tomography program has been used successfully for a decade to reconstruct and forecast coronal mass ejections from interplanetary scintillation observations. More recently, we have extended this tomography technique to use remote-sensing data from the Solar Mass Ejection Imager (SMEI) on board the Coriolis spacecraft; from the Ootacamund (Ooty) radio telescope in India; and from the European Incoherent SCATter (EISCAT) radar telescopes in northern Scandinavia. Finally, we intend these analyses to be used with observations from the Murchison Widefield Array (MWA), or the LOw Frequency ARray (LOFAR) now being developed respectively in Australia and Europe. In this article we demonstrate how in-situ velocity measurements from the Advanced Composition Explorer (ACE) space-borne instrumentation can be used in addition to remote-sensing data to constrain the time-dependent tomographic solution. Supplementing the remote-sensing observations with in-situ measurements provides additional information to construct an iterated solar-wind parameter that is propagated outward from near the solar surface past the measurement location, and throughout the volume. While the largest changes within the volume are close to the radial directions that incorporate the in-situ measurements, their inclusion significantly reduces the uncertainty in extending these measurements to global 3-D reconstructions that are distant in time and space from the spacecraft. At Earth, this can provide a finely-tuned real-time measurement up to the latest time for which in-situ measurements are available, and enables more-accurate forecasting beyond this than remote-sensing observations alone allow.

  20. Real-time remote sensing driven river basin modeling using radar altimetry

    DEFF Research Database (Denmark)

    Pereira Cardenal, Silvio Javier; Riegels, Niels; Bauer-Gottwein, Peter

    2011-01-01

    and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models. In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling...... evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat) measurements of reservoir water levels. The modeling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several...... large reservoirs and scarce hydrometeorological data that is located in Central Asia and shared between 4 countries with conflicting water management interests. The modeling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar...

  1. Design of a real-time system of moving ship tracking on-board based on FPGA in remote sensing images

    Science.gov (United States)

    Yang, Tie-jun; Zhang, Shen; Zhou, Guo-qing; Jiang, Chuan-xian

    2015-12-01

    With the broad attention of countries in the areas of sea transportation and trade safety, the requirements of efficiency and accuracy of moving ship tracking are becoming higher. Therefore, a systematic design of moving ship tracking onboard based on FPGA is proposed, which uses the Adaptive Inter Frame Difference (AIFD) method to track a ship with different speed. For the Frame Difference method (FD) is simple but the amount of computation is very large, it is suitable for the use of FPGA to implement in parallel. But Frame Intervals (FIs) of the traditional FD method are fixed, and in remote sensing images, a ship looks very small (depicted by only dozens of pixels) and moves slowly. By applying invariant FIs, the accuracy of FD for moving ship tracking is not satisfactory and the calculation is highly redundant. So we use the adaptation of FD based on adaptive extraction of key frames for moving ship tracking. A FPGA development board of Xilinx Kintex-7 series is used for simulation. The experiments show that compared with the traditional FD method, the proposed one can achieve higher accuracy of moving ship tracking, and can meet the requirement of real-time tracking in high image resolution.

  2. EPA REMOTE SENSING RESEARCH

    Science.gov (United States)

    The 2006 transgenic corn imaging research campaign has been greatly assisted through a cooperative effort with several Illinois growers who provided planting area and crop composition. This research effort was designed to evaluate the effectiveness of remote sensed imagery of var...

  3. Section summary: Remote sensing

    Science.gov (United States)

    Belinda Arunarwati Margono

    2013-01-01

    Remote sensing is an important data source for monitoring the change of forest cover, in terms of both total removal of forest cover (deforestation), and change of canopy cover, structure and forest ecosystem services that result in forest degradation. In the context of Intergovernmental Panel on Climate Change (IPCC), forest degradation monitoring requires information...

  4. Remote sensing: best practice

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Gareth [Sgurr Energy (Canada)

    2011-07-01

    This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

  5. LIDAR and atmosphere remote sensing

    CSIR Research Space (South Africa)

    Venkataraman, S

    2008-05-01

    Full Text Available and to consist of theory and practical exercises • Theory: Remote sensing process, Photogrammetry, introduction to multispectral, remote sensing systems, Thermal infra-red remote sensing, Active and passive remote sensing, LIDAR, Application of remotely... Aerosol measurements and cloud characteristics head2right Water vapour measurements in the lower troposphere region up to 8 km head2right Ozone measurements in the troposphere regions up to 18 km Slide 22 © CSIR 2008 www...

  6. Research on Key Technology of Mining Remote Sensing Dynamic Monitoring Information System

    Science.gov (United States)

    Sun, J.; Xiang, H.

    2017-09-01

    Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.

  7. 3D Visualization of near real-time remote-sensing observation for hurricanes field campaign using Google Earth API

    Science.gov (United States)

    Li, P.; Turk, J.; Vu, Q.; Knosp, B.; Hristova-Veleva, S. M.; Lambrigtsen, B.; Poulsen, W. L.; Licata, S.

    2009-12-01

    NASA is planning a new field experiment, the Genesis and Rapid Intensification Processes (GRIP), in the summer of 2010 to better understand how tropical storms form and develop into major hurricanes. The DC-8 aircraft and the Global Hawk Unmanned Airborne System (UAS) will be deployed loaded with instruments for measurements including lightning, temperature, 3D wind, precipitation, liquid and ice water contents, aerosol and cloud profiles. During the field campaign, both the spaceborne and the airborne observations will be collected in real-time and integrated with the hurricane forecast models. This observation-model integration will help the campaign achieve its science goals by allowing team members to effectively plan the mission with current forecasts. To support the GRIP experiment, JPL developed a website for interactive visualization of all related remote-sensing observations in the GRIP’s geographical domain using the new Google Earth API. All the observations are collected in near real-time (NRT) with 2 to 5 hour latency. The observations include a 1KM blended Sea Surface Temperature (SST) map from GHRSST L2P products; 6-hour composite images of GOES IR; stability indices, temperature and vapor profiles from AIRS and AMSU-B; microwave brightness temperature and rain index maps from AMSR-E, SSMI and TRMM-TMI; ocean surface wind vectors, vorticity and divergence of the wind from QuikSCAT; the 3D precipitation structure from TRMM-PR and vertical profiles of cloud and precipitation from CloudSAT. All the NRT observations are collected from the data centers and science facilities at NASA and NOAA, subsetted, re-projected, and composited into hourly or daily data products depending on the frequency of the observation. The data products are then displayed on the 3D Google Earth plug-in at the JPL Tropical Cyclone Information System (TCIS) website. The data products offered by the TCIS in the Google Earth display include image overlays, wind vectors, clickable

  8. Remote sensing of forest insect disturbances: Current state and future directions.

    Science.gov (United States)

    Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

    2017-08-01

    Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

  9. Remote sensing of forest insect disturbances: Current state and future directions

    Science.gov (United States)

    Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

    2017-08-01

    Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

  10. Stochastic models of cover class dynamics. [remote sensing of vegetation

    Science.gov (United States)

    Barringer, T. H.; Robinson, V. B.

    1981-01-01

    Investigations related to satellite remote sensing of vegetation have been concerned with questions of signature identification and extension, cover inventory accuracy, and change detection and monitoring. Attention is given to models of ecological succession, present directions in successional modeling and analysis, nondynamic spatial models, issues in the analysis of spatial data, and aspects of spatial modeling. Issues in time-series analysis are considered along with dynamic spatial models, and problems of model specification and identification.

  11. Production of a Dynamic Cropland Mask by Processing Remote Sensing Image Series at High Temporal and Spatial Resolutions

    Directory of Open Access Journals (Sweden)

    Silvia Valero

    2016-01-01

    Full Text Available The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. The Sentinel-2 for Agriculture project S2Agri (http://www.esa-sen2agri.org/SitePages/Home.aspx is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring for many agricultural systems across the globe. In the framework of this project, this article studies the construction of a dynamic cropland mask. This mask consists of a binary “annual-cropland/no-annual-cropland” map produced several times during the season to serve as a mask for monitoring crop growing conditions over the growing season. The construction of the mask relies on two classical pattern recognition techniques: feature extraction and classification. One pixel- and two object-based strategies are proposed and compared. A set of 12 test sites are used to benchmark the methods and algorithms with regard to the diversity of the agro-ecological context, landscape patterns, agricultural practices and actual satellite observation conditions. The classification results yield promising accuracies of around 90% at the end of the agricultural season. Efforts will be made to transition this research into operational products once Sentinel-2 data become available.

  12. 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

  13. Time Series

    OpenAIRE

    Gil-Alana, L.A.; Moreno, A; Pérez-de-Gracia, F. (Fernando)

    2011-01-01

    The last 20 years have witnessed a considerable increase in the use of time series techniques in econometrics. The articles in this important set have been chosen to illustrate the main themes in time series work as it relates to econometrics. The editor has written a new concise introduction to accompany the articles. Sections covered include: Ad Hoc Forecasting Procedures, ARIMA Modelling, Structural Time Series Models, Unit Roots, Detrending and Non-stationarity, Seasonality, Seasonal Adju...

  14. Remote sensing-based analysis on temporal and spatial changes about environmental elements in the northwest of Junggar basin, China

    Science.gov (United States)

    Yang, Liu; Nannan, Zhang; Wentong, Dong; Liqun, Zou; Shanghong, Huang

    2016-11-01

    This paper presents a study of revealing the environmental elements change during the process of local industrialization based on remote sensing technique in the western part of China. Spatio-temporal evolution of vegetation cover derived from NDVI and land surface water distribution was analyzed by time-series analysis of MSS and Landsat data from 1977 to 2011. Results show that remote sensing provide a way for monitoring the influence of local industrialization on regional environment elements in gobi region.

  15. Multiscale and Multitemporal Urban Remote Sensing

    Science.gov (United States)

    Mesev, V.

    2012-07-01

    The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.

  16. Levee Health Monitoring With Radar Remote Sensing

    Science.gov (United States)

    Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.

    2012-12-01

    Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers

  17. Remote Sensing and Imaging Physics

    Science.gov (United States)

    2012-03-07

    Program Manager AFOSR/RSE Air Force Research Laboratory Remote Sensing and Imaging Physics 7 March 2012 Report Documentation Page Form...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Remote Sensing And Imaging Physics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Imaging of Space Objects •Information without Imaging •Predicting the Location of Space Objects • Remote Sensing in Extreme Conditions •Propagation

  18. NODC Standard Format Coastal Ocean Wave and Current (F181) Data from the Atlantic Remote Sensing Land/Ocean Experiment (ARSLOE) (1980) (NODC Accession 0014202)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains time series coastal ocean wave and current data collected during the Atlantic Remote Sensing Land/Ocean Experiment (ARSLOE). ARSLOE was...

  19. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  20. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  1. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  2. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  3. Research Advances in Monitoring Agro-meteorological Disasters Using Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    Xueyan; SUI; Rujuan; WANG; Huimin; YAO; Meng; WANG; Shaokun; LI; Xiaodong; ZHANG

    2014-01-01

    Remote sensing is an important method for rapidly obtaining farmland information. Once meteorological disaster occurs,using the remote sensing technology to extract disaster area of crops and monitor disaster level has great significance for evaluating disasters and making a timely remedy. This paper elaborated the importance of monitoring agro-meteorological disasters using remote sensing in current special historical period,overviewed remote sensing methods both at home and abroad,analyzed existing problems,made clear major problems to be solved in monitoring agro-meteorological disasters using remote sensing,and discussed the development prospect of the remote sensing technology.

  4. Remote sensing fire and fuels in southern California

    Science.gov (United States)

    Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen

    2011-01-01

    Airborne remote sensing at infrared wavelengths has the potential to quantify large-fire properties related to energy release or intensity, residence time, fuel-consumption rate, rate of spread, and soil heating. Remote sensing at a high temporal rate can track fire-line outbreaks and acceleration and spotting ahead of a fire front. Yet infrared imagers and imaging...

  5. Processing and analysis of Global snow cover time series for climate change assessment

    OpenAIRE

    2014-01-01

    Remote sensing data offer the opportunity to detect terrestrial snow cover in high temporal and spatial resolution. Such information is essential for various applications – ranging from small scale predictions of runoff or floods, ground water recharge and hydro power generation to large scale planetary processes connected to climate change. The processing of globally available time series of remote sensing data constitutes a challenging task due to the huge data volume and computational dema...

  6. Real time measurement of transient event emissions of air toxics by tomographic remote sensing in tandem with mobile monitoring

    Science.gov (United States)

    Olaguer, Eduardo P.; Stutz, Jochen; Erickson, Matthew H.; Hurlock, Stephen C.; Cheung, Ross; Tsai, Catalina; Colosimo, Santo F.; Festa, James; Wijesinghe, Asanga; Neish, Bradley S.

    2017-02-01

    During the Benzene and other Toxics Exposure (BEE-TEX) study, a remote sensing network based on long path Differential Optical Absorption Spectroscopy (DOAS) was set up in the Manchester neighborhood beside the Ship Channel of Houston, Texas in order to perform Computer Aided Tomography (CAT) scans of hazardous air pollutants. On 18-19 February 2015, the CAT scan network detected large nocturnal plumes of toluene and xylenes most likely associated with railcar loading and unloading operations at Ship Channel petrochemical facilities. The presence of such plumes during railcar operations was confirmed by a mobile laboratory equipped with a Proton Transfer Reaction-Mass Spectrometer (PTR-MS), which measured transient peaks of toluene and C2-benzenes of 50 ppb and 57 ppb respectively around 4 a.m. LST on 19 February 2015. Plume reconstruction and source attribution were performed using the 4D variational data assimilation technique and a 3D micro-scale forward and adjoint air quality model based on both tomographic and PTR-MS data. Inverse model estimates of fugitive emissions associated with railcar transfer emissions ranged from 2.0 to 8.2 kg/hr for toluene and from 2.2 to 3.5 kg/hr for xylenes in the early morning of 19 February 2015.

  7. 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.

  8. Detecting plant metabolic responses induced by ground shock using hyperspectral remote sensing and physiological contact measurements

    Energy Technology Data Exchange (ETDEWEB)

    Pickles, W.L.; Cater, G.A.

    1996-12-03

    A series of field experiments were done to determine if ground shock could have induced physiological responses in plants and if the level of the response could be observed. The observation techniques were remote sensing techniques and direct contact physiological measurements developed by Carter for detecting pre-visual plant stress. The remote sensing technique was similar to that used by Pickles to detect what appeared to be ground shock induced plant stress above the 1993 Non Proliferation Experiment`s underground chemical explosion. The experiment was designed to provide direct plant physiological measurements and remote sensing ratio images and from the same plants at the same time. The simultaneous direct and remote sensing measurements were done to establish a ground truth dataset to compare to the results of the hyperspectral remote sensing measurements. In addition, the experiment was designed to include data on what was thought to be the most probable interfering effect, dehydration. The experimental design included investigating the relative magnitude of the shock induced stress effects compared to dehydration effects.

  9. Research Progress of Farmland Drought Monitoring and Prediction Based on Multi-Source Remote Sensing Data

    Science.gov (United States)

    Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Raffaele; Pascucci, Simone; Silvesrtro, Paolo Cosmo

    2014-11-01

    Since the Kick-off of the Dragon-3 project Farmland Drought Monitoring and Prediction Based on Multi-source Remote Sensing Data (ID: 10448), our research focuses on three points including 1) the monitoring of key biophysical variables of crop and soil in farmland drought by optical and radar remote sensing data, 2) the risk assessment of farmland drought by time series remote sensing and meteorological data, and 3) the crop loss evaluation under farmland drought mainly based on AquaCrop crop model. Our study area is mainly located in Beijing, and Shaanxi Province (semi-arid region), China. Experiment campaign and data analysis were carried out and some new methods aiming at farmland drought monitoring and prediction were developed, which highlighting the importance of ESA-NRSCC Dragon cooperation.

  10. Advances in Research on Soil Moisture by Microwave Remote Sensing in China

    Institute of Scientific and Technical Information of China (English)

    SONG Dongsheng; ZHAO Kai; GUAN Zhi

    2007-01-01

    Soil moisture is an important factor in global hydrologic circulation and plays a significant role in the research of hydrology, climatology, and agriculture. Microwave remote sensing is less limited by climate and time, and can measure in large scale. With these characteristics, this technique becomes an effective tool to measure soil moisture. Since the 1980s, Chinese researchers have investigated the soil moisture using microwave instruments. The active remote sensors are characteristic of high spatial resolution, thus with launch of a series of satellites, active microwave remote sensing of soil moisture will be emphasized. The passive microwave remote sensing of soil moisture has a long research history, and its retrieval algorithms were developed well, so it is an important tool to retrieve large scale moisture information from satellite data in the future.

  11. Signal processing for remote sensing

    CERN Document Server

    Chen, CH

    2007-01-01

    Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seism

  12. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available (s)) is the data vector for a pixel located at s θ(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba...(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image...

  13. Remote sensing of oil slicks

    Digital Repository Service at National Institute of Oceanography (India)

    Fondekar, S.P.; Rao, L.V.G.

    the drawback of expensive conventional surveying methods. An airborne remote sensing system used for monitoring and surveillance of oil comprises different sensors such as side-looking airborne radar, synthetic aperture radar, infrared/ultraviolet line scanner...

  14. Scale issues in remote sensing

    CERN Document Server

    Weng, Qihao

    2014-01-01

    This book provides up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. The book is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as a supplemental reading for graduate level students.

  15. The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

    Science.gov (United States)

    Chen, Xi; Zhou, Liqing

    2015-12-01

    With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

  16. Laser And Nonlinear Optical Materials For Laser Remote Sensing

    Science.gov (United States)

    Barnes, Norman P.

    2005-01-01

    NASA remote sensing missions involving laser systems and their economic impact are outlined. Potential remote sensing missions include: green house gasses, tropospheric winds, ozone, water vapor, and ice cap thickness. Systems to perform these measurements use lanthanide series lasers and nonlinear devices including second harmonic generators and parametric oscillators. Demands these missions place on the laser and nonlinear optical materials are discussed from a materials point of view. Methods of designing new laser and nonlinear optical materials to meet these demands are presented.

  17. Ten ways remote sensing can contribute to conservation.

    Science.gov (United States)

    Rose, Robert A; Byler, Dirck; Eastman, J Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A; Laporte, Nadine; Leidner, Allison; Leimgruber, Peter; Morisette, Jeffrey; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

    2015-04-01

    In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to

  18. Operational Use of Near Real Time Remote sensing Data at the U.S. National Ice Center (NIC)

    Science.gov (United States)

    Clemente-Colon, P.

    2012-12-01

    The National Ice Center (NIC) is a U.S. Government agency that brings together the Department of Defense - Navy, Department of Commerce - National Oceanic and Atmospheric Administration (NOAA), and the Department of Homeland Security - U.S. Coast Guard (USCG) to support coastal and marine sea ice operations and research in the Polar Regions. The NIC provides specialized strategic and tactical ice analyses to meet the operational needs of the U.S. government and is the only operational ice service in the world that monitors sea ice in both the Arctic, Antarctic regions as well as in other ice infested waters. NIC utilizes multiple sources of near real time satellite and in-situ observations as well as NWP and ocean-sea ice model output to produce sea ice analyses. Key users of NIC products in the Arctic include the Navy submarine force, National Weather Service, USCG and Canadian Coast Guard icebreakers, Military Sealift Command on re-supply missions to Antarctica and Greenland, and NOAA research vessels operating near sea ice cover in both hemispheres as well. Time series of NIC weekly or bi-weekly ice analysis charts, daily marginal ice zone and ice edge routine products, as well as tactical support annotated imagery are generated by expert analysts with wide access to near real time satellite imagery from VIS/IR to passive and active microwave sensors. The status of these satellite data streams and the expected availability of new capabilities in the near future will be discussed.

  19. Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

    Science.gov (United States)

    Kiang, Richard; Adimi, Farida; Kempler, Steven

    2008-01-01

    Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial

  20. Tropical Forest Monitoring in Southeast Asia Using Remotely Sensed Optical Time Series

    DEFF Research Database (Denmark)

    Grogan, Kenneth Joseph

    -scale plantations. In particular, the global demand for natural rubber (Hevea brasiliensis) has been reported as the cause of widespread forest conversion. A critical component of forest conservation strategies, such as Reduced Emission from Deforestation and forest Degradation (REDD+), relies upon the monitoring...... monitoring systems. Thematic objectives of the research focussed on estimating forest loss in Cambodia in the post-2000 era, determining how much of this loss was caused by conversions to natural rubber tree cover, and analysing if there is a link between forest-to-rubber conversion rates and global rubber...... of the forest transition curve. Forest-to-rubber conversions were estimated to be responsible for 20% of total forest clearances, and were more prevalent in the later years. Annual forest-to-rubber conversion rates were found to be highly correlated to global rubber prices at local and national scales. Although...

  1. Tropical Forest Monitoring in Southeast Asia Using Remotely Sensed Optical Time Series

    DEFF Research Database (Denmark)

    Grogan, Kenneth Joseph

    -scale plantations. In particular, the global demand for natural rubber (Hevea brasiliensis) has been reported as the cause of widespread forest conversion. A critical component of forest conservation strategies, such as Reduced Emission from Deforestation and forest Degradation (REDD+), relies upon the monitoring...... global rubber markets can be linked to forest cover change, the effects of land policy in Cambodia, and beyond, have also had a major influence. It remains to be seen if intervention initiatives such as REDD+ can materialise over the coming years to make a meaningful contribution to tropical forest...... conservation....

  2. Long-Term Time Series of Remote Sensing Observations for Development of Regulatory Water Quality Standards

    Science.gov (United States)

    Blonski, Slawomir; Spiering, Bruce A.; Holekamp, Kara L.

    2010-01-01

    Water quality standards in the U.S. consist of: designated uses (the services that a water body provides; e.g., drinking water, aquatic life, harvestable species, recreation) . criteria that define the environmental conditions that must be maintained to support the uses For estuaries and coastal waters in the Gulf of Mexico, there are no numeric (quantitative) criteria to protect designated uses from effects of nutrients. This is largely due to the absence of adequate data that would quantitatively link biological conditions to nutrient concentrations. The Gulf of Mexico Alliance, an organization fostering collaboration between the Gulf States and U.S. Federal agencies, has identified the development of the numeric nutrient criteria as a major step leading to reduction in MODIS Products Figure 6. Map of the Mobile Bay with a yellow patch indicating the Bon Secour Bay area selected in this study for averaging water clarity parameters retrieved from MODIS datasets. nutrient inputs to coastal ecosystems. Nutrient enrichment in estuaries and coastal waters can be quantified based on response variables that measure phytoplankton biomass and water clarity. Long-term, spatially and temporally resolved measurements of chlorophyll a concentration, total concentration of suspended solids, and water clarity are needed to establish reference conditions and to quantify stressor-response relationships.

  3. Photogrammetry - Remote Sensing and Geoinformation

    Science.gov (United States)

    Lazaridou, M. A.; Patmio, E. N.

    2012-07-01

    Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS) is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc), and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers) in the Lab. of Photogrammetry - Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.

  4. Assessment of Watershed Drought Using Remote Sensing

    Science.gov (United States)

    Chataut, S.; Piechota, T.

    2005-12-01

    This paper focuses on drought assessment of the Upper Colorado River Basin (UCRB) using remote sensing. Lee's Ferry discharge data for Colorado river in the UCRB and the various Palmer Drought Indices (PDI) such as Palmer Hydrological Drought Indices (PHDI), Palmer Drought Severity Index (PDSI), and Palmer Z Index (ZINDX) for the five climatic divisions of the UCRB for last 100 years will be analyzed to find out the best climatic division in the UCRB for carrying out the further analysis between the Normalized Difference Vegetation Index (NDVI) obtained from 5 km resolution Advanced Very High Radiometric Radar (AVHRR) data and the various PDI. The multivariate statistical technique called rotated principal component analysis will be carried out in the time series of the NDVI data in order to avoid multicollinearity and to extract the component that significantly explains the variance in the dataset. The corresponding significant principal scores will be correlated with the PDI to derive relationship between the NDVI and PDI. Preliminary analysis has shown that there is significant correlation between the NDVI and the various PDI, which implies that NDVI could be used as an important data source to detect and monitor the drought condition in the UCRB.

  5. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... of the compendium, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state......-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  6. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to add more topics in future editions and to update as necessary, to provide a truly state-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  7. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Badger, Merete

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art ‘guideline’ available for people involved in Remote Sensing...... in Wind Energy....

  8. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Lange, Julia

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

  9. Remote sensing for urban planning

    Science.gov (United States)

    Davis, Bruce A.; Schmidt, Nicholas; Jensen, John R.; Cowen, Dave J.; Halls, Joanne; Narumalani, Sunil; Burgess, Bryan

    1994-01-01

    Utility companies are challenged to provide services to a highly dynamic customer base. With factory closures and shifts in employment becoming a routine occurrence, the utility industry must develop new techniques to maintain records and plan for expected growth. BellSouth Telecommunications, the largest of the Bell telephone companies, currently serves over 13 million residences and 2 million commercial customers. Tracking the movement of customers and scheduling the delivery of service are major tasks for BellSouth that require intensive manpower and sophisticated information management techniques. Through NASA's Commercial Remote Sensing Program Office, BellSouth is investigating the utility of remote sensing and geographic information system techniques to forecast residential development. This paper highlights the initial results of this project, which indicate a high correlation between the U.S. Bureau of Census block group statistics and statistics derived from remote sensing data.

  10. Remote Sensing of Environmental Pollution

    Science.gov (United States)

    North, G. W.

    1971-01-01

    Environmental pollution is a problem of international scope and concern. It can be subdivided into problems relating to water, air, or land pollution. Many of the problems in these three categories lend themselves to study and possible solution by remote sensing. Through the use of remote sensing systems and techniques, it is possible to detect and monitor, and in some cases, identify, measure, and study the effects of various environmental pollutants. As a guide for making decisions regarding the use of remote sensors for pollution studies, a special five-dimensional sensor/applications matrix has been designed. The matrix defines an environmental goal, ranks the various remote sensing objectives in terms of their ability to assist in solving environmental problems, lists the environmental problems, ranks the sensors that can be used for collecting data on each problem, and finally ranks the sensor platform options that are currently available.

  11. Fundamentals of polarimetric remote sensing

    CERN Document Server

    Schott, John R

    2009-01-01

    This text is for those who need an introduction to polarimetric signals to begin working in the field of polarimetric remote sensing, particularly where the contrast between manmade objects and natural backgrounds are the subjects of interest. The book takes a systems approach to the physical processes involved with formation, collection, and analysis of polarimetric remote sensing data in the visible through longwave infrared. Beginning with a brief review of the polarized nature of electromagnetic energy and radiometry, Dr. Schott then introduces ways to characterize a beam of polarized ene

  12. Advances in Remote Sensing of Flooding

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2015-11-01

    Full Text Available With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS-based urban flood vulnerability and risk maps.

  13. Using remotely-sensed data for optimal field sampling

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-09-01

    Full Text Available to carry out a fieldwork sample is an important issue as it avoids subjective judgement and can save on time and costs in the field. STATISTICAL SAMPLING, USING DATA OBTAINED FROM REMOTE SENSING, FINDS APPLICATION IN A VARIETY OF FIELDS... M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical...

  14. An Ecophysiological Model for Remote Sensing of GPP

    Science.gov (United States)

    Tu, K. P.

    2010-12-01

    Remote sensing light use efficiency (LUE) models of terrestrial gross primary productivity (GPP) are currently limited by three main problems: 1) the ability to distinguish light absorption by the photosynthetically-active (FAPAR) and the non-photosynthetically active (FIPAR) portions of the canopy, 2) the spatial and temporal variation of the maximum LUE within and across biomes, and 3) parameterization of temperature and moisture scalars for different vegetation types. We address these three issues by 1) using the Enhanced Vegetation Index (EVI) or Soil-Adjusted Vegetation Index (SAVI) to estimate light absorption by the photosynthetically active fraction of the canopy (FAPAR), as opposed to using NDVI which appears to be sensitive to the non-photosynthetically active fraction and is therefore more indicative of the total canopy light interception (FIPAR), 2) estimating the maximum unstressed LUE based on the maximum quantum yield of photosynthesis, a physiological and well-constrained parameter, and 3) inferring seasonal variation in temperature and moisture stress using the phenological information in FAPAR time series, with a unique temperature optimum (Topt) determined for each pixel and moisture stress estimated from relative changes in FAPAR. In this approach, the model can be applied entirely with remote sensing observations of EVI (or EVI2 or SAVI), air temperature (Tair), and incident photosynthetically-active radiation (PAR). Aside from improved parameterization of stress functions based entirely on remote sensing observations, this approach is similar to previous LUE models based on the quantum yield of photosynthesis. However, it differs in that we incorporate recent evidence indicating that the time-averaged quantum yield is roughly one-half that of the instantaneous maximum quantum yield. This translates to time-averaged rates of GPP being roughly one-half the maximum instantaneous rates or GPPmean=GPPmax/2, consistent with studies showing strong

  15. Remote sensing in soil science.

    NARCIS (Netherlands)

    Mulders, M.A.

    1987-01-01

    This book provides coverage of remote sensing techniques and their application in soil science. A clear, step-by-step approach to the various aspects ensures that the reader will gain a good grasp of the subject so that he can apply the techniques to his own field of study. The book opens with an in

  16. [Review of change detection methods using multi-temporal remotely sensed images].

    Science.gov (United States)

    Yin, Shou-Jing; Wu, Chuan-Qing; Wang, Qiao; Ma, Wan-Dong; Zhu, Li; Yao, Yan-Juan; Wang, Xue-Lei; Wu, Di

    2013-12-01

    With the development of platforms and sensors, continuous repetition of remote sensing observation of the earth surface has been realized, and a mass of multi-source, multi-scale, multi-resolution remote sensing data has been accumulated. Those images have detailedly recorded the changing process of ground objects on the earth, which makes the long term global change research, such as change detection, based on remote sensing become possible, and greatly push forward the research on image processing and application. Although plenty of successful research has been reported, there are still enormous challenges in multi-temporal imagery change detection. A relatively complete mature theoretical system has not formed, and there is still a lack of systematic summary of research progress. Firstly, the current progress in change detection methods using multi-temporal remotely sensed imagery has been reviewed in this paper. Then, the methods are classified into three categories and summarized according to the type and amount of the input data, single-phase post-classification comparison, two-phase comparison, and time series analysis. After that, the possible existing problems in the current development of multi-temporal change detection are analyzed, and the development trend is discussed finally.

  17. Comparison of various remote sensing snow products in a distributed hydrological model

    Science.gov (United States)

    Berezowski, Tomasz; Chormański, Jarosław; Batelaan, Okke

    2014-05-01

    With the development of remote sensing, more and more data series with spatially distributed snow cover become available. These data can be obtained for free, from many sources varying in spatial and temporal resolution, the length of the time series and the method of acquisition (VIS-NIR or microwave sensors). A popular use of remotely sensed snow distribution data is in hydrological modelling. However, a suitability test of different remote sensing snow products for hydrological models was so far not conducted. In this work, some of the most common remote sensing snow products (MOD10A1, IMS , GLOBSNOW and AMSR-E_DySno) are used as input data in the WetSpa distributed hydrological model. Each of the snow products has different properties and is based on different algorithms, which makes the analysis interesting and multidimensional. The area of research is the Biebrza River catchment - located in north-eastern Poland, comprising approximately 7000 km2. Biebrza is a natural river with a snow melt regime, making it very suitable for this kind of analysis. In total 6 modelling scenarios were conducted (4 with remote sensing data, 1 standard approach - temperature threshold for snow accumulation and melting, 1 based on snow data from meteorological stations). Each model was calibrated against discharge with the Shuffled Complex Evolution (SCE) algorithm. The calibration was repeated three times for each model to make sure that the global optimum was found. The calibration and validation periods were both 3 years long. The next stage was a comparison with the GLUE uncertainty analysis for each of the models, on a shorter, one-year period. The best model in terms of Nash-Sutcliffe efficiency and r2 was using the MOD10A1 data; however, the models using GLOBSNOW SWE and the standard approach received similar scores. In terms of the model bias the best results were obtained for the IMS and MOD10A1 data. Nevertheless, the lowest root mean square error was found for the

  18. Remote Sensing Best Paper Award 2013

    OpenAIRE

    Prasad Thenkabail

    2013-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for 2013. Nominations were selected by the Editor-in-Chief and selected editorial board members from among all the papers published in 2009. Reviews and research papers were evaluated separately.

