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.
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...
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...
Brown, R. L. (Principal Investigator)
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.
Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.
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
Genco, S.; Bortoli, D.; Ravegnani, F.
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
Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F
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.
Sun, J.; Xiang, H.
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.
Full Text Available Mine environment problem caused by the exploitation of mineral resources has become a key factor which affects normal production of mine and safety of ecological environment for human settlement. For better protection and management of mine environment, this article has introduced the important role of remote sensing technology in pollution monitoring of mine environment, geological disaster monitoring and monitoring of mining activities.
Bolton, W.; Lapp, M.; Vitko, J. Jr. [Sandia National Labs., Livermore, CA (United States); Phipps, G. [Sandia National Labs., Albuquerque, NM (United States)
This report documents the results of a Laboratory Directed Research and Development (LDRD) program to explore how best to utilize Sandia`s defense-related sensing expertise to meet the Department of Energy`s (DOE) ever-growing needs for environmental monitoring. In particular, we focused on two pressing DOE environmental needs: (1) reducing the uncertainties in global warming predictions, and (2) characterizing atmospheric effluents from a variety of sources. During the course of the study we formulated a concept for using unmanned aerospace vehicles (UAVs) for making key 0798 climate measurements; designed a highly accurate, compact, cloud radiometer to be flown on those UAVs; and established the feasibility of differential absorption Lidar (DIAL) to measure atmospheric effluents from waste sites, manufacturing processes, and potential treaty violations. These concepts have had major impact since first being formulated in this ,study. The DOE has adopted, and DoD`s Strategic Environmental Research Program has funded, much of the UAV work. And the ultraviolet DIAL techniques have already fed into a major DOE non- proliferation program.
The extent of past and anticipated plantings of transgenic corn in the United States requires a new approach to monitor this important crop for the development of pest resistance. Remote sensing by aerial and/or satellite images may provide a method of identifying transgenic pest...
Current plantings of 25+ million acres of transgenic corn in the United States require a new approach to monitor this important crop for the development of pest resistance. Remote sensing by aerial or satellite images may provide a method of identifying transgenic pesticidal cro...
Li, Na; Lü, Jian-sheng; Altemann, W
Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.
Rhee, Jinyoung; Im, Jungho; Park, Seonyoung
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
Jones, Cathleen E.
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.
Wu, Dai-hui; Fan, Wen-jie; Cui, Yao-kui; Yan, Bin-yan; Xu, Xi-ru
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.
Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moist...
Xueyan; SUI; Rujuan; WANG; Huimin; YAO; Meng; WANG; Shaokun; LI; Xiaodong; ZHANG
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.
Crosetto, Michele; Monserrat, Oriol; Luzi, Guido; Cuevas-González, María; Devanthéry, Núria
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...
McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall
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
Ecological and crop condition monitoring requires high temporal and spatial resolution remote sensing data. Due to technical limitations and budget constraints, remote sensing instruments trade spatial resolution for swath width. As a result, it is difficult to acquire remotely sensed data with both...
Wang, Guangjun; Fu, Meichen; Xiao, Qiuping; Wang, Zeng
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.
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.).
Full Text Available Agricultural drought is a natural hazard that can be characterized by shortage of water supply. In the scope of this paper, we synthesized the importance of agricultural drought and methods commonly employed to monitor agricultural drought conditions. These include: (i in-situ based methods, (ii optical remote sensing methods, (iii thermal remote sensing methods, (iv microwave remote sensing methods, (v combined remote sensing methods, and (vi synergy between in-situ and remote sensing based methods. The in-situ indices can provide accurate results at the point of measurements; however, unable to provide spatial dynamics over large area. This can potentially be addressed by using remote sensing based methods because remote sensing platforms have the ability to view large area at a near continuous fashion. The remote sensing derived agricultural drought related indicators primarily depend on the characteristics of reflected/emitted energy from the earth surface, thus the results can be relatively less accurate in comparison to the in-situ derived outcomes. Despite a significant amount of research and development has been accomplished in particular to the area of remote sensing of agricultural drought, still there are several challenges. Those include: monitoring relatively small area, filling gaps in the data, developing consistent historical dataset, developing remote sensing-based agricultural drought forecasting system, integrating the recently launched and upcoming remote sensors, and developing standard validation schema, among others.
Williams, Richard S., Jr.; Southworth, C. Scott
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)
H S Negi; N K Thakur; A Ganju; Snehmani
In this study, Gangotri glacier was monitored using Indian Remote Sensing (IRS) LISS-III sensor data in combination with field collected snow-meteorological data for a period of seven years (2001–2008). An overall decreasing trend in the areal extent of seasonal snow cover area (SCA) was observed. An upward shifting trend of wet snow line was observed in the beginning of melt period, i.e., in May and dominant wet snow conditions were observed between May and October. Snow meteorological parameters collected in the Gangotri sub-basin suggest reduction in fresh snowfall amount during winter, increase in rainfall amount during summer, decrease in snowfall days, increase in rainfall days and rising trend of average temperature. The prevailing wet snow condition on glacier has caused scouring of slopes which led the excessive soil/debris deposition on the glacier surface. This was observed as one of the major factor for activating fast melting and affecting the glacier health significantly. Apart from climatic conditions, terrain factors were observed for changing the glacio-morphology. The significant changes on the glacier surface were observed in the regions of abrupt slope change. The above factors affecting the Gangotri glacier health were also validated using high resolution satellite imageries and field visit. A deglaciation of 6% in overall area of Gangotri glacier was observed between the years 1962 and 2006.
Watkins, Allen H.; Lauer, D.T.; Bailey, G.B.; Moore, D.G.; Rohde, W.G.
Space remote sensing systems are compared for suitability in assessing and monitoring the Earth's renewable resources. Systems reviewed include the Landsat Thematic Mapper (TM), the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), the French Systeme Probatoire d'Observation de la Terre (SPOT), the German Shuttle Pallet Satellite (SPAS) Modular Optoelectronic Multispectral Scanner (MOMS), the European Space Agency (ESA) Spacelab Metric Camera, the National Aeronautics and Space Administration (NASA) Large Format Camera (LFC) and Shuttle Imaging Radar (SIR-A and -B), the Russian Meteor satellite BIK-E and fragment experiments and MKF-6M and KATE-140 camera systems, the ESA Earth Resources Satellite (ERS-1), the Japanese Marine Observation Satellite (MOS-1) and Earth Resources Satellite (JERS-1), the Canadian Radarsat, the Indian Resources Satellite (IRS), and systems proposed or planned by China, Brazil, Indonesia, and others. Also reviewed are the concepts for a 6-channel Shuttle Imaging Spectroradiometer, a 128-channel Shuttle Imaging Spectrometer Experiment (SISEX), and the U. S. Mapsat.
Wilson, Natalie R; Norman, Laura M.; Villarreal, Miguel; Gass, Leila; Tiller, Ron; Salywon, Andrew
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.
Tamás, János; Nagy, Attila; Fehér, János
There is a close quality relationship between the harmful levels of all three drought indicator groups (meteorological, hydrological and agricultural). However, the numerical scale of the relationships between them is unclear and the conversion of indicators is unsolved. Different areas or an area with different forms of drought cannot be compared. For example, from the evaluation of meteorological drought using the standardized precipitation index (SPI) values of a river basin, it cannot be stated how many tonnes of maize will be lost during a given drought period. A reliable estimated rate of yield loss would be very important information for the planned interventions (i.e. by farmers or river basin management organisations) in terms of time and cost. The aim of our research project was to develop a process which could provide information for estimating relevant drought indexes and drought related yield losses more effectively from remotely sensed spectral data and to determine the congruency of data derived from spectral data and from field measurements. The paper discusses a new calculation method, which provides early information on physical implementation of drought risk levels. The elaborated method provides improvement in setting up a complex drought monitoring system, which could assist hydrologists, meteorologists and farmers to predict and more precisely quantify the yield loss and the role of vegetation in the hydrological cycle. The results also allow the conversion of different-purpose drought indices, such as meteorological, agricultural and hydrological ones, as well as allow more water-saving agricultural land use alternatives to be planned in the river basins.
Goodman, James A; Phinn, Stuart R
This book offers a multi-level examination of remote-sensing technologies for mapping and monitoring coral reef ecosystems, ranging from satellite and airborne imagery to ship-based observation. Includes examples of practical applications of the technologies.
Pickles, W; Cover, W
This project's goal is to develop remote sensing methods for early detection and spatial mapping, over whole regions simultaneously, of any surface areas under which there are significant CO2 leaks from deep underground storage formations. If large amounts of CO2 gas percolated up from a storage formation below to within plant root depth of the surface, the CO2 soil concentrations near the surface would become elevated and would affect individual plants and their local plant ecologies. Excessive soil CO2 concentrations are observed to significantly affect local plant and animal ecologies in our geothermal exploration, remote sensing research program at Mammoth Mountain CA USA. We also know from our geothermal exploration remote sensing programs, that we can map subtle hidden faults by spatial signatures of altered minerals and of plant species and health distributions. Mapping hidden faults is important because in our experience these highly localized (one to several centimeters) spatial pathways are good candidates for potentially significant CO2 leaks from deep underground formations. The detection and discrimination method we are developing uses primarily airborne hyperspectral, high spatial (3 meter) with 128 band wavelength resolution, visible and near infrared reflected light imagery. We also are using the newly available ''Quickbird'' satellite imagery that has high spatial resolution (0.6 meter for panchromatic images, 2.4 meters for multispectral). We have a commercial provider, HyVista Corp of Sydney Australia, of airborne hyperspectral imagery acquisitions and very relevant image data post processing, so that eventually the ongoing surveillance of CO2 storage fields can be contracted for commercially. In this project we have imaged the Rangely Colorado Oil field and surrounding areas with an airborne hyperspectral visible and near infrared reflected light sensor. The images were analyzed by several methods using the suite of
Wang, H.; Lin, H.; Liu, D.
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.
Hamada, Yuki [Argonne National Lab. (ANL), Argonne, IL (United States); Rollins, Katherine E. [Argonne National Lab. (ANL), Argonne, IL (United States)
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.
Xu, Hua; Gu, Xingfa; Yin, Qiu; Li, Li; Chen, Qiang; Ren, Yuhuan; Chen, Hong; Liu, Xudong; Zhang, Juan
This paper aims at bridging the gap between the academic research and practical application in water environment monitoring by remote sensing. It mainly focuses on how to rapidly construct the Inland and coastal Water Environment Remote Sensing Monitoring System (IWERSMS) in a software perspective. In this paper, the remote sensed data processing framework, dataflow and product levels are designed based on the retrieval algorithms of water quality parameters. The prototype is four-tier architecture and modules are designed elaborately. The paper subsequently analyzes the strategy and key technology of conglutinating hybrid components, adopting semantic metafiles and tiling image during rapid construction of prototype. Finally, the paper introduces the successful application to 2008 Qingdao enteromorpha prolifra disaster emergency monitoring in Olympics Sailing Match fields. The solution can also fit other domains in remote sensing and especially it provides a clue for researchers who are in an attempt to establish a prototype to apply research fruits to practical applications.
Liu, Z.; Zou, X.; Liu, H.
As one of the serious ecological environmental problems of the Tibetan plateau, desertification has critically hampered the economic and social development in Tibet, so it is imperative to monitoring the desertification in Tibet area. Due to its 200 thousand km2 vast area and steep terrain, this paper uses multi-source remote sensing image to survey the current situation of land desertification in Tibetan plateau, and study dynamic desertification change on the 10 km2 land between Namucuo lake and Selincuo lake. Data of the 250 meters time-series MODIS-NDVI images, 30 m resolution Landsat TM images and 90 m SRTM DEM data were used. Through the analysis of the relationship between MODIS-NDVI, vegetation growth characteristics and vegetation vertical distribution, this paper chooses the MODIS-NDVI time series data and principal component analysis of the first band (PC1), vegetation coverage(VC), DEM and its derived slope data as indicators for desertification monitoring. Visual interpretation based on 30 m TM image is also used to classify each type of desertification. Using the high temporal resolution data, we can quickly obtain desertification hot spot areas then accurately distinguish each degree of desertification with high spatial resolution images. The results are: (1) The desertification area in Tibetan plateau in 2008 is 218,286 km2, which is 18.91% of the total area, and mainly distributed in the Ali region, next by Nagqu and Xigaze. The severe desertification land area is 8,866 km2 ( 4.06% of the desertified land), of which the mobile dune area is 3224 km2, heavy saline area is 5641 km2. Moderate desertified land area is 110,915 km2( 50.81% of the desertified land), of which semi-fixed sand dune area is 10,075 km2 and the bare sand area is 100,839 km2. Mild desertified land area is 98,504 km2 ( 45.12% of the desertified land), of which the fixed dune area is 4,177 km2 and the half bare gravel area is 94,326 km2. (2) By using GIS spatial analysis, westudied
Huang, Qing; Zhou, Qing-bo; Zhang, Li
China is a large agricultural country. To understand the agricultural production condition timely and accurately is related to government decision-making, agricultural production management and the general public concern. China Agriculture Remote Sensing Monitoring System (CHARMS) can monitor crop acreage changes, crop growing condition, agriculture disaster (drought, floods, frost damage, pest etc.) and predict crop yield etc. quickly and timely. The basic principles, methods and regular operation of crop growing condition monitoring in CHARMS are introduced in detail in the paper. CHARMS can monitor crop growing condition of wheat, corn, cotton, soybean and paddy rice with MODIS data. An improved NDVI difference model was used in crop growing condition monitoring in CHARMS. Firstly, MODIS data of every day were received and processed, and the max NDVI values of every fifteen days of main crop were generated, then, in order to assessment a certain crop growing condition in certain period (every fifteen days, mostly), the system compare the remote sensing index data (NDVI) of a certain period with the data of the period in the history (last five year, mostly), the difference between NDVI can indicate the spatial difference of crop growing condition at a certain period. Moreover, Meteorological data of temperature, precipitation and sunshine etc. as well as the field investigation data of 200 network counties were used to modify the models parameters. Last, crop growing condition was assessment at four different scales of counties, provinces, main producing areas and nation and spatial distribution maps of crop growing condition were also created.
BO Li-qun; ZHAO Yun-ping; HUA Ren-kui
Volcanic eruption is one of the most serious geological disasters, however, a host of facts have proven that the Changbai Mountains volcano is a modem dormant one and has ever erupted disastrously. With the rapid development of remote sensing technology, space monitoring of volcanic activities has already become possible, particularly in the application of thermal infrared remote sensing. The paper, through the detailed analysis of geothermal anomaly factors such as heat radiation, heat conduction and convection, depicts the monitoring principles by which volcano activities would be monitored efficiently and effectively. Reasons for abrupt geothermal anomaly are mainly analyzed, and transmission mechanism of geothermal anomaly in the volcanic regions is explained. Also, a variety of noises disturbing the transmission of normal geothermal anomaly are presented. Finally, some clues are given based on discussing thermal infrared remote sensing monitoring mechanism toward the volcanic areas.
Iacoboaea, Cristina; Petrescu, Florian
Landfill monitoring is one of the most important components of waste management. This article presents a case study on landfill monitoring using remote sensing technology. The study area was the Glina landfill, one of the largest municipal waste disposal sites in Romania. The methodology consisted of monitoring the differences of temperature computed for several distinct waste disposal zones with respect to a ground reference area, all of them located within the landfill site. The remote sensing data used were Landsat satellite multi-temporal data. The differences of temperature were computed using Landsat thermal infrared data. The study confirmed the use of multi-temporal Landsat imagery as a complementary data source.
Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Raffaele; Pascucci, Simone; Silvesrtro, Paolo Cosmo
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.
Full Text Available Coastal lands and nearshore marine areas are productive and rapidly changing places. However, these areas face many environmental challenges related to climate change and human-induced impacts. Space-borne remote sensing systems may be restricted in monitoring these areas because of their spatial and temporal resolutions. In situ measurements are also constrained from accessing the area and obtaining wide-coverage data. In these respects, airborne remote sensing sensors could be the most appropriate tools for monitoring these coastal areas. In this study, a cost-effective airborne remote sensing system with synthetic aperture radar and thermal infrared sensors was implemented to survey coastal areas. Calibration techniques and geophysical model algorithms were developed for the airborne system to observe the topography of intertidal flats, coastal sea surface current, sea surface temperature, and submarine groundwater discharge.