  19. Fractals and Spatial Methods for Mining Remote Sensing Imagery

    Science.gov (United States)

    Lam, Nina; Emerson, Charles; Quattrochi, Dale

    2003-01-01

    The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of

  20. 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

  1. Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

    Science.gov (United States)

    Ellison, Luke; Ichoku, Charles

    2012-01-01

    A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

  2. Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Zhaoqin Li

    2014-11-01

    Full Text Available Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1 scale issue; (2 transportability issue; (3 data availability; and (4 uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

  3. Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

    Science.gov (United States)

    Li, Zhaoqin; Xu, Dandan; Guo, Xulin

    2014-11-07

    Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

  4. APPLICATION OF REMOTE SENSING TECHNOLOGY TO POPULATION ESTIMATION

    Institute of Scientific and Technical Information of China (English)

    ZHANG Bao-guang

    2003-01-01

    This paper attempts to explore a new avenue of urban small-regional population estimation by remote sensing technology, creatively and comprehensively for the first time using a residence count method, area (density) method and model method, incorporating the application experience of American scholars in the light of the state of our country. Firstly, the author proposes theoretical basis for population estimation by remote sensing, on the basis of analysing and evaluating the history and state quo of application of methods of population estimation by remote sens-ing. Secondly, two original types of mathematical models of population estimation are developed on the basis of remote sensing data, taking Tianjin City as an example. By both of the mathematical models the regional population may be estimated from remote sensing variable values with high accuracy. The number of the independent variables in the lat-ter model is somewhat smaller and the collection of remote sensing data is somewhat easier, but the deviation is a little larger. Finally, some viewpoints on the principled problems about the practical application of remote sensing to popu-lation estimation are put forward.

  5. Remote-Sensing and Automated Water Resources Tracking: Near Real-Time Decision Support for Water Managers Facing Drought and Flood

    Science.gov (United States)

    Reiter, M. E.; Elliott, N.; Veloz, S.; Love, F.; Moody, D.; Hickey, C.; Fitzgibbon, M.; Reynolds, M.; Esralew, R.

    2016-12-01

    Innovative approaches for tracking the Earth's natural resources, especially water which is essential for all living things, are essential during a time of rapid environmental change. The Central Valley is a nexus for water resources in California, draining the Sacramento and San Joaquin River watersheds. The distribution of water throughout California and the Central Valley, while dynamic, is highly managed through an extensive regional network of canals, levees, and pumps. Water allocation and delivery is determined through a complex set of rules based on water contracts, historic priority, and other California water policies. Furthermore, urban centers, agriculture, and the environment throughout the state are already competing for water, particularly during drought. Competition for water is likely to intensify as California is projected to experience continued increases in demand due to population growth and more arid growing conditions, while also having reduced or modified water supply due to climate change. As a result, it is difficult to understand or predict how water will be used to fulfill wildlife and wetland conservation needs. A better understanding of the spatial distribution of water in near real-time can facilitate adaptation of water resource management to changing conditions on the landscape, both over the near- and long-term. The Landsat satellite mission delivers imagery every 16-days from nearly every place on the earth at a high spatial resolution. We have integrated remote sensing of satellite data, classification modeling, bioinformatics, optimization, and ecological analyses to develop an automated near real-time water resources tracking and decision-support system for the Central Valley of California. Our innovative system has applications for coordinated water management in the Central Valley to support people, places, and wildlife and is being used to understand the factors that drive variation in the distribution and abundance of water

  6. Filtering remotely sensed chlorophyll concentrations in the Red Sea using a space-time covariance model and a Kalman filter

    KAUST Repository

    Dreano, Denis

    2015-04-27

    A statistical model is proposed to filter satellite-derived chlorophyll concentration from the Red Sea, and to predict future chlorophyll concentrations. The seasonal trend is first estimated after filling missing chlorophyll data using an Empirical Orthogonal Function (EOF)-based algorithm (Data Interpolation EOF). The anomalies are then modeled as a stationary Gaussian process. A method proposed by Gneiting (2002) is used to construct positive-definite space-time covariance models for this process. After choosing an appropriate statistical model and identifying its parameters, Kriging is applied in the space-time domain to make a one step ahead prediction of the anomalies. The latter serves as the prediction model of a reduced-order Kalman filter, which is applied to assimilate and predict future chlorophyll concentrations. The proposed method decreases the root mean square (RMS) prediction error by about 11% compared with the seasonal average.

  7. Remote Sensing of the Night-time Lower Ionosphere from Lightning Generated Sferics Recorded in the South Pacific Region

    Science.gov (United States)

    Sushil, K.; Ramachandran, V.

    The lightning generated Extremely Low Frequency ELF and Very Low Frequency VLF radio signals tweeks recorded using the lightning detection system under Word Wide Lightning Location WWLL Network at Suva 18 2 o S 178 3 o E Fiji a low latitude ground wave station in the South Pacific region are used to determine the lower ionospheric electron content and its variation during night-time Due to its least relative inaccessibility the lower ionosphere consisting of D-region is among the least studied regions of the Earth s atmosphere The lightning generated sferics which are short pulses typically of 1-10 ms with significant spectral contents over the ELF VLF can be used in the study of the lower ionosphere A total of 400 tweeks recoded in the time period of 1800-0600 hrs FST during 2003- 2004 have been analysed Matlab codes are used to analyse the data files recorded using lightning software and each of data file is of 11 MB with one minute duration The value of ionospheric reflecting height h calculated using waveguide mode theory of electromagnetic wave propagation in the spherical cell Earth-ionosphere waveguide having perfectly conducting boundaries is found to vary from 80-95 km in the night-time To estimate the electron density at the ionospheric reflection heights i e lower ionosphere we perform a qualitative analysis based on the propagation theory of radio waves in an infinite collisionless anisotropic ionospheric plasma Shvets and Hayakawa J Atmos Sol -Terr Phys 60 461

  8. Monitoring desertification around Huolinguole using multitemporal remotely sensed imagery

    Science.gov (United States)

    Wang, Guangjun; Fu, Meichen; Xiao, Qiuping; Wang, Zeng

    2010-11-01

    Because of the capability of remote sensing to acquire synoptic coverage and repetitive data acquisition it has become a widely used technique for monitoring the effects of human activity on terrestrial ecosystems. This paper presents the spatial extent, magnitude and temporal behavior of land desertification around Holinguole caused by city expansion. The selected test area, Huoliguole City, is a typical grassland city in China that is located in the northeast of China. A time-series of Landsat TM images covering a period of 20 years (1987-2006) were used. The data sets were geometrically and radiometrically pre-processed in a rigorous fashion, followed by a linear spectral mixture unmixing model to extract feature images of vegetation and sandy soil. The biomass images were derived using a polynomial regression model based on the ground-based observations of the amount of grass and a vegetation index based on satellite remote sensing. By combing the vegetation fraction images, the sandy soil fraction images, biomass images, and PC (principal components) images, the grassland desertification information around the built-up area of the city was extracted based on BP (Back-Propagation) neural network algorithm. The results of our studies indicate significant expansion of the city over the last 20 years, and a similar trend was also observed in the temporal magnitude behavior of severe grassland desertification away from the city.

  9. OPTIMAL WAVELET FILTER DESIGN FOR REMOTE SENSING IMAGE COMPRESSION

    Institute of Scientific and Technical Information of China (English)

    Yang Guoan; Zheng Nanning; Guo Shugang

    2007-01-01

    A new approach for designing the Biorthogonal Wavelet Filter Bank (BWFB) for the purpose of image compression is presented in this letter. The approach is decomposed into two steps.First, an optimal filter bank is designed in theoretical sense based on Vaidyanathan's coding gain criterion in SubBand Coding (SBC) system. Then the above filter bank is optimized based on the criterion of Peak Signal-to-Noise Ratio (PSNR) in JPEG2000 image compression system, resulting in a BWFB in practical application sense. With the approach, a series of BWFB for a specific class of applications related to image compression, such as remote sensing images, can be fast designed. Here,new 5/3 BWFB and 9/7 BWFB are presented based on the above approach for the remote sensing image compression applications. Experiments show that the two filter banks are equally performed with respect to CDF 9/7 and LT 5/3 filter in JPEG2000 standard; at the same time, the coefficients and the lifting parameters of the lifting scheme are all rational, which bring the computational advantage, and the ease for VLSI implementation.

  10. Modeling Global Urbanization Supported by Nighttime Light Remote Sensing

    Science.gov (United States)

    Zhou, Y.

    2015-12-01

    Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering carbon cycling and climate. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the nighttime light remote sensing data, extended this method to the global domain by developing a computational method (parameterization) to estimate the key parameters in the cluster-based method, and built a consistent 20-year global urban map series to evaluate the time-reactive nature of global urbanization (e.g. 2000 in Fig. 1). Supported by urban maps derived from nightlights remote sensing data and socio-economic drivers, we developed an integrated modeling framework to project future urban expansion by integrating a top-down macro-scale statistical model with a bottom-up urban growth model. With the models calibrated and validated using historical data, we explored urban growth at the grid level (1-km) over the next two decades under a number of socio-economic scenarios. The derived spatiotemporal information of historical and potential future urbanization will be of great value with practical implications for developing adaptation and risk management measures for urban infrastructure, transportation, energy, and water systems when considered together with other factors such as climate variability and change, and high impact weather events.

  11. A surge of the glaciers Skobreen–Paulabreen, Svalbard, observed by time-lapse photographs and remote sensing data

    Directory of Open Access Journals (Sweden)

    Lene Kristensen

    2012-11-01

    Full Text Available We present observations of a surge of the glaciers Skobreen–Paulabreen, Svalbard, during 2003–05, including a time-lapse movie of the frontal advance during 2005, Advanced Spaceborne Thermal Emission (ASTER imagery and oblique aerial photographs. The surge initiated in Skobreen, and then propagated downglacier into the lower parts of Paulabreen. ASTER satellite images from different stages of the surge are used to evaluate the surge progression. Features on the glacier surface advanced 2800 m over 2.4 yr, averaging 3.2 m/day, while the front advanced less (ca. 1300 m due to contemporaneous calving. The surge resulted in a lateral displacement of the medial moraines of Paulabreen of ca. 600 m at the glacier front. The time-lapse movie captured the advance of the frontal part of the glacier, and dramatically illustrates glacier dynamic processes in an accessible way. The movie documents a range of processes such as a plug-like flow of the glacier, proglacial thrusting, incorporation of old, dead ice at the margin, and calving into the fjord. The movie provides a useful resource for researchers, educators seeking to teach and inspire students, and those wishing to communicate the fascination of glacier science to a wider public.

  12. NEON Airborne Remote Sensing of Terrestrial Ecosystems

    Science.gov (United States)

    Kampe, T. U.; Leisso, N.; Krause, K.; Karpowicz, B. M.

    2012-12-01

    The National Ecological Observatory Network (NEON) is the continental-scale research platform that will collect information on ecosystems across the United States to advance our understanding and ability to forecast environmental change at the continental scale. One of NEON's observing systems, the Airborne Observation Platform (AOP), will fly an instrument suite consisting of a high-fidelity visible-to-shortwave infrared imaging spectrometer, a full waveform small footprint LiDAR, and a high-resolution digital camera on a low-altitude aircraft platform. NEON AOP is focused on acquiring data on several terrestrial Essential Climate Variables including bioclimate, biodiversity, biogeochemistry, and land use products. These variables are collected throughout a network of 60 sites across the Continental United States, Alaska, Hawaii and Puerto Rico via ground-based and airborne measurements. Airborne remote sensing plays a critical role by providing measurements at the scale of individual shrubs and larger plants over hundreds of square kilometers. The NEON AOP plays the role of bridging the spatial scales from that of individual organisms and stands to the scale of satellite-based remote sensing. NEON is building 3 airborne systems to facilitate the routine coverage of NEON sites and provide the capacity to respond to investigator requests for specific projects. The first NEON imaging spectrometer, a next-generation VSWIR instrument, was recently delivered to NEON by JPL. This instrument has been integrated with a small-footprint waveform LiDAR on the first NEON airborne platform (AOP-1). A series of AOP-1 test flights were conducted during the first year of NEON's construction phase. The goal of these flights was to test out instrument functionality and performance, exercise remote sensing collection protocols, and provide provisional data for algorithm and data product validation. These test flights focused the following questions: What is the optimal remote

  13. Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve, India using remote sensing and GIS.

    Science.gov (United States)

    Saranya, K R L; Reddy, C Sudhakar; Rao, P V V Prasada; Jha, C S

    2014-05-01

    Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.

  14. Remote sensing and water resources

    CERN Document Server

    Champollion, N; Benveniste, J; Chen, J

    2016-01-01

    This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives. Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of th...

  15. Sensitivity analysis in remote sensing

    CERN Document Server

    Ustinov, Eugene A

    2015-01-01

    This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...

  16. Remote sensing of natural resources

    CERN Document Server

    Wang, Guangxing

    2013-01-01

    "… a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. … state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources."-Yuhong He, University of Toronto Mississauga, Ontario, Canada"The list of topics covered is so complete that I would recommend the book to anyone teaching a graduate course on vegetation analysis through digital image analysis. … I recommend this book then for anyone doing advanced digital image analysis and environmental GIS courses who want to cover topics related to applied remote sensing work involving vegetation analysis."-Charles Roberts, Florida Atlantic University, Boca Raton, USA, in Economic Bota...

  17. Hyperspectral remote sensing tools for quantifying plant litter and invasive species in arid ecosystems

    Science.gov (United States)

    Nagler, Pamela L.; Sridhar, B.B. Maruthi; Olsson, Aaryn Dyami; Glenn, Edward P.; van Leeuwen, Willem J.D.; Thenkabail, Prasad S.; Huete, Alfredo; Lyon, John G.

    2012-01-01

    Green vegetation can be distinguished using visible and infrared multi-band and hyperspectral remote sensing methods. The problem has been in identifying and distinguishing the non-photosynthetically active radiation (PAR) landscape components, such as litter and soils, and from green vegetation. Additionally, distinguishing different species of green vegetation is challenging using the relatively few bands available on most satellite sensors. This chapter focuses on hyperspectral remote sensing characteristics that aim to distinguish between green vegetation, soil, and litter (or senescent vegetation). Quantifying litter by remote sensing methods is important in constructing carbon budgets of natural and agricultural ecosystems. Distinguishing between plant types is important in tracking the spread of invasive species. Green leaves of different species usually have similar spectra, making it difficult to distinguish between species. However, in this chapter we show that phenological differences between species can be used to detect some invasive species by their distinct patterns of greening and dormancy over an annual cycle based on hyperspectral data. Both applications require methods to quantify the non-green cellulosic fractions of plant tissues by remote sensing even in the presence of soil and green plant cover. We explore these methods and offer three case studies. The first concerns distinguishing surface litter from soil using the Cellulose Absorption Index (CAI), as applied to no-till farming practices where plant litter is left on the soil after harvest. The second involves using different band combinations to distinguish invasive saltcedar from agricultural and native riparian plants on the Lower Colorado River. The third illustrates the use of the CAI and NDVI in time-series analyses to distinguish between invasive buffelgrass and native plants in a desert environment in Arizona. Together the results show how hyperspectral imagery can be applied to

  18. Application of Remote Sensing Data in a Distributed Hydrological Model for the Gambia River Basin

    Science.gov (United States)

    Stisen, S.; Sandholt, I.; Jensen, K. H.

    2003-12-01

    Distributed hydrological models have an extensive demand of high resolution spatial and temporal data for driving and validating the models. Most of the variables are only available as point measurements which impose serious constraints to the applicability and the credibility of such models particularly for large regional scales and in areas where the availability and quality of hydrological data are limited. Remote sensing information appears to offer useful data that not only can fill some of the gaps in data availability but also can supply data at the appropriate scale for distributed hydrological models. In this study we tested three types of remote sensing derived variables in a distributed hydrological model of the 42,000 km2 Gambia River Basin in West Africa: (1) potential evapotranspiration estimated by the Makkink equation and based on daily global radiation fields derived from the geostationary meteorological satellite Meteosat, (2) leaf area index (LAI) based on data from the MODIS satellite, and (3) Temperature Vegetation Dryness Index (TVDI) derived form NOAA AVHRR images. The remote sensing derived time series of potential evapotranspiration and LAI were used as input to the model while TVDI was used for validating the spatial simulations of soil moisture. The effects of introducing remote sensing based input were evaluated for both discharge simulations and spatial outputs by comparing the model simulations to those based on traditional data. Application of remote sensing based input of potential evapotranspiration and LAI had in both cases little effects on the simulated discharges while some effects were seen on the spatial and temporal variation of variables like actual evapotranspiration and soil moisture. Improved spatial simulations of these variables may potentially allow for better design of e.g. irrigation schemes. The comparative analysis of TVDI estimates and spatial model simulations of soil moisture content in the root zone was however

  19. Remote Sensing Information Science Research

    Science.gov (United States)

    Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin

    2002-01-01

    This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

  20. Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time

    NARCIS (Netherlands)

    Sutanudjaja, E.H.; De Jong, S.M.; Van Geer, F.C.; Bierkens, M.F.P.

    2013-01-01

    The study presented in this paper is to investigate the possibility of using spaceborne remote sensing data for groundwater head prediction. Remotely-sensed soil moisture time series of SWI (Soil Water Index) derived from ERS (European Remote Sensing) scatterometers are used to predict groundwater

  1. Using ERS spaceborne microwave soil moisture observations to predict groundwater heads in space and time

    NARCIS (Netherlands)

    Sutanudjaja, E.H.; Jong, S.M. de; Bierkens, M.F.P.; Geer, F.C. van

    2013-01-01

    The study presented in this paper is to investigate the possibility of using spaceborne remote sensing data for groundwater head prediction. Remotely-sensed soil moisture time series of SWI (Soil Water Index) derived from ERS (European Remote Sensing) scatterometers are used to predict groundwater

  2. Remote sensing for wind energy

    Energy Technology Data Exchange (ETDEWEB)

    Pena, A.; Bay Hasager, C.; Lange, J. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark) (and others

    2013-06-15

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risoe) during the first PhD Summer School: Remote Sensing in Wind Energy. Thus it is closely linked to the PhD Summer Schools where state-of-the-art is presented during the lecture sessions. The advantage of the report is to supplement with in-depth, article style information. Thus we strive to provide link from the lectures, field demonstrations, and hands-on exercises to theory. The report will allow alumni to trace back details after the course and benefit from the collection of information. This is the third edition of the report (first externally available), after very successful and demanded first two, and we warmly acknowledge all the contributing authors for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art 'guideline' available for people involved in Remote Sensing in Wind Energy. (Author)

  3. An overview of GNSS remote sensing

    Science.gov (United States)

    Yu, Kegen; Rizos, Chris; Burrage, Derek; Dempster, Andrew G.; Zhang, Kefei; Markgraf, Markus

    2014-12-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters.

  4. 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.

  5. Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

    Science.gov (United States)

    Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

    2013-01-01

    Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

  6. Sensing our Environment: Remote sensing in a physics classroom

    Science.gov (United States)

    Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

    2017-04-01

    Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora

  7. Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics

    Directory of Open Access Journals (Sweden)

    Prasad S. Thenkabail

    2009-04-01

    Full Text Available The goal of this research was to compare the remote-sensing derived irrigated areas with census-derived statistics reported in the national system. India, which has nearly 30% of global annualized irrigated areas (AIAs, and is the leading irrigated area country in the World, along with China, was chosen for the study. Irrigated areas were derived for nominal year 2000 using time-series remote sensing at two spatial resolutions: (a 10-km Advanced Very High Resolution Radiometer (AVHRR and (b 500-m Moderate Resolution Imaging Spectroradiometer (MODIS. These areas were compared with the Indian National Statistical Data on irrigated areas reported by the: (a Directorate of Economics and Statistics (DES of the Ministry of Agriculture (MOA, and (b Ministry of Water Resources (MoWR. A state-by-state comparison of remote sensing derived irrigated areas when compared with MoWR derived irrigation potential utilized (IPU, an equivalent of AIA, provided a high degree of correlation with R2 values of: (a 0.79 with 10-km, and (b 0.85 with MODIS 500-m. However, the remote sensing derived irrigated area estimates for India were consistently higher than the irrigated areas reported by the national statistics. The remote sensing derived total area available for irrigation (TAAI, which does not consider intensity of irrigation, was 101 million hectares (Mha using 10-km and 113 Mha using 500-m. The AIAs, which considers intensity of irrigation, was 132 Mha using 10-km and 146 Mha using 500-m. In contrast the IPU, an equivalent of AIAs, as reported by MoWR was 83 Mha. There are “large variations” in irrigated area statistics reported, even between two ministries (e.g., Directorate of Statistics of Ministry of Agriculture and Ministry of Water Resources of the same national system. The causes include: (a reluctance on part of the states to furnish irrigated area data in view of their vested interests in sharing of water, and (b reporting of large volumes of data

  8. China national space remote sensing infrastructure and its application

    Science.gov (United States)

    Li, Ming

    2016-07-01

    Space Infrastructure is a space system that provides communication, navigation and remote sensing service for broad users. China National Space Remote Sensing Infrastructure includes remote sensing satellites, ground system and related systems. According to the principle of multiple-function on one satellite, multiple satellites in one constellation and collaboration between constellations, series of land observation, ocean observation and atmosphere observation satellites have been suggested to have high, middle and low resolution and fly on different orbits and with different means of payloads to achieve a high ability for global synthetically observation. With such an infrastructure, we can carry out the research on climate change, geophysics global surveying and mapping, water resources management, safety and emergency management, and so on. I This paper gives a detailed introduction about the planning of this infrastructure and its application in different area, especially the international cooperation potential in the so called One Belt and One Road space information corridor.

  9. Investigating a Quadrant Surface Coil Array for NQR Remote Sensing

    Science.gov (United States)

    2014-10-23

    2006 IEEE James E. Burke received a Bachelors of Science degree in electrical engineering, Florida International University, Miami, Florida...Resonance) remote sensing. In this paper, each of four surface coils will be parallel tuned and series matched with common electrical components to

  10. A global evaluation of harmonic analysis of time series under distrinct gap conditions

    NARCIS (Netherlands)

    Zhou, J.; Hu, G.; Menenti, M.

    2013-01-01

    Reconstruction of time series of satellite image data to obtain continuous, consistent and accurate data for downstream applications is playing a crucial role in remote sensing applications such as vegetation dynamics, land cover changes, land-atmosphere interactions and climate changes. Among the n

  11. Multi-resolution time series imagery for forest disturbance and regrowth monitoring in Queensland, Australia

    NARCIS (Netherlands)

    Schmidt, M.; Lucas, R.; Bunting, P.; Verbesselt, J.; Armston, J.

    2015-01-01

    High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011) with an 8-day interval of a 30 m spatial resolution data was generated by the use of

  12. A comparison of time series similarity measures for classification and change detection of ecosystem dynamics

    NARCIS (Netherlands)

    Lhermitte, S.; Verbesselt, J.; Verstraeten, W.W.; Coppin, P.

    2011-01-01

    Time series of remote sensing imagery or derived vegetation indices and biophysical products have been shown particularly useful to characterize land ecosystem dynamics. Various methods have been developed based on temporal trajectory analysis to characterize, classify and detect changes in ecosyste

  13. Biogeochemical cycling and remote sensing

    Science.gov (United States)

    Peterson, D. L.

    1985-01-01

    Research is underway at the NASA Ames Research Center that is concerned with aspects of the nitrogen cycle in terrestrial ecosystems. An interdisciplinary research group is attempting to correlate nitrogen transformations, processes, and productivity with variables that can be remotely sensed. Recent NASA and other publications concerning biogeochemical cycling at global scales identify attributes of vegetation that could be related or explain the spatial variation in biologically functional variables. These functional variables include net primary productivity, annual nitrogen mineralization, and possibly the emission rate of nitrous oxide from soils.

  14. Remote Sensing Open Access Journal: Increasing Impact through Quality Publications

    Directory of Open Access Journals (Sweden)

    Prasad S. Thenkabail

    2014-08-01

    Full Text Available Remote Sensing, an open access journal (http://www.mdpi.com/journal/remotesensing has grown at rapid pace since its first publication five years ago, and has acquired a strong reputation. It is a “pathfinder” being the first open access journal in remote sensing. For those academics who were used to waiting a year or two for their peer-reviewed scientific work to be reviewed, revised, edited, and published, Remote Sensing offers a publication time frame that is unheard of (in most cases, less than four months. However, we do this after multiple peer-reviews, multiple revisions, much editorial scrutiny and decision-making, and professional editing by an editorial office before a paper is published online in our tight time frame, bringing a paradigm shift in scientific publication. As a result, there has been a swift increase in submissions of higher and higher quality manuscripts from the best authors and institutes working on Remote Sensing, Geographic Information Systems (GIS, Global Navigation Satellite System (GNSS, GIScience, and all related geospatial science and technologies from around the world. The purpose of this editorial is to update everyone interested in Remote Sensing on the progress made over the last year, and provide an outline of our vision for the immediate future. [...

  15. Remote Sensing and Reflectance Profiling in Entomology.

    Science.gov (United States)

    Nansen, Christian; Elliott, Norman

    2016-01-01

    Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

  16. Introductory remote sensing principles and concepts principles and concepts

    CERN Document Server

    Gibson, Paul

    2013-01-01

    Introduction to Remote Sensing Principles and Concepts provides a comprehensive student introduction to both the theory and application of remote sensing. This textbook* introduces the field of remote sensing and traces its historical development and evolution* presents detailed explanations of core remote sensing principles and concepts providing the theory required for a clear understanding of remotely sensed images.* describes important remote sensing platforms - including Landsat, SPOT and NOAA * examines and illustrates many of the applications of remotely sensed images in various fields.

  17. LWIR Microgrid Polarimeter for Remote Sensing Studies

    Science.gov (United States)

    2010-02-28

    Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo

  18. Basic Remote Sensing Investigations for Beach Reconnaissance.

    Science.gov (United States)

    Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in

  19. Preface: Remote Sensing in Coastal Environments

    OpenAIRE

    Deepak R. Mishra; Gould, Richard W.

    2016-01-01

    The Special Issue (SI) on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology i...

  20. Data Quality in Remote Sensing

    Science.gov (United States)

    Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.

    2017-09-01

    The issue of data quality (DQ) is of growing importance in Remote Sensing (RS), due to the widespread use of digital services (incl. apps) that exploit remote sensing data. In this position paper a body of experts from the ISPRS Intercommission working group III/IVb "DQ" identifies, categorises and reasons about issues that are considered as crucial for a RS research and application agenda. This ISPRS initiative ensures to build on earlier work by other organisations such as IEEE, CEOS or GEO, in particular on the meritorious work of the Quality Assurance Framework for Earth Observation (QA4EO) which was established and endorsed by the Committee on Earth Observation Satellites (CEOS) but aims to broaden the view by including experts from computer science and particularly database science. The main activities and outcomes include: providing a taxonomy of DQ dimensions in the RS domain, achieving a global approach to DQ for heterogeneous-format RS data sets, investigate DQ dimensions in use, conceive a methodology for managing cost effective solutions on DQ in RS initiatives, and to address future challenges on RS DQ dimensions arising in the new era of the big Earth data.

  1. Use of remote sensing in agriculture

    Science.gov (United States)

    Pettry, D. E.; Powell, N. L.; Newhouse, M. E.

    1974-01-01

    Remote sensing studies in Virginia and Chesapeake Bay areas to investigate soil and plant conditions via remote sensing technology are reported ant the results given. Remote sensing techniques and interactions are also discussed. Specific studies on the effects of soil moisture and organic matter on energy reflection of extensively occurring Sassafras soils are discussed. Greenhouse and field studies investigating the effects of chlorophyll content of Irish potatoes on infrared reflection are presented. Selected ground truth and environmental monitoring data are shown in summary form. Practical demonstrations of remote sensing technology in agriculture are depicted and future use areas are delineated.

  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. Remote sensing and characterization of anomalous debris

    Science.gov (United States)

    Sridharan, R.; Beavers, W.; Lambour, R.; Gaposchkin, E. M.; Kansky, J.; Stansbery, E.

    1997-01-01

    The analysis of orbital debris data shows a band of anomalously high debris concentration in the altitude range between 800 and 1000 km. Analysis indicates that the origin is the leaking coolant fluid from nuclear power sources that powered a now defunct Soviet space-based series of ocean surveillance satellites. A project carried out to detect, track and characterize a sample of the anomalous debris is reported. The nature of the size and shape of the sample set, and the possibility of inferring the composition of the droplets were assessed. The technique used to detect, track and characterize the sample set is described and the results of the characterization analysis are presented. It is concluded that the nature of the debris is consistent with leaked Na-K fluid, although this cannot be proved with the remote sensing techniques used.

  4. Microwave Remote Sensing: Needs and Requirements Concerning Technology

    DEFF Research Database (Denmark)

    Skou, Niels

    2003-01-01

    Spaceborne microwave remote sensing instruments, like the imaging radiometer and the synthetic aperture radar, are over timed faced with two partly conflicting requirements: performance expectations (resolutions, sensitivity, coverage) steadily increase with resource allocations (weight, power, b......, bulk, cost) decrease. This results in needs and requirements to the development of advanced technology thus enabling the future advanced systems to be viable and realistic.......Spaceborne microwave remote sensing instruments, like the imaging radiometer and the synthetic aperture radar, are over timed faced with two partly conflicting requirements: performance expectations (resolutions, sensitivity, coverage) steadily increase with resource allocations (weight, power...

  5. Assessment of biochemical concentrations of vegetation using remote sensing technology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The main biochemicals (such as lignin, protein, cellulose, sugar, starch, chlorophyll and water) of vegetation are directly or indirectly involved in major ecological processes, such as the functions of terrestrial ecosystems (i.e., nutrient-cycling processes, primary production, and decomposition). Remote sensing techniques provide a very convenient way of data acquisition capable of covering a large area several times during one season, so it can play a unique and essential role provided that we can relate remote sensing measurements to the biochemical characteristics of the Earth surface in a reliable and operational way. The application of remote sensing techniques for the estimation of canopy biochemicals was reviewed. Three methods of estimating biochemical concentrations of vegetation were included in this paper: index, stepwise multiple linear regression, and stepwise multiple linear regression based on a model of the forest crown. In addition, the vitality and potential applying value are stressed.

  6. Remote Sensing Image Deblurring Based on Grid Computation

    Institute of Scientific and Technical Information of China (English)

    LI Sheng-yang; ZHU Chong-guang; GE Ping-ju

    2006-01-01

    In general, there is a demand for real-time processing of mass quantity remote sensing images. However, the task is not only data-intensive but also computating-intensive. Distributed processing is a hot topic in remote sensing processing and image deblurring is also one of the most important needs. In order to satisfy the demand for quick processing and deblurring of mass quantity satellite images, we developed a distributed, grid computation-based platform as well as a corresponding middleware for grid computation. Both a constrained power spectrum equalization algorithm and effective block processing measures, which can avoid boundary effect, were applied during the processing. The result is satisfactory since computation efficiency and visual effect were greatly improved. It can be concluded that the technology of spatial information grids is effective for mass quantity remote sensing image processing.