Hively, Wells; Sjoerd Duiker,; Greg McCarty,; Prabhakara, Kusuma
In the Chesapeake Bay Watershed, winter cereal cover crops are often planted in rotation with summer crops to reduce the loss of nutrients and sediment from agricultural systems. Cover crops can also improve soil health, control weeds and pests, supplement forage needs, and support resilient cropping systems. In southeastern Pennsylvania, cover crops can be successfully established following corn (Zea mays L.) silage harvest and are strongly promoted for use in this niche. They are also planted following corn grain, soybean (Glycine max L.), and vegetable harvest. In Pennsylvania, the use of winter cover crops for agricultural conservation has been supported through a combination of outreach, regulation, and incentives. On-farm implementation is thought to be increasing, but the actual extent of cover crops is not well quantified. Satellite imagery can be used to map green winter cover crop vegetation on agricultural fields and, when integrated with additional remote sensing data products, can be used to evaluate wintertime vegetative groundcover following specific summer crops. This study used Landsat and SPOT (System Probatoire d’ Observation de la Terre) satellite imagery, in combination with the USDA National Agricultural Statistics Service Cropland Data Layer, to evaluate the extent and amount of green wintertime vegetation on agricultural fields in four Pennsylvania counties (Berks, Lebanon, Lancaster, and York) from 2010 to 2013. In December of 2010, a windshield survey was conducted to collect baseline data on winter cover crop implementation, with particular focus on identifying corn harvested for silage (expected earlier harvest date and lower levels of crop residue), versus for grain (expected later harvest date and higher levels of crop residue). Satellite spectral indices were successfully used to detect both the amount of green vegetative groundcover and the amount of crop residue on the surveyed fields. Analysis of wintertime satellite imagery
Full Text Available Monitoring of forest burnt areas has several aims: to locate and estimate the extent of such areas; to assess the damages suffered by the forest stands; to check the ability of the ecosystem to naturally recover after the fire; to support the planning of reclamation interventions; to assess the dynamics (pattern and speed of the natural recovery; to check the outcome of any eventual restoration intervention. Remote sensing is an important source of information to support all such tasks. In the last decades, the effectiveness of remotely sensed imagery is increasing due to the advancement of tools and techniques, and to the lowering of the costs, in relative terms. For an effective support to post-fire management (burnt scar perimeter mapping, damage severity assessment, post-fire vegetation monitoring, a mapping scale of at least 1:10000-1:20000 is required: hence, the selection of remotely sensed data is restricted to aerial imagery and to satellite imagery characterized by high (HR and, above all, very high (VHR spatial resolution. In the last decade, HR and VHR passive remote sensing has widespread, providing affordable multitemporal and multispectral pictures of the considered phenomena, at different scales (spatial, temporal and spectral resolutions with reference to the monitoring needs. In the light of such a potential, the integration of GPS field survey and HR (Landsat 7, Spot HVR and VHR satellite imagery (Ikonos, Quickbird, Spot 5 is currently sought as a highly viable option for the post-fire monitoring.
With a changing climate, drought has become more intensified, of which agriculture is the major affected sector. Satellite observations have proven great utilities for real-time drought monitoring as well as crop yield estimation, and many remotely sensed indicators have been developed for drought monitoring based on vegetation growth conditions, surface temperature and evapotranspiration information. However, those current drought indicators typically don't take into account the different responses of various input information and the drought impacts during the growing season, revealing some limitations for effective agricultural drought monitoring and impact analysis. Therefore, the goal of this research is to build a framework for the development of an impact-oriented and remote sensing based agricultural drought indicator. Firstly, the global agricultural drought risk was characterized to provide an overview of the agricultural drought prone areas in the world. Then, the responses of different remotely sensed indicators to drought and the impacts of drought on crop yield from the remote sensing perspective during the growing season were explored. Based on previous works on drought risk, drought indicator response and drought impact analysis, an impact-oriented drought indicator will be prototyped from the integration of the drought responses of different indicators and the drought impacts during the growing season. This research can inform an impact-oriented agricultural drought indicator, help prototype an impact-oriented agricultural drought monitoring system, and thus provide valuable inputs for effective agricultural management.
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.
Sarna, K.; Russchenberg, H.W.J.
A method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of cloud microphysical changes due to the changing aerosol concentration. We use high resolution measurements from lid
Sarna, K.; Russchenberg, H.W.J.
A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution mea
Robert E. Kennedy; Philip A. Townsend; John E. Gross; Warren B. Cohen; Paul Bolstad; Wang Y. Q.; Phyllis Adams
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...
Belinda Arunarwati Margono
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...
Stumpf, Richard P.; Tomlinson, Michelle C.
Harmful algal blooms (HABs) have impacts on coastal economies, public health, and various endangered species. HABs are caused by a variety of organisms, most commonly dinoflagellates, diatoms, and cyanobacteria. In the late 1970's, optical remote sensing was found to have a potential for detecting the presence of blooms of Karenia brevis on the US Florida coast. Due to the nearly annual frequency of these blooms and the ability to note them with ocean color imagery, K. brevis blooms have strongly influenced the field of HAB remote sensing. However, with the variability between phytoplankton blooms, heir environment and their relatively narrow range of pigment types, particularly between toxic and non-toxic dinoflagellates and diatoms, techniques beyond optical detection are required for detecting and monitoring HABs. While satellite chlorophyll has some value, ecological or environmental characteristics are required to use chlorophyll. For example, identification of new blooms can be an effective means of identifying HABs that are quie intense, also blooms occurring after specific rainfall or wind events can be indicated as HABs. Several HAB species do not bloom in the traditional sense, in that they do not dominate the biomass. In these cases, remote sensing of SST or chlorophyll can be coupled with linkages to seasonal succession, changes in circulation or currents, and wind-induced transport--including upwelling and downwelling, to indicate the potential for a HAB to occur. An effective monitoring and forecasting system for HABs will require the coupling of remote sensing with an environmental and ecological understanding of the organism.
John D. Hedley
Full Text Available Coral reefs are in decline worldwide and monitoring activities are important for assessing the impact of disturbance on reefs and tracking subsequent recovery or decline. Monitoring by field surveys provides accurate data but at highly localised scales and so is not cost-effective for reef scale monitoring at frequent time points. Remote sensing from satellites is an alternative and complementary approach. While remote sensing cannot provide the level of detail and accuracy at a single point than a field survey, the statistical power for inferring large scale patterns benefits in having complete areal coverage. This review considers the state of the art of coral reef remote sensing for the diverse range of objectives relevant for management, ranging from the composition of the reef: physical extent, benthic cover, bathymetry, rugosity; to environmental parameters: sea surface temperature, exposure, light, carbonate chemistry. In addition to updating previous reviews, here we also consider the capability to go beyond basic maps of habitats or environmental variables, to discuss concepts highly relevant to stakeholders, policy makers and public communication: such as biodiversity, environmental threat and ecosystem services. A clear conclusion of the review is that advances in both sensor technology and processing algorithms continue to drive forward remote sensing capability for coral reef mapping, particularly with respect to spatial resolution of maps, and synthesis across multiple data products. Both trends can be expected to continue.
Liu, Qian; Zhao, Yingshi
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.
Full Text Available Mangrove forests, distributed in the tropical and subtropical regions of the world, are in a constant flux. They provide important ecosystem goods and services to nature and society. In recent years, the carbon sequestration potential and protective role of mangrove forests from natural disasters is being highlighted as an effective option for climate change adaptation and mitigation. The forests are under threat from both natural and anthropogenic forces. However, accurate, reliable, and timely information of the distribution and dynamics of mangrove forests of the world is not readily available. Recent developments in the availability and accessibility of remotely sensed data, advancement in image pre-processing and classification algorithms, significant improvement in computing, availability of expertise in handling remotely sensed data, and an increasing awareness of the applicability of remote sensing products has greatly improved our scientific understanding of changing mangrove forest cover attributes. As reported in this special issue, the use of both optical and radar satellite data at various spatial resolutions (i.e., 1 m to 30 m to derive meaningful forest cover attributes (e.g., species discrimination, above ground biomass is on the rise. This multi-sensor trend is likely to continue into the future providing a more complete inventory of global mangrove forest distributions and attribute inventories at enhanced temporal frequency. The papers presented in this “Special Issue” provide important remote sensing monitoring advancements needed to meet future scientific objectives for global mangrove forest monitoring from local to global scales.
Eilander, D.M.; Annor, F.O.; Iannini, L.; Van de Giesen, N.C.
Multipurpose small reservoirs are important for livelihoods in rural semi-arid regions. To manage and plan these reservoirs and to assess their hydrological impact at a river basin scale, it is important to monitor their water storage dynamics. This paper introduces a Bayesian approach for monitorin
elmi, omid; javad tourian, mohammad; sneeuw, nico
Monitoring the variation of water storage in a long period is a primary issue for understanding the impact of climate change and human activities on earth water resources. In order to obtain the change in water volume in a lake and reservoir, in addition to water level, water extent must be repeatedly determined in an appropriate time interval. Optical satellite imagery as a passive system is the main source of determination of coast line change as it is easy to interpret. Optical sensors acquire the reflected energy from the sunlight in various bands from visible to near infrared. Also, panchromatic mode provides more geometric details. Establishing a ratio between visible bands is the most common way of extract coastlines because with this ratio, water and land can be separated directly. Also, since the reflectance value of water is distinctly less than soil in infrared bands, applying a histogram threshold on this band is a effective way of coastline extraction. However, optical imagery is highly vulnerable to occurrence of dense clouds and fog. Moreover, the coastline is hard to detect where it is covered by dense vegetation. Synthetic aperture radar (SAR) as an active system provides an alternative source for monitoring the spatial change in coastlines. Two methods for monitoring the shoreline with SAR data have been published. First, the backscatter difference is calculated between two images acquired at different times. Second, the change in coastline is detected by computing the coherence of two SAR images acquired at different times. A SAR system can operate in all weather, so clouds and fog don't impact its efficiency. Also, it can penetrate into the plant canopy. However, in comparison with optical imagery, interpretation of SAR image in this case is relatively hard because of limitation in the number of band and polarization modes, also due to effects caused by speckle noises, slant-range imaging and shadows. The primary aim of this study is a
Full Text Available This study monitors the great Himalayas between the year 1998–2008 using satellite data. The Landsat satellite data was used to monitor variations in the area of glacier. Further the snow-covered area (SCA of the part of Alaknanda basin was computed both for the winter and the summer season. The analysis for the same was done between 1998 and 2008. It was observed that the amount of decrease in the SCA was more in winter season compared to summer season, which also shows the rate of retreat of glacier. This study also classifies the snow into two categories (1 dry snow and (2 wet snow. The pattern in the change in area of these two categories was analysed both for the winter and summer season.
Canty, Morton J.; Nielsen, Allan Aasbjerg; Schlittenhardt, Jörg
or uninteresting changes, see e.g. (Canty and Schlittenhardt 2001). In our contribution we focus attention on the use of conventional multispectral earth observation satellite platforms with moderate ground resolution (Landsat TM, ASTER, SPOT) to detect changes over wide areas which are relevant to nuclear non......Triggered in part by the advent of high resolution commercial optical satellites, the analysis of open-source satellite imagery has now established itself as an important tool for monitoring nuclear activities throughout the world (Chitumbo et al 2001). Whereas detection of land cover and land use...... the framework of the Global Monitoring for Security and Stability Network of Excellence (GMOSS) initiated by the European Commission. Chitumbo, K., Robb, S., Bunney, J. and Lev\\$\\backslash\\$'e, G., IAEA Satellite imagery and the Department of Safeguards, Proceedings of the Symposium on International Safeguards...
Furtney, M.; Pritchard, M. E.; Carn, S. A.; McCormick, B.; Ebmeier, S. K.; Jay, J.
Volcanoes exhibit variable eruption frequencies and styles, from near-continuous eruptions of effusive lavas to more intermittent, explosive eruptions. The monitoring frequency necessary to capture precursory signals at any volcano remains uncertain, as some warnings allot hours for evacuation. Likewise, no precursory signal appears deterministic for each volcano. Volcanic activity manifests in a variety of ways (i.e. tremor, deformation), thus requiring multiple monitoring mechanisms (i.e. geodetic, geochemical, geothermal). We are developing databases to compare relationships among remotely sensed volcanic unrest signals and eruptions. Satellite remote sensing utilizes frequent temporal measurements (daily to bi-weekly), an essential component of worldwide volcano monitoring. Remote sensing methods are also capable of detecting diverse precursory signals such as ground deformation from satellite interferometric synthetic aperture radar—InSAR— (multiple space agencies), degassing from satellite spectroscopy (i.e. OMI SO2 from NASA), and hot spots from thermal infrared (i.e. MODIS from NASA). We present preliminary results from seven SAR satellites and two thermal infrared satellites for 24 volcanoes with prominent SO2 emissions. We find near-continuous emissions at Ibu (Indonesia) since 2008 corresponded with hotspots and 10 cm of subsidence, with degassing and comparable subsidence observed at Pagan (Marianas). A newcomer to volcano monitoring, remote sensing data are only beginning to be utilized on a global scale, let alone as a synthesized dataset for monitoring developing eruptions. We foresee a searchable tool for rapidly accessing basic volcanic unrest characteristics for different types of volcanoes and whether or not they resulted in eruption. By including data from multiple satellite sensors in our database we hope to develop quantitative assessments for calculating the likelihood of eruption from individual events.
Fan, Jinlong; Defourny, Pierre
The European medium resolution satellite data ENVISAT/MERIS were available in 2002 while the Chinese medium resolution spectrometer data with 5 bands in 250m spatial resolution and 15 bands in 1000m onboard Fengyun 3 series satellites became a new data source at the end of the year 2008. Under the framework of Dragon program 3, both teams demonstrated the utilization of medium resolution satellite data in crop monitoring. The Chinese team has made efforts to improve the processing of the Chinese Medium resolution satellite data (MERSI) in order to promote its applications in crop monitoring. The European team has checked and evaluated the processed FY3A/3B MERSI data and inspiring findings have found in terms of the imaging quality and the performance of retrieving LAI and GAI etc. The Chinese team has mapped the winter wheat area in North China Plain in the growing season from 2009 to 2014 with the finely processed FY3A MERSI 250m data. The LAI retrieval algorithm with the FY3 MERSI data was developed based on the in-situ data and other satellite products. The participation of young scientists is critical for the implementation of the project. 4 Chinese master students were involving in this project and the Chinese team hosted a European young master student to carry out research in China in the spring of 2014. Both research teams are looking forward to successful and productive achievements for this Dragon project and new deep cooperation in Dragon 4.
Full Text Available Multipurpose small reservoirs are important for livelihoods in rural semi-arid regions. To manage and plan these reservoirs and to assess their hydrological impact at a river basin scale, it is important to monitor their water storage dynamics. This paper introduces a Bayesian approach for monitoring small reservoirs with radar satellite images. The newly developed growing Bayesian classifier has a high degree of automation, can readily be extended with auxiliary information and reduces the confusion error to the land-water boundary pixels. A case study has been performed in the Upper East Region of Ghana, based on Radarsat-2 data from November 2012 until April 2013. Results show that the growing Bayesian classifier can deal with the spatial and temporal variability in synthetic aperture radar (SAR backscatter intensities from small reservoirs. Due to its ability to incorporate auxiliary information, the algorithm is able to delineate open water from SAR imagery with a low land-water contrast in the case of wind-induced Bragg scattering or limited vegetation on the land surrounding a small reservoir.
JI Guangrong; SUN Jie; ZHAO Wencang; ZHANG Hande
This paper proposes a red tide monitoring method based on clustering and modular neural networks. To obtain the features of red tide from a mass of aerial remote sensing hyperspectral data, first the Log Residual Correction (LRC) is used to normalize the data, and then clustering analysis is adopted to select and form the training samples for the neural networks. For rapid monitoring, the discriminator is composed of modular neural networks, whose structure and learning parameters are determined by an Adaptive Genetic Algorithm (AGA). The experiments showed that this method can monitor red tide rapidly and effectively.