  7. Validating firn compaction model with remote sensing data

    DEFF Research Database (Denmark)

    Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland shows a clear layering. The observed layers from the radar data can be used as an in-situ validation...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...

  8. Researching on the process of remote sensing video imagery

    Science.gov (United States)

    Wang, He-rao; Zheng, Xin-qi; Sun, Yi-bo; Jia, Zong-ren; Wang, He-zhan

    Unmanned air vehicle remotely-sensed imagery on the low-altitude has the advantages of higher revolution, easy-shooting, real-time accessing, etc. It's been widely used in mapping , target identification, and other fields in recent years. However, because of conditional limitation, the video images are unstable, the targets move fast, and the shooting background is complex, etc., thus it is difficult to process the video images in this situation. In other fields, especially in the field of computer vision, the researches on video images are more extensive., which is very helpful for processing the remotely-sensed imagery on the low-altitude. Based on this, this paper analyzes and summarizes amounts of video image processing achievement in different fields, including research purposes, data sources, and the pros and cons of technology. Meantime, this paper explores the technology methods more suitable for low-altitude video image processing of remote sensing.

  9. Parameterization of High Resolution Vegetation Characteristics using Remote Sensing Products for the Nakdong River Watershed, Korea

    Directory of Open Access Journals (Sweden)

    Hyun Il Choi

    2013-01-01

    Full Text Available Mesoscale regional climate models (RCMs, the primary tool for climate predictions, have recently increased in sophistication and are being run at increasingly higher resolutions to be also used in climate impact studies on ecosystems, particularly in agricultural crops. As satellite remote sensing observations of the earth terrestrial surface become available for assimilation in RCMs, it is possible to incorporate complex land surface processes, such as dynamics of state variables for hydrologic, agricultural and ecologic systems at the smaller scales. This study focuses on parameterization of vegetation characteristics specifically designed for high resolution RCM applications using various remote sensing products, such as Advanced Very High Resolution Radiometer (AVHRR, Système Pour l’Observation de la Terre-VEGETATION (SPOT-VGT and Moderate Resolution Imaging Spectroradiometer (MODIS. The primary vegetative parameters, such as land surface characteristics (LCC, fractional vegetation cover (FVC, leaf area index (LAI and surface albedo localization factors (SALF, are currently presented over the Nakdong River Watershed domain, Korea, based on 1-km remote sensing satellite data by using the Geographic Information System (GIS software application tools. For future high resolution RCM modeling efforts on climate-crop interactions, this study has constructed the deriving parameters, such as FVC and SALF, following the existing methods and proposed the new interpolation methods to fill missing data with combining the regression equation and the time series trend function for time-variant parameters, such as LAI and NDVI data at 1-km scale.

  10. Geological remote sensing in Africa

    Science.gov (United States)

    Sabins, Floyd F., Jr.; Bailey, G. Bryan; Abrams, Michael J.

    1987-01-01

    Programs using remote sensing to obtain geologic information in Africa are reviewed. Studies include the use of Landsat MSS data to evaluate petroleum resources in sedimentary rock terrains in Kenya and Sudan and the use of Landsat TM 30-m resolution data to search for mineral deposits in an ophiolite complex in Oman. Digitally enhanced multispectral SPOT data at a scale of 1:62,000 were used to map folds, faults, diapirs, bedding attitudes, and stratigraphic units in the Atlas Mountains in northern Algeria. In another study, SIR-A data over a vegetated and faulted area of Sierra Leone were compared with data collected by the Landsat MSS and TM systems. It was found that the lineaments on the SIR-A data were more easily detected.

  11. Lunar remote sensing and measurements

    Science.gov (United States)

    Moore, H.J.; Boyce, J.M.; Schaber, G.G.; Scott, D.H.

    1980-01-01

    Remote sensing and measurements of the Moon from Apollo orbiting spacecraft and Earth form a basis for extrapolation of Apollo surface data to regions of the Moon where manned and unmanned spacecraft have not been and may be used to discover target regions for future lunar exploration which will produce the highest scientific yields. Orbital remote sensing and measurements discussed include (1) relative ages and inferred absolute ages, (2) gravity, (3) magnetism, (4) chemical composition, and (5) reflection of radar waves (bistatic). Earth-based remote sensing and measurements discussed include (1) reflection of sunlight, (2) reflection and scattering of radar waves, and (3) infrared eclipse temperatures. Photographs from the Apollo missions, Lunar Orbiters, and other sources provide a fundamental source of data on the geology and topography of the Moon and a basis for comparing, correlating, and testing the remote sensing and measurements. Relative ages obtained from crater statistics and then empirically correlated with absolute ages indicate that significant lunar volcanism continued to 2.5 b.y. (billion years) ago-some 600 m.y. (million years) after the youngest volcanic rocks sampled by Apollo-and that intensive bombardment of the Moon occurred in the interval of 3.84 to 3.9 b.y. ago. Estimated fluxes of crater-producing objects during the last 50 m.y. agree fairly well with fluxes measured by the Apollo passive seismic stations. Gravity measurements obtained by observing orbiting spacecraft reveal that mare basins have mass concentrations and that the volume of material ejected from the Orientale basin is near 2 to 5 million km 3 depending on whether there has or has not been isostatic compensation, little or none of which has occurred since 3.84 b.y. ago. Isostatic compensation may have occurred in some of the old large lunar basins, but more data are needed to prove it. Steady fields of remanent magnetism were detected by the Apollo 15 and 16 subsatellites

  12. Natural Resource Information System. Remote Sensing Studies.

    Science.gov (United States)

    Leachtenauer, J.; And Others

    A major design objective of the Natural Resource Information System entailed the use of remote sensing data as an input to the system. Potential applications of remote sensing data were therefore reviewed and available imagery interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and…

  13. Remote sensing and reflectance profiling in entomology

    Science.gov (United States)

    Remote sensing is about characterizing the status of objects and/or classifies their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be ground-based, and therefore acquired at a high spatial resolutio...

  14. Planning and Implementation of Remote Sensing Experiments.

    Science.gov (United States)

    Contents: TEKTITE II experiment-upwelling detection (NASA Mx 138); Design of oceanographic experiments (Gulf of Mexico, Mx 159); Design of oceanographic experiments (Gulf of Mexico, Mx 165); Experiments on thermal pollution; Remote sensing newsletter; Symposium on remote sensing in marine biology and fishery resources.

  15. Preface: Remote Sensing of Water Resources

    OpenAIRE

    Deepak R. Mishra; Eurico J. D’Sa; Sachidananda Mishra

    2016-01-01

    The Special Issue (SI) on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  16. Technology Progress Report for Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; DONG Xiaolong; LIU Heguang

    2004-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for China's lunar exploration satellite (Chang'E-1), meteorological satellite FY-3 and ocean dynamic measurement satellite (HY-2) are reported.

  17. Remote sensing of essential ecosystem functional variables

    Science.gov (United States)

    Alcaraz-Segura, D.; Bagnato, C. E.; Paruelo, J. M.; Berbery, E. H.; Cabello, J.; Castro, A.; Cazorla, B. P.; Epstein, H. E.; Fernández, N.; Jobbagy, E. G.; Oyonarte, C.; Pacheco, M.; Peñas, J.; Vallejos, M.

    2016-12-01

    Essential Biodiversity Variables should inform on the status of the three dimensions recognised for biodiversity: composition, structure and function. Whereas composition and structure (from genes to ecosystems) have been traditionally used to assess biodiversity status, functional components of biodiversity, particularly at the ecosystem level, have been scarcely included. Satellite remote sensing can provide multiple descriptors of ecosystem function, though their relevance as essential biodiversity variables still needs to be assessed. Time-series of spectral data derived from satellite images can inform on key attributes of the dynamics of carbon, water, energy balance, disturbance regime or nutrient cycling. These ecosystem functional attributes can be integrated to identify Ecosystem Functional Types (EFTs), defined as groups of ecosystems with similar dynamics of matter and energy exchanges between the biota and the physical environment. Most popular EFTs used the three most informative metrics of the seasonal curves of spectral vegetation indices as surrogates of the most integrative descriptor of ecosystem functioning, the primary production dynamics: annual mean (estimator of primary production), seasonal coefficient of variation (descriptor of seasonality), and date of maximum (indicator of phenology). To search for simple metrics that could be used as a set of highly informative ecosystem functional attributes, we extended the analysis to the global scale across all terrestrial biomes and to other key dimensions of ecosystem functioning, i.e., albedo and surface temperature (related to the energy balance) and evapotranspiration (related to the water cycle and the energy balance). The three first axes of a Principal Component Analysis run on the average seasonal dynamics of each variable and biome explained from 85% to 97% of variance. From more than 20 summary metrics analysed, the annual mean was highly correlated to the first axis (r2>0.9). The second

  18. 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).

  19. Integration of Field and Remote Sensing Techniques For Landslides Monitoring

    Science.gov (United States)

    Allievi, J.; Ambrosi, C.; Ceriani, M.; Colesanti, C.; Crosta, G. B.; Ferretti, A.; Fossati, D.; Menegaz, A.

    The definition of the state of activity of slope movements is of major interest both at local and at regional scale. The Geological Survey of the Regione Lombardia has re- cently started a series of projects aimed to the identification of areas subjected to slope instability and to the assessment of their state of activity. Field survey, aerial photo interpretation and advanced remote sensing techniques have been applied. Some ex- amples of large rock slope instabilities have been investigated in the Valtellina area (Lombardia, Northern Italy). In particular, we demonstrate the degree of integration of the adopted techniques for one of the largest rock slope movements actually recog- nised in the area. The remote sensing approach that has been adopted is the Perma- nent Scatterers (PS) Technique. This technique has been recently developed as a new methodology for surface deformation monitoring, using ESA ERS-SAR data. Its ap- plication to large slope movements in alpine and prealpine areas, with a relatively low urban development, has been tried for the first time in order to evaluate its potential in supporting studies for landslide hazard assessment. Previous results show that this ap- proach allows to reach an accuracy very close to the theoretical limit. This study shows the very good agreement reached for displacement velocities between historical trends and recent PS measurements. Scatterers have been identified by field surveying and some of them are located close to historically monitored benchmark for topographic measurements. Furthermore, the integration of these data with field observations al- lowed us to perform a preliminary reconstrucion of the landslide mechanism and to assess the activity of different landslide structures (scarps, etc.).

  20. A Merging Approach for Urban Boundary Correction Acquired By Remote Sensing Images

    Science.gov (United States)

    Zhang, P. L.; Shi, W. Z.; Wu, X. Y.

    2014-11-01

    Since reform and opening up to outside world, ever-growing economy and development of urbanization of China have caused expansion of the urban land scale. It's necessary to grasp the information about urban spatial form change, expansion situation and expanding regularity, in order to provide the scientific basis for urban management and planning. The traditional methods, like land supply cumulative method and remote sensing, to get the urban area, existed some defects. Their results always doesn't accord with the reality, and can't reflects the actual size of the urban area. Therefore, we propose a new method, making the best use of remote sensing, the population data, road data and other social economic statistic data. Because urban boundary not only expresses a geographical concept, also a social economic systems.It's inaccurate to describe urban area with only geographic areas. We firstly use remote sensing images, demographic data, road data and other data to produce urban boundary respectively. Then we choose the weight value for each boundary, and in terms of a certain model the ultimate boundary can be obtained by a series of calculations of previous boundaries. To verify the validity of this method, we design a set of experiments and obtained the preliminary results. The results have shown that this method can extract the urban area well and conforms with both the broad and narrow sense. Compared with the traditional methods, it's more real-time, objective and ornamental.

  1. 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.

  2. Grid cells analysis of urban growth using remote sensing and population census data

    Science.gov (United States)

    Bagan, H.; Yamagata, Y.

    2012-12-01

    Urban growth and sprawl have drastically altered the ecosystems and ecosystem services. Urban areas are an increasingly important component of the global environment, yet they remain one of the most challenging areas for conducting research. Remote sensing based information is one of the most important resources to support urban planning and administration in megacities. It is possible to provide the up-to-date information regarding the extent, growth, and physical characteristics of urban land. Remote sensing provides spatially consistent image information that covers broad areas with both high spatial resolution and high temporal frequency. Therefore, remote sensing is an important tool for providing information on urban land-cover characteristics and their changes over time at various spatial and temporal scales. Urban land-use and land-cover changes are linked to socio-economic activities. Urbanization includes both the physical growth of a city and the movement of people to urban areas. As a consequence, it is essential to combine remote sensing derived parameters with socio-economic parameter to analyze the spatial-temporal changes and interaction of both factors. The aim of the research was to use1-km2 grid cells to investigate the spatial and temporal dynamics of urban growth in the world mega cities. The research was conducted in the 50 global cities using Landsat ETM/TM remote sensing imagery from 1985 - 2011, and time series population census data (1-km2 resolution gridded population census data of Japan and 2.5 arc-minute resolutions Gridded Population of the World). First, maximum likelihood classification (MLC) method were used to produce land cover maps by using Landsat images. Then intersect the land cover maps with 1-km2 grid cell maps to represents the proportion of each land cover category within each 1-km2 grid cell. Finally, we combined the proportional land cover maps with gridded population census data on 1-km2 resolution grid cells to

  3. Application of remote sensing technology in the study of vegetation: Example of vegetation of zhejiang province in China

    Science.gov (United States)

    CHU, MengRu

    2015-04-01

    Application of remote sensing technology in the study of vegetation: Example of vegetation of zhejiang province in China Remote sensing technology , is one of the pillars of the space information technology in the 21st century ,play an important role in the study of vegetation. Vegetation coverage as an important parameter reflecting surface information, has been an important research topic in the field of vegetation remote sensing. Administrative region in zhejiang Province as the study area, use of microwave remote sensing and hyperspectral remote sensing technology, combined with the related data, to survey the area of forest resources in zhejiang Province, establishes an index system of sustainable forest resources management ability in zhejiang, and to evaluate its ability. Remote Sensing is developed in the 1960 s of the earth observation technology, comprehensive instruments refers to the application, not contact with the object detection phase, the target characteristics of electromagnetic waves recorded from a distance, through the analysis, reveals the characteristics of the object properties and changes of comprehensive detection technology. Investigation of vegetation is an important application field of remote sensing investigation. Vegetation is an important factor of environment, and also is one of the best sign to reflect the regional ecological environment, at the same times is the interpretation of soil, hydrological elements such as logo, individual or prospecting indicator plant. Vegetation imaging and interpretation of research results for environmental monitoring, biodiversity conservation, agriculture, forestry and other relevant departments to provide information services.Microwave remote sensing hyperspectral remote sensing technology and application in the research of vegetation is an important direction of remote sensing technology in the future. This paper introduces the principle of microwave remote sensing and hyperspectral remote

  4. Microwave interferometric radiometry in remote sensing: An invited historical review

    DEFF Research Database (Denmark)

    Martin-Neira, M.; LeVine, D. M.; Kerr, Y.

    2014-01-01

    The launch of the Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009 marked a milestone in remote sensing for it was the first time a radiometer capable of acquiring wide field of view images at every single snapshot, a unique feature of the synthetic aperture technique, made it t...

  5. Multisensor image fusion techniques in remote sensing

    Science.gov (United States)

    Ehlers, Manfred

    Current and future remote sensing programs such as Landsat, SPOT, MOS, ERS, JERS, and the space platform's Earth Observing System (Eos) are based on a variety of imaging sensors that will provide timely and repetitive multisensor earth observation data on a global scale. Visible, infrared and microwave images of high spatial and spectral resolution will eventually be available for all parts of the earth. It is essential that efficient processing techniques be developed to cope with the large multisensor data volumes. This paper discusses data fusion techniques that have proved successful for synergistic merging of SPOT HRV, Landsat TM and SIR-B images. It is demonstrated that these techniques can be used to improve rectification accuracies, to depicit greater cartographic detail, and to enhance spatial resolution in multisensor image data sets.

  6. Adaptive Remote Sensing Texture Compression on GPU

    Directory of Open Access Journals (Sweden)

    Xiao-Xia Lu

    2010-11-01

    Full Text Available Considering the properties of remote sensing texture such as strong randomness and weak local correlation, a novel adaptive compression method based on vector quantizer is presented and implemented on GPU. Utilizing the property of Human Visual System (HVS, a new similarity measurement function is designed instead of using Euclid distance. Correlated threshold between blocks can be obtained adaptively according to the property of different images without artificial auxiliary. Furthermore, a self-adaptive threshold adjustment during the compression is designed to improve the reconstruct quality. Experiments show that the method can handle various resolution images adaptively. It can achieve satisfied compression rate and reconstruct quality at the same time. Index is coded to further increase the compression rate. The coding way is designed to guarantee accessing the index randomly too. Furthermore, the compression and decompression process is speed up with the usage of GPU, on account of their parallelism.

  7. Remote sensing of vegetation at regional scales

    Science.gov (United States)

    Hall, F. G.

    1984-01-01

    Relations between spectroscopy and the concept of inferring surface cover type and condition from measurements of reflected or emitted radiation are examined, taking into account the observation of 'spectral signatures'. It has now become evident that the paradigm which had provided the basis for the spectroscopic identification of materials, is incomplete when applied to the inference of type and condition of materials in a natural environment. It was found that one could not collect a remote sensing signature from an unknown ground cover class at a particular time and place and match that signature with an a priori catalog value to infer the properties of the unknown cover class. The spectroscopy paradigm was, therefore, largely abandoned in favor of decision theoretic approaches. Attention is given to the temporal greenness profile feature space, the crop stage of development estimation using a temporal greenness profile, the temporal greenness profile for crop yield, and applications to regional scales.

  8. Monitoring vegetation responses to drought -- linking Remotely-sensed Drought Indices with Meteorological drought indices

    Science.gov (United States)

    Wang, H.; Lin, H.; Liu, D.

    2013-12-01

    Abstract: Effectively monitoring vegetation drought is of great significance in ecological conservation and agriculture irrigation at the regional scale. Combining meteorological drought indices with remotely sensed drought indices can improve tracking vegetation dynamic under the threat of drought. This study analyzes the dynamics of spatially-defined Temperature Vegetation Dryness Index (TVDI) and temporally-defined Vegetation Health Index (VHI) from remotely sensed NDVI and LST datasets in the dry spells in Southwest China. We analyzed the correlation between remotely sensed drought indices and meteorological drought index of different time scales. The results show that TVDI was limited by the spatial variations of LST and NDVI, while VHI was limited by the temporal variations of LST and NDVI. Station-based buffering analysis indicates that the extracted remotely sensed drought indices and Standard Precipitation Index (SPI) could reach stable correlation with buffering radius larger than 35 km. Three factors affect the spatiotemporal relationship between remotely sensed drought indices and SPI: i) different vegetation types; ii) the timescale of SPI; and iii) remote sensing data noise. Vegetation responds differently to meteorological drought at various time scales. The correlation between SPI6 and VHI is more significant than that between SPI6 and TVDI. Spatial consistency between VHI and TVDI varies with drought aggravation. In early drought period from October to December, VHI and TVDI show limited consistency due to the low quality of remotely sensed images. The study helps to improve monitoring vegetation drought using both meteorological drought indices and remotely sensed drought indices.

  9. Remote sensing monitoring of the global ozonosphere

    Science.gov (United States)

    Genco, S.; Bortoli, D.; Ravegnani, F.

    2013-10-01

    The use of CFCs, which are the main responsible for the ozone depletion in the upper atmosphere and the formation of the so-called "ozone hole" over Antarctic Region, was phase out by Montreal Protocol (1989). CFCs' concentration is recently reported to decrease in the free atmosphere, but severe episodes of ozone depletion in both Arctic and Antarctic regions are still occurring. Nevertheless the complete recovery of the Ozone layer is expected by about 2050. Recent simulation of perturbations in stratospheric chemistry highlight that circulation, temperature and composition are strictly correlated and they influence the global climate changes. Chemical composition plays an important role in the thermodynamic of the atmosphere, as every gaseous species can absorb and emit in different wavelengths, so their different concentration is responsible for the heating or cooling of the atmosphere. Therefore long-term observations are required to monitor the evolution of the stratospheric ozone layer. Measurements from satellite remote sensing instruments, which provide wide coverage, are supplementary to selective ground-based observations which are usually better calibrated, more stable in time and cover a wider time span. The combination of the data derived from different space-borne instruments calibrated with ground-based sensors is needed to produce homogeneous and consistent long-term data records. These last are required for robust investigations and especially for trend analysis. Here, we perform a review of the major remote-sensing techniques and of the principal datasets available to study the evolution of ozone layer in the past decades and predict future behavio

  10. MICROWAVE REMOTE SENSING IN SOIL QUALITY ASSESSMENT

    Directory of Open Access Journals (Sweden)

    S. K. Saha

    2012-08-01

    Full Text Available Information of spatial and temporal variations of soil quality (soil properties is required for various purposes of sustainable agriculture development and management. Traditionally, soil quality characterization is done by in situ point soil sampling and subsequent laboratory analysis. Such methodology has limitation for assessing the spatial variability of soil quality. Various researchers in recent past showed the potential utility of hyperspectral remote sensing technique for spatial estimation of soil properties. However, limited research studies have been carried out showing the potential of microwave remote sensing data for spatial estimation of various soil properties except soil moisture. This paper reviews the status of microwave remote sensing techniques (active and passive for spatial assessment of soil quality parameters such as soil salinity, soil erosion, soil physical properties (soil texture & hydraulic properties; drainage condition; and soil surface roughness. Past and recent research studies showed that both active and passive microwave remote sensing techniques have great potentials for assessment of these soil qualities (soil properties. However, more research studies on use of multi-frequency and full polarimetric microwave remote sensing data and modelling of interaction of multi-frequency and full polarimetric microwave remote sensing data with soil are very much needed for operational use of satellite microwave remote sensing data in soil quality assessment.

  11. Remote sensing applications in evaluation of cadmium pollution effects

    Science.gov (United States)

    Kozma-Bognar, Veronika; Martin, Gizella; Berke, Jozsef

    2013-04-01

    According to the 21st century developments in information technology the remote sensing applications open new perspectives to the data collection of our environment. Using the images in different spectral bands we get more reliable and accurate information about the condition, process and phenomena of the earth surface compared to the traditional aircraft image technologies (RGB images). The effects of particulate pollution originated from road traffic were analysed by the research team of Department of Meteorology and Water Management (University of Pannonia, Georgikon Faculty) with the application of visible, near infrared and thermal infrared remote sensing aircraft images. In the scope of our research was to detect and monitor the effects of heavy metal contamination in plant-atmosphere system under field experiments. The testing area was situated at Agro-meteorological Research Station in Keszthely (Hungary), where maize crops were polluted once a week (0,5 M concentration) by cadmium. In our study we simulated the effects of cadmium pollution because this element is one of the most common toxic heavy metals in our environment. During two growing seasons (2011, 2012) time-series analyses were carried out based on the remote sensing data and parallel collected variables of field measurement. In each phenological phases of plant we took aerial images, in order to follow the changes of the structure and intensity values of plots images. The spatial resolution of these images were under 10x10 cm, which allowed to use a plot-level evaluation. The structural and intensity based measurement evaluation methods were applied to examine cadmium polluted and control maize canopy after data pre-processing. Research activities also focused on the examination of the influence of the irrigation and the comparison of aerial and terrain parameters. As conclusion, it could be determined the quantification of cadmium pollution effects is possible on maize plants by using remote

  12. Hyperspectral remote sensing for terrestrial applications

    Science.gov (United States)

    Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Murali Krishna Gumma,; Venkateswarlu Dheeravath,

    2015-01-01

    Remote sensing data are considered hyperspectral when the data are gathered from numerous wavebands, contiguously over an entire range of the spectrum (e.g., 400–2500 nm). Goetz (1992) defines hyperspectral remote sensing as “The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element of an image it is possible to derive a complete reflectance spectrum.” However, Jensen (2004) defines hyperspectral remote sensing as “The simultaneous acquisition of images in many relatively narrow, contiguous and/or non contiguous spectral bands throughout the ultraviolet, visible, and infrared portions of the electromagnetic spectrum.

  13. An international organization for remote sensing

    Science.gov (United States)

    Helm, Neil R.; Edelson, Burton I.

    1991-01-01

    A recommendation is presented for the formation of a new commercially oriented international organization to acquire or develop, coordinate or manage, the space and ground segments for a global operational satellite system to furnish the basic data for remote sensing and meteorological, land, and sea resource applications. The growing numbers of remote sensing programs are examined and possible ways of reducing redundant efforts and improving the coordination and distribution of these global efforts are discussed. This proposed remote sensing organization could play an important role in international cooperation and the distribution of scientific, commercial, and public good data.

  14. Remote sensing and urban public health

    Science.gov (United States)

    Rush, M.; Vernon, S.

    1975-01-01

    The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

  15. Preface: Remote Sensing in Coastal Environments

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-08-01

    Full Text Available The Special Issue (SI on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology in the coastal zone. This preface provides a brief summary of each article published in the SI.

  16. Suntracker for atmospheric remote sensing

    Science.gov (United States)

    Hawat, Toufic-Michel; Camy-Peyret, Claude; Torguet, Roger J.

    1998-05-01

    A heliostat is designed and built to track the sun for optical remote sensing of the stratosphere from a balloon- borne pointed gondola. The tracking mechanism is controlled by two direct torque motors used to drive a single flat acquisition mirror. A horizontal turntable, rigidly attached to the azimuth drive, supports the elevation assembly. A position sensor receiving a small part of the solar beam reflected off the main acquisition mirror is used for the fine servo control. Using a CCD camera prepointing of the acquisition mirror is achieved when the sun is in the field of view of the heliostat. This system is coupled with a high-resolution (0.02-cm-1) Fourier transform IR spectrometer to retrieve stratospheric trace species concentration profiles. The suntracker directs the solar radiation in a stable direction along the spectrometer optical axis. The pointing precision is 1 arcmin from a stratospheric gondola, which has static and dynamic angular excursions up to 6 deg. The heliostat coupled to the Limb Profile Monitor of the Atmosphere instrument performs successfully on several balloon flights. The description, ground tests, and balloon flight results of the suntracker are presented.

  17. Remote sensing and eLearning 2.0 for school education

    Science.gov (United States)

    Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

    2010-10-01

    The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.

  18. A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.

    Science.gov (United States)

    Maynard, Jonathan J; Karl, Jason W

    2017-01-01

    Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral 'fingerprint' of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites

  19. Remote sensing applications to hydrologic modeling

    Science.gov (United States)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  20. Application of Spaceborne Remote Sensing to Archaeology

    Science.gov (United States)

    Crippen, Robert E.

    1997-01-01

    Spaceborne remote sensing data have been underutilized in archaeology for a variety of seasons that are slowly but surely being overcome. Difficulties have included cost/availability of data, inadequate resolution, and data processing issues.

  1. GNSS remote sensing theory, methods and applications

    CERN Document Server

    Jin, Shuanggen; Xie, Feiqin

    2014-01-01

    This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. It contains detailed theory and study cases to help the reader put the material into practice.

  2. Remote Sensing Wind and Wind Shear System.

    Science.gov (United States)

    Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

  3. NOAA Coastal Mapping Remote Sensing Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Remote Sensing Division is responsible for providing data to support the Coastal Mapping Program, Emergency Response efforts, and the Aeronautical Survey Program...

  4. 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.

  5. Integrating spatial statistics and remote sensing.

    NARCIS (Netherlands)

    Stein, A.; Bastiaanssen, W.G.M.; Bruin, de S.; Cracknell, A.P.; Curran, P.J.; Fabbri, A.G.; Gorte, B.G.H.; Groenigen, van J.W.; Meer, van der F.D.; Saldana, A.

    1998-01-01

    This paper presents an integrated approach towards spatial statistics for remote sensing. Using the layer concept in Geographical Information Systems we treat successively elements of spatial statistics, scale, classification, sampling and decision support. The layer concept allows to combine contin

  6. Remote sensing, imaging, and signal engineering

    Energy Technology Data Exchange (ETDEWEB)

    Brase, J.M.

    1993-03-01

    This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.

  7. Freeware for GIS and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Lena Halounová

    2007-12-01

    Full Text Available Education in remote sensing and GIS is based on software utilization. The software needs to be installed in computer rooms with a certain number of licenses. The commercial software equipment is therefore financially demanding and not only for universities, but especially for students. Internet research brings a long list of free software of various capabilities. The paper shows a present state of GIS, image processing and remote sensing free software.

  8. An overview of GNSS remote sensing

    OpenAIRE

    Kegen, Yu; Rizos, Chris; Burrage, Derek; Dempster, Andrew; Zhang, Kefei; Markgraf, Markus

    2014-01-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote ...

  9. Preface: Remote Sensing of Water Resources

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-02-01

    Full Text Available The Special Issue (SI on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  10. Talisman-Saber 2009 Remote Sensing Experiment

    Science.gov (United States)

    2012-03-30

    Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/7230--12-9404 Talisman -Saber 2009 Remote Sensing Experiment March 30, 2012 Approved for... Talisman -Saber 2009 Remote Sensing Experiment Charles M. Bachmann, Robert A. Fusina, Marcos J. Montes, Rong-Rong Li, Carl Gross, C. Reid Nichols,* John C...sensor were used to build shallow water bathymetric charts and trafficability maps that were provided to military planners during Exercise Talisman

  11. Remote sensing of coastal and ocean studies

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.

    the sensors on board 2 satellites or aircrafts (and vice versa). Hence, they cannot be used in remote sensing. Similarly, long waves like radio waves are also not used in remote sensing because of their poor information carrying capacity. Only visible, infra..., infra-red radiation is also affected by clouds (though less significantly). This requires atmospheric corrections to be applied to such data. At present, sea surface temperatures are routinely being retrieved from the sensor called AVBRR (Advanced Vary...

  12. Accurate Annotation of Remote Sensing Images via Active Spectral Clustering with Little Expert Knowledge

    Directory of Open Access Journals (Sweden)

    Gui-Song Xia

    2015-11-01

    Full Text Available It is a challenging problem to efficiently interpret the large volumes of remotely sensed image data being collected in the current age of remote sensing “big data”. Although human visual interpretation can yield accurate annotation of remote sensing images, it demands considerable expert knowledge and is always time-consuming, which strongly hinders its efficiency. Alternatively, intelligent approaches (e.g., supervised classification and unsupervised clustering can speed up the annotation process through the application of advanced image analysis and data mining technologies. However, high-quality expert-annotated samples are still a prerequisite for intelligent approaches to achieve accurate results. Thus, how to efficiently annotate remote sensing images with little expert knowledge is an important and inevitable problem. To address this issue, this paper introduces a novel active clustering method for the annotation of high-resolution remote sensing images. More precisely, given a set of remote sensing images, we first build a graph based on these images and then gradually optimize the structure of the graph using a cut-collect process, which relies on a graph-based spectral clustering algorithm and pairwise constraints that are incrementally added via active learning. The pairwise constraints are simply similarity/dissimilarity relationships between the most uncertain pairwise nodes on the graph, which can be easily determined by non-expert human oracles. Furthermore, we also propose a strategy to adaptively update the number of classes in the clustering algorithm. In contrast with existing methods, our approach can achieve high accuracy in the task of remote sensing image annotation with relatively little expert knowledge, thereby greatly lightening the workload burden and reducing the requirements regarding expert knowledge. Experiments on several datasets of remote sensing images show that our algorithm achieves state

  13. Time series analysis.

    NARCIS (Netherlands)

    2013-01-01

    Time series analysis can be used to quantitatively monitor, describe, explain, and predict road safety developments. Time series analysis techniques offer the possibility of quantitatively modelling road safety developments in such a way that the dependencies between the observations of time series

  14. Integrating field plots, lidar, and landsat time series to provide temporally consistent annual estimates of biomass from 1990 to present

    Science.gov (United States)

    Warren B. Cohen; Hans-Erik Andersen; Sean P. Healey; Gretchen G. Moisen; Todd A. Schroeder; Christopher W. Woodall; Grant M. Domke; Zhiqiang Yang; Robert E. Kennedy; Stephen V. Stehman; Curtis Woodcock; Jim Vogelmann; Zhe Zhu; Chengquan. Huang

    2015-01-01

    We are developing a system that provides temporally consistent biomass estimates for national greenhouse gas inventory reporting to the United Nations Framework Convention on Climate Change. Our model-assisted estimation framework relies on remote sensing to scale from plot measurements to lidar strip samples, to Landsat time series-based maps. As a demonstration, new...