A. S. Arya
Full Text Available Desert ecosystems are unique but fragile ecosystems , mostly vulnerable to a variety of degradational processes like water erosion, vegetal degradation, salinity, wind erosion , water logging etc. Some researchers consider desertification to be a process of change, while others view it as the end result of a process of change. There is an urgent need to arrest the process of desertification and combat land degradation. Under the auspices of the United Nations Convention to Combat Desertification (UNCCD, Space Applications Centre, Ahmedabad has undertaken the task of mapping, monitoring and assessment of desertification carrying out pilot project in hot and cold desert regions in drylands on 1:50,000 scale followed by systematic Desertification Status Mappaing (DSM of India on 1:500,000 scale.
张仁华; 孙晓敏; 朱治林; 苏红波; 唐新斋
The presently applied remote sensing algorithms and approaches to monitor soil surface fluxes are reviewed at the beginning of this paper, and the bottleneck of the estimation of soil surface fluxes lies in the dependence on non remotely sensed parameters (NRSP). A soil surface evaporation model based on differential thermal inertia, only using remotely sensed information, has thus been proposed after many experiments. The key of the model is to derive soil moisture availability by differential thermal inertia rather than local soil parameters such as soil properties and type. Bowen ratio is estimated by means of soil moisture availability instead of NRSP, such as temperature and wind velocity. Net radiation flux and apparent thermal inertia have been used for soil heat flux parameterization, therefore, the objective of evaporation (latent heat flux) inversion for bare soil only by remotely sensed information can be realized. Two NOAA-AVHRR five-band images, taken at Shapotou northwest of China when soil surface temperature approximated to the highest and lowest of the region, were applied in combination with the ground surface information measured synchronously. The distribution of soil evaporation in Shapotou could be determined. Model verification has been performed between the measured soil surface evaporation and the corresponding calculated value of the images, and the result has proved model to be feasible. Finally, the possible errors and further modifications when applying model to fulling vegetation canopy have been discussed.
Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.
Climate change is expected to have the greatest impact on the world's 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 actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.
Horqin Sand Land is regarded as the typical region for studying the problem of desertification. The integration of 3S(GIS, GPS and RS) techniques offer a most helpful method to study and monitor the dynamics of desertification.Based on the data derived from 3 periods' mulfitemporal Landsat TM imagery of the 1990s, the regional land use and dynamics of desertification in Horqin Sand L and were studied. The main results revealed that: 1 ) as long as the general changetendency was concerned, the desertification of Horqin Sand Land would continue to spread; 2) there was a gradual decrease in the area of both moving sand dunes and semi-stabilized ones, which meant that fruitful progress had been madeto control the desertification during the 1990s; 3) as a result of unreasonable cultivation, the total area of stabilized sanddunes and grassland in the middle and western region decreased obviously. It suggested that the increasing damagecaused by human was leading to the hazard of further desertitication. So in the future, it is necessary to take more effective measures to control the spread of desertification and restore the degraded ecosystems for the purpose of optimizing theglobal eco-environment in Horqin Sand Land.
Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, P.; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Nouvellon, Y.; Scholes, R.; Kutsch, W.
Climate change is expected to have the greatest impact on the world's 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 actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.
Full Text Available Climate change is expected to have the greatest impact on the world's 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 actual evapotranspiration (AET, a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.
Noomen, Marleen; Hakkarainen, Annika; van der Meijde, Mark; van der Werff, Harald
In recent years, several studies focused on the detection of hydrocarbon pollution in the environment using hyperspectral remote sensing. Particularly the indirect detection of hydrocarbon pollution, using vegetation reflectance in the red edge region, has been studied extensively. Bioremediation is one of the methods that can be applied to clean up polluted sites. So far, there have been no studies on monitoring of bioremediation using (hyperspectral) remote sensing. This study evaluates the feasibility of hyperspectral remote sensing for monitoring the effect of bioremediation over time. Benzene leakage at connection points along a pipeline was monitored by comparing the red edge position (REP) in 2005 and 2008 using HyMap airborne hyperspectral images. REP values were normalized in order to enhance local variations caused by a change in benzene concentrations. 11 out of 17 locations were classified correctly as remediated, still polluted, or still clean, with a total accuracy of 65%. When only polluted locations that were remediated were taken into account, the (user's) accuracy was 71%.
Yuliang Qiao, Pro.
As an important city in the southern part of Chu Chiang Delta, Zhuhai is one of the four special economic zones which are opening up to the outside at the earliest in China. With pure and fresh air and trees shading the street, Zhuhai is a famous beach port city which is near the mountain and by the sea. On the basis of Garden City, the government of Zhuhai decides to build National Forest City in 2011, which firstly should understand the situation of greenbelt in Zhuhai in short term. Traditional methods of greenbelt investigation adopt the combination of field surveying and statistics, whose efficiency is low and results are not much objective because of artificial influence. With the adventure of the information technology such as remote sensing to earth observation, especially the launch of many remote sensing satellites with high resolution for the past few years, kinds of urban greenbelt information extraction can be carried out by using remote sensing technology; and dynamic monitoring to spatial pattern evolvement of forest and greenbelt in Zhuhai can be achieved by the combination of remote sensing and GIS technology. Taking Landsat5 TM data in 1995, Landsat7 ETM+ data in 2002, CCD and HR data of CBERS-02B in 2009 as main information source, this research firstly makes remote sensing monitoring to dynamic change of forest and greenbelt in Zhuhai by using the combination of vegetation coverage index and three different information extraction methods, then does a driving force analysis to the dynamic change results in 3 months. The results show: the forest area in Zhuhai shows decreasing tendency from 1995 to 2002, increasing tendency from 2002 to 2009; overall, the forest area show a small diminution tendency from 1995 to 2009. Through the comparison to natural and artificial driving force, the artificial driving force is the leading factor to the change of forest and greenbelt in Zhuhai. The research results provide a timely and reliable scientific basis
Full Text Available Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs. We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.
Imhoff, Marc L.; Rosenquist, A.; Milne, A. K.; Dobson, M. C.; Qi, J.
An International workshop was held to address how remote sensing technology could be used to support the environmental monitoring requirements of the Kyoto Protocol. An overview of the issues addressed and the findings of the workshop are discussed.
The application of remote sensing techniques to land management, urban planning, agriculture, oceanography, and environmental monitoring is discussed. The results of various projects are presented along with cost effective considerations.
Full Text Available Many remote sensing applications are devoted to the agricultural sector. Representative case studies are presented in the special issue “Advances in Remote Sensing of Agriculture”. To complement the examples published within the special issue, a few main applications with regional to global focus were selected for this review, where remote sensing contributions are traditionally strong. The selected applications are put in the context of the global challenges the agricultural sector is facing: minimizing the environmental impact, while increasing production and productivity. Five different applications have been selected, which are illustrated and described: (1 biomass and yield estimation, (2 vegetation vigor and drought stress monitoring, (3 assessment of crop phenological development, (4 crop acreage estimation and cropland mapping and (5 mapping of disturbances and land use/land cover (LULC changes. Many other applications exist, such as precision agriculture and irrigation management (see other special issues of this journal, but were not included to keep the paper concise. The paper starts with an overview of the main agricultural challenges. This section is followed by a brief overview of existing operational monitoring systems. Finally, in the main part of the paper, the mentioned applications are described and illustrated. The review concludes with some key recommendations.
CHE Tao; LI Xin; JIN Rui
The Qinghai Lake is the largest inland lake in China.The significant difference of dielectric properties between water and ice suggests that a simple method of monitoring the Qinghai lake freeze-up and break-up dates using satellite passive microwave remote sensing data could be used.The freeze-up and break-up dates from the Qinghai Lake hydrological station and the MODIS L1B reflectance data were used to validate the passive microwave remote sensing results.The validation shows that passive microwave remote sensing data can accurately monitor the lake ice.Some uncertainty comes mainly from the revisit frequency of satellite overpass.The data from 1978 to 2006 show that lake ice duration is reduced by about 14-15 days.The freeze-up dates are about 4 days later and break-up dates about 10 days earlier.The regression analyses show that,at the 0.05 significance level,the correlations are 0.83,0.66 and 0.89 between monthly mean air temperature (MMAT) and lake ice duration days,freeze-up dates,break-up dates,respectively.Therefore,inter-annual variations of the Qinghai Lake ice duration days can significantly reflect the regional climate variation.
Qin, Lin; Wang, Xianghong; Jiang, Jing; Yang, Xianchang; Ke, Daiyan; Li, Hongqun; Wang, Dingyi
The pine wilt disease is a devastating disease of pine trees. In China, the first discoveries of the pine wilt disease on 1982 at Dr. Sun Yat-sen's Mausoleum in Nanjing. It occurred an area of 77000 hm2 in 2005, More than 1540000 pine trees deaths in the year. Many districts of Chongqing in Three Gorges Reservoir have different degrees of pine wilt disease occurrence. It is a serious threat to the ecological environment of the reservoir area. Use unmanned airship to carry high spectrum remote sensing monitoring technology to develop the study on pine wood nematode disease early diagnosis and early warning and forecasting in this study. The hyper spectral data and the digital orthophoto map data of Fuling District Yongsheng Forestry had been achieved In September 2015. Using digital image processing technology to deal with the digital orthophoto map, the number of disease tree and its distribution is automatic identified. Hyper spectral remote sensing data is processed by the spectrum comparison algorithm, and the number and distribution of disease pine trees are also obtained. Two results are compared, the distribution area of disease pine trees are basically the same, indicating that using low air remote sensing technology to monitor the pine wood nematode distribution is successful. From the results we can see that the hyper spectral data analysis results more accurate and less affected by environmental factors than digital orthophoto map analysis results, and more environment variable can be extracted, so the hyper spectral data study is future development direction.
Zhou, M.; Yuan, X.; Sun, L.
Wetland is important natural resource. The main method to monitor the landcover change in wetland natural reserve is to extract and analyze information from remote sensing image. In this paper, the landcover information is extracted, summarized and analyzed by using multi-temporal HJ and Landsat satellite image in Zhalong natural reserve, Heilongjiang, China. The method can monitor the wetland landcover change accurately in real time and long term. This paper expounds the natural factors and human factors influence on wetland land use type, for scientific and effective support for the development of the rational use of wetlands in Zhalong natural wetland reserve.
Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas; Petrov, Nikolay; Stoev, Antoniy
Remote sensing technologies have advanced significantly at last decade and have improved the capability to gather information about Earth’s resources and environment. They have many applications in Earth observation, such as mapping and updating land-use and cover, weather forecasting, biodiversity determination, etc. Hyperspectral remote sensing offers unique opportunities in the environmental monitoring and sustainable use of natural resources. Remote sensing sensors on space-based platforms, aircrafts, or on ground, are capable of providing detailed spectral, spatial and temporal information on terrestrial ecosystems. Ground-based sensors are used to record detailed information about the land surface and to create a data base for better characterizing the objects which are being imaged by the other sensors. In this paper some applications of two hyperspectral remote sensing techniques, leaf reflectance and chlorophyll fluorescence, for monitoring and assessment of the effects of adverse environmental conditions on plant ecosystems are presented. The effect of stress factors such as enhanced UV-radiation, acid rain, salinity, viral infections applied to some young plants (potato, pea, tobacco) and trees (plums, apples, paulownia) as well as of some growth regulators were investigated. Hyperspectral reflectance and fluorescence data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (450-850 nm and 600-900 nm), respectively. The differences between the reflectance data of healthy (control) and injured (stressed) plants were assessed by means of statistical (Student’s t-criterion), first derivative, and cluster analysis and calculation of some vegetation indices in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm). Fluorescence spectra were analyzed at five characteristic wavelengths located at the
Benali, A. A.
At the present there is a major challenge to monitor coastaltransitional systems in a robust, frequent, systematic and accurate fashion. With the implementation of the Water Framework Directive (WFD), the EU Member States must monitor regularly the most relevant physical and biological parameters. The work assessed the applicability and accuracy of chl-a products from the MODIS Terra sensor in the Tagus estuary, comparing them with simulations of an ecological model (EcoWin2000), at a box scale, which was previously calibrated and validated. It is proposed a conceptual and methodological framework for future monitoring of the estuary using remote sensing data, concerning data processing, handling and integration. Typical Case 1 algorithms were pre-assessed and Case 2 empirical algorithms were regionally calibrated. The GSM and Clark algorithms had the best performances, with errors of approximately of 1.1 μg chl-a l-1 (or 20%) and correlations ranging 0.4-0.5. During calibration, the ratio R678/R551 had good correlation (r = 0.83) and low errors ( 1μg chl-a l-1), however, its evaluation showed low performances. In agreement with the pre-assessment, the GSM algorithm had the best correlation (r 0.50) and errors of approximately 0.8μg chl-a l-1. Remote sensing is a tool with high potential to assist the EU Member States to accomplish the WFD objectives, however, extensive future work is still needed. Systematic chl-a monitoring in the Tagus estuary is feasible and future work should also be aimed at developing multisource monitoring procedures integrating model, in-situ and remote sensing data thus, minimizing their individual limitations and flaws.
Jucker, Tommaso; Caspersen, John; Chave, Jérôme; Antin, Cécile; Barbier, Nicolas; Bongers, Frans; Dalponte, Michele; van Ewijk, Karin Y; Forrester, David I; Haeni, Matthias; Higgins, Steven I; Holdaway, Robert J; Iida, Yoshiko; Lorimer, Craig; Marshall, Peter L; Momo, Stéphane; Moncrieff, Glenn R; Ploton, Pierre; Poorter, Lourens; Rahman, Kassim Abd; Schlund, Michael; Sonké, Bonaventure; Sterck, Frank J; Trugman, Anna T; Usoltsev, Vladimir A; Vanderwel, Mark C; Waldner, Peter; Wedeux, Beatrice M M; Wirth, Christian; Wöll, Hannsjörg; Woods, Murray; Xiang, Wenhua; Zimmermann, Niklaus E; Coomes, David A
Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.
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
Cracknell, Arthur P
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
Pettersson, L.H.; Johannessen, O.M.; Frette, O. (Nansen Remote Sensing Center, Bergen (Norway))
During the late spring of 1988 an extensive bloom of the toxic algae Chrysocromulina polylepis occurred in the Skagerrak region influencing most life in the upper 30 meter of the ocean. The algal front was advected northward with the Norwegian Coastal Current along the coast of southern Norway, where it became a severe threat to the Norwegian seafarming industry. An ad-hoc expert team was established to monitor and forecast the movement of the algae front. Remote sensing of sea surface temperature from the operational US NOAA satellites monitored the movement of the algal front, consistent with a warm ocean front. The lack of any optical remote sensing instrumentation was recognized as a major de-efficiency during this algal bloom. To prepare for similar events in the future Nansen Remote Sensing Center initiated a three week pilot study in the Oslofjord and Skagerrak region, during May 1989. The Canadian Compact Airborne Spectrographic Imager (CASI) was installed in the surveillance aircraft. Extensive in situ campaigns was also carried out by the Norwegian Institute for Water Research and Institute of Marine Research. A ship-borne non-imaging spectrometer was operated from the vessels participating in the field campaign. As a contribution from a joint campaign (EISAC '89) between the Joint Research Centre (JRC) of the European Community and the European Space Agency (ESA) both the Canadian Fluorescence Line Imager (FLI) and the US 64-channel GER scanner was operated simultaneously at the NORSMAP 89 test site. Regions of different biological and physical conditions were covered during the pilot study and preliminary analysis are obtained from oil slicks, suspended matter from river, as well as minor algal bloom. The joint analysis of the data collected during the NORSMAP 89 campaign and conclussions will be presented, as well as suggestions for future utilization of airborne spectroscopy systems for operational monitoring of algal bloom and water pollution.
Washington-Allen, R. A.
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.
Hamandawana, Hamisai; Eckardt, Frank; Chanda, Raban
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
Nikolakopoulos, Konstantinos G.; Kavoura, Katerina; Depountis, Nikolaos; Argyropoulos, Nikolaos; Koukouvelas, Ioannis; Sabatakakis, Nikolaos
An active landslide can be monitored using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GPS and photogrammetric techniques using airphotos or high resolution satellite images. As the cost of the aerial photo campaign and the acquisition of very high resolution satellite data is quite expensive the use of cameras on board UAV could be an identical solution. Small UAVs (Unmanned Aerial Vehicles) have started their development as expensive toys but they currently became a very valuable tool in remote sensing monitoring of small areas. The purpose of this work is to demonstrate a cheap but effective solution for an active landslide monitoring. We present the first experimental results of the synergistic use of UAV, GPS measurements and remote sensing data. A six-rotor aircraft with a total weight of 6 kg carrying two small cameras has been used. Very accurate digital airphotos, high accuracy DSM, DGPS measurements and the data captured from the UAV are combined and the results are presented in the current study.