  15. Tunnel-Site Selection by Remote Sensing Techniques

    Science.gov (United States)

    A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave

  16. Remote Sensing Best Paper Award for the Year 2014

    OpenAIRE

    Prasad Thenkabail

    2014-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for the year 2014.

  17. 溢油遥感监测时效性分析——以大连新港溢油为例%Time Effectiveness Analysis of Remote Sensing Monitoring of Oil Spill Emergencies: A Case Study of Oil Spill in the Dalian Xingang Port

    Institute of Scientific and Technical Information of China (English)

    兰国新; 李颖; 陈澎

    2012-01-01

    在溢油运动模型分析的基础上,确立遥感数据服务于应急所需的时间分辨率,并进一步分析遥感数据处理时间构成,讨论应急反应下的溢油轨迹预测、遥感监测技术的协同,提出优化建议.研究成果在2010-07-16发生的大连新港溢油事件发挥了关键作用,结果表明溢油应急遥感应用时效具有实践可行性及重要性.%Time is a critical factor in the response of oil spill emergency because the oil spilled in the sea can rapidly be diffused to a large area by winds and currents in a short time. Since the models for oil-spill trajectory have uncertainties and some key parameters influencing the accuracy of prediction, e. g. the oil-spill area and position, can change with time, the data from remote sensing are mostly needed. The prediction of oil-spill trajectory and the cooperation with remote sensing techniques are discussed for the response of oil spill emergencies. Based on a model analysis of oil-spill motion, the time resolution needed for the response of oil spill emergencies and resulted from the remote sensing data is determined, a method for remote sensing application time is further described and then an optimized proposal is put forward for the time processing by using remote sensing data. This result played a key role in the oil spill event that happened in the Dalian Xingang Port on July 26, 2010. It has been showed that the application of remote sensing data for the time effectiveness of oil-spill emergencies is practical and significant.

  18. Research Dynamics of the Classification Methods of Remote Sensing Images

    Institute of Scientific and Technical Information of China (English)

    Yan; ZHANG; Baoguo; WU; Dong; WANG

    2013-01-01

    As the key technology of extracting remote sensing information,the classification of remote sensing images has always been the research focus in the field of remote sensing. The paper introduces the classification process and system of remote sensing images. According to the recent research status of domestic and international remote sensing classification methods,the new study dynamics of remote sensing classification,such as artificial neural networks,support vector machine,active learning and ensemble multi-classifiers,were introduced,providing references for the automatic and intelligent development of remote sensing images classification.

  19. Progress in the application of ocean color remote sensing in China

    Institute of Scientific and Technical Information of China (English)

    PAN Delu; BAI Yan

    2008-01-01

    After many years'endeavor of research and application practice,the ocean color remote sensing in China has been growing into a new technique with valuable practicality from its initiate stage of trial research.With the aim of operational service,several kinds of ocean color remote sensing application systems have been developed and realized the long-term marine environmental monitoring utilizing the real-time or near real-time satellite and airborne remote sensing data.New progresses in the technology and application of ocean color remote sensing in China are described,including the research of key techniques and the development of various application systems.Meanwhile,according to the application status and demand,the prospective development of Chinese ocean color remote sensing is brought forward.With Chinese second ocean color satellite (HY-1B) orbiting on 11 April 2007 and the development of airborne ocean color remote sensing system for Chinese surveillance planes,great strides will take place in Chinese ocean color remote sensing application with the unique function in marine monitoring,resources management and national security,etc.

  20. Theme section for 36th International Symposium for Remote Sensing of the Environment in Berlin

    Science.gov (United States)

    Trinder, John; Waske, Björn

    2016-09-01

    The International Symposium for Remote Sensing of the Environment (ISRSE) is the longest series of international conferences held on the topic of Remote Sensing, commencing in Ann Arbor, Michigan USA in 1962. While the name of the conference has changed over the years, it is regularly held approximately every 2 years and continues to be one of the leading international conferences on remote sensing. The latest of these conferences, the 36th ISRSE, was held in Berlin, Germany from 11 to 15 May 2015. All complete papers from the conference are available in the ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences at http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/index.html.

  1. Lidar Remote Sensing for Characterizing Forest Vegetation - Special Issue. Foreword

    Science.gov (United States)

    Popescu, Sorin C.; Nelson, Ross F.

    2011-01-01

    The Silvilaser 2009 conference held in College Station, Texas, USA, was the ninth conference in the Silvilaser series, which started in 2002 with the international workshop on using lidar (Light Detection and Ranging) for analyzing forest structure, held in Victoria, British Columbia, Canada. Following the Canadian workshop, subsequent forestry-lidar conferences took place in Australia, Sweden, Germany, USA, Japan, Finland, and the United Kingdom (UK). By the time this Silvilaser 2009 special issue of PE&RS is published, the 10th international conference will have been held in Freiburg, Germany, and planning will be ongoing for the 11th meeting to take place in Tasmania, Australia, in October 2011. Papers presented at the 2005 conference held in Blacksburg, Virginia, USA, were assembled in a special issue of PE&RS published in December 2006. Other special issues resulting from previous conferences were published in journals such as the Canadian Journal of Remote Sensing (2003), the Scandinavian Journal of Forest Research (2004), and Japan s Journal of Forest Planning (2008). Given the conference history and the much longer record of publications on lidar applications for estimating forest biophysical parameters, which dates back to the early 1980s, we may consider lidar an established remote sensing technology for characterizing forest canopy structure and estimating forest biophysical parameters. Randy Wynne, a professor at Virginia Tech and the final keynote speaker at Silvilaser 2009, made the case that it was time to push 30 years of research into operations, along the lines of what has already been done to good effect in the Scandinavian countries. In Randy s words, it s time to "Just do it!" This special issue includes a selection of papers presented during the 2009 Silvilaser conference, which consisted of eight sections as follows: (1) biomass and carbon stock estimates, (2) tree species and forest type classification, (3) data fusion and integration, (4, 5

  2. Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

    Science.gov (United States)

    Verma, Manish K.

    -situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

  3. Comparison of the remotely sensed start of the season and ground phenology observations of the cereal crops

    Science.gov (United States)

    Bohovic, Roman; Hlavinka, Petr; Semerádová, Daniela; Bálek, Jan; Trnka, Mirek

    2015-04-01

    Phenology monitoring such as start of the season of agricultural crops are important characteristics observed on the ground basis by the farmers and authorities already for the long time. Due to costs, coverage, site disparities and time demands of ground observations is remote sensing phenology an interesting option. Satellite observations enable monitoring of the ground vegetation already at sufficient resolution and in country and regional scale at the same time. However, ground and remote sensing phenology differ in nature of its object. First is focused on single species and limited individuals at the observation spot. Remote sensing is from its construction definition able to monitor area-wide vegetation communities. To understand these differences and to set the procedures to overcome it is the aim of this study. Case study area covers Czech Republic in Central Europe with typical four season temperate climate that strongly influence the vegetation. Daily MODIS (Moderate Resolution Imaging Spectroradiometer) remote sensing data in 250 by 250 meters resolution were used to compute NDVI (normalized difference vegetation index). Iterative developed method for the filtering of NDVI time series since 2000 up till now is crucial for overcoming missing periods mainly due to atmospheric conditions. From improved curve of NDVI start of the season is derived as absolute threshold value of 50% NDVI. Comparison of remotely sensed start of the season with observations of emergence of spring barley and beginning of leaf sheath elongation for winter wheat was done. Data were correlated at 90 ground stations across Czech Republic between the years 2000 and 2012. Correlations at original 250x250 meters resolution and aggregations of 5x5 km were investigated. Different land cover classes were considered for aggregated areas. Correlation of start of the season shows lower results for spring barley caused by strong influence of winter signal and crop sowing date by farmers

  4. Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

    Science.gov (United States)

    Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

    2010-01-01

    Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

  5. Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

    Directory of Open Access Journals (Sweden)

    Marc Cattet

    2010-11-01

    Full Text Available Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC. Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI, inversion algorithm, data fusion, and the integration of remote sensing (RS and geographic information system (GIS.

  6. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  7. Integrating remotely sensed surface water extent into continental scale hydrology.

    Science.gov (United States)

    Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

    2016-12-01

    In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R(2), RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that

  8. Integrating remotely sensed surface water extent into continental scale hydrology

    Science.gov (United States)

    Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

    2016-12-01

    In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that

  9. A RBF classification method of remote sensing image based on genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote imaging data of large scale and cross-time, due to the increase of remote image quantities and image resolutions. In the paper, the genetic algorithms were employed to solve the weighting of the radial basis faction networks in order to improve the precision of remote sensing image classification. The remote sensing image classification was also introduced for the GIS spatial analysis and the spatial online analytical processing (OLAP) ,and the resulted effectiveness was demonstrated in the analysis of land utilization variation of Daqing city.

  10. Linking archival and remotely sensed data for long-term environmental monitoring

    Science.gov (United States)

    Hamandawana, Hamisai; Eckardt, Frank; Chanda, Raban

    2005-12-01

    The broad objective of this paper is to illustrate how archival, historical and remotely sensed data can be used to complement each other for long-term environmental monitoring. One of the major constraints confronting scientific investigation in the area of long-term environmental monitoring is lack of data at the required temporal and spatial scales. While remotely sensed data have provided dependable change detection databases since 1972, long-term changes such as those associated with typical climate scenarios often require longer time series data. The lack of data in readily accessible and usable formats for periods predating commercial satellite products has for a long time restricted the scope of environmental studies to temporally brief, synoptic overviews covering short time scales, thereby compromising our understanding of complex environmental processes. One way to improve this understanding is by cross-linking different forms of data at different temporal scales. However, most remote sensing based change research has tended to marginalize the utility of archival and historical sources in environmental monitoring. While the accuracy of data from non-instrumental records is often source-specific and varies from place to place, carefully conducted searches can yield useful information that can be effectively used to extend the temporal coverage of projects dependant on time series data. This paper is based on an ongoing project on environmental monitoring in the world's largest Ramsar site, the Okavango Delta, located on the northeastern fringes of Southern Africa's Kalahari-Namib desert in northern Botswana. With a database covering over 150 years between 1849 and 2001, the primary objectives of this paper are to: (1) outline how modern remotely sensed data (i.e., CORONA and Landsat) can be complemented by historical in situ observations (i.e., travellers' records and archival maps) to extend temporal coverage into the historical past, (2) illustrate that

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

    Science.gov (United States)

    Mishchenko, M. I.; Glory APS Science Team

    2011-12-01

    Aerosol and cloud particles exert a strong influence on the regional and global climates of the Earth. More often than not it is impossible to collect samples of such particles and subject them to a laboratory test. Therefore, in most cases one has to rely on theoretical analyses of remote measurements of the electromagnetic radiation scattered by the particles. Fortunately, the scattering and absorption properties of small particles often exhibit a strong dependence on their size, shape, orientation, and refractive index. This factor makes remote sensing an extremely useful and often the only practicable means of physical and chemical particle characterization in atmospheric physics. For a long time remote-sensing studies had relied on measurements of only the scattered intensity and its spectral dependence. Eventually, however, it has become widely recognized that polarimetric characteristics of the scattered radiation contain much more accurate and specific information about such important properties of particles as their size, morphology, and chemical composition. The progress in polarimetric remote-sensing research has always been hampered by the fact that the human eye is "polarization blind" and responds only to the intensity of light impinging on the retina. As a consequence, to give a simple definition of polarization readily intelligible to a non-expert is almost as difficult as to describe color to a color-blind person. However, continuing progress in electromagnetic scattering theory coupled with great advances in the polarization measurement capability has resulted in overwhelming examples of the immense practical power of polarimetric remote sensing which are no longer possible to ignore. As a result of persistent research efforts, polarimetry has become one of the most informative, accurate, and efficient means of terrestrial remote sensing. The only space-borne polarimeter flown around the Earth has been the French instrument POLDER. The recent

  12. Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

    Science.gov (United States)

    Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

    2014-05-01

    Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety

  13. Specific sensors for special roles in oil spill remote sensing

    Science.gov (United States)

    Brown, Carl E.; Fingas, Mervin F.

    1997-01-01

    Remote sensing is becoming an increasingly important tool for the effective direction of oil spill countermeasures. Cleanup personnel have recognized that remote sensing can increase spill cleanup efficiency. The general public expects that the government and/or the spiller know the location and the extent of the contamination. The Emergencies Science Division (ESD) of Environment Canada, is responsible for remote sensing during oil spill emergencies along Canada's three coastlines, extensive inland waterways, as well as over the entire land mass. In addition to providing operational remote sensing, ESD conducts research into the development of airborne oil spill remote sensors, including the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) and the Laser Ultrasonic Remote SEnsing of Oil Thickness (LURSOT) sensor. It has long been recognized that there is not one sensor or 'magic bullet' which is capable of detecting oil and related petroleum products in all environments and spill scenarios. There are sensors which possess a wide filed-of-view and can therefore be used to map the overall extent of the spill. These sensors, however lack the specificity required to positively identify oil and related products. This is even more of a problem along complicated beach and shoreline environments where several substrates are present. The specific laser- based sensors under development by Environment Canada are designed to respond to special roles in oil spill response. In particular, the SLEAF is being developed to unambiguously detect and map oil and related petroleum products in complicated marine and shoreline environments where other non-specific sensors experience difficulty. The role of the SLEAF would be to confirm or reject suspected oil contamination sites that have been targeted by the non- specific sensors. This confirmation will release response crews from the time consuming task of physically inspecting each site, and direct crews to sites that

  14. Central Asian Snow Cover Characteristics between 1986 and 2012 derived from Time Series of Medium Resolution Remote Sensing Data

    OpenAIRE

    2014-01-01

    The eminent importance of snow cover for climatic, hydrologic, anthropogenic, and economic reasons has been widely discussed in scientific literature. Up to 50% of the Northern Hemisphere is covered by snow at least temporarily, turning snow to the most prevalent land cover types at all. Depending on regular precipitation and temperatures below freezing point it is obvious that a changing climate effects snow cover characteristics fundamentally. Such changes can have severe impacts on local, ...

  15. What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series?

    NARCIS (Netherlands)

    Coops, N.C.; Schaepman, M.E.; Mücher, C.A.

    2013-01-01

    Understanding which environmental conditions are critical for species survival is a critical, ongoing question in ecology. These conditions can range from climate, at the broadest scale, through to elevation and other local landscape conditions, to fine scale landscape patterns of land cover and use

  16. Hyperspectral remote sensing techniques for grass nutrient estimations in savannah ecosystems

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2010-03-01

    Full Text Available at various scales such as local, regional and global scale. Traditional field techniques to measure grass nutrient concentration have been reported to be laborious and time consuming. Remote sensing techniques provide opportunity to map grass nutrient...

  17. Remote sensing applications in environmental research

    CERN Document Server

    Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir

    2014-01-01

    Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today's sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

  18. Remote Sensing of Bioindicators for Forest Health Assessment

    Science.gov (United States)

    Kefauver, Shawn Carlisle

    The impacts of tropospheric ozone on forest health in Mediterranean type climates in California, USA and Catalonia, Spain were investigated using a combination of remote sensing, Geographic Information System (GIS), and field studies focused on sensitive bioindicator conifer species and ambient ozone monitoring. For the field validation of impacts of tropospheric ozone on conifer health, the Ozone Injury Index (OII) was applied to the bioindicator species Pinus ponderosa, Pinus jeffreyi, and Pinus uncinata. Combining these three tools, it was possible to build meaningful ecological models covering large areas to enhance our understanding of the biotic and abiotic interactions which affect forest health. Regression models predicting ozone injury improved considerably when incorporating ozone exposure with GIS related to plant water status, including water availability and water usage, as a proxies for estimating the stomatal conductance and ozone uptake R2=0.35, p = 0.016 in Catalonia, R2=0.36, p < 0.001 in Yosemite and R2=0.33, p = 0.007 in Sequoia/Kings Canyon National Parks in California). Individual OII components in Catalonia were modeled with improved success compared to the original full OII, in particular visible chlorotic mottling (R2=0.60, p < 0.001). The visual chlorotic mottling component of the OII was the most strongly correlated to remote sensing indices, in particular the photochemical reflectance index (PRI; R2=0.28, p=0.0044 for OIIVI-amount and R 2=0.33 and p=0.0016 for OIIVI -severity). Regression models assessing ozone injury to conifers using imaging spectroscopy techniques also improved when incorporating the GIS proxies of stomatal conductance (R 2=0.59, p<0.0001 for OII in California and R2=0.68, p<0.0001 for OIIVI in Catalonia). Finally, taking advantage of a time series of ambient ozone monitoring in Catalonia, it was found that all models improved when incorporating the cumulative exposure to ozone over a period of three years (R2=0.56, p

  19. Radar-based remote sensing monitoring of roads

    OpenAIRE

    Crosetto, Michele; Monserrat, Oriol; Luzi, Guido; Cuevas-González, María; Devanthéry, Núria

    2014-01-01

    This paper provides a brief description of two powerful radar-based remote sensing techniques to monitor the deformations of roads, their associated infrastructures and, more in general, their surroundings. The first technique is the satellite radar interferometric technique. In this work a specific technique, named Persistent Scatterer Interferometry (PSI), is considered. This technique has wide-area coverage capability (e.g. covering thousands of square kilometres at the time) and,at the...

  20. remote sensing data combinations - global AOD maps

    Science.gov (United States)

    Kinne, S.

    2009-04-01

    More accurate and more complete measurement-based data-sets are needed to constrain the freedom of global modeling and raise confidence in model predictions. In remote sensing, different methods and sensors frequently yield estimates for the same (or a strongly related) atmospheric property. For maximum benefit to data-users (e.g. input or evaluation data to modeling) - in the context of differences in sensor capabilities and retrieval limitations - there is a desire to combine the strengths of these individual data sources for superior products. In a demonstration, different multi-annual global monthly maps for aerosol optical depth (AOD) from satellite remote sensing been compared and scored against local quality reference data from ground remote sensing. The regionally best performing satellite data-sets have been combined into global monthly AOD maps. As expected, this satellite composite scores better than any individual satellite retrieval. Further improvements are achieved by merging statistics of ground remote sensing into the composite. The global average mid-visible AOD of this remote sensing composite is near 0.13 annually, with lower values during northern hemispheric fall and winter (0.12) and larger values during northern hemispheric spring and summer (0.14). This measurement based data composite also reveals characteristic deficiencies in global modeling: Modeling tends to overestimates AOD over the northern mid-latitudes and to underestimate AOD over tropical and sub-tropical land regions. Also noteworthy are AOD underestimates by modeling in remote oceanic regions, though only in relative sense as AOD values in that region as small. The AOD remote sensing data composite is far from perfect, but it demonstrates the extra value of data-combinations.

  1. Time Series Momentum

    DEFF Research Database (Denmark)

    Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

    2012-01-01

    under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...... of speculators and hedgers, we find that speculators profit from time series momentum at the expense of hedgers....

  2. Periodic Time Series Models

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    2004-01-01

    textabstractThis book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book

  3. Anomaly Detection from Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Qiandong Guo

    2016-12-01

    Full Text Available Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection. In this study, two real hyperspectral data sets were used for anomaly detection. One data set was an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS data covering the post-attack World Trade Center (WTC and anomalies are fire spots. The other data set called SpecTIR contained fabric panels as anomalies compared to their background. Existing anomaly detection algorithms including the Reed–Xiaoli detector (RXD, the blocked adaptive computation efficient outlier nominator (BACON, the random selection based anomaly detector (RSAD, the weighted-RXD (W-RXD, and the probabilistic anomaly detector (PAD are reviewed here. The RXD generally sets strict assumptions to the background, which cannot be met in many scenarios, while BACON, RSAD, and W-RXD employ strategies to optimize the estimation of background information. The PAD firstly estimates both background information and anomaly information and then uses the information to conduct anomaly detection. Here, the BACON, RSAD, W-RXD, and PAD outperformed the RXD in terms of detection accuracy, and W-RXD and PAD required less time than BACON and RSAD.

  4. Visibility assesment using remote sensing data

    Science.gov (United States)

    Toanca, Florica; Vasilescu, Jeni; Nicolae, Doina; Stefan, Sabina

    2016-04-01

    Severe weather events like fog have a high impact on all kinds of traffic operations. During the last decade was proven the capability of remote sensing equipments to detect fog cases in terms of duration, occurrence and dissipation. Therefore, in this study the data from Väïsälä CL31 ceilometer and Raman Depolarization Lidar installed at Magurele, Romania (44.35 N, 26.03 E) were used. The backscatter coefficient from Ceilometer and extinction coefficient and different lidar ratios (LR) values from Lidar were used in order to determine horizontal visibility during the fog events in Magurele area. Ceilometer backscatter coefficient profiles are obtained with a time resolution of 16 s and up to 7.5 km altitude. . A neural network algorithm was used to calculate the lidar ratio values for different aerosol types and also for different relative humidity. Thus, for continental aerosol the LR value is 58srad, for continental polluted is 60srad and for smoke LR is 55srad. The average visibility computed for radiation fog , dominant type (57 cases) occurring in Magurele, during 2012-2014 was 50m. An important result is that the dependence of horizontal visibility for radiation fog at Magurele on LR is insignificant. This means that radiation, meteorological and geographical factors influence fog generation more much than aerosol type.

  5. 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.

  6. Spectroscopic Methods of Remote Sensing for Vegetation Characterization

    Science.gov (United States)

    Kokaly, R. F.

    2013-12-01

    been applied to map the distributions of minerals in soils and rocks; however, its application to characterize vegetation cover has been less widespread than SFA. Using IS data and the USGS Processing Routines in IDL for Spectroscopic Measurements (PRISM; http://pubs.usgs.gov/of/2011/1155/), this talk will examine requirements for and limitations in applying SFA and SFC to characterize vegetation. A time series of Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data collected in the marshes of Louisiana following the Deepwater Horizon oil spill will be used to examine the impact of varying leaf water content on the shapes of the SWIR 1700, 2100, and 2300 nm features and the implications of these changes on vegetation identification and biochemical estimation. The USGS collection of HyMap data over Afghanistan, the largest terrestrial coverage of IS data to date, will be used to demonstrate the characterization of vegetation in arid and semi-arid regions, in which chlorophyll absorption is often weak and soil and rock mineral absorption features overlap vegetation features. Hyperion data, overlapping the HyMap data, will be presented to illustrate the complications that arise when signal-to-noise is low. The benefits of and challenges to applying a spectroscopic remote sensing approach to imaging spectrometer data will be discussed.

  7. Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica

    Directory of Open Access Journals (Sweden)

    Xiuhong Li

    2016-11-01

    Full Text Available Of the modern technologies in polar-region monitoring, the remote sensing technology that can instantaneously form large-scale images has become much more important in helping acquire parameters such as the freezing and melting of ice as well as the surface temperature, which can be used in the research of global climate change, Antarctic ice sheet responses, and cap formation and evolution. However, the acquirement of those parameters is impacted remarkably by the climate and satellite transit time which makes it almost impossible to have timely and continuous observation data. In this research, a wireless sensor-based online monitoring platform (WSOOP for the extreme polar environment is applied to obtain a long-term series of data which is site-specific and continuous in time. Those data are compared and validated with the data from a weather station at Zhongshan Station Antarctica and the result shows an obvious correlation. Then those data are used to validate the remote sensing products of the freezing and melting of ice and the surface temperature and the result also indicated a similar correlation. The experiment in Antarctica has proven that WSOOP is an effective system to validate remotely sensed data in the polar region.

  8. Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica.

    Science.gov (United States)

    Li, Xiuhong; Cheng, Xiao; Yang, Rongjin; Liu, Qiang; Qiu, Yubao; Zhang, Jialin; Cai, Erli; Zhao, Long

    2016-11-17

    Of the modern technologies in polar-region monitoring, the remote sensing technology that can instantaneously form large-scale images has become much more important in helping acquire parameters such as the freezing and melting of ice as well as the surface temperature, which can be used in the research of global climate change, Antarctic ice sheet responses, and cap formation and evolution. However, the acquirement of those parameters is impacted remarkably by the climate and satellite transit time which makes it almost impossible to have timely and continuous observation data. In this research, a wireless sensor-based online monitoring platform (WSOOP) for the extreme polar environment is applied to obtain a long-term series of data which is site-specific and continuous in time. Those data are compared and validated with the data from a weather station at Zhongshan Station Antarctica and the result shows an obvious correlation. Then those data are used to validate the remote sensing products of the freezing and melting of ice and the surface temperature and the result also indicated a similar correlation. The experiment in Antarctica has proven that WSOOP is an effective system to validate remotely sensed data in the polar region.

  9. Thermal infrared remote sensing sensors, methods, applications

    CERN Document Server

    Kuenzer, Claudia

    2013-01-01

    This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techni

  10. Remotely sensing the photochemical reflectance index, PRI

    Science.gov (United States)

    Vanderbilt, Vern; Daughtry, Craig; Dahlgren, Robert

    2015-09-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside leaves in a plant stand. Developed by1,2, PRI evolved from laboratory reflectance measurements of individual leaves. Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We compared values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. Our results show the polarized leaf surface reflection should be removed when calculating PRI and that the leaf physiology information is in leaf interior reflectance, not leaf transmittance.

  11. 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...

  12. Monitoring water quality by remote sensing

    Science.gov (United States)

    Brown, R. L. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. A limited study was conducted to determine the applicability of remote sensing for evaluating water quality conditions in the San Francisco Bay and delta. Considerable supporting data were available for the study area from other than overflight sources, but short-term temporal and spatial variability precluded their use. The study results were not sufficient to shed much light on the subject, but it did appear that, with the present state of the art in image analysis and the large amount of ground truth needed, remote sensing has only limited application in monitoring water quality.

  13. Space remote sensing systems an introduction

    CERN Document Server

    Chen, H S

    1985-01-01

    Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

  14. Geobotanical Remote Sensing for Geothermal Exploration

    Energy Technology Data Exchange (ETDEWEB)

    Pickles, W L; Kasameyer, P W; Martini, B A; Potts, D C; Silver, E A

    2001-05-22

    This paper presents a plan for increasing the mapped resource base for geothermal exploration in the Western US. We plan to image large areas in the western US with recently developed high resolution hyperspectral geobotanical remote sensing tools. The proposed imaging systems have the ability to map visible faults, surface effluents, historical signatures, and discover subtle hidden faults and hidden thermal systems. Large regions can be imaged at reasonable costs. The technique of geobotanical remote sensing for geothermal signatures is based on recent successes in mapping faults and effluents the Long Valley Caldera and Mammoth Mountain in California.

  15. 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.

  16. A technology path to distributed remote sensing

    Science.gov (United States)

    Fountain, Glen H.; Gold, Robert E.; Jenkins, Robert E.; Lew, Ark L.; Raney, R. Keith

    2000-03-01

    The Johns Hopkins University Applied Physics Laboratory (APL) has been engaged for over 40 years in Earth science missions spanning geodesy to atmospheric science. In parallel, APL's Advanced Technology Program is supporting research in autonomy, scalable architectures, miniaturization, and instrument innovation. These are key technologies for the development of affordable observation programs that could benefit from distributed remote sensing. This paper brings these applications and technology themes together in the form of an innovative, three-satellite remote sensing scenario. This pathfinding mission fills an important scientific niche, and relies on state-of-the-art small-satellite technology.

  17. Remote sensing/vegetation classification. [California

    Science.gov (United States)

    Parker, I. E.

    1981-01-01

    The CALVEG classification system for identification of vegetation is described. This hierarchical system responds to classification requirements and to interpretation of vegetation at various description levels, from site description to broad identification levels. The system's major strength is its flexibility in application of remote sensing technology to assess, describe and communicate data relative to vegetative resources on a state-wide basis. It is concluded that multilevel remote sensing is a cost effective tool for assessment of the natural resource base. The CLAVEG system is found to be an economically efficient tool for both existing and potential vegetation.

  18. Optimized Radar Remote Sensing for Levee Health Monitoring

    Science.gov (United States)

    Jones, Cathleen E.

    2013-01-01

    Radar remote sensing offers great potential for high resolution monitoring of ground surface changes over large areas at one time to detect movement on and near levees and for location of seepage through levees. Our NASA-funded projects to monitor levees in the Sacramento Delta and the Mississippi River have developed and demonstrated methods to use radar remote sensing to measure quantities relevant to levee health and of great value to emergency response. The DHS-funded project will enable us is to define how to optimally monitor levees in this new way and set the stage for transition to using satellite SAR (synthetic aperture radar) imaging for better temporal and spatial coverage at lower cost to the end users.

  19. Application of airborne remote sensing to the ancient Pompeii site

    Science.gov (United States)

    Vitiello, Fausto; Giordano, Antonio; Borfecchia, Flavio; Martini, Sandro; De Cecco, Luigi

    1996-12-01

    The ancient Pompeii site is in the Sarno Valley, an area of about 400 km2 in the South of Italy near Naples, that was utilized by man since old time (thousands of years ago). Actually the valley is under critical environmental conditions because of the relevant industrial development. ENEA is conducting various studies and research in the valley. ENEA is employing historical research, ground campaigns, cartography and up-to-date airborne multispectral remote sensing technologies to make a geographical information system. Airborne remote sensing technologies are very suitable for situations as that of the Sarno Valley. The paper describes the archaeological application of the research in progress as regarding the ancient site of Pompeii and its fluvial port.

  20. Remote sensing for rural development planning in Africa

    Science.gov (United States)

    Dunford, C.; Mouat, D. A.; Norton-Griffiths, M.; Slaymaker, D. M.

    1983-01-01

    Multilevel remote-sensing techniques were combined to provide land resource and land-use information for rural development planning in Arusha Region, Tanzania. Enhanced Landsat imagery, supplemented by low-level aerial survey data, slope angle data from topographic sheets, and existing reports on vegetation and soil conditions, was used jointly by image analysts and district-level land-management officials to divide the region's six districts into land-planning units. District-planning officials selected a number of these land-planning units for priority planning and development activities. For the priority areas, natural color aerial photographs provided detailed information for land-use planning discussions between district officials and villagers. Consideration of the efficiency of this remote sensing approach leads to general recommendations for similar applications. The technology and timing of data collection and interpretation activities should allow maximum participation by intended users of the information.

  1. Ocean primary productivity estimation of China Sea by remote sensing

    Institute of Scientific and Technical Information of China (English)

    PAN Delu; GUAN Wenjiang; BAI Yan; HUANG Haiqing

    2005-01-01

    Ocean primary productivity is a key parameter in the research of global carbon cycle, ocean biological resources, and in evaluation of the feature and quality of ocean biological environment. Traditional shipboard measurement which is costly and time-consuming is impossible to obtain the spatial and temporal information on primary productivity on a large scale in a short period of time. Satellite remote sensing is an effective strategy to acquire the ocean information in near real time. Here we propose a model special for China Sea based on the concept of primary productivity using in situ primary productivity and environmental data from 1984 to 1990, and discuss every modeling parameter which can be retrieved by remote sensing in detail. The reliability of this model is tested by in situ data, and the comparison of other primary productivity models is made. We also analyze the temporal and spatial distribution of China Sea primary productivity in 2000. From our analysis the satellite remote sensing data have been proved very useful for ocean primary productivity study.