Wang, Li-Tao; Wang, Shi-Xin; Zhou, Yi; Liu, Wen-Liang; Wang, Fu-Tao
The vegetation is one of main drying carriers. The change of Vegetation Water Content (VWC) reflects the spatial-temporal distribution of drought situation and the degree of drought. In the present paper, a method of retrieving the VWC based on remote sensing data is introduced and analyzed, including the monitoring theory, vegetation water content indicator and retrieving model. The application was carried out in the region of Southwest China in the spring, 2010. The VWC data was calculated from MODIS data and spatially-temporally analyzed. Combined with the meteorological data from weather stations, the relationship between the EWT and weather data shows that precipitation has impact on the change in vegetation moisture to a certain extent. However, there is a process of delay during the course of vegetation absorbing water. So precipitation has a delaying impact on VWC. Based on the above analysis, the probability of drought monitoring and evaluation based on multi-spectral VWC data was discussed. Through temporal synthesis and combined with auxiliary data (i. e. historical data), it will help overcome the limitation of data itself and enhance the application of drought monitoring and evaluation based on the multi-spectral remote sensing.
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...
Full Text Available Essential Biodiversity Variables (EBVs have been suggested to harmonize biodiversity monitoring worldwide. Their aim is to provide a small but comprehensive set of monitoring variables that would give a balanced picture of the development of biodiversity and the reaching of international and national biodiversity targets. Globally, GEO BON (Group on Earth Observations Biodiversity Observation Network has suggested 22 candidate EBVs to be monitored. In this article we regard EBVs as a conceptual tool that may help in making national scale biodiversity monitoring more robust by pointing out where to focus further development resources. We look at one country –Finland –with a relatively advanced biodiversity monitoring scheme and study how well Finland’s current biodiversity state indicators correspond with EBVs. In particular, we look at how national biodiversity monitoring could be improved by using available remote sensing (RS applications. Rapidly emerging new technologies from drones to airborne laser scanning and new satellite sensors providing imagery with very high resolution (VHR open a whole new world of opportunities for monitoring the state of biodiversity and ecosystems at low cost. In Finland, several RS applications already exist that could be expanded into national indicators. These include the monitoring of shore habitats and water quality parameters, among others. We hope that our analysis and examples help other countries with similar challenges. Along with RS opportunities, our analysis revealed also some needs to develop the EBV framework itself.
Hong, Yang; Adler, Robert F.; Huffman, George J.
Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.
The world is experiencing a rapid rate of urban expansion, largely contributed by the population growth. Other factors supporting urban growth include the improved efficiency in the transportation sector and increasing dependence on cars as a means of transport. The problems attributed to the urban growth include: depletion of energy resources, water and air pollution; loss of landscapes and wildlife, loss of agricultural land, inadequate social security and lack of employment or underemployment. Aerial photography is one of the popular techniques for analyzing, planning and minimizing urbanization related problems. However, with the advances in space technology, satellite remote sensing is increasingly being utilized in the analysis and planning of the urban environment. This article outlines the strengths and limitations of potential remote sensing techniques for monitoring urban growth. The selected methods include: Principal component analysis, Maximum likelihood classification and "decision tree". The results indicate that the "classification tree" approach is the most promising for monitoring urban change, given the improved accuracy and smooth transition between the various land cover classes
Albright, T.P.; Ode, D.J.
Potamogeton crispus L. (curly pondweed) is a cosmopolitan aquatic macrophyte considered invasive in North America and elsewhere. Its range is expanding and, on individual water bodies, its coverage can be dynamic both within and among years. In this study, we evaluate the use of free and low-cost satellite remote sensing data to monitor a problematic emergent macrophyte community dominated by P. crispus. Between 2000 and 2006, we acquired eight satellite images of 24,000-ha Lake Sharpe, South Dakota (USA). During one of the dates for which satellite imagery was acquired, we sampled the lake for P. crispus and other emergent macrophytes using GPS and photography for documentation. We used cluster analysis to assist in classification of the satellite imagery and independently validated results using the field data. Resulting estimates of emergent macrophyte coverage ranged from less than 20 ha in 2002 to 245 ha in 2004. Accuracy assessment indicated 82% of image pixels were correctly classified, with errors being primarily due to failure to identify emergent macrophytes. These results emphasize the dynamic nature of P. crispus-dominated macrophyte communities and show how they can be effectively monitored over large areas using low-cost remote sensing imagery. While results may vary in other systems depending on water quality and local flora, such an approach could be applied elsewhere and for a variety of macrophyte communities. ?? Springer Science+Business Media B.V. 2010.
Subhash Palmate, Santosh; Pandey, Ashish
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.
Hestir, E. L.; Schoellhamer, D. H.; Santos, M. J.; Greenberg, J. A.; Morgan-King, T.; Khanna, S.; Ustin, S.
Estuarine ecosystems and their biogeochemical processes are extremely vulnerable to climate and environmental changes, and are threatened by sea level rise and upstream activities such as land use/land cover and hydrological changes. Despite the recognized threat to estuaries, most aspects of how change will affect estuaries are not well understood due to the poorly resolved understanding of the complex physical, chemical and biological processes and their interactions in estuarine systems. Remote sensing technologies such as high spectral resolution optical systems enable measurements of key environmental parameters needed to establish baseline conditions and improve modeling efforts. The San Francisco Bay-Delta is a highly modified estuary system in a state of ecological crisis due to the numerous threats to its sustainability. In this study, we used a combination of hyperspectral remote sensing and long-term in situ monitoring records to investigate how water clarity has been responding to extreme climatic events, anthropogenic watershed disturbances, and submerged aquatic vegetation (SAV) invasions. From the long-term turbidity monitoring record, we found that water clarity underwent significant increasing step changes associated with sediment depletion and El Nino-extreme run-off events. Hyperspectral remote sensing data revealed that invasive submerged aquatic pant species have facultative C3 and C4-like photosynthetic pathways that give them a competitive advantage under the changing water clarity conditions of the Bay-Delta system. We postulate that this adaptation facilitated the rapid expansion of SAV following the significant step changes in increasing water clarity caused by watershed disturbances and the 1982-1983 El Nino events. Using SAV maps from hyperspectral remote sensing, we estimate that SAV-water clarity feedbacks were responsible for 20-70% of the increasing water clarity trend in the Bay-Delta. Ongoing and future developments in airborne and
Zhang, P.; Zhang, X. Y.; Bai, W. G.; Wang, W. H.; Huang, F. X.; Li, X. J.; Sun, L.; Wang, G.; Qi, J.; Qiu, H.; Zhang, Y.; van der A, R. J.; Mijling, B.
This paper summarizes the achievements related to atmospheric compositions remote sensing from the bilateral cooperation under the framework of MOST-ESA Dragon Programme. The algorithms to retrieve Aerosol, ozone amount and profile, NO2, SO2, CH4, CO2, etc. have been developed since 2004. Such algorithms are used to process FY-3 series (Chinese second generation polar orbit satellites) observation and ground based FTIR observation. The results are validated with in-situ measurements. Aerosol, total ozone amount shows the very good consistent with the ground measurements. The temporal and spatial characteristics of the important atmospheric compositions, such as aerosol, O3, NO2, SO2, CH4, CO etc., have been analysed from satellite derived products. These works demonstrate the satellite’s capacity on atmospheric composition monitoring, as well as the possible application in the air quality monitoring and climate change research.
Jaud, M.; Delacourt, C.; Allemand, P.; Deschamps, A.; Cancouët, R.; Ammann, J.; Grandjean, P.; Suanez, S.; Fichaut, B.; Cuq, V.