  2. Recent Progresses in Atmospheric Remote Sensing Research in China-- Chinese National Report on Atmospheric Remote Sensing Research in China during 1999-2003

    Institute of Scientific and Technical Information of China (English)

    邱金桓; 陈洪滨

    2004-01-01

    Progresses of atmospheric remote sensing research in China during 1999-2003 are summarily introduced.This research includes: (1) microwave remote sensing of the atmosphere; (2) Lidar remote sensing; (3)remote sensing of aerosol optical properties; and (4) other research related to atmospheric remote sensing,including GPS remote sensing of precipitable water vapor and radiation model development.

  3. Study on the construction of multi-dimensional Remote Sensing feature space for hydrological drought

    Science.gov (United States)

    Xiang, Daxiang; Tan, Debao; Cui, Yuanlai; Wen, Xiongfei; Shen, Shaohong; Li, Zhe

    2014-03-01

    Hydrological drought refers to an abnormal water shortage caused by precipitation and surface water shortages or a groundwater imbalance. Hydrological drought is reflected in a drop of surface water, decrease of vegetation productivity, increase of temperature difference between day and night and so on. Remote sensing permits the observation of surface water, vegetation, temperature and other information from a macro perspective. This paper analyzes the correlation relationship and differentiation of both remote sensing and surface measured indicators, after the selection and extraction a series of representative remote sensing characteristic parameters according to the spectral characterization of surface features in remote sensing imagery, such as vegetation index, surface temperature and surface water from HJ-1A/B CCD/IRS data. Finally, multi-dimensional remote sensing features such as hydrological drought are built on a intelligent collaborative model. Further, for the Dong-ting lake area, two drought events are analyzed for verification of multi-dimensional features using remote sensing data with different phases and field observation data. The experiments results proved that multi-dimensional features are a good method for hydrological drought.

  4. Remotely Sensed, catchment scale, estimations of flow resistance

    Science.gov (United States)

    Carbonneau, P.; Dugdale, S. J.

    2009-12-01

    Despite a decade of progress in the field of fluvial remote sensing, there are few published works using this new technology to advance and explore fundamental ideas and theories in fluvial geomorphology. This paper will apply remote sensing methods in order to re-visit a classic concept in fluvial geomorphology: flow resistance. Classic flow resistance equations such as those of Strickler and Keulegan typically use channel slope, channel depth or hydraulic radius and some measure channel roughness usually equated to the 50th or 84th percentile of the bed material size distribution. In this classic literature, empirical equations such as power laws are usually calibrated and validated with a maximum of a few hundred data points. In contrast, fluvial remote sensing methods are now capable of delivering millions of high resolution data points in continuous, catchment scale, surveys. On the river Tromie in Scotland, a full dataset or river characteristics is now available. Based on low altitude imagery and NextMap topographic data, this dataset has a continuous sampling of channel width at a resolution of 3cm, of depth and median grain size at a resolution of 1m, and of slope at a resolution of 5m. This entire data set is systematic and continuous for the entire 20km length of the river. When combined with discharge at the time of data acquisition, this new dataset offers the opportunity to re-examine flow resistance equations with a 2-4 orders of magnitude increase in calibration data. This paper will therefore re-examine the classic approaches of Strickler and Keulagan along with other more recent flow resistance equations. Ultimately, accurate predictions of flow resistance from remotely sensed parameters could lead to acceptable predictions of velocity. Such a usage of classic equations to predict velocity could allow lotic habitat models to account for microhabitat velocity at catchment scales without the recourse to advanced and computationally intensive

  5. Developing particle emission inventories using remote sensing (PEIRS).

    Science.gov (United States)

    Tang, Chia-Hsi; Coull, Brent A; Schwartz, Joel; Lyapustin, Alexei I; Di, Qian; Koutrakis, Petros

    2017-01-01

    Information regarding the magnitude and distribution of PM2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM2.5. This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R(2) = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

  6. Laser-based sensors for oil spill remote sensing

    Science.gov (United States)

    Brown, Carl E.; Fingas, Mervin F.; Mullin, Joseph V.

    1997-07-01

    Remote sensing is becoming an increasingly important tool for the effective direction of oil spill countermeasures. Cleanup personnel have recognized that remote sensing can increase spill cleanup efficiency. It has long been recognized that there is no one sensor which is capable of detecting oil and related petroleum products in all environments and spill scenarios. There are sensors which possess a wide field-of- view and can therefore be used to map the overall extent of the spill. These sensors, however lack the capability to positively identify oil and related products, especially along complicated beach and shoreline environments where several substrates are present. The laser-based sensors under development by the Emergencies Science Division of Environment Canada are designed to fill specific roles in oil spill response. The scanning laser environmental airborne fluorosensor (SLEAF) is being developed to detect and map oil and related petroleum products in complex marine and shoreline environments where other non-specific sensors experience difficulty. The role of the SLEAF would be to confirm or reject suspected oil contamination sites that have been targeted by the non-specific sensors. This confirmation will release response crews from the time-consuming task of physically inspecting each site, and direct crews to sites that require remediation. The laser ultrasonic remote sensing of oil thickness (LURSOT) sensor will provide an absolute measurement of oil thickness from an airborne platform. There are presently no sensors available, either airborne or in the laboratory which can provide an absolute measurement of oil thickness. This information is necessary for the effective direction of spill countermeasures such as dispersant application and in-situ burning. This paper describes the development of laser-based airborne oil spill remote sensing instrumentation at Environment Canada and identifies the anticipated benefits of the use of this technology

  7. Malaria Modeling using Remote Sensing and GIS Technologies

    Science.gov (United States)

    Kiang, Richard

    2004-01-01

    Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

  8. Malaria Modeling using Remote Sensing and GIS Technologies

    Science.gov (United States)

    Kiang, Richard

    2004-01-01

    Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

  9. Beyond Monitoring: A Brief Review of the Use of Remote Sensing Technology for Assessing Dryland Sustainability

    Science.gov (United States)

    Washington-Allen, R. A.

    2015-12-01

    Drylands cover 41% of the terrestrial surface and provide > $1 trillion in ecosystem services to one-third of the global population, yet are not well studied with estimates of degradation ranging from 10 - 80%. Here I will present an abbreviated history of the use of remote sensing (RS) to monitor Dryland degradation, review contemporary applications, and provide guidance for future directions. These early monitoring attempts (and some recent efforts) assumed the social model of "Tragedy of the Commons" and the ecological model of "the Balance of Nature". These assumptions justified a monitoring approach rather than an assessment, where land degradation was understood to be primarily a function of human action through livestock grazing management. The perceived linear impact of grazing on grassland biomass led to the early development of a remote sensing-based proxy of vegetation response: the normalized difference vegetation index (NDVI). Many RS studies of Drylands are biased towards the NDVI or variants, whereas the contemporary view of Drylands as complex systems has led to a new synthesis of approaches from ecological modeling, ecohydrology, landscape ecology, and remote sensing that now explicitly confront both multiple drivers that include land-use policy, droughts & floods, fire, and responses that include increased soil erosion and changes in soil quality, landscape composition, pattern, and structure. However, problems still abound including 1) a consensus on the definition of Drylands, 2) the need for time series of drivers to conduct assessments, 3) a lack of understanding of below-ground biomass dynamics, 4) improved mapping of grassland, shrubland, and savanna dryland cover types and their 3D structure. There are new technologies in Dryland RS including multi-frequency ground penetrating radar (GPR), RADAR, IFSAR, LIDAR, and MISR that may lead to the development of new indicators to address these issues.

  10. Application of optical remote sensing in the Wenchuan earthquake assessment

    Science.gov (United States)

    Zhang, Bing; Lei, Liping; Zhang, Li; Liu, Liangyun; Zhu, Boqin; Zuo, Zhengli

    2009-06-01

    A mega-earthquake of magnitude 8 of Richter scale occurred in Wenchuan County, Sichuan Province, China on May 12, 2008. The earthquake inflicted heavy loss of human lives and properties. The Wenchuan earthquake induced geological disasters, house collapse, and road blockage. In this paper, we demonstrate an application of optical remote sensing images acquired from airborne and satellite platforms in assessing the earthquake damages. The high-resolution airborne images were acquired by the Chinese Academy of Sciences (CAS). The pre- and post-earthquake satellite images of QuickBird, IKONOS, Landsat TM, ALOS, and SPOT were collected by the Center for Earth Observation & Digital Earth (CEODE), CAS, and some of the satellite data were provided by the United States, Japan, and the European Space Agency. The pre- and post-earthquake remote sensing images integrated with DEM and GIS data were adopted to monitor and analyze various earthquake disasters, such as road blockage, house collapse, landslides, avalanches, rock debris flows, and barrier lakes. The results showed that airborne optical images provide a convenient tool for quick and timely monitoring and assessing of the distribution and dynamic changes of the disasters over the earthquake-struck regions. In addition, our study showed that the optical remote sensing data integrated with GIS data can be used to assess disaster conditions such as damaged farmlands, soil erosion, etc, which in turn provides useful information for the postdisaster reconstruction.

  11. Super-resolution Restoration of Remote-sensing Images

    Institute of Scientific and Technical Information of China (English)

    LIU Yang-yang; JIN Wei-qi; SU Bing-hua; CHEN Hua; ZHANG Nan

    2006-01-01

    A novel image restoration scheme, which is super-resolution image restoration algorithm Poisson-maximum-afterword-probability based on Markvo constraint (MPMAP) combined with evaluating image detail parameter D, has been proposed. The advantage of super-resolution algorithm MPMAP incorporated with parameter D lies in the fact that super-resolution algorithm MPMAP model is discrete, which is in accordance with remote-sensing imaging model, and the algorithm MPMAP is proved applicable to linear and non-linear imaging models with a unique solution when noise is not severe. According to simulation experiments for practical images, super-resolution algorithm MPMAP can retain image details better than most of traditional restoration methods; at the same time, the proposed parameter D can help to identify real point spread function (PSF) value of degradation process. Processing result of practical remote-sensing images by MPMAP combined with parameter D are given, it illustrates that MPMAP restoration scheme combined PSF estimation has a better restoration result than that of Photoshop processing, based on the same original images. It is proved that the proposed scheme is helpful to offset the lack of resolution of the original remote-sensing images and has its extensive application foreground.

  12. Parallelized LEDAPS method for Remote Sensing Preprocessing Based on MPI

    Institute of Scientific and Technical Information of China (English)

    Xionghua; CHEN; Xu; ZHANG; Ying; GUO; Yong; MA; Yanchen; YANG

    2013-01-01

    Based on Landsat image,the Landsat Ecosystem Disturbance Adaptive Processing System(LEDAPS)uses radiation change detection method for image processing and offers the surface reflectivity products for ecosystem carbon sequestration and carbon reserves.As the accumulation of massive remote sensing data especially for the Landsat image,the traditional serial LEDAPS for image processing has a long cycle that make a lot of difficulties in practical application.For this problem,this paper design a high performance parallel LEDAPS processing method based on MPI.The results not only aimed to improve the calculation speed and save computing time,but also considered the load balance between the flexibly extended computing nodes.Results show that the highest speed ratio of parallelized LEDAPS reached 7.37 when the number of MPI process is 8.It effectively improves the ability of LEDAPS to handle massive remote sensing data and reduces the forest carbon stocks calculation cycle by using the remote sensing images.

  13. [Review of monitoring soil water content using hyperspectral remote sensing].

    Science.gov (United States)

    Wu, Dai-hui; Fan, Wen-jie; Cui, Yao-kui; Yan, Bin-yan; Xu, Xi-ru

    2010-11-01

    Soil water content is a key parameter in monitoring drought. In recent years, a lot of work has been done on monitoring soil water content based on hyperspectral remotely sensed data both at home and abroad. In the present review, theories, advantages and disadvantages of the monitoring methods using different bands are introduced first. Then the unique advantages, as well as the problems, of the monitoring method with the aid of hyperspectral remote sensing are analyzed. In addition, the impact of soil water content on soil reflectance spectrum and the difference between values at different wavelengths are summarized. This review lists and summarizes the quantitative relationships between soil water content and soil reflectance obtained through analyzing the physical mechanism as well as through statistical way. The key points, advantages and disadvantages of each model are also analyzed and evaluated. Then, the problems in experimental study are pointed out, and the corresponding solutions are proposed. At the same time, the feasibility of removing vegetation effect is discussed, when monitoring soil water content using hyperspectral remote sensing. Finally, the future research trend is prospected.

  14. Advances in remote sensing of vegetation function and traits

    KAUST Repository

    Houborg, Rasmus

    2015-07-09

    Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.

  15. Assessment of remotely sensed drought features in vulnerable agriculture

    Directory of Open Access Journals (Sweden)

    N. R. Dalezios

    2012-10-01

    Full Text Available The growing number and effectiveness of Earth observation satellite systems, along with the increasing reliability of remote sensing methodologies and techniques, present a wide range of new capabilities in monitoring and assessing droughts. A number of drought indices have been developed based on NOAA-AVHRR data exploiting the remote sensing potential at different temporal scales. In this paper, the remotely sensed Reconnaissance Drought Index (RDI is employed for the quantification of drought. RDI enables the assessment of hydro-meteorological drought, since it uses hydrometeorological parameters, such as precipitation and potential evapotranspiration. The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Several drought features are analyzed and assessed by using monthly RDI images over the period 1981–2001: severity, areal extent, duration, periodicity, onset and end time. The results show an increase in the areal extent during each drought episode and that droughts are classified into two classes, namely small areal extent drought and large areal extent drought, respectively, lasting 12 or 13 months coinciding closely with the hydrological year. The onset of large droughts coincides with the beginning of the hydrological year, whereas the onset of small droughts is in spring. During each drought episode, the maximum occurs usually in the summer and they all last until the end of the hydrological year. This finding could justify an empirical prognostic potential of drought assessment.

  16. 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...

  17. Remote sensing and today's forestry issues

    Science.gov (United States)

    Sayn-Wittgenstein, L.

    1977-01-01

    The actual and the desirable roles of remote sensing in dealing with current forestry issues, such as national forest policy, supply and demand for forest products and competing demands for forest land are discussed. Topics covered include wood shortage, regional timber inventories, forests in tropical and temperate zones, Skylab photography, forest management and protection, available biomass studies, and monitoring.

  18. 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...

  19. Multisensor image fusion guidelines in remote sensing

    Science.gov (United States)

    Pohl, C.

    2016-04-01

    Remote sensing delivers multimodal and -temporal data from the Earth's surface. In order to cope with these multidimensional data sources and to make the most of them, image fusion is a valuable tool. It has developed over the past few decades into a usable image processing technique for extracting information of higher quality and reliability. As more sensors and advanced image fusion techniques have become available, researchers have conducted a vast amount of successful studies using image fusion. However, the definition of an appropriate workflow prior to processing the imagery requires knowledge in all related fields - i.e. remote sensing, image fusion and the desired image exploitation processing. From the findings of this research it can be seen that the choice of the appropriate technique, as well as the fine-tuning of the individual parameters of this technique, is crucial. There is still a lack of strategic guidelines due to the complexity and variability of data selection, processing techniques and applications. This paper gives an overview on the state-of-the-art in remote sensing image fusion including sensors and applications. Putting research results in image fusion from the past 15 years into a context provides a new view on the subject and helps other researchers to build their innovation on these findings. Recommendations of experts help to understand further needs to achieve feasible strategies in remote sensing image fusion.

  20. Remote sensing information sciences research group

    Science.gov (United States)

    Estes, John E.; Smith, Terence; Star, Jeffrey L.

    1988-01-01

    Research conducted under this grant was used to extend and expand existing remote sensing activities at the University of California, Santa Barbara in the areas of georeferenced information systems, matching assisted information extraction from image data and large spatial data bases, artificial intelligence, and vegetation analysis and modeling. The research thrusts during the past year are summarized. The projects are discussed in some detail.

  1. Remote Sensing Analysis of Forest Disturbances

    Science.gov (United States)

    Asner, Gregory P. (Inventor)

    2015-01-01

    The present invention provides systems and methods to automatically analyze Landsat satellite data of forests. The present invention can easily be used to monitor any type of forest disturbance such as from selective logging, agriculture, cattle ranching, natural hazards (fire, wind events, storms), etc. The present invention provides a large-scale, high-resolution, automated remote sensing analysis of such disturbances.

  2. 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...

  3. 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.

  4. 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.

  5. Multivariate Time Series Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  6. Managing and distributing remote sensing images based on metadata and microimage

    Science.gov (United States)

    Su, Lihong; Deng, Xiaolian; Wang, Jindi; Li, Xiaowen

    2003-06-01

    Remote sensing images acquired by the sensors at platforms near land surface, airplane and satellite, usually have large volume and miscellaneous data formats. So it is not feasible for the users to browse remote sensing images and evaluate the quality of images and select the suitable images on Internet. Moreover, it is inefficient to read and transfer remote sensing images real-timely in a standard image viewer due to their miscellaneous data formats. In order to clear up the problems, the metadata and microimage are extracted from various remote sensing images, managed by the database management system software, and browsed and evaluated on Internet to decide which images are the real wanted. The process of working includes the 4 steps (1) Create metadata for the remote sensing images. The metadata consist of image data format, longitude and latitude of image range, data and time, spatial resolution, sensor attributes (field of view, bands, performance and precision etc), platform attributes (stand near land surface, airplane or satellite), flight path or orbit attributes of aerial and space observation etc. (2) Create microimage for remote sensing image. Firstly, the remote sensing images are projected to the same coordinate system by the geometric correction, so all images can be matched correctly. Then the microimages are built through 1:10 or 1:5 cubic convolution sampling the corrected images. (3) Build a database to store and manage the metadata and microimages, and create pointers to hyperlink the remote sensing images self. (4) Develop the browse interface, publish the remote sensing image base on Internet, and receive the users' order forms. The wanted images will be sent on CDROM if the orders are accepted. The interface is visualized. Here, a color spectrum is used to express the bands. A clock is for time and landscape is for days in one year. And place is located by moving your mouse on the map. The pixel sizes are shown through levels on a pyramid

  7. Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

    Science.gov (United States)

    Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

    2015-12-01

    Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in

  8. Long time series

    DEFF Research Database (Denmark)

    Hisdal, H.; Holmqvist, E.; Hyvärinen, V.;

    Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

  9. Long time series

    DEFF Research Database (Denmark)

    Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

    Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

  10. Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects

    Science.gov (United States)

    Robert E. Kennedy; Philip A. Townsend; John E. Gross; Warren B. Cohen; Paul Bolstad; Wang Y. Q.; Phyllis Adams

    2009-01-01

    Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis...

  11. Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones

    CSIR Research Space (South Africa)

    Rowlinson, LC

    1999-10-01

    Full Text Available of large amounts of water from riparian zones, is one of the methods of maximising water supply in South Africa. Remote sensing is a cost- and time-effective technique for identifying alien vegetation in riparian zones and remote sensing data can...

  12. Hyperspectral Remote Sensing of Foliar Nitrogen Content

    Science.gov (United States)

    Knyazikhin, Yuri; Schull, Mitchell A.; Stenberg, Pauline; Moettus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Carmona, Pedro Latorre; Kaufmann, Robert K.; Lewis, Philip; Disney, Mathias I.; Vanderbilt, Vern; Davis, Anthony B.; Baret, Frederic; Jacquemoud, Stephane; Lyapustin, Alexei; Myneni, Ranga B.

    2013-01-01

    A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact - it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

  13. AmericaView - A State-Based Remote Sensing Initiative Integrating Remote Sensing Data Into Geospatial Education and Applications

    Science.gov (United States)

    Dodge, R. L.; Lawrence, R.

    2007-12-01

    AmericaView (AV) is a national program created to advance the availability, timely distribution, and widespread use of land remote sensing data, especially among users within the university and government communities. Since the 1970s the federal government and private sector have spent billions of dollars on satellite-based earth observing systems, but distribution of data and development of real-world applications have been tough issues for the government and the academic research communities. It has often been hard for researchers to use or even access the data, particularly at smaller schools or research facilities, hindering applied research and current and future workforce development. Many state and local agencies working with applied research programs have not been able to effectively integrate remote sensing data into their geospatial management or decision-support programs. AV addresses these issues through a partnership between the U.S. Geological Survey and the AmericaView Consortium, which is a 501c3 non-profit comprised of university-led, state-based consortia. AmericaView is the federal government's partner in achieving the program vision and goals, which focus both on making data available in usable, cost-effective formats and on helping the university, secondary-education, and public sectors in each state identify, develop, and implement the kinds of remote sensing applications each state needs most. AV is developing applied remote sensing research programs in each of its thirty StateViews. Partner academic institutions are creating internships programs involving students and faculty with applications development, in cooperation with local, state, and federal government agencies. Education and training outreach programs are improving workforce preparation at K-12, post-secondary, and professional levels. Data distribution and sharing infrastructure that leverages funding and avoids duplication is enabling practical archive expansion and distribution

  14. Mapping Irrigated Areas of Ghana Using Fusion of 30 m and 250 m Resolution Remote-Sensing Data

    Directory of Open Access Journals (Sweden)

    Arnel Rala

    2011-04-01

    Full Text Available Maps of irrigated areas are essential for Ghana’s agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+ data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS data were used to map irrigated agricultural areas as well as other land use/land cover (LULC classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks and dug-outs (in river bottoms that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha was 20–57% higher than irrigated areas reported by Ghana’s Irrigation Development Authority (GIDA. This was because of the uncertainties involved in factors such as: (a absence of shallow irrigated area statistics in GIDA statistics, (b non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c errors of omissions and commissions in the remote sensing approach, and (d comparison involving widely varying data types, methods, and approaches used in determining irrigated

  15. Mapping irrigated areas of Ghana using fusion of 30 m and 250 m resolution remote-sensing data

    Science.gov (United States)

    Gumma, M.K.; Thenkabail, P.S.; Hideto, F.; Nelson, A.; Dheeravath, V.; Busia, D.; Rala, A.

    2011-01-01

    Maps of irrigated areas are essential for Ghana's agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+) data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to map irrigated agricultural areas as well as other land use/land cover (LULC) classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI) pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks) and dug-outs (in river bottoms) that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha) was 20-57% higher than irrigated areas reported by Ghana's Irrigation Development Authority (GIDA). This was because of the uncertainties involved in factors such as: (a) absence of shallow irrigated area statistics in GIDA statistics, (b) non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c) errors of omissions and commissions in the remote sensing approach, and (d) comparison involving widely varying data types, methods, and approaches used in determining irrigated area statistics

  16. NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

    NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through

  17. NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

    NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through

  18. Research Status and Development Trend of Remote Sensing in China Using Bibliometric Analysis

    Science.gov (United States)

    Zeng, Y.; Zhang, J.; Niu, R.

    2015-06-01

    Remote sensing was introduced into China in 1970s and then began to flourish. At present, China has developed into a big remote sensing country, and remote sensing is increasingly playing an important role in various fields of national economic construction and social development. Based on China Academic Journals Full-text Database and China Citation Database published by China National Knowledge Infrastructure, this paper analyzed academic characteristics of 963 highly cited papers published by 16 professional and academic journals in the field of surveying and mapping from January 2010 to December 2014 in China, which include hot topics, literature authors, research institutions, and fundations. At the same time, it studied a total of 51,149 keywords published by these 16 journals during the same period. Firstly by keyword selection, keyword normalization, keyword consistency and keyword incorporation, and then by analysis of high frequency keywords, the progress and prospect of China's remote sensing technology in data acquisition, data processing and applications during the past five years were further explored and revealed. It can be seen that: highly cited paper analysis and word frequency analysis is complementary on subject progress analysis; in data acquisition phase, research focus is new civilian remote sensing satellite systems and UAV remote sensing system; research focus of data processing and analysis is multi-source information extraction and classification, laser point cloud data processing, objectoriented high resolution image analysis, SAR data and hyper-spectral image processing, etc.; development trend of remote sensing data processing is quantitative, intelligent, automated, and real-time, and the breadth and depth of remote sensing application is gradually increased; parallel computing, cloud computing and geographic conditions monitoring and census are the new research focuses to be paid attention to.

  19. Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

    Science.gov (United States)

    Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

    2016-04-01

    A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

  20. Wageningen UR Unmanned Aerial Remote Sensing Facility - Overview of activities

    Science.gov (United States)

    Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe

    2016-04-01

    To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all

  1. Geometric calibration of high-resolution remote sensing sensors

    Institute of Scientific and Technical Information of China (English)

    LIANG Hong-you; GU Xing-fa; TAO Yu; QIAO Chao-fei

    2007-01-01

    This paper introduces the applications of high-resolution remote sensing imagery and the necessity of geometric calibration for remote sensing sensors considering assurance of the geometric accuracy of remote sensing imagery. Then the paper analyzes the general methodology of geometric calibration. Taking the DMC sensor geometric calibration as an example, the paper discusses the whole calibration procedure. Finally, it gave some concluding remarks on geometric calibration of high-resolution remote sensing sensors.

  2. A Map-Reduce-enabled SOLAP cube for large-scale remotely sensed data aggregation

    Science.gov (United States)

    Li, Jiyuan; Meng, Lingkui; Wang, Frank Z.; Zhang, Wen; Cai, Yang

    2014-09-01

    Spatial On-Line Analytical Processing (SOLAP) is a powerful decision support systems tool for exploring the multidimensional perspective of spatial data. In recent years, remotely sensed data have been integrated into SOLAP cubes, and this improvement has advantages in spatio-temporal analysis for environment monitoring. However, the performance of aggregations in SOLAP still faces a considerable challenge from the large-scale dataset generated by Earth observation. From the perspective of data parallelism, a tile-based SOLAP cube model, the so-called Tile Cube, is presented in this paper. The novel model implements Roll-Up/Drill-Across operations in the SOLAP environment based on Map-Reduce, a popular data-intensive computing paradigm, and improves the throughput and scalability of raster aggregation. Therefore, the long time-series, wide-range and multi-view analysis of remotely sensed data can be processed in a short time. The Tile Cube prototype was built on Hadoop/Hbase, and drought monitoring is used as an example to illustrate the aggregations in the model. The performance testing indicated the model can be scaled along with both the data growth and node growth. It is applicable and natural to integrate the SOLAP cube with Map-Reduce. Factors that influence the performance are also discussed, and the balance of them will be considered in future works to make full use of data locality for model optimisation.

  3. Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

    Science.gov (United States)

    Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

    2016-05-01

    Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

  4. Fast-earth: A global image caching architecture for fast access to remote-sensing data

    Science.gov (United States)

    Talbot, B. G.; Talbot, L. M.

    We introduce Fast-Earth, a novel server architecture that enables rapid access to remote sensing data. Fast-Earth subdivides a WGS-84 model of the earth into small 400 × 400 meter regions with fixed locations, called plats. The resulting 3,187,932,913 indexed plats are accessed with a rapid look-up algorithm. Whereas many traditional databases store large original images as a series by collection time, requiring long searches and slow access times for user queries, the Fast-Earth architecture enables rapid access. We have prototyped a system in conjunction with a Fast-Responder mobile app to demonstrate and evaluate the concepts. We found that new data could be indexed rapidly in about 10 minutes/terabyte, high-resolution images could be chipped in less than a second, and 250 kB image chips could be delivered over a 3G network in about 3 seconds. The prototype server implemented on a very small computer could handle 100 users, but the concept is scalable. Fast-Earth enables dramatic advances in rapid dissemination of remote sensing data for mobile platforms as well as desktop enterprises.

  5. Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

    Science.gov (United States)

    Quattrochi, Dale A.; Luvall, Jeffrey C.

    1998-01-01

    Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of

  6. Towards operational environmental applications using terrestrial remote sensing

    NARCIS (Netherlands)

    Veldkamp JG; Velde RJ van de; LBG

    1996-01-01

    Dit rapport beschrijft de resultaten van het Beleidscommissie Remote Sensing (BCRS) project 'Verankering van toepassingen van terrestrische remote sensing bij RIVM'. Het had ten eerste tot doel te voldoen aan de voorwaarden, zoals gesteld in de inventarisatie van remote sensing als

  7. An introduction to quantitative remote sensing. [data processing

    Science.gov (United States)

    Lindenlaub, J. C.; Russell, J.

    1974-01-01

    The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

  8. Near-earth orbital guidance and remote sensing

    Science.gov (United States)

    Powers, W. F.

    1972-01-01

    The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

  9. The application of hyperspectral remote sensing to coast environment investigation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Liang; ZHANG bing; CHEN Zhengchao; ZHENG Lanfen; TONG Qingxi

    2009-01-01

    Requirements for monitoring the coastal zone environment are first summarized. Then the application of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

  10. NASA Remote Sensing Data for Epidemiological Studies

    Science.gov (United States)

    Maynard, Nancy G.; Vicente, G. A.

    2002-01-01

    In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.

  11. Comparison of time series using entropy and mutual correlation

    Science.gov (United States)

    Madonna, Fabio; Rosoldi, Marco

    2015-04-01

    The potential for redundant time series to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. Moreover, comparison among time series of in situ and ground based remote sensing measurements have been performed using several methods, but quite often relying on linear models. In this work, the concepts of entropy (H) and mutual correlation (MC), defined in the frame of the information theory, are applied to the study of essential climate variables with the aim of characterizing the uncertainty of a time series and the redundancy of collocated measurements provided by different surface-based techniques. In particular, integrated water vapor (IWV) and water vapour mixing ratio times series obtained at five highly instrumented GRUAN (GCOS, Global Climate Observing System, Reference Upper-Air Network) stations with several sensors (e.g radiosondes, GPS, microwave and infrared radiometers, Raman lidar), in the period from 2010-2012, are analyzed in terms of H and MC. The comparison between the probability density functions of the time series shows that caution in using linear assumptions is needed and the use of statistics, like entropy, that are robust to outliers, is recommended to investigate measurements time series. Results reveals that the random uncertainties on the IWV measured with radiosondes, global positioning system, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8 % over the considered time period. Comparisons of the time series of IWV content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy with the IWV time series measured by radiosondes and therefore the highest potential to reduce the random uncertainty of the radiosondes time series. Moreover, the random uncertainty of a time series from one instrument can be reduced by 60% by constraining the measurements with those from

  12. Multi- and hyperspectral remote sensing of tropical marine benthic habitats

    Science.gov (United States)

    Mishra, Deepak R.

    Tropical marine benthic habitats such as coral reef and associated environments are severely endangered because of the environmental degradation coupled with hurricanes, El Nino events, coastal pollution and runoff, tourism, and economic development. To monitor and protect this diverse environment it is important to not only develop baseline maps depicting their spatial distribution but also to document their changing conditions over time. Remote sensing offers an important means of delineating and monitoring coral reef ecosystems. Over the last twenty years the scientific community has been investigating the use and potential of remote sensing techniques to determine the conditions of the coral reefs by analyzing their spectral characteristics from space. One of the problems in monitoring coral reefs from space is the effect of the water column on the remotely sensed signal. When light penetrates water its intensity decreases exponentially with increasing depth. This process, known as water column attenuation, exerts a profound effect on remotely sensed data collected over water bodies. The approach presented in this research focuses on the development of semi-analytical models that resolves the confounding influence water column attenuation on substrate reflectance to characterize benthic habitats from high resolution remotely sensed imagery on a per-pixel basis. High spatial resolution satellite and airborne imagery were used as inputs in the models to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). These parameters were subsequently used in various bio-optical algorithms to deduce bottom albedo and then to classify the benthos, generating a detailed map of benthic habitats. IKONOS and QuickBird multispectral satellite data and AISA Eagle hyperspectral airborne data were used in this research for benthic habitat mapping along the north shore of Roatan Island, Honduras. The AISA Eagle classification was

  13. Introduction to This Special Issue on Geostatistics and Geospatial Techniques in Remote Sensing

    Science.gov (United States)

    Atkinson, Peter; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

    2000-01-01

    The germination of this special Computers & Geosciences (C&G) issue began at the Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG) annual meeting in January 1997 held at the University of Exeter, UK. The snow and cold of the English winter were tempered greatly by warm and cordial discussion of how to stimulate and enhance cooperation on geostatistical and geospatial research in remote sensing 'across the big pond' between UK and US researchers. It was decided that one way forward would be to hold parallel sessions in 1998 on geostatistical and geospatial research in remote sensing at appropriate venues in both the UK and the US. Selected papers given at these sessions would be published as special issues of C&G on the UK side and Photogrammetric Engineering and Remote Sensing (PE&RS) on the US side. These issues would highlight the commonality in research on geostatistical and geospatial research in remote sensing on both sides of the Atlantic Ocean. As a consequence, a session on "Geostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the RGS-IBG annual meeting in Guildford, Surrey, UK in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). A similar session was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). The 10 papers that make up this issue of C&G, comprise 7 papers from the UK and 3 papers from the LIS. We are both co-editors of each of the journal special issues, with the lead editor of each journal issue being from their respective side of the Atlantic. The special issue of PE&RS (vol. 65) that constitutes the other half of this co-edited journal series was published in early 1999, comprising 6 papers by US authors. We are indebted to the International Association for Mathematical

  14. Comparison of remote sensing indices for monitoring of desert cienegas

    Science.gov (United States)

    Wilson, Natalie R; Norman, Laura M.; Villarreal, Miguel; Gass, Leila; Tiller, Ron; Salywon, Andrew

    2016-01-01

    This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.

  15. An experiment using mid and thermal infrared in quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    The concept of quantum remote sensing and the differences between quantum remote sensing and remote sensing is introduced, an experiment about the uses of mid and thermal infrared in quantum remote sensing is described and results are analyzed.

  16. Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil

    Science.gov (United States)

    Oliveira, Eduardo N.; Fernandes, Alexandre M.; Kampel, Milton; Cordeiro, Renato C.; Brandini, Nilva; Vinzon, Susana B.; Grassi, Renata M.; Pinto, Fernando N.; Fillipo, Alessandro M.; Paranhos, Rodolfo

    2016-04-01

    The Guanabara Bay (GB) is an estuarine system in the metropolitan region of Rio de Janeiro (Brazil), with a surface area of ˜346 km2 threatened by anthropogenic pressure. Remote sensing can provide frequent data for studies and monitoring of water quality parameters, such as chlorophyll-a concentration (Chl-a). Different combination of Medium Resolution Imaging Spectrometer (MERIS) remote sensing reflectance band ratios were used to estimate Chl-a. Standard algorithms such as Ocean Color 3-band, Ocean Color-4 band, fluorescence line height, and maximum chlorophyll index were also tested. The MERIS Chl-a estimates were statistically compared with a dataset of in situ Chl-a (2002 to 2012). Good correlations were obtained with the use of green, red, and near-infrared bands. The best performing algorithm was based on the red (665 nm) and green (560 nm) band ratio, named "RG3" algorithm (r2=0.71, chl-a=62,565*x1.6118). The RG3 was applied to a time series of MERIS images (2003- to 2012). The GB has a high temporal and spatial variability of Chl-a, with highest values found in the wet season (October to March) and in some of the most internal regions of the estuary. Lowest concentrations are found in the central circulation channel due to the flushing of ocean water masses promoted by pumping tide.

  17. Remote Sensing as a Tool to Track Algal Blooms in the Great Salt Lake, Utah, USA

    Science.gov (United States)

    Bradt, S. R.; Wurtsbaugh, W. A.; Naftz, D.; Moore, T.; Haney, J.

    2006-12-01

    The Great Salt Lake is a large hypersaline, terminal water body in northern Utah, USA. The lake has both a significant economic importance to the local community as a source of brine shrimp and mineral resources, as well as, an ecological importance to large numbers of migratory waterfowl. Due to nutrient input from sewage treatment plants, sections of the Great Salt Lake are subjected to highly eutrophic conditions. One of the main tributaries, Farmington Bay, experiences massive blooms of cyanobacteria which can reach concentrations in excess of 300 mg l-1 in the bay. Effects of these blooms can be observed stretching into the rest of the lake. The detrimental outcomes of the blooms include unsightly scums, foul odor and the danger of cyanobacterial toxins. While the blooms have an obvious effect on Farmington Bay, it is quite possible that the cyanobacteria impact a much wider area of the lake as currents move eutrophic water masses. Of particular interest is the reaction of brine shrimp to the plumes of cyanobacteria-rich water leaving Farmington Bay. We are employing remote sensing as a tool to map the distribution of algae throughout the lake and produce lake-wide maps of water quality on a regular basis. On-lake reflectance measurements have been coupled with MODIS satellite imagery to produce a time series of maps illustrating changes in algal distribution. The successes and shortcomings of our remote sensing technique will be a central topic of this presentation.

  18. Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes

    NARCIS (Netherlands)

    Eberenz, Johannes; Verbesselt, Jan; Herold, Martin; Tsendbazar, Nandika; Sabatino, Giovanni; Rivolta, Giancarlo

    2016-01-01

    Satellite based land cover classification for Africa’s semi-arid ecosystems is hampered commonly by heterogeneous landscapes with mixed vegetation and small scale land use. Higher spatial resolution remote sensing time series data can improve classification results under these difficult conditions.

  19. Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes

    NARCIS (Netherlands)

    Eberenz, Johannes; Verbesselt, Jan; Herold, Martin; Tsendbazar, Nandika; Sabatino, Giovanni; Rivolta, Giancarlo

    2016-01-01

    Satellite based land cover classification for Africa’s semi-arid ecosystems is hampered commonly by heterogeneous landscapes with mixed vegetation and small scale land use. Higher spatial resolution remote sensing time series data can improve classification results under these difficult conditions.

  20. Time series analysis

    CERN Document Server

    Madsen, Henrik

    2007-01-01

    ""In this book the author gives a detailed account of estimation, identification methodologies for univariate and multivariate stationary time-series models. The interesting aspect of this introductory book is that it contains several real data sets and the author made an effort to explain and motivate the methodology with real data. … this introductory book will be interesting and useful not only to undergraduate students in the UK universities but also to statisticians who are keen to learn time-series techniques and keen to apply them. I have no hesitation in recommending the book.""-Journa

  1. Applied time series analysis

    CERN Document Server

    Woodward, Wayne A; Elliott, Alan C

    2011-01-01

    ""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

  2. Remote sensing for disaster mitigation of Sinabung

    Science.gov (United States)

    Tampubolon, T.; Yanti, J.

    2016-05-01

    Indonesia, a country with many active volcanoes, potentially occur natural disaster due to eruptions. One of volcanoes at Indonesia was Sinabung mountain, that located on Karo Regency, North Sumatera 3°10'12″ N 98°23'31" E, 2,460 masl. A fasile and new observation method for mapping the erupted areas was remote sensing. the remote sensing consisted of Landsat 8 OLI that was published on February 8th 2015 as input data ENVI 4.7 and ArcGIS 10 as mapping tools. The Land surface temperature (LST) was applied on mapping this resulted. The highest LST was 90.929657 °C. In addition, the LST distribution indicated that the flowing lava through south east. Therefore, the south east areas should be considered as mitigated areas.

  3. Remote sensing science - new concepts and applications

    Energy Technology Data Exchange (ETDEWEB)

    Gerstl, S.A.; Cooke, B.J.; Henderson, B.G.; Love, S.P.; Zardecki, A.

    1996-10-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The science and technology of satellite remote sensing is an emerging interdisciplinary field that is growing rapidly with many global and regional applications requiring quantitative sensing of earth`s surface features as well as its atmosphere from space. It is possible today to resolve structures on the earth`s surface as small as one meter from space. If this high spatial resolution is coupled with high spectral resolution, instant object identification can also be achieved. To interpret these spectral signatures correctly, it is necessary to perform a computational correction on the satellite imagery that removes the distorting effects of the atmosphere. This project studied such new concepts and applied innovative new approaches in remote sensing science.

  4. Review of oil spill remote sensing.

    Science.gov (United States)

    Fingas, Merv; Brown, Carl

    2014-06-15

    Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Measurement Strategies for Remote Sensing Applications

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Theiler, J.; Smith, B.; Love, S.P.; LaDelfe, P.C.; Cooke, B.J.; Clodius, W.B.; Borel, C.C.; Bender, S.C.

    1999-03-06

    Remote sensing has grown to encompass many instruments and observations, with concomitant data from a huge number of targets. As evidenced by the impressive growth in the number of published papers and presentations in this field, there is a great deal of interest in applying these capabilities. The true challenge is to transition from directly observed data sets to obtaining meaningful and robust information about remotely sensed targets. We use physics-based end-to-end modeling and analysis techniques as a framework for such a transition. Our technique starts with quantified observables and signatures of a target. The signatures are propagated through representative atmospheres to realistically modeled sensors. Simulated data are then propagated through analysis routines, yielding measurements that are directly compared to the original target attributes. We use this approach to develop measurement strategies which ensure that our efforts provide a balanced approach to obtaining substantive information on our targets.

  6. The Fundamental Framework of Remote Sensing Validation System

    Science.gov (United States)

    Jiang, X.-G.; Xi, X.-H.; Wu, M.-J.; Li, Z.-L.

    2009-04-01

    Remote sensing is a very complicated course. It is influenced by many factors, such as speciality of remote sensing sensor, radiant transmission characteristic of atmosphere, work environment of remote sensing platform, data transmission, data reception, data processing, and property of observed object etc. Whether the received data is consistent with the design specifications? Can the data meet the demands of remote sensing applications? How about the accuracy of the data products, retrieval products and application products of remote sensing? It is essential to carry out the validation to assess the data quality and application potential. Validation is effective approach to valuate remote sensing products. It is the significant link between remote sensing data and information. Research on remote sensing validation is very important for sensor development, data quality analysis and control. This paper focuses on the study of remote sensing validation and validation system. Different from the previous work done by other researchers, we study the validation from the viewpoint of systematic engineering considering that validation is involved with many aspects as talked about. Validation is not just a single and simple course. It is complicated system. Validation system is the important part of whole earth observation system. First of all, in this paper the category of remote sensing validation is defined. Remote sensing validation includes not only the data products validation, but also the retrieval products validation and application products validation. Second, the new concept, remote sensing validation system, is proposed. Then, the general framework, software structure and functions of validation system are studied and put forward. The validation system is composed of validation field module, data acquirement module, data processing module, data storage and management module, data scaling module, and remote sensing products validation module. And finally the

  7. Flood Risk and Climate Change: The Contributions of Remote Sensing

    Science.gov (United States)

    Brakenridge, R.; Slayback, D. A.; Kettner, A. J.; Cohen, S.; Syvitski, J. A.; Overeem, I.; de Groeve, T.

    2015-12-01

    Since the mid-1970s, satellite observation has gathered an exceptionally valuable but largely un-harvested record of flood inundation world-wide. Commencing in late 1999, the two MODIS sensors also obtained daily surveillance of all of the Earth's surface waters. These data are analogous to the record of earthquake seismicity provided by seismographic stations; they provide the only objective characterization of many extreme, damaging flood events. This information should be deployed to its maximum utility in defining areas of flood risk. In the developing nations, the remote sensing archive provides the immediate opportunity, without hydrological data infrastructure, to directly identify hazardous land areas. As well, satellite passive microwave radiometry, commencing with near-daily global coverage in 1998, has the ability to characterize at-a-site flood hydrographs. When combined with the satellite record of mapped inundation, this allows exceedance probabilities to be placed on observed inundation limits. The coupled data set can then be used to validate predictive flood modeling. As climate changes, flood statistics change. Yet hazard evaluation has for many decades proceeded using assumed stationarity of flood frequency distributions. New floods-of-record at any location thereby present a dilemma to policy makers and to hydrologists: immediately include the new extreme flood in the flow series, and thus increase the size of the regulatory floodplain, or use the pre-flood flow records to label the exceptional new event as, for example, "the 1000 yr flood". The remote sensing record also includes defended floodplains where levees have failed, sometimes even during relatively common floods. We can use the powerful observations provided by remote sensing to confront the old probability estimates directly: by arguing that the recent observed record of inundation from actual floods must take priority in guiding public policy.

  8. Processing Remote Sensing Data with Python

    OpenAIRE

    Dillon, Ryan J., 1984-

    2013-01-01

    With public access available for numerous satellite imaging products, modelling in atmospheric and oceanographic applications has become increasingly more prevalent. Though there are numerous tools available for geospatial development, their use is more commonly applied towards mapping applications. With this being the case, there are a number of valuable texts for using these tools in such mapping applications; though, documentation for processing of remote sensing datasets is limited to ...

  9. Wind Predictability and Remote Sensing Techniques,

    Science.gov (United States)

    The report presents the unclassified findings from the Investigation of Airborne Wind Sensing Systems conducted under AIRTASK A30303/323/70F17311002. Included is a summary of the current accuracy of wind speed and direction forecasts, a list of possible methods for remote sensing meteorological data, a list of areas of application of the given methods and a list of contacts made for information relevant to this evaluation. (Author)

  10. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  11. International Commercial Remote Sensing Practices and Policies: A Comparative Analysis

    Science.gov (United States)

    Stryker, Timothy

    In recent years, there has been much discussion about U.S. commercial remoteUnder the Act, the Secretary of Commerce sensing policies and how effectively theylicenses the operations of private U.S. address U.S. national security, foreignremote sensing satellite systems, in policy, commercial, and public interests.consultation with the Secretaries of Defense, This paper will provide an overview of U.S.State, and Interior. PDD-23 provided further commercial remote sensing laws,details concerning the operation of advanced regulations, and policies, and describe recentsystems, as well as criteria for the export of NOAA initiatives. It will also addressturnkey systems and/or components. In July related foreign practices, and the overall2000, pursuant to the authority delegated to legal context for trade and investment in thisit by the Secretary of Commerce, NOAA critical industry.iss ued new regulations for the industry. Licensing and Regulationsatellite systems. NOAA's program is The 1992 Land Remote Sensing Policy Act ("the Act"), and the 1994 policy on Foreign Access to Remote Sensing Space Capabilities (known as Presidential Decision Directive-23, or PDD-23) put into place an ambitious legal and policy framework for the U.S. Government's licensing of privately-owned, high-resolution satellite systems. Previously, capabilities afforded national security and observes the international obligations of the United States; maintain positive control of spacecraft operations; maintain a tasking record in conjunction with other record-keeping requirements; provide U.S. Government access to and use of data when required for national security or foreign policy purposes; provide for U.S. Government review of all significant foreign agreements; obtain U.S. Government approval for any encryption devices used; make available unenhanced data to a "sensed state" as soon as such data are available and on reasonable cost terms and conditions; make available unenhanced data as requested

  12. GPS Remote Sensing Measurements Using Aerosonde UAV

    Science.gov (United States)

    Grant, Michael S.; Katzberg, Stephen J.; Lawrence, R. W.

    2005-01-01

    In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

  13. Remote sensing application on geothermal exploration

    Science.gov (United States)

    Gaffar, Eddy Z.

    2013-09-01

    Geothermal energy is produced when water coming down from the surface of the earth and met with magma or hot rocks, which the heat comes from the very high levels of magma rises from the earth. This process produced a heated fluid supplied to a power generator system to finally use as energy. Geothermal field usually associated with volcanic area with a component from igneous rocks and a complex geological structures. The fracture and fault structure are important geological structures associated with geothermal. Furthermore, their geothermal manifestations also need to be evaluated associated their geological structures. The appearance of a geothermal surface manifestation is close to the structure of the fracture and the caldera volcanic areas. The relationship between the fault and geothermal manifestations can be seen in the form of a pattern of alignment between the manifestations of geothermal locations with other locations on the fault system. The use of remote sensing using electromagnetic radiation sensors to record images of the Earth's environment that can be interpreted to be a useful information. In this study, remote sensing was applied to determine the geological structure and mapping of the distribution of rocks and alteration rocks. It was found that remote sensing obtained a better localize areas of geothermal prospects, which in turn could cut the chain of geothermal exploration to reduce a cost of geothermal exploration.

  14. A Review of Wetland Remote Sensing.

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-04-05

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.

  15. A Review of Wetland Remote Sensing

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-01-01

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers. PMID:28379174

  16. Assessing aspen using remote sensing

    Science.gov (United States)

    Randy Hamilton; Kevin Megown; Jeff DiBenedetto; Dale Bartos; Anne Mileck

    2009-01-01

    Large areas of aspen (Populus tremuloides) have disappeared and continue to disappear from western forests due to successional decline and sudden aspen decline (SAD). This loss of aspen ecosystems negatively impacts watersheds, wildlife, plants, and recreation. Much can still be done to restore aspen if timely and appropriate action is taken. However, land managers...

  17. Visual time series analysis

    DEFF Research Database (Denmark)

    Fischer, Paul; Hilbert, Astrid

    2012-01-01

    commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...

  18. Remote Sensing Archeology in China

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ China is a country noted for its vast territory and time-honored civilization. Cultural sites can be found across the country, including the famous Silk Road, which was started in the 2nd century BC and served as terrestrial and maritime outlets for the cultural exchanges between China and the rest of the world. So understanding these legacies of human development is of great significance in exploration of the history both Chinese and worldwide.

  19. The application of time series models to cloud field morphology analysis

    Science.gov (United States)

    Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

    1987-01-01

    A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

  20. Detecting neighborhood vacancy level in Detroit city using remote sensing

    Science.gov (United States)

    Li, X.; Wang, R.; Yang, A.; Vojnovic, I.

    2015-12-01

    With the decline of manufacturing industries, many Rust Belt cities, which enjoyed prosperity in the past, are now suffering from financial stress, population decrease and urban poverty. As a consequence, urban neighborhoods deteriorate. Houses are abandoned and left to decay. Neighborhood vacancy brings on many problems. Governments and agencies try to survey the vacancy level by going through neighborhoods and record the condition of each structure, or by buying information of active mailing addresses to get approximate neighborhood vacancy rate. But these methods are expensive and time consuming. Remote sensing provides a quick and comparatively cost-efficient way to access spatial information on social and demographical attributes of urban area. In our study, we use remote sensing to detect a major aspect of neighborhood deterioration, the vacancy levels of neighborhoods in Detroit city. We compared different neighborhoods using Landsat 8 images in 2013. We calculated NDVI that indicates the greenness of neighborhoods with the image in July 2013. Then we used thermal infrared information from image in February to detect human activities. In winter, abandoned houses will not consume so much energy and therefore neighborhoods with more abandoned houses will have smaller urban heat island effect. Controlling for the differences in terms of the greenness obtained from summer time image, we used thermal infrared from winter image to determine the temperatures of urban surface. We find that hotter areas are better maintained and have lower house vacancy rates. We also compared the changes over time for neighborhoods using Landsat 7 images from 2003 to 2013. The results show that deteriorated neighborhoods have increased NDVI in summer and get colder in winter due to abandonment of houses. Our results show the potential application of remote sensing as an easily accessed and efficient way to obtain data about social conditions in cities. We used the neighborhood

  1. Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Maes, P.; Clement, J.; Aerts, J. M.; Farifteh, J.; Lagrou, K.; Van Ranst, M.; Coppin, P.

    2012-08-01

    The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were tested as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.

  2. Scientific Programming Using Java and C: A Remote Sensing Example

    Science.gov (United States)

    Prados, Donald; Johnson, Michael; Mohamed, Mohamed A.; Cao, Chang-Yong; Gasser, Jerry; Powell, Don; McGregor, Lloyd

    1999-01-01

    This paper presents results of a project to port code for processing remotely sensed data from the UNIX environment to Windows. Factors considered during this process include time schedule, cost, resource availability, reuse of existing code, rapid interface development, ease of integration, and platform independence. The approach selected for this project used both Java and C. By using Java for the graphical user interface and C for the domain model, the strengths of both languages were utilized and the resulting code can easily be ported to other platforms. The advantages of this approach are discussed in this paper.

  3. The Remote Sensing of Surface Radiative Temperature over Barbados.

    Science.gov (United States)

    remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

  4. Model-based acoustic remote sensing of seafloor characteristics

    Digital Repository Service at National Institute of Oceanography (India)

    De, Ch.; Chakraborty, B.

    characterization using time- dependent acoustic backscatter: Study of Arabian Sea,” in Proc. IEEE Oceans, Kobe, Japan, 2008, pp. 1–4. 3876 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 49, NO. 10, OCTOBER 2011 [6] C. De and B. Chakraborty, “Acoustic... characterization of seafloor sediment employing a hybrid method of neural network architecture and fuzzy algorithm,” IEEE Geosci. Remote Sens. Lett., vol. 6, no. 4, pp. 743–747, Oct. 2009. [7] C. De and B. Chakraborty, “Preference of echo features...

  5. A Remotely Sensed Global Terrestrial Drought Severity Index

    Science.gov (United States)

    Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

    2012-12-01

    Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

  6. Footprint Representation of Planetary Remote Sensing Data

    Science.gov (United States)

    Walter, S. H. G.; Gasselt, S. V.; Michael, G.; Neukum, G.

    The geometric outline of remote sensing image data, the so called footprint, can be represented as a number of coordinate tuples. These polygons are associated with according attribute information such as orbit name, ground- and image resolution, solar longitude and illumination conditions to generate a powerful base for classification of planetary experiment data. Speed, handling and extended capabilites are the reasons for using geodatabases to store and access these data types. Techniques for such a spatial database of footprint data are demonstrated using the Relational Database Management System (RDBMS) PostgreSQL, spatially enabled by the PostGIS extension. Exemplary, footprints of the HRSC and OMEGA instruments, both onboard ESA's Mars Express Orbiter, are generated and connected to attribute information. The aim is to provide high-resolution footprints of the OMEGA instrument to the science community for the first time and make them available for web-based mapping applications like the "Planetary Interactive GIS-on-the-Web Analyzable Database" (PIG- WAD), produced by the USGS. Map overlays with HRSC or other instruments like MOC and THEMIS (footprint maps are already available for these instruments and can be integrated into the database) allow on-the-fly intersection and comparison as well as extended statistics of the data. Footprint polygons are generated one by one using standard software provided by the instrument teams. Attribute data is calculated and stored together with the geometric information. In the case of HRSC, the coordinates of the footprints are already available in the VICAR label of each image file. Using the VICAR RTL and PostgreSQL's libpq C library they are loaded into the database using the Well-Known Text (WKT) notation by the Open Geospatial Consortium, Inc. (OGC). For the OMEGA instrument, image data is read using IDL routines developed and distributed by the OMEGA team. Image outlines are exported together with relevant attribute

  7. 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.

  8. A Simple Method to Determine the Timing of Snow Melt by Remote Sensing with Application to the CO2 Balances of Northern Mire and Heath Ecosystems

    Directory of Open Access Journals (Sweden)

    Terhikki Manninen

    2009-11-01

    Full Text Available The timing of the disappearance of the snow cover in spring, or snow melt day (SMD, is a key parameter controlling the carbon dioxide balance between the northern mire and heath ecosystems and the atmosphere. We present a simple method for the determination of the SMD using a satellite-based surface albedo product (SAL. The method is based on the local change of albedo from higher wintertime values towards the lower summertime values. The satellite SMD timing correlates well with the SMD determined from snow depth measurements at Finnish weather stations (r = 0.86, slope 1.05. In 50% of the cases the error was 3.4 days or less and bias less than half a day. This would lead to a moderate uncertainty in the annual CO2 balance of mire and heath ecosystems, if the published SMD—CO2 balance relations are valid. However, due to the limited data sets available a systematic validation is left for the future.

  9. Development of a Near Ground Remote Sensing System

    Directory of Open Access Journals (Sweden)

    Yanchao Zhang

    2016-05-01

    Full Text Available Unmanned Aerial Vehicles (UAVs have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1 mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2 power supply and control parts; (3 onboard application components. This platform covers five degrees of freedom (DOFs: horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.

  10. Development of a Near Ground Remote Sensing System.

    Science.gov (United States)

    Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong

    2016-05-06

    Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail's repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.

  11. Discrimination of wetland vegetation using close-range remote sensing

    Science.gov (United States)

    Demarey, Deborah Marie

    The protection and conservation of sensitive environmental habitats has, in recent years, focused public attention on wetland ecosystems. Traditional methods of wetland assessment have been augmented through the use of remote sensing technologies. Remote sensing offers acquisition of copious amounts of data in short periods of time over land areas that might otherwise be inaccessible. The problem, however, from a remote sensing standpoint is that verification of wetland composition relies on accurate ground truth inventories. The establishment of a library containing unique spectral responses for obligates and facultative wetland plant species would provide baseline reference data for accurate assessment of wetland condition. This research focused on the spectral discrimination of five species of wetland plants that commonly coexist in temperate North American non-tidal wetlands. A specially designed wetland was constructed to closely approximate natural conditions, and was planted with monospecific stands of Typha angustifolia L., Nymphaea tuberosa Paine, Sparganium eurycarpum Engelm., Scirpus acutus Muhl., and Sagittaria latifolia Willd. Spectral data from multiple quadrats were collected through the use of a hyperspectral spectroradiometer operating at close range. The degree of similarity and difference within each monospecific stand was evaluated as was the difference and similarity among the species on each of nine dates throughout a single growing season. If identification of a unique spectral response ("signature") was possible, the degree of variation within the stand must not exceed variation among the stands. A temporal investigation compared plant life cycles and physiology to spectral responses. Patterns of spectral variation clearly reflect seasonal lifecycle changes from juvenility through senescence, but do not exhibit spectral integrity that would consistently permit discrimination. Chlorophyll assays were compared to hyperspectral response to

  12. Development of a Near Ground Remote Sensing System

    Science.gov (United States)

    Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong

    2016-01-01

    Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies. PMID:27164111

  13. Remote Sensing Tertiary Education Meets High Intensity Interval Training

    Science.gov (United States)

    Joyce, K. E.; White, B.

    2015-04-01

    Enduring a traditional lecture is the tertiary education equivalent of a long, slow, jog. There are certainly some educational benefits if the student is able to maintain concentration, but they are just as likely to get caught napping and fall off the back end of the treadmill. Alternatively, a pre-choreographed interactive workshop style class requires students to continually engage with the materials. Appropriately timed breaks or intervals allow students to recover briefly before being increasingly challenged throughout the class. Using an introductory remote sensing class at Charles Darwin University, this case study presents a transition from the traditional stand and deliver style lecture to an active student-led learning experience. The class is taught at undergraduate and postgraduate levels, with both on-campus as well as online distance learning students. Based on the concept that active engagement in learning materials promotes 'stickiness' of subject matter, the remote sensing class was re-designed to encourage an active style of learning. Critically, class content was reviewed to identify the key learning outcomes for the students. This resulted in a necessary sacrifice of topic range for depth of understanding. Graduates of the class reported high levels of enthusiasm for the materials, and the style in which the class was taught. This paper details a number of techniques that were used to engage students in active and problem based learning throughout the semester. It suggests a number of freely available tools that academics in remote sensing and related fields can readily incorporate into their teaching portfolios. Moreover, it shows how simple it can be to provide a far more enjoyable and effective learning experience for students than the one dimensional lecture.

  14. Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

    Science.gov (United States)

    Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

    2017-06-12

    Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

  15. Remotely Sensed Quantitative Drought Risk Assessment in Vulnerable Agroecosystems

    Science.gov (United States)

    Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.

    2012-04-01

    Hazard may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, economy and society. This paper deals with drought risk assessment, which the first step designed to find out what the problems are and comprises three distinct steps, namely risk identification, risk management which is not covered in this paper, there should be a fourth step to address the need for feedback and to take post-audits of all risk assessment exercises. In particular, quantitative drought risk assessment is attempted by using statistical methods. For the qualification of drought, the Reconnaissance Drought Index (RDI) is employed, which is a new index based on hydrometeorological parameters, such as precipitation and potential evapotranspiration. The remotely sensed estimation of RDI is based on NOA-AVHRR satellite data for a period of 20 years (1981-2001). The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Specifically, the undertaken drought risk assessment processes are specified as follows: 1. Risk identification: This step involves drought quantification and monitoring based on remotely sensed RDI and extraction of several features such as severity, duration, areal extent, onset and end time. Moreover, it involves a drought early warning system based on the above parameters. 2. Risk estimation: This step includes an analysis of drought severity, frequency and their relationships. 3. Risk evaluation: This step covers drought evaluation based on analysis of RDI images before and after each drought episode, which usually lasts one hydrological year (12month). The results of these three-step drought assessment processes are considered quite satisfactory in a drought-prone region such as Thessaly in central

  16. Improvements in agricultural water decision support using remote sensing

    Science.gov (United States)

    Marshall, M. T.

    2012-12-01

    Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of

  17. Future Opportunities and Challenges in Remote Sensing of Drought

    Science.gov (United States)

    Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

    2011-01-01

    The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and

  18. Future opportunities and challenges in remote sensing of drought

    Science.gov (United States)

    Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

    2012-01-01

    The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and

  19. Assimilation of remotely sensed latent heat flux in a distributed hydrological model

    NARCIS (Netherlands)

    Schuurmans, J.M.; Troch, P.A.A.; Veldhuizen, A.A.; Bastiaanssen, W.G.M.; Bierkens, M.F.P.

    2003-01-01

    This paper addresses the question of whether remotely sensed latent heat flux estimates over a catchment can be used to improve distributed hydrological model water balance computations by the process of data assimilation. The data used is a series of satellite images for the Drentse Aa catchment in

  20. Causality between time series

    CERN Document Server

    Liang, X San

    2014-01-01

    Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...

  1. Estimation of biogenic volatile organic compound (BVOC emissions from the terrestrial ecosystem in China using real-time remote sensing data

    Directory of Open Access Journals (Sweden)

    M. Li

    2012-03-01

    Full Text Available Because of the high emission rate and reactivity, biogenic volatile organic compounds (BVOCs play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and coarsely resolved meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in the atmosphere, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature, with MM5 (the Fifth-Generation Mesoscale Model providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8 and seven monoterpene species (C10H16 in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer data were introduced to update the land surface parameters and to improve the simulation performance of MM5, and to determine the influence of leaf area index (LAI and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value compared with past studies. Therein, the most important individual contributor was isoprene (9.36 Tg C yr−1, followed by α-pinene (1.24 Tg C yr−1 and β-pinene (0.84 Tg C yr−1. Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial and temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. While Southeast China was the top-ranking contributor of monoterpenes, in which the dominant

  2. Estimation of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem in China using real-time remote sensing data

    Science.gov (United States)

    Li, M.; Huang, X.; Li, J.; Song, Y.

    2012-04-01

    Because of the high emission intensity and reactivity, biogenic volatile organic compounds (BVOCs) play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and limited meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in atmospheric chemical processes, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature) with MM5 (the Fifth-Generation Mesoscale Model) providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8) and seven monoterpene species (C10H16) in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer) data were introduced to update the land surface parameters and improve the simulation performance of MM5, and to modify the influence of leaf area index (LAI) and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value much lower than that given in global estimations but higher than the past estimations in China. Therein, the most important individual contributor was isoprene (9.36 Tg C), followed by α-pinene (1.24 Tg C yr-1) and β-pinene (0.84 Tg C yr-1). Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial-temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. On the other hand, Southeast China was the top-ranking contributor of monoterpenes, in which the dominant vegetation

  3. Mapping Tamarix: New techniques for field measurements, spatial modeling and remote sensing

    Science.gov (United States)

    Evangelista, Paul H.

    Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during

  4. Hyperspectral remote sensing of wild oyster reefs

    Science.gov (United States)

    Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent

    2016-04-01

    The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal

  5. 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

  6. Optical Remote Sensing Potentials for Looting Detection

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-10-01

    Full Text Available Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social impact. In recent years, the employment of remote sensing technologies using ground-based and/or space-based sensors has assisted in dealing with this issue. Novel remote sensing techniques have tackled heritage destruction occurring in war-conflicted areas, as well as illicit archeological activity in vast areas of archaeological interest with limited surveillance. The damage performed by illegal activities, as well as the scarcity of reliable information are some of the major concerns that local stakeholders are facing today. This study discusses the potential use of remote sensing technologies based on the results obtained for the archaeological landscape of Ayios Mnason in Politiko village, located in Nicosia district, Cyprus. In this area, more than ten looted tombs have been recorded in the last decade, indicating small-scale, but still systematic, looting. The image analysis, including vegetation indices, fusion, automatic extraction after object-oriented classification, etc., was based on high-resolution WorldView-2 multispectral satellite imagery and RGB high-resolution aerial orthorectified images. Google Earth© images were also used to map and diachronically observe the site. The current research also discusses the potential for wider application of the presented methodology, acting as an early warning system, in an effort to establish a systematic monitoring tool for archaeological areas in Cyprus facing similar threats.

  7. Evaluation of line transect sampling based on remotely sensed data from underwater video

    Science.gov (United States)

    Bergstedt, R.A.; Anderson, D.R.

    1990-01-01

    We used underwater video in conjunction with the line transect method and a Fourier series estimator to make 13 independent estimates of the density of known populations of bricks lying on the bottom in shallows of Lake Huron. The pooled estimate of density (95.5 bricks per hectare) was close to the true density (89.8 per hectare), and there was no evidence of bias. Confidence intervals for the individual estimates included the true density 85% of the time instead of the nominal 95%. Our results suggest that reliable estimates of the density of objects on a lake bed can be obtained by the use of remote sensing and line transect sampling theory.

  8. Remote Sensing and Modeling of Landslides: Detection, Monitoring and Risk Evaluation

    Science.gov (United States)

    Kirschbaum, Dalia; Fukuoka, Hiroshi

    2012-01-01

    Landslides are one of the most pervasive hazards in the world, resulting in more fatalities and economic damage than is generally recognized_ Occurring over an extensive range of lithologies, morphologies, hydrologies, and climates, mass movements can be triggered by intense or prolonged rainfall, seismicity, freeze/thaw processes, and antbropogertic activities, among other factors. The location, size, and timing of these processes are characteristically difficult to predict and assess because of their localized spatial scales, distribution, and complex interactions between rainfall infiltration, hydromechanical properties of the soil, and the underlying surface composition. However, the increased availability, accessibility, and resolution of remote sensing data offer a new opportunity to explore issues of landslide susceptibility, hazard, and risk over a variety of spatial scales. This special issue presents a series of papers that investigate the sources, behavior, and impacts of different mass movement types using a diverse set of data sources and evaluation methodologies.

  9. 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.

  10. Remote Sensing and Modeling of Landslides: Detection, Monitoring and Risk Evaluation

    Science.gov (United States)

    Kirschbaum, Dalia; Fukuoka, Hiroshi

    2012-01-01

    Landslides are one of the most pervasive hazards in the world, resulting in more fatalities and economic damage than is generally recognized_ Occurring over an extensive range of lithologies, morphologies, hydrologies, and climates, mass movements can be triggered by intense or prolonged rainfall, seismicity, freeze/thaw processes, and antbropogertic activities, among other factors. The location, size, and timing of these processes are characteristically difficult to predict and assess because of their localized spatial scales, distribution, and complex interactions between rainfall infiltration, hydromechanical properties of the soil, and the underlying surface composition. However, the increased availability, accessibility, and resolution of remote sensing data offer a new opportunity to explore issues of landslide susceptibility, hazard, and risk over a variety of spatial scales. This special issue presents a series of papers that investigate the sources, behavior, and impacts of different mass movement types using a diverse set of data sources and evaluation methodologies.

  11. UNMANNED AERIAL VEHICLE (UAV) HYPERSPECTRAL REMOTE SENSING FOR DRYLAND VEGETATION MONITORING

    Energy Technology Data Exchange (ETDEWEB)

    Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson; Ryan C. Hruska

    2012-06-01

    UAV-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Idaho State University, Boise Center Aerospace Lab, were recently tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. Overall, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. Future mapping efforts that leverage ground reference data, ultra-high spatial resolution photos and time series analysis should be able to effectively distinguish native grasses such as Sandberg bluegrass (Poa secunda), from invasives such as burr buttercup (Ranunculus testiculatus) and cheatgrass (Bromus tectorum).

  12. A remote sensing assessment of pest infestation on sorghum

    Science.gov (United States)

    Singh, D.; Sao, R.; Singh, K. P.

    The damage caused by the pest to crop is well known. The major aspects of remote sensing are timely estimates of agriculture crop yield, prediction of pest. Therefore, in this paper, an attempt has been made to investigate the utility and potential application of microwave remote sensing for detection of pest infestation within sorghum field. The studies were made on crop sorghum (Meethi Sudan) that is a forage variety and the pest observed was a species of grasshopper. The beds of crop sorghum were specially prepared for pests as well as microwave scattering measurements. In first phase of study, dependence of occurrence of pests on sorghum plant parameters (i.e., crop covered moist soil (SM), plant height (PH), leaf area index (LAI), percentage biomass (BIO), total chlorophyll (TC)) have been observed and analyzed and it was noticed that pests were more dependent on sorghum chlorophyll than other plant parameters, while climatic conditions were taken as constant. An empirical relationship has been developed between occurrence of pests and TC with quite significant values of coefficient of determination ( r2 = 0.82). These crop parameters are easily assessable through microwave remote sensing and therefore they can form the basis for prediction of pest remotely. In the second phase of this study, several observations were carried out for various growth stages of sorghum using scatterometer for both like polarizations (i.e., HH- and VV-) and different incidence angles at X-band (9.5 GHz). Linear regression analysis was carried out to obtain the best suitable incidence angle and polarization to assess the sorghum TC. VV-pol gives better results than HH-pol and incidence angle should be more than 40° for both like polarizations for assessing the sorghum TC at X-band. A negative correlation has been obtained between TC and scattering coefficient with the r2 values (0.69 and 0.75 for HH- and VV-pol, respectively). The TC assessed by the microwave measurements was

  13. Shape saliency for remote sensing image

    Science.gov (United States)

    Xu, Sheng; Hong, Huo; Fang, Tao; Li, Deren

    2007-11-01

    In this paper, a shape saliency measure for only shape feature of each object in the image is described. Instead biologically-inspired bottom-up Itti model, the dissimilarity is measured by the shape feature. And, Fourier descriptor is used for measuring dissimilarity in this paper. In the model, the object is determined as a salient region, when it is far different from others. Different value of the saliency is ranged to generate a saliency map. It is shown that the attention shift processing can be recorded. Some results from psychological images and remote sensing images are shown and discussed in the paper.

  14. Remote sensing and actuation using unmanned vehicles

    CERN Document Server

    Chao, Haiyang

    2012-01-01

    Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.

  15. Characrterizing frozen ground with multisensor remote sensing

    Science.gov (United States)

    Csatho, B. M.; Ping, C.; Everett, L. R.; Kimble, J. M.; Michaelson, G.; Tremper, C.

    2006-12-01

    We have a physically based, conceptual understanding of many of the significant interactions that impact permafrost-affected soils. Our observationally based knowledge, however, is inadequate in many cases to quantify these interactions or to predict their net impact. To pursue key goals, such as understanding the response of permafrost-affected soil systems to global environmental changes and their role in the carbon balance, and to transform our conceptual understanding of these processes into quantitative knowledge, it is necessary to acquire geographically diverse sets of fundamental observations at high spatial and often temporal resolution. The main goals of the research presented here are developing methods for mapping soil and permafrost distributions in polar environment as well as characterizing glacial and perglacial geomorphology from multisensor, multiresolution remotely sensed data. The sheer amount of data and the disparate data sets (e.g., LIDAR, stereo imagery, multi- hyperspectral, and SAR imagery) make the joint interpretation (fusion) a daunting task. We combine remote sensing, pattern recognition and landscape analysis techniques for the delineation of soil landscape units and other geomorphic features, for inferring the physical properties and composition of the surface, and for generating numerical measurements of geomorphic features from remotely sensed data. Examples illustrating the concept are presented from the North Slope of Alaska and from the McMurdo Sound region in Antarctica. (1) On the North Slope, Alaska we separated different vegetative, soil and landscape units along the Haul Road. Point-source soils (pedon) data and field spectrometry data have been acquired at different units to provide ground-truth for the satellite image interpretation. (2) A vast amount of remote sensing data, such as multi- and hyperspectral (Landsat, SPOT, ASTER, HYPERION) and SAR satellite imagery (ERS, RADARSAT and JERS), high resolution topographic

  16. Introduction to Remote Sensing Image Registration

    Science.gov (United States)

    Le Moigne, Jacqueline

    2017-01-01

    For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

  17. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  18. Optical remote sensing of the earth

    Science.gov (United States)

    Goetz, A. F. H.; Wellman, J. B.; Barnes, W. L.

    1985-01-01

    In the present assessment of the contributions of optical earth resources remote sensing in the 0.4-15.0 micron region, attention is given to underlying principles, applications to scientific disciplines such as geology, hydrology and oceanography, the recent development history of the requisite sensors, and sensor development trends. Development status characterizations are given for thematic mapping, modular optoelectronic multispectral scanning, the telescope/CCD 'SPOT' program of France, the thermal IR multispectral scanner for mineral signature identification, airborne imaging spectrometry, and the Advanced Visible and IR Imaging Spectrometer that is nearing deployment. Technology development trends and the capabilities they portend are projected.

  19. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  20. Remote sensing of vegetation and soil moisture

    Science.gov (United States)

    Kong, J. A.; Shin, R. T. (Principal Investigator)

    1983-01-01

    Progress in the investigation of problems related to the remote sensing of vegetation and soil moisture is reported. Specific topics addressed include: (1) microwave scattering from periodic surfaces using a rigorous modal technique; (2) combined random rough surface and volume scattering effects; (3) the anisotropic effects of vegetation structures; (4) the application of the strong fluctuation theory to the the study of electromagnetic wave scattering from a layer of random discrete scatterers; and (5) the investigation of the scattering of a plane wave obliquely incident on a half space of densely distributed spherical dielectric scatterers using a quantum mechanical potential approach.

  1. Downscaled TRMM Rainfall Time-Series for Catchment Hydrology Applications

    Science.gov (United States)

    Tarnavsky, E.; Mulligan, M.

    2009-04-01

    Hydrology in semi-arid regions is controlled, to a large extent, by the spatial and temporal distribution of rainfall defined in terms of rainfall depth and intensity. Thus, appropriate representation of the space-time variability of rainfall is essential for catchment-scale hydrological models applied in semi-arid regions. While spaceborne platforms equipped with remote sensing instruments provide information on a range of variables for hydrological modelling, including rainfall, the necessary spatial and temporal detail is rarely obtained from a single dataset. This paper presents a new dynamic model of dryland hydrology, DryMOD, which makes best use of free, public-domain remote sensing data for representation of key variables with a particular focus on (a) simulation of spatial rainfall fields and (b) the hydrological response to rainfall, particularly in terms of rainfall-runoff partitioning. In DryMOD, rainfall is simulated using a novel approach combining 1-km spatial detail from a climatology derived from the TRMM 2B31 dataset (mean monthly rainfall) and 3-hourly temporal detail from time-series derived from the 0.25-degree gridded TRMM 3B42 dataset (rainfall intensity). This allows for rainfall simulation at the hourly time step, as well as accumulation of infiltration, recharge, and runoff at the monthly time step. In combination with temperature, topography, and soil data, rainfall-runoff and soil moisture dynamics are simulated over large dryland regions. In order to investigate the hydrological response to rainfall and variable catchment characteristics, the model is applied to two very different catchments in the drylands of North and West Africa. The results of the study demonstrate the use of remote sensing-based estimates of precipitation intensity and volume for the simulation of critical hydrological parameters. The model allows for better spatial planning of water harvesting activities, as well as for optimisation of agricultural activities

  2. Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review

    Directory of Open Access Journals (Sweden)

    J. M. Barbosa

    2014-01-01

    Full Text Available Tropical landscapes are, in general, a mosaic of pasture, agriculture, and forest undergoing various stages of succession. Forest succession is comprised of continuous structural changes over time and results in increases in aboveground biomass (AGB. New remote sensing methods, including sensors, image processing, statistical methods, and uncertainty evaluations, are constantly being developed to estimate biophysical forest changes. We review 318 peer-reviewed studies related to the use of remotely sensed AGB estimations in tropical forest succession studies and summarize their geographic distribution, sensors and methods used, and their most frequent ecological inferences. Remotely sensed AGB is broadly used in forest management studies, conservation status evaluations, carbon source and sink investigations, and for studies of the relationships between environmental conditions and forest structure. Uncertainties in AGB estimations were found to be heterogeneous with biases related to sensor type, processing methodology, ground truthing availability, and forest characteristics. Remotely sensed AGB of successional forests is more reliable for the study of spatial patterns of forest succession and over large time scales than that of individual stands. Remote sensing of temporal patterns in biomass requires further study, in particular, as it is critical for understanding forest regrowth at scales useful for regional or global analyses.

  3. FRACTAL DIMENSION OF URBAN EXPANSION BASED ON REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    IACOB I. CIPRIAN

    2012-11-01

    Full Text Available Fractal Dimension of Urban Expansion Based on Remote Sensing Images: In Cluj-Napoca city the process of urbanization has been accelerated during the years and implication of local authorities reflects a relevant planning policy. A good urban planning framework should take into account the society demands and also it should satisfy the natural conditions of local environment. The expansion of antropic areas it can be approached by implication of 5D variables (time as a sequence of stages, space: with x, y, z and magnitude of phenomena into the process, which will allow us to analyse and extract the roughness of city shape. Thus, to improve the decision factor we take a different approach in this paper, looking at geometry and scale composition. Using the remote sensing (RS and GIS techniques we manage to extract a sequence of built-up areas (from 1980 to 2012 and used the result as an input for modelling the spatialtemporal changes of urban expansion and fractal theory to analysed the geometric features. Taking the time as a parameter we can observe behaviour and changes in urban landscape, this condition have been known as self-organized – a condition which in first stage the system was without any turbulence (before the antropic factor and during the time tend to approach chaotic behaviour (entropy state without causing an disequilibrium in the main system.

  4. From Remotely Sensed Vegetation Onset to Sowing Dates: Aggregating Pixel-Level Detections into Village-Level Sowing Probabilities

    Directory of Open Access Journals (Sweden)

    Eduardo Marinho

    2014-11-01

    Full Text Available Monitoring the start of the crop season in Sahel provides decision makers with valuable information for an early assessment of potential production and food security threats. Presently, the most common method for the estimation of sowing dates in West African countries consists of applying given thresholds on rainfall estimations. However, the coarse spatial resolution and the possible inaccuracy of these estimations are limiting factors. In this context, the remote sensing approach, which consists of deriving green-up onset dates from satellite remote sensing data, appears as an interesting alternative. It builds upon a novel statistic model that translates vegetation onset detections derived from MODIS time series into sowing probabilities at the village level. Results for Niger show that this approach outperforms the standard method adopted in the region based on rainfall thresholds.

  5. A High Performance Remote Sensing Product Generation System Based on a Service Oriented Architecture for the Next Generation of Geostationary Operational Environmental Satellites

    Directory of Open Access Journals (Sweden)

    Satya Kalluri

    2015-08-01

    Full Text Available The Geostationary Operational Environmental Satellite (GOES series R, S, T, U (GOES-R will collect remote sensing data at several orders of magnitude compared to legacy missions, 24 × 7, over its 20-year operational lifecycle. A suite of 34 Earth and space weather products must be produced at low latency for timely delivery to forecasters. A ground system (GS has been developed to meet these challenging requirements, using High Performance Computing (HPC within a Service Oriented Architecture (SOA. This approach provides a robust, flexible architecture to support the operational GS as it generates remote sensing products by ingesting and combining data from multiple sources. Test results show that the system meets the key latency and availability requirements for all products.

  6. Remote sensing research in geographic education: An alternative view

    Science.gov (United States)

    Wilson, H.; Cary, T. K.; Goward, S. N.

    1981-01-01

    It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

  7. DUE PERMAFROST: A Circumpolar Remote Sensing Service for Permafrost - Evaluation Case Studies and Intercomparison with Regional Climate Model Simulations

    Science.gov (United States)

    Heim, B.; Bartsch, A.; Elger, K. K.; Rinke, A.; Matthes, H.; Zhou, X.; Klehmet, K.; Buchhorn, M.; Soliman, A. S.; Duguay, C. R.

    2013-12-01

    stakeholders and the IPA, and the ongoing evaluation of the remote sensing derived products make the DUE Permafrost products accepted by the scientific community. The Helmholtz Climate Initiative REKLIM (Regionale KlimaAnderungen/Regional climate change) is a climate research program where regional observations and process studies are coupled with model simulations (http://www.reklim.de/en/home/). The ESA DUE Permafrost User workshops initiated the use of the DUE time series within the REKLIM framework for inter-comparison experiments in order to assist the evaluation of calculated parameter fields of models. Within the REKLIM framework we spatio-temporally compare the geophysical surface parameters simulated by regional climate models with the spatio-temporal variability of Earth Observational remote sensing products. Earth Observational remote sensing products are: DUE Permafrost, DUE GlobSnow (http://www.globsnow.info) and the MODIS albedo product (MOD 43). We show intercomparison substudies on simulated fields of surface temperature and ground frozen, non-frozen state simulated by the regional climate models HIRHAM for the circumpolar domain and COSMO-CLM for Central Siberia.

  8. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

    Science.gov (United States)

    Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

    2017-01-01

    Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

  9. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research.Key contents of basic research in remote sensing,including modeling,inversion,scaling and scientific experiments,are reviewed.Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  10. An Overview on Data Mining of Nighttime Light Remote Sensing

    Directory of Open Access Journals (Sweden)

    LI Deren

    2015-06-01

    Full Text Available When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future

  11. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    2013-09-30

    WA 98105 phone: (206) 685-2609 fax: (206) 543-6785 email: jessup@apl.washington.edu Robert A. Holman Merrick Haller, Alexander Kuropov, Tuba...Ozkan-Haller Oregon State University Corvallis, OR 97331 phone: (541) 737-2914 fax: (541) 737-2064 email: holman @coas.oregonstate.edu Steve...Infrared Remote Sensing and Lidar– UW: Chickadel and Jessup B. Electro-Optical Remote Sensing – OSU: Holman C. Microwave Remote Sensing – UW

  12. [A review on polarization information in the remote sensing detection].

    Science.gov (United States)

    Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

    2010-04-01

    Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

  13. SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

    Science.gov (United States)

    The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

  14. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    徐冠华

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research. Key contents of basic research in remote sensing, including modeling, inversion, scaling and scientific experiments, are reviewed. Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  15. Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval

    Directory of Open Access Journals (Sweden)

    Weixun Zhou

    2017-05-01

    Full Text Available Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs for high-resolution remote sensing image retrieval (HRRSIR. To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.

  16. Thermal Infrared Remote Sensing of the Yellowstone Geothermal System

    Science.gov (United States)

    Vaughan, R. G.; Keszthelyi, L. P.; Heasler, H.; Jaworowski, C.; Lowenstern, J. B.; Schneider, D. J.

    2009-12-01

    The Yellowstone National Park (YNP) geothermal system is one of the largest in the world, with thousands of individual thermal features ranging in size from a few centimeters to tens of meters across, (e.g., fumaroles, geysers, mud pots and hot spring pools). Together, large concentrations of these thermal features make up dozens of distinct thermal areas, characterized by sparse vegetation, hydrothermally altered rocks, and usually either sinter, travertine, or acid sulfate alteration. The temperature of these thermal features generally ranges from ~30 to ~93 oC, which is the boiling temperature of water at the elevation of Yellowstone. In-situ temperature measurements of various thermal features are sparse in both space and time, but they show a dynamic time-temperature relationship. For example, as geysers erupt and send pulses of warm water down slope, the warm water cools rapidly and is then followed by another pulse of warm water, on time scales of minutes. The total heat flux from the Park’s thermal features has been indirectly estimated from chemical analysis of Cl- flux in water flowing from Yellowstone’s rivers. We are working to provide a more direct measurement, as well as estimates of time variability, of the total heat flux using satellite multispectral thermal infrared (TIR) remote sensing data. Over the last 10 years, NASA’s orbiting ASTER and MODIS instruments have acquired hundreds and thousands of multispectral TIR images, respectively, over the YNP area. Compared with some volcanoes, Yellowstone is a relatively low-temperature geothermal system, with low thermal contrast to the non-geothermal surrounding areas; therefore we are refining existing techniques to extract surface temperature and thermal flux information. This task is complicated by issues such as, during the day, solar heated surfaces may be warmer than nearby geothermal features; and there is some topographic (elevation) influence on surface temperatures, even at night. Still

  17. Remotely Sensing the Photochemical Reflectance Index (PRI)

    Science.gov (United States)

    Vanderbilt, Vern

    2015-01-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.

  18. Theory of Geological Anomaly in Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Geological anomaly is geological body or complex body with obviously different compositions, structures or orders of genesis as compared with those in the surrounding areas. Geological anomaly, restrained by the geological factors closely associated with ore-forming process, is an important clue to ore deposits. The geological anomaly serves as a geological sign to locate ore deposits. Therefore, it is very important to study how to define the characteristics of geological anomaly and further to locate the changes in these characteristics. In this paper, the authors propose the geological anomaly based on the remote-sensing images and data, and expound systematically such image features as scale, size, boundary, morphology and genesis of geological anomalies. Then the authors introduce the categorization of the geological anomalies according to their geneses. The image characteristics of some types of geological anomalies, such as the underground geological anomaly, are also explained in detail. Based on the remote-sensing interpretation of these geological anomalies, the authors conclude that the forecasting and exploration of ore deposits should be focused on the following three aspects: (1) the analysis of geological setting and geological anomaly; (2) the analysis of circular geological anomaly, and (3) the comprehensive forecasting of ore deposits and the research into multi-source information.

  19. Machine learning in geosciences and remote sensing

    Institute of Scientific and Technical Information of China (English)

    David J. Lary; Amir H. Alavi; Amir H. Gandomi; Annette L. Walker

    2016-01-01

    Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regres-sion or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the ef-ficiency of ML for tackling the geosciences and remote sensing problems.

  20. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  1. Benthic habitat mapping using hyperspectral remote sensing

    Science.gov (United States)

    Vélez-Reyes, Miguel; Goodman, James A.; Castrodad-Carrau, Alexey; Jiménez-Rodriguez, Luis O.; Hunt, Shawn D.; Armstrong, Roy

    2006-09-01

    Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.

  2. Remote sensing application for property tax evaluation

    Science.gov (United States)

    Jain, Sadhana

    2008-02-01

    This paper presents a study for linking remotely sensed data with property tax related issues. First, it discusses the key attributes required for property taxation and evaluates the capabilities of remote sensing technology to measure these attributes accurately at parcel level. Next, it presents a detailed case study of six representative wards of different characteristics in Dehradun, India, that illustrates how measurements of several of these attributes supported by field survey can be combined to address the issues related to property taxation. Information derived for various factors quantifies the property taxation contributed by an average dwelling unit of the different income groups. Results show that the property tax calculated in different wards varies between 55% for the high-income group, 32% for the middle-income group, 12% for the low-income group and 1% for squatter units. The study concludes that higher spatial resolution satellite data and integrates social survey helps to assess the socio-economic status of the population for tax contribution purposes.

  3. Method of determining forest production from remotely sensed forest parameters

    Science.gov (United States)

    Corey, J.C.; Mackey, H.E. Jr.

    1987-08-31

    A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

  4. Integrating Dendrochronology, Climate and Satellite Remote Sensing to Better Understand Savanna Landscape Dynamics in the Okavango Delta, Botswana

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2013-11-01

    Full Text Available This research examines the integration and potential uses of linkages between climate dynamics, savanna vegetation and landscape level processes within a highly vulnerable region, both in terms of climate variability and social systems. We explore the combined applications of two time-series methodologies: (1 climate signals detected in tree ring growth, from published literature, chronologies from the International Tree-Ring Data Bank, and minimal preliminary field data; and (2 new primary production (NPP data of vegetation cover over time derived from remotely sensed analyses. Both time-series are related to the regional patterns of precipitation, the principle driver of plant growth in the area. The approach is temporally and spatially multiscalar and examines the relationships between vegetation cover, type and amount, and precipitation shifts. We review literature linking dendrochronology, climate, and remotely sensed imagery, and, in addition, provide unique preliminary analyses from a dry study site located on the outer limit of the Okavango Delta. The work demonstrates integration across the different data sources, to provide a more holistic view of landscape level processes occurring in the last 30-50 years. These results corroborate the water-limited nature of the region and the dominance of precipitation in controlling vegetation growth. We present this integrative analysis of vegetation and climate change, as a prospective approach to facilitate the development of long-term climate/vegetation change records across multiple scales.

  5. GNSS reflectometry and remote sensing: New objectives and results

    Science.gov (United States)

    Jin, Shuanggen; Komjathy, Attila

    2010-07-01

    The Global Navigation Satellite System (GNSS) has been a very powerful and important contributor to all scientific questions related to precise positioning on Earth's surface, particularly as a mature technique in geodesy and geosciences. With the development of GNSS as a satellite microwave (L-band) technique, more and wider applications and new potentials are explored and utilized. The versatile and available GNSS signals can image the Earth's surface environments as a new, highly precise, continuous, all-weather and near-real-time remote sensing tool. The refracted signals from GNSS radio occultation satellites together with ground GNSS observations can provide the high-resolution tropospheric water vapor, temperature and pressure, tropopause parameters and ionospheric total electron content (TEC) and electron density profile as well. The GNSS reflected signals from the ocean and land surface could determine the ocean height, wind speed and wind direction of ocean surface, soil moisture, ice and snow thickness. In this paper, GNSS remote sensing applications in the atmosphere, oceans, land and hydrology are presented as well as new objectives and results discussed.

  6. Automatic Registration and Mosaicking System for Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    Emiliano Castejon

    2006-04-01

    Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.

  7. Some insights on grassland health assessment based on remote sensing.

    Science.gov (United States)

    Xu, Dandan; Guo, Xulin

    2015-01-29

    Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  8. USING COVARIANCE INTERSECTION FOR CHANGE DETECTION IN REMOTE SENSING IMAGES

    Institute of Scientific and Technical Information of China (English)

    Yang Meng; Zhang Gong

    2011-01-01

    In this paper,an unsupervised change detection technique for remote sensing images acquired on the same geographical area but at different time instances is proposed by conducting Covariance Intersection (CI) to perform unsupervised fusion of the final fuzzy partition matrices from the Fuzzy C-Means (FCM) clustering for the feature space by applying compressed sampling to the given remote sensing images.The proposed approach exploits a CI-based data fusion of the membership function matrices,which are obtained by taking the Fuzzy C-Means (FCM) clustering of the frequency-domain feature vectors and spatial-domain feature vectors,aimed at enhancing the unsupervised change detection performance.Compressed sampling is performed to realize the image local feature sampling,which is a signal acquisition framework based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable recovery.The experimental results demonstrate that the proposed algorithm has a good change detection results and also performs quite well on denoising purpose.

  9. Remote sensing techniques applied to seismic vulnerability assessment

    Science.gov (United States)

    Juan Arranz, Jose; Torres, Yolanda; Hahgi, Azade; Gaspar-Escribano, Jorge

    2016-04-01

    Advances in remote sensing and photogrammetry techniques have increased the degree of accuracy and resolution in the record of the earth's surface. This has expanded the range of possible applications of these data. In this research, we have used these data to document the construction characteristics of the urban environment of Lorca, Spain. An exposure database has been created with the gathered information to be used in seismic vulnerability assessment. To this end, we have used data from photogrammetric flights at different periods, using both orthorectified images in the visible and infrared spectrum. Furthermore, the analysis is completed using LiDAR data. From the combination of these data, it has been possible to delineate the building footprints and characterize the constructions with attributes such as the approximate date of construction, area, type of roof and even building materials. To carry out the calculation, we have developed different algorithms to compare images from different times, segment images, classify LiDAR data, and use the infrared data in order to remove vegetation or to compute roof surfaces with height value, tilt and spectral fingerprint. In addition, the accuracy of our results has been validated with ground truth data. Keywords: LiDAR, remote sensing, seismic vulnerability, Lorca

  10. Scalability Issues for Remote Sensing Infrastructure: A Case Study.

    Science.gov (United States)

    Liu, Yang; Picard, Sean; Williamson, Carey

    2017-04-29

    For the past decade, a team of University of Calgary researchers has operated a large "sensor Web" to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system's memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

  11. Scalability Issues for Remote Sensing Infrastructure: A Case Study

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-04-01

    Full Text Available For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging. Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

  12. Some Insights on Grassland Health Assessment Based on Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dandan Xu

    2015-01-01

    Full Text Available Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  13. Monitoring volcanic activity with satellite remote sensing to reduce aviation hazard and mitigate the risk: application to the North Pacific

    Science.gov (United States)

    Webley, P. W.; Dehn, J.

    2012-12-01

    Volcanic activity across the North Pacific (NOPAC) occurs on a daily basis and as such monitoring needs to occur on a 24 hour, 365 days a year basis. The risk to the local population and aviation traffic is too high for this not to happen. Given the size and remoteness of the NOPAC region, satellite remote sensing has become an invaluable tool to monitor the ground activity from the regions volcanoes as well as observe, detect and analyze the volcanic ash clouds that transverse across the Pacific. Here, we describe the satellite data collection, data analysis, real-time alert/alarm systems, observational database and nearly 20-year archive of both automated and manual observations of volcanic activity. We provide examples of where satellite remote sensing has detected precursory activity at volcanoes, prior to the volcanic eruption, as well as different types of eruptive behavior that can be inferred from the time series data. Additionally, we illustrate how the remote sensing data be used to detect volcanic ash in the atmosphere, with some of the pro's and con's to the method as applied to the NOPAC, and how the data can be used with other volcano monitoring techniques, such as seismic monitoring and infrasound, to provide a more complete understanding of a volcanoes behavior. We focus on several large volcanic events across the region, since our archive started in 1993, and show how the system can detect both these large scale events as well as the smaller in size but higher in frequency type events. It's all about how to reduce the risk, improve scenario planning and situational awareness and at the same time providing the best and most reliable hazard assessment from any volcanic activity.

  14. Spatial sensitivity analysis of remote sensing snow cover fraction data in a distributed hydrological model

    Science.gov (United States)

    Berezowski, Tomasz; Chormański, Jarosław; Nossent, Jiri; Batelaan, Okke

    2014-05-01

    Distributed hydrological models enhance the analysis and explanation of environmental processes. As more spatial input data and time series become available, more analysis is required of the sensitivity of the data on the simulations. Most research so far focussed on the sensitivity of precipitation data in distributed hydrological models. However, these results can not be compared until a universal approach to quantify the sensitivity of a model to spatial data is available. The frequently tested and used remote sensing data for distributed models is snow cover. Snow cover fraction (SCF) remote sensing products are easily available from the internet, e.g. MODIS snow cover product MOD10A1 (daily snow cover fraction at 500m spatial resolution). In this work a spatial sensitivity analysis (SA) of remotely sensed SCF from MOD10A1 was conducted with the distributed WetSpa model. The aim is to investigate if the WetSpa model is differently subjected to SCF uncertainty in different areas of the model domain. The analysis was extended to look not only at SA quantities but also to relate them to the physical parameters and processes in the study area. The study area is the Biebrza River catchment, Poland, which is considered semi natural catchment and subject to a spring snow melt regime. Hydrological simulations are performed with the distributed WetSpa model, with a simulation period of 2 hydrological years. For the SA the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm is used, with a set of different response functions in regular 4 x 4 km grid. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different landscape features. Moreover, the spatial patterns of the SA results are related to the WetSpa spatial parameters and to different physical processes. Based on the study results, it is clear that spatial approach of SA can be performed with the proposed algorithm and the MOD10A1 SCF is spatially sensitive in

  15. Remotely Sensed Imagery from USGS: Update on Products and Portals

    Science.gov (United States)

    Lamb, R.; Lemig, K.