Because the anthropogenic pressure on the coastal fringe is continuously increasing, the comprehension of morphological coastal changes is a key problem. An efficient, practical and affordable monitoring strategy is essential to investigate the physical processes that are on the origin of these changes and to model the changes to come. This paper presents an assessment of several very high resolution remote sensing techniques (DGPS, stereo-photogrammetry by drone, Terrestrial Laser Scanning and shallow-water multi-beam echo-sounder) which have been jointly used to survey a beach in French Brittany. These techniques allow an integrated approach for Digital Elevation Model (DEM) differencing in order to quantify morphological changes and to monitor the beach evolution. Gathering topographic and bathymetric data enables to draw up the sediment budget of a complete sediment compartment.
Schmid, Thomas; Rico, Celia; Rodríguez-Rastrero, Manuel; José Sierra, María; Javier Díaz-Puente, Fco; Pelayo, Marta; Millán, Rocio
The Almadén area in Spain has a long history of mercury mining with prolonged human-induced activities that are related to mineral extraction and metallurgical processes before the closure of the mines and a more recent post period dominated by projects that reclaim the mine dumps and tailings and recuperating the entire mining area. Furthermore, socio-economic alternatives such as crop cultivation, livestock breeding and tourism are increasing in the area. Up till now, only scattered information on these activities is available from specific studies. However, improved acquisition systems using satellite borne data in the last decades opens up new possibilities to periodically study an area of interest. Therefore, comparing the influence of these activities on the environment and monitoring their impact on the ecosystem vastly improves decision making for the public policy makers to implement appropriate land management measures and control environmental degradation. The objective of this work is to monitor environmental changes affected by human-induced activities within the Almadén area occurring before, during and after the mine closure over a period of nearly three decades. To achieve this, data from numerous sources at different spatial scales and time periods are implemented into a methodology based on advanced remote sensing techniques. This includes field spectroradiometry measurements, laboratory analyses and satellite borne data of different surface covers to detect land cover and use changes throughout the mining area. Finally, monitoring results show that the distribution of areas affected by mercury mining is rapidly diminishing since activities ceased and that rehabilitated mining areas form a new landscape. This refers to mine tailings that have been sealed and revegetated as well as an open pit mine that has been converted to an "artificial" lake surface. Implementing a methodology based on remote sensing techniques that integrate data from
Wang, H. B.; Wang, G. H.; Tang, X. M.; Li, C. H.
Monitoring the response of Yellow River icicle hazard change requires accurate and repeatable topographic surveys. A new method based on unmanned aerial vehicle (UAV) aerial remote sensing technology is proposed for real-time data processing in Yellow River icicle hazard dynamic monitoring. The monitoring area is located in the Yellow River ice intensive care area in southern BaoTou of Inner Mongolia autonomous region. Monitoring time is from the 20th February to 30th March in 2013. Using the proposed video data processing method, automatic extraction covering area of 7.8 km2 of video key frame image 1832 frames took 34.786 seconds. The stitching and correcting time was 122.34 seconds and the accuracy was better than 0.5 m. Through the comparison of precise processing of sequence video stitching image, the method determines the change of the Yellow River ice and locates accurate positioning of ice bar, improving the traditional visual method by more than 100 times. The results provide accurate aid decision information for the Yellow River ice prevention headquarters. Finally, the effect of dam break is repeatedly monitored and ice break five meter accuracy is calculated through accurate monitoring and evaluation analysis.
Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.
Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for
LeMarie, Margarita; van der Zaag, Pieter; Menting, Geert; Baquete, Evaristo; Schotanus, Daniel
The Incomati river basin is a transboundary basin shared by three countries: South Africa, Mozambique and Swaziland. To assess the water requirements of the environment, as stated in the Tripartite Interim Agreement (TIA) signed by the three riparian countries in Johannesburg in 2002, Mozambique needs to monitor the ecological state of the river, including the estuary. A monitoring system has to be established that can evaluate the environmental fresh water requirements based on appropriate indicators that reflect the health of the Incomati estuary. The estuary of the Incomati has important ecological functions but it also is an important socio-economic resource. Local communities depend on the estuary’s natural resources. Modifications of the river flow regime by upstream developments impact on the productivity of the estuary, diminishing fish and shrimp production, reducing biomass of natural vegetation such as grasses, reeds and mangroves and increasing salt intrusion. A decrease in estuary productivity consequently affects the incomes and living conditions of these communities. Based on an understanding of the effects of different pressures on the estuary ecosystem some indicators for monitoring the environmental state of the estuary are suggested, including the extent and vitality of mangrove forests. This latter indicator is further elaborated in the paper. Remote sensing techniques were used to identify and quantify mangrove forests in two selected areas of the estuary (Xefina Pequeña Island and Benguelene Island). Five satellite images covering a period of 20 years (1984-2003) showed that the area covered by non-degraded mangroves significantly decreased on both islands, by 25% in Xefina Pequeña Island and 40% in Benguelene Island. Moreover, the study of biomass reflection using NDVI also showed a significant decline in biomass densities over the last 20 years. Possible causes of these changes are reviewed: natural rainfall trends, modifications of the
Dettmering, Denise; Strehl, Franziska; Schwatke, Christian; Seitz, Florian
Large wetlands are an important component of the global water cycle and the knowledge of water flow and storage dynamics within these regions is valuable for many applications such as flood risk assessment and water availability studies. Most of the inundation areas are remote regions without significant infrastructure, especially without in-situ gauging observations. Remote sensing techniques can help to provide highly valuable information for hydrological questions.Combining water level and water extent from different remote sensing sensors allows for the quantification of water volume changes in remote inundation areas.
Imen, Sanaz; Chang, Ni-Bin; Yang, Y Jeffrey
Adjustment of the water treatment process to changes in water quality is a focus area for engineers and managers of water treatment plants. The desired and preferred capability depends on timely and quantitative knowledge of water quality monitoring in terms of total suspended solids (TSS) concentrations. This paper presents the development of a suite of nowcasting and forecasting methods by using high-resolution remote-sensing-based monitoring techniques on a daily basis. First, the integrated data fusion and mining (IDFM) technique was applied to develop a near real-time monitoring system for daily nowcasting of the TSS concentrations. Then a nonlinear autoregressive neural network with external input (NARXNET) model was selected and applied for forecasting analysis of the changes in TSS concentrations over time on a rolling basis onward using the IDFM technique. The implementation of such an integrated forecasting and nowcasting approach was assessed by a case study at Lake Mead hosting the water intake for Las Vegas, Nevada, in the water-stressed western U.S. Long-term monthly averaged results showed no simultaneous impact from forest fire events on accelerating the rise of TSS concentration. However, the results showed a probable impact of a decade of drought on increasing TSS concentration in the Colorado River Arm and Overton Arm. Results of the forecasting model highlight the reservoir water level as a significant parameter in predicting TSS in Lake Mead. In addition, the R-squared value of 0.98 and the root mean square error of 0.5 between the observed and predicted TSS values demonstrates the reliability and application potential of this remote sensing-based early warning system in terms of TSS projections at a drinking water intake. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available Chlorophyll-a (chl-a levels in lake water could indicate the presence of cyanobacteria, which can be a concern for public health due to their potential to produce toxins. Monitoring of chl-a has been an important practice in aquatic systems, especially in those used for human services, as they imply an increased risk of exposure. Remote sensing technology is being increasingly used to monitor water quality, although its application in cases of small urban lakes is limited by the spatial resolution of the sensors. Lake Thonotosassa, FL, USA, a 3.45-km2 suburban lake with several uses for the local population, is being monitored monthly by traditional methods. We developed an empirical bio-optical algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS daily surface reflectance product to monitor daily chl-a. We applied the same algorithm to four different periods of the year using 11 years of water quality data. Normalized root mean squared errors were lower during the first (0.27 and second (0.34 trimester and increased during the third (0.54 and fourth (1.85 trimesters of the year. Overall results showed that Earth-observing technologies and, particularly, MODIS products can also be applied to improve environmental health management through water quality monitoring of small lakes.
Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.
The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991
Timmermans, J.; Gokmen, M.; Eden, U.; Abou Ali, M.; Vekerdy, Z.; Su, Z.
The need to good drought monitoring and management for the Horn of Africa has never been greater. This ongoing drought is the largest in the past sixty years and is effecting the life of around 10 million people, according to the United Nations. The impact of drought is most apparent in food security and health. In addition secondary problems arise related to