    2016-12-01

    The USGS Earth Resources Observation and Science (EROS) Center has recently implemented a number of additions and changes to its existing suite of products and user access systems. Together, these changes will enhance the accessibility, breadth, and usability of the remotely sensed image products and delivery mechanisms available from USGS. As of late 2016, several new image products are now available for public download at no charge from USGS/EROS Center. These new products include: (1) global Level 1T (precision terrain-corrected) products from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), provided via NASA's Land Processes Distributed Active Archive Center (LP DAAC); and (2) Sentinel-2 Multispectral Instrument (MSI) products, available through a collaborative effort with the European Space Agency (ESA). Other new products are also planned to become available soon. In an effort to enable future scientific analysis of the full 40+ year Landsat archive, the USGS also introduced a new "Collection Management" strategy for all Landsat Level 1 products. This new archive and access schema involves quality-based tier designations that will support future time series analysis of the historic Landsat archive at the pixel level. Along with the quality tier designations, the USGS has also implemented a number of other Level 1 product improvements to support Landsat science applications, including: enhanced metadata, improved geometric processing, refined quality assessment information, and angle coefficient files. The full USGS Landsat archive is now being reprocessed in accordance with the new `Collection 1' specifications. Several USGS data access and visualization systems have also seen major upgrades. These user interfaces include a new version of the USGS LandsatLook Viewer which was released in Fall 2017 to provide enhanced functionality and Sentinel-2 visualization and access support. A beta release of the USGS Global Visualization Tool ("Glo

  16. TCR backscattering characterization for microwave remote sensing

    Science.gov (United States)

    Riccio, Giovanni; Gennarelli, Claudio

    2014-05-01

    A Trihedral Corner Reflector (TCR) is formed by three mutually orthogonal metal plates of various shapes and is a very important scattering structure since it exhibits a high monostatic Radar Cross Section (RCS) over a wide angular range. Moreover it is a handy passive device with low manufacturing costs and robust geometric construction, the maintenance of its efficiency is not difficult and expensive, and it can be used in all weather conditions (i.e., fog, rain, smoke, and dusty environment). These characteristics make it suitable as reference target and radar enhancement device for satellite- and ground-based microwave remote sensing techniques. For instance, TCRs have been recently employed to improve the signal-to-noise ratio of the backscattered signal in the case of urban ground deformation monitoring [1] and dynamic survey of civil infrastructures without natural corners as the Musmeci bridge in Basilicata, Italy [2]. The region of interest for the calculation of TCR's monostatic RCS is here confined to the first quadrant containing the boresight direction. The backscattering term is presented in closed form by evaluating the far-field scattering integral involving the contributions related to the direct illumination and the internal bouncing mechanisms. The Geometrical Optics (GO) laws allow one to determine the field incident on each TCR plate and the patch (integration domain) illuminated by it, thus enabling the use of a Physical Optics (PO) approximation for the corresponding surface current densities to consider for integration on each patch. Accordingly, five contributions are associated to each TCR plate: one contribution is due to the direct illumination of the whole internal surface; two contributions originate by the impinging rays that are simply reflected by the other two internal surfaces; and two contributions are related to the impinging rays that undergo two internal reflections. It is useful to note that the six contributions due to the

  17. Remote Sensing Training for Middle School through the Center of Excellence in Remote Sensing Education

    Science.gov (United States)

    Hayden, L. B.; Johnson, D.; Baltrop, J.

    2012-12-01

    Remote sensing has steadily become an integral part of multiple disciplines, research, and education. Remote sensing can be defined as the process of acquiring information about an object or area of interest without physical contact. As remote sensing becomes a necessity in solving real world problems and scientific questions an important question to consider is why remote sensing training is significant to education and is it relevant to training students in this discipline. What has been discovered is the interest in Science, Technology, Engineering and Mathematics (STEM) fields, specifically remote sensing, has declined in our youth. The Center of Excellence in Remote Sensing Education and Research (CERSER) continuously strives to provide education and research opportunities on ice sheet, coastal, ocean, and marine science. One of those continued outreach efforts are Center for Remote Sensing of Ice Sheets (CReSIS) Middle School Program. Sponsored by the National Science Foundation CReSIS Middle School Program offers hands on experience for middle school students. CERSER and NSF offer students the opportunity to study and learn about remote sensing and its vital role in today's society as it relate to climate change and real world problems. The CReSIS Middle School Program is an annual two-week effort that offers middle school students experience with remote sensing and its applications. Specifically, participants received training with Global Positioning Systems (GPS) where the students learned the tools, mechanisms, and applications of a Garmin 60 GPS. As a part of the program the students were required to complete a fieldwork assignment where several longitude and latitude points were given throughout campus. The students had to then enter the longitude and latitude points into the Garmin 60 GPS, navigate their way to each location while also accurately reading the GPS to make sure travel was in the right direction. Upon completion of GPS training the

  18. A remote sensing tool to monitor and predict epidemiologic outbreaks of Hanta virus infections and Lyme disease

    Science.gov (United States)

    Barrios, M.; Verstraeten, W. W.; Amipour, S.; Wambacq, J.; Aerts, J.-M.; Maes, P.; Berckmans, D.; Lagrou, K.; van Ranst, M.; Coppin, P.

    2009-04-01

    understanding and modelling of the interactions between relevant climatic parameters (temperature, humidity, precipitation) and the main features of vegetation systems which host the vectors and determine the survival and infectious potential of the causal agents. Among the most important study subjects in this research initiative one can mention the time series analysis of vegetation parameters derived from satellite remote sensing and its relation to climatic time series and historical records of infected cases; with special attention to the assessment of remotely sensed evidences of the mast phenomenon. This analysis will constitute important buildind bricks in the construction of the INFOPRESS system in what concerns the assessment of the potentials of satellite remote sensing as information source for the prediction of infection outbreaks. The bank voles habitat description will also be supported by on-ground remote sensing techniques, specially LiDAR technology and soil humidity modelling. These measurements are to be coupled to bank voles epidemiologic features obtained from field capturing and lab analysis in which the presence of Hanta virus will be assessed.

  19. Six decades of urban growth using remote sensing and GIS in the city of Bandar Abbas, Iran

    Science.gov (United States)

    Dadras, Mohsen; Zulhaidi Mohd Shafri, Helmi; Ahmad, Noordin; Pradhan, Biswajeet; Safarpour, Sahabeh

    2014-06-01

    Bandar Abbas is the capital city of Hormozgan province, is the south of Iran. The city has witnessed rapid growth in the last three decades, mostly because of its economic, commercial and social attractions. However, forms and operations of urban sprawl may vary in important manners according to determine geographical and historical characteristics, and these difference need to be reviewed with creation geodatabase of spatial and attribute data during past periods until now of urban formation and expansion. We implemented this research to understand Bandar Abbas city growth dynamic during last six decades using aerial photo, Remote Sensing (RS) data and Geographical Information System (GIS), to investigate its sprawl for the during six decades and to prepare a basis for urban planning and management. We calibrated it with geospatial data derived from a time series of aerial photos and satellite images. Treated remote sensing data covering the six decades were used to calculate land use/cover and urban growth. The application of classification techniques to the remote sensing data enabled the extraction of eight main types of land use: agricultural, barren, coastal, hole, river, rocky hill, urban, and built-up. Growth was calculated through Shannon's entropy model. The urbanized area increased from 403.77 ha to 4959.59 ha from 1956 to 2012, a rate almost five times that of the population growth observed in the same period. Such findings make the case of Bandar Abbas important for several reasons. First, Bandar Abbas has undergone a rapid increase in urban sprawl according to urban growth indicators. Second, the urban sprawl quickly grew from medium-sized to large a process considered inappropriate according to physical and structural limitations on urban growth. Lastly, the excessive extension of the built-up boundary in the city resulted in the loss of coastal land and open space, two main sources of tourist attraction and economic sustainable development.

  20. 7th IGRSM International Remote Sensing & GIS Conference and Exhibition

    Science.gov (United States)

    Shariff, Abdul Rashid Mohamed

    2014-06-01

    IGRSM This proceedings consists of the peer-reviewed papers from the 7th IGRSM International Conference and Exhibition on Remote Sensing & GIS (IGRSM 2014), which was held on 21-22 April 2014 at Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. The conference, with the theme Geospatial Innovation for Nation Building was aimed at disseminating knowledge, and sharing expertise and experiences in geospatial sciences in all aspects of applications. It also aimed to build linkages between local and international professionals in this field with industries. Highlights of the conference included: Officiation by Y B Datuk Dr Abu Bakar bin Mohamad Diah, Deputy Minister of Minister of Science, Technology & Innovation Keynote presentations by: Associate Professor Dr Francis Harvey, Chair of the Geographic Information Science Commission at the International Geographical Union (IGU) and Director of U-Spatial, University of Minnesota, US: The Next Age of Discovery and a Future in a Post-GIS World. Professor Dr Naoshi Kondo, Bio-Sensing Engineering, University of Kyoto, Japan: Mobile Fruit Grading Machine for Precision Agriculture. Datuk Ir Hj Ahmad Jamalluddin bin Shaaban, Director-General, National Hydraulic Research Institute of Malaysia (NAHRIM), Malaysia: Remote Sensing & GIS in Climate Change Analyses. Oral and poster presentations from 69 speakers, from both Malaysia (35) and abroad (34), covering areas of water resources management, urban sprawl & social mobility, agriculture, land use/cover mapping, infrastructure planning, disaster management, technology trends, environmental monitoring, atmospheric/temperature monitoring, and space applications for the environment. Post-conference workshops on: Space Applications for Environment (SAFE), which was be organised by the Japan Aerospace Exploration Agency (JAXA) Global Positioning System (GPS) Receiver Evaluation Using GPS Simulation, which was be organised by the Science & Technology Research Institute for Defence

  1. Introduction to Time Series Modeling

    CERN Document Server

    Kitagawa, Genshiro

    2010-01-01

    In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

  2. "Trends" and variations of global oceanic evaporation data sets from remote sensing

    Institute of Scientific and Technical Information of China (English)

    CHIU LongS; CHOKNGAMWONG R; XING Yukun; YANG Ruixin; SHIE Chung-Lin

    2008-01-01

    The variability in global oceanic evaporation data sets was examined for the period 1988--2000. These data sets are satellite esti-mates based on bulk aerodynamic formulations and include the NASA/Coddard Space Flight Center Satellite-based Surface Turbu-lent Flux version 2 (GSSTF2), the Japanese-ocean flux using remote sensing observations (J-OFURO), and the Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite version 2 (HOAPS2). The National Center for Environmental Prediction (NCEP) reanalysis is also included for comparison. An increase in global average surface latent heat flux (SLHF) can be ob-served in all the data sets. Empirical mode decomposition (EMD) shows long-term increases that started around 1990 for all re-mote sensing data sets. The effect of Mr. Pinatubo eruption in 1991 is clearly evident in HOAPS2 but is independent of the long-term increase. Linear regression analyses show increases of 9.4%, 13.0%, 7.3%, and 3.9% for GSSTF2,J-OFURO, HOAPS2 and NCEP, for the periods of the data sets. Empirical orthogonal function (EOF) analyses show that the pattern of the first EOF of all data sets is consistent with a decadal variation associated with the enhancement of the tropical Hadley circulation, which is supported by other satellite observations. The second EOF of all four data sets is an ENSO mode, and the correlations be-tween their time series and an SOI are 0.74, 0.71, 0.59, and 0.61 for GSSTF2, J-OFURO, HOAPS2, and NCEP in that order. When the Hadley modes are removed from the remote sensing data, the residue global increases are reduced to 2.2%, 7.3%,and < 1% for GSSTF2, J-OFURO and HOAPS, respectively. If the ENSO mode is used as a calibration standard for the data sets, the Hadley mode is at least comparable to, if not larger than, the ENSO mode during our study period.

  3. Red Tide Information Extraction Based on Multi-source Remote Sensing Data in Haizhou Bay

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment mon...

  4. 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.

  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. Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

    Science.gov (United States)

    Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

    2016-06-01

    Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand

  7. Adult mortality in a low-density tree population using high-resolution remote sensing.

    Science.gov (United States)

    Kellner, James R; Hubbell, Stephen P

    2017-06-01

    We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr(-1) (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr(-1) , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations. © 2017 by the Ecological Society of America.

  8. Seasonality of microphytobenthos revealed by remote-sensing in a South European estuary

    Science.gov (United States)

    Brito, Ana C.; Benyoucef, Ismaїl; Jesus, Bruno; Brotas, Vanda; Gernez, Pierre; Mendes, Carlos Rafael; Launeau, Patrick; Dias, Maria Peixe; Barillé, Laurent

    2013-09-01

    The spatio-temporal variation of microphytobenthos (MPB) at the scale of a large estuary (Tagus estuary, Portugal) was studied using a combination of field and satellite remote sensing data during 2003. This is the first attempt to use remote sensing to study MPB in an ecosystem with a Mediterranean-like climate. Satellite pour l'Observation de la Terre (SPOT) and Medium Resolution Imaging Spectrometer (MERIS) images were used to map benthic microalgae through the application of a Normalized Difference Vegetation index (NDVI). A significant relationship between in-situ benthic chlorophyll a measurements and SPOT NDVI values was used to derive a map for biomass spatial distribution. At the scale of the whole intertidal area, NDVI time-series from 2003 revealed that MPB showed clear temporal variations, with lower values observed in summer compared to winter. This seasonal trend was found both in the SPOT and MERIS images and may be the result of extreme high temperatures that inhibit MPB growth. The main MPB biofilms were spatially stable through time at a large scale. Maximum NDVI values during the winter were found in the high shore with decreasing NDVI values towards the low shore. MPB light limitation at the lowest bathymetries is likely to occur in winter due to the high turbidity of Tagus estuary. The biomass spatial distribution map, obtained for January 2003, indicated low values ranging from 0 to 20 mg Chl a m-2 for the lower shores, while in the upper shore biomass varied between 60 and 80 mg Chl a m-2. This study suggests striking differences in MPB seasonal patterns between the northern and southern European estuaries and stresses the need for ecophysiological approaches to investigate the role of thermo- and photo-inhibition as structuring factors for MPB biomass distribution.

  9. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  10. Remote Sensing of Parasitic Nematodes in Plants

    Science.gov (United States)

    Lawrence, Gary W.; King, Roger; Kelley, Amber T.; Vickery, John

    2007-01-01

    A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.

  11. Toward interactive search in remote sensing imagery

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Do [Los Alamos National Laboratory; Harvey, Neal [Los Alamos National Laboratory; Theile, James [Los Alamos National Laboratory

    2010-01-01

    To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new design criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.

  12. Remote sensing of balsam fir forest vigor

    Science.gov (United States)

    Luther, Joan E.; Carroll, Allen L.

    1997-12-01

    The potential of remote sensing to monitor indices of forest health was tested by examining the spectral separability of plots with different balsam fir, Abies balsamea (L.) Mill, vigor. Four levels of vigor were achieved with controlled experimental manipulations of forest stands. In order of increasing vigor, the treatments were root pruning, control, thinning and thinning in combination with fertilization. Spectral reflectance of branchlets from each plot were measured under laboratory conditions using a field portable spectroradiometer with a spectral range from 350 - 2500 nm. Branchlets were discriminated using combinations of factor and discriminant analyses techniques with classification accuracies of 91% and 83% for early and late season analyses, respectively. Relationships between spectral reflectance measurements at canopy levels, stand vigor, and foliage quality for an insect herbivore will be analyzed further in support of future large scale monitoring of balsam fir vulnerability to insect disturbance.

  13. Benefits to world agriculture through remote sensing

    Science.gov (United States)

    Buffalano, A. C.; Kochanowski, P.

    1976-01-01

    Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy, and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 300 to 400 million dollars annually for the rest of the world.

  14. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  15. Recent Progresses of Microwave Marine Remote Sensing

    Science.gov (United States)

    Yang, Jingsong; Ren, Lin; Zheng, Gang; Wang, He; He, Shuangyan; Wang, Juan; Li, Xiaohui

    2016-08-01

    It is presented in this paper the recent progresses of Dragon 3 Program (ID. 10412) in the field of microwave marine remote sensing including (1) ocean surface wind fields from full polarization synthetic aperture radars (SAR), (2) joint retrieval of directional ocean wave spectra from SAR and wave spectrometer, (3) error analysis on ENVISAT ASAR wave mode significant wave height (SWH) retrievals using triple collocation model, (4) typhoon observation from SAR and optical sensors, (5) ocean internal wave observation from SAR and optical sensors, (6) ocean eddy observation from SAR and optical sensors, (7) retrieval models of water vapor and wet tropospheric path delay for the HY-2A calibration microwave radiometer, (8) calibration of SWH from HY-2A satellite altimeter.

  16. Remote sensing with laser spectrum radar

    Science.gov (United States)

    Wang, Tianhe; Zhou, Tao; Jia, Xiaodong

    2016-10-01

    The unmanned airborne (UAV) laser spectrum radar has played a leading role in remote sensing because the transmitter and the receiver are together at laser spectrum radar. The advantages of the integrated transceiver laser spectrum radar is that it can be used in the oil and gas pipeline leak detection patrol line which needs the non-contact reflective detection. The UAV laser spectrum radar can patrol the line and specially detect the swept the area are now in no man's land because most of the oil and gas pipelines are in no man's land. It can save labor costs compared to the manned aircraft and ensure the safety of the pilots. The UAV laser spectrum radar can be also applied in the post disaster relief which detects the gas composition before the firefighters entering the scene of the rescue.

  17. Urban environmental health applications of remote sensing

    Science.gov (United States)

    Rush, M.; Goldstein, J.; Hsi, B. P.; Olsen, C. B.

    1974-01-01

    An urban area was studied through the use of the inventory-by-surrogate method rather than by direct interpretation of photographic imagery. Prior uses of remote sensing in urban and public research are examined. The effects of crowding, poor housing conditions, air pollution, and street conditions on public health are considered. Color infrared photography was used to categorize land use features and the grid method was used in photo interpretation analysis. The incidence of shigella and salmonella, hepatitis, meningitis, tuberculosis, myocardial infarction and veneral disease were studied, together with mortality and morbidity rates. Sample census data were randomly collected and validated. The hypothesis that land use and residential quality are associated with and act as an influence upon health and physical well-being was studied and confirmed.

  18. Hyperspectral Remote Sensing for Tropical Rain Forest

    Directory of Open Access Journals (Sweden)

    Kamaruzaman Jusoff

    2009-01-01

    Full Text Available Problem statement: Sensing, mapping and monitoring the rain forest in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions and are now included in climate change negotiations. Approach: We reviewed the potential for air and spaceborne hyperspectral sensing to identify and map individual tree species measure carbon stocks, specifically Aboveground Biomass (AGB and provide an overview of a range of approaches that have been developed and used to map tropical rain forest across a diverse set of conditions and geographic areas. We provided a summary of air and spaceborne hyperspectral remote sensing measurements relevant to mapping the tropical forest and assess the relative merits and limitations of each. We then provided an overview of modern techniques of mapping the tropical forest based on species discrimination, leaf chlorophyll content, estimating aboveground forest productivity and monitoring forest health. Results: The challenges in hyperspectral Imaging of tropical forests is thrown out to researchers in such field as to come with the latest techniques of image processing and improved mapping resolution leading towards higher precision mapping accuracy. Some research results from an airborne hyperspectral imaging over Bukit Nanas forest reserve was shared implicating high potential of such very high resolution imaging techniques for tropical mixed dipterocarp forest inventory and mapping for species discrimination, aboveground forest productivity, leaf chlorophyll content and carbon mapping. Conclusion/Recommendations: We concluded that while spaceborne hyperspectral remote sensing has often been discounted as inadequate for the task, attempts to map with airborne sensors are still insufficient in tropical developing countries like Malaysia. However, we demonstrated this with a case

  19. Acoustic Remote Sensing of Rogue Waves

    Science.gov (United States)

    Parsons, Wade; Kadri, Usama

    2016-04-01

    We propose an early warning system for approaching rogue waves using the remote sensing of acoustic-gravity waves (AGWs) - progressive sound waves that propagate at the speed of sound in the ocean. It is believed that AGWs are generated during the formation of rogue waves, carrying information on the rogue waves at near the speed of sound, i.e. much faster than the rogue wave. The capability of identifying those special sound waves would enable detecting rogue waves most efficiently. A lot of promising work has been reported on AGWs in the last few years, part of which in the context of remote sensing as an early detection of tsunami. However, to our knowledge none of the work addresses the problem of rogue waves directly. Although there remains some uncertainty as to the proper definition of a rogue wave, there is little doubt that they exist and no one can dispute the potential destructive power of rogue waves. An early warning system for such extreme waves would become a demanding safety technology. A closed form expression was developed for the pressure induced by an impulsive source at the free surface (the Green's function) from which the solution for more general sources can be developed. In particular, we used the model of the Draupner Wave of January 1st, 1995 as a source and calculated the induced AGW signature. In particular we studied the AGW signature associated with a special feature of this wave, and characteristic of rogue waves, of the absence of any local set-down beneath the main crest and the presence of a large local set-up.

  20. Remote sensing of sagebrush canopy nitrogen

    Science.gov (United States)

    Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.

    2012-01-01

    This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.

  1. A selected bibliography: Remote sensing applications in wildlife management

    Science.gov (United States)

    Carneggie, David M.; Ohlen, Donald O.; Pettinger, Lawrence R.

    1980-01-01

    Citations of 165 selected technical reports, journal articles, and other publications on remote sensing applications for wildlife management are presented in a bibliography. These materials summarize developments in the use of remotely sensed data for wildlife habitat mapping, habitat inventory, habitat evaluation, and wildlife census. The bibliography contains selected citations published between 1947 and 1979.

  2. Estimation of Areal Soil Water Content through Microwave Remote Sensing

    NARCIS (Netherlands)

    Oevelen, van P.J.

    2000-01-01

    In this thesis the use of microwave remote sensing to estimate soil water content is investigated. A general framework is described which is applicable to both passive and active microwave remote sensing of soil water content. The various steps necessary to estimate areal soil water content are disc

  3. Hydrological Application of Remote Sensing: Surface States -- Snow

    Science.gov (United States)

    Hall, Dorothy K.; Kelly, Richard E. J.; Foster, James L.; Chang, Alfred T. C.

    2004-01-01

    Remote sensing research of snow cover has been accomplished for nearly 40 years. The use of visible, near-infrared, active and passive-microwave remote sensing for the analysis of snow cover is reviewed with an emphasis on the work on the last decade.

  4. Remote sensing observation used in offshore wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

    2008-01-01

    Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

  5. Deriving harmonised forest information in Europe using remote sensing methods

    DEFF Research Database (Denmark)

    Seebach, Lucia Maria

    the need for harmonised forest information can be satisfied using remote sensing methods. In conclusion, the study showed that it is possible to derive harmonised forest information of high spatial detail in Europe with remote sensing. The study also highlighted the imperative provision of accuracy...

  6. Potential benefits of remote sensing: Theoretical framework and empirical estimate

    Science.gov (United States)

    Eisgruber, L. M.

    1972-01-01

    A theoretical framwork is outlined for estimating social returns from research and application of remote sensing. The approximate dollar magnitude is given of a particular application of remote sensing, namely estimates of corn production, soybeans, and wheat. Finally, some comments are made on the limitations of this procedure and on the implications of results.

  7. Streamflow modelling by remote sensing: a contribution to digital earth

    NARCIS (Netherlands)

    Tan, M.L.; Latif, A.B.; Pohl, C.; Duan, Z.

    2014-01-01

    Remote sensing contributes valuable information to streamflow estimates. This paper discusses its relevance to the digital earth concept. The authors categorize the role of remote sensing in streamflow modelling and estimation. This paper emphasizes the applications and challenges of satellite-based

  8. Application of remote sensing to agricultural field trials.

    NARCIS (Netherlands)

    Clevers, J.G.P.W.

    1986-01-01

    Remote sensing techniques enable quantitative information about a field trial to be obtained instantaneously and non-destructively. The aim of this study was to identify a method that can reduce inaccuracies in field trial analysis, and to identify how remote sensing can support and/or replace conve

  9. International Models and Methods of Remote Sensing Education and Training.

    Science.gov (United States)

    Anderson, Paul S.

    A classification of remote sensing courses throughout the world, the world-wide need for sensing instruction, and alternative instructional methods for meeting those needs are discussed. Remote sensing involves aerial photointerpretation or the use of satellite and other non-photographic imagery; its focus is to interpret what is in the photograph…

  10. Study on spectral structure of quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    A study of the use of fine spectral structure in quantum remote sensing, including an expression, begins with a summary of present-day applications of spectrum remote sensing, which is followed by a theoretical discussion of the influence of electronic spin upon hydrogen-like atom energy levels and the calculation of spectral line in the absence of a circumstance field.

  11. Quantitative Application Study on Remote Sensing of Suspended Sediment

    Institute of Scientific and Technical Information of China (English)

    CHEN Yi-mei; XU Su-dong; LIN Qiang

    2012-01-01

    Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study.In this paper,the Xiamen Bay is chosen as the study area.Eleven different phases of the remote sensing data are selected to establish a quantitative remote sensing model to map suspended sediment by using remote sensing images and the quasi-synchronous measured sediment data.Based on empirical statistics developed are the conversion models between instantaneous suspended sediment concentration and tidally-averaged suspended sediment concentration as well as the conversion models between surface layer suspended sediment concentration and the depth-averaged suspended sediment concentration.On this basis,the quantitative application integrated model on remote sensing of suspended sediment is developed.By using this model as well as multi-temporal remote sensing images,multi-year averaged suspended sediment concentration of the Xiamen Bay are predicted.The comparison between model prediction and observed data shows that the multi-year averaged suspended sediment concentration of studied sites as well as the concentration difference of neighboring sites can be well predicted by the remote sensing model with an error rate of 21.61% or less,which can satisfy the engineering requirements of channel deposition calculation.

  12. Technology Progress Report for Spaceborne Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JHANG Jingshan; LIU Heguang; DONG Xiaolong

    2006-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments formeteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (H J-1C) and China's lunar exploration satellite (Chang'E-1), are reported.

  13. Progress for Spaceborne Microwave Remote Sensing in China

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; LIU Heguang; DONG Xiaolong

    2008-01-01

    In this paper, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for meteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (HJ-1C) and China's lunar exploration satellite (Chang'E-1), geostationary orbit meteorological satellite FY-4M,are reported.

  14. MONITORING PHENOLOGICAL VARIABILITY ACROSS A TROPICAL SAVANNA ARIDITY GRADIENT WITH REMOTE SENSING ACROSS SEASONAL TO ANNUALAND EXTREME EVENTS

    Directory of Open Access Journals (Sweden)

    A. Huete

    2012-08-01

    Full Text Available Tropical savannas are key components of the global carbon and water cycles and understanding their functioning is critical to understanding ecosystem feedbacks to global climate. By observing broad scale vegetation responses to climatic variability, remote sensing offers powerful insights into the patterns and processes underlying savanna behaviour. However, savannas are highly complex, multi-layer and heterogenous ecosystems composed of C3 (herbaceous and C4 (woodland components with asynchronous phenological responses to environmental controls. There are concerns about optimizing the detection of savanna functioning as well as in understanding their environmental controls with remote-sensing data due to their coarse resolution. Furthermore, seasonalphenologic variations in satellite observations need to be sufficiently accurate to ensure confidence in interpreting vegetation responses to interannual climatic variation and to aid in constraining models of carbon and water fluxes. In this study, we analysed several years of high temporal frequency MODIS and TRMM satellite data sets of vegetation dynamics and rainfall, respectively, to seasonal and interannual responses of savanna multifunctional components to climate variability across a tropical savanna aridity gradient (1760 to 580 mm annual rainfall in northern Australia. We compared our results with a series of eddy covariance (EC tower flux data of gross primary production and analyzed a wide set of ecosystem processes including photosynthesis, net primary productivity, phenological metrics in timing of the growing season, and rain use efficiencies. We found MODIS satellite measurements to yield highly accurate spatial and temporal variability in ecosystem functioning and able to replicate interannual patterns and responses to rainfall observed with the EC tower data. Although these results appear promising for regional extensions of satelliteflux tower relationships at the landscape level

  15. Monitoring soil moisture through assimilation of active microwave remote sensing observation into a hydrologic model

    Science.gov (United States)

    Liu, Qian; Zhao, Yingshi

    2015-08-01

    Soil moisture can be estimated from point measurements, hydrologic models, and remote sensing. Many researches indicated that the most promising approach for soil moisture is the integration of remote sensing surface soil moisture data and computational modeling. Although many researches were conducted using passive microwave remote sensing data in soil moisture assimilation with coarse spatial resolution, few researches were carried out using active microwave remote sensing observation. This research developed and tested an operational approach of assimilation for soil moisture prediction using active microwave remote sensing data ASAR (Advanced Synthetic Aperture Radar) in Heihe Watershed. The assimilation was based on ensemble Kalman filter (EnKF), a forward radiative transfer model and the Distributed Hydrology Soil Vegetation Model (DHSVM). The forward radiative transfer model, as a semi-empirical backscattering model, was used to eliminate the effect of surface roughness and vegetation cover on the backscatter coefficient. The impact of topography on soil water movement and the vertical and lateral exchange of soil water were considered. We conducted experiments to assimilate active microwave remote sensing data (ASAR) observation into a hydrologic model at two field sites, which had different underlying conditions. The soil moisture ground-truth data were collected through the field Time Domain Reflectometry (TDR) tools, and were used to assess the assimilation method. The temporal evolution of soil moisture measured at point-based monitoring locations were compared with EnKF based model predictions. The results indicated that the estimate of soil moisture was improved through assimilation with ASAR observation and the soil moisture based on data assimilation can be monitored in moderate spatial resolution.

  16. Geospatial Education and Research Development: A Laboratory for Remote Sensing and Environmental Analysis (LaRSEA)

    Science.gov (United States)

    Allen, Thomas R., Jr.

    1999-01-01

    Old Dominion University has claimed the title "University of the 21st Century," with a bold emphasis on technology innovation and application. In keeping with this claim, the proposed work has implemented a new laboratory equipped for remote sensing as well as curriculum and research innovations afforded for present and future faculty and students. The developments summarized within this report would not have been possible without the support of the NASA grant and significant cost-sharing of several units within the University. The grant effectively spring-boarded the university into major improvements in its approach to remote sensing and geospatial information technologies. The university has now committed to licensing Erdas Imagine software for the laboratory, a campus-wide ESRI geographic information system (GIS) products license, and several smaller software and hardware utilities available to faculty and students through the laboratory. Campus beneficiaries of this grant have included faculty from departments including Ocean, Earth. and Atmospheric Sciences, Political Science and Geography, Ecological Sciences, Environmental Health, and Civil and Environmental Engineering. High student interest is evidenced in students in geology, geography, ecology, urban studies, and planning. Three new courses have been added to the catalog and offered this year. Cross-cutting curriculum changes are in place with growing enrollments in remote sensing, GIS, and a new co-taught seminar in applied coastal remote sensing. The enabling grant has also allowed project participants to attract external funding for research grants, thereby providing additional funds beyond the planned matching, maintenance and growth of software and hardware, and stipends for student assistants. Two undergraduate assistants and two graduate assistants have been employed by full-time assistantships as a result. A new certificate is offered to students completing an interdisciplinary course sequence

  17. GPS Position Time Series @ JPL

    Science.gov (United States)

    Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

    2013-01-01

    Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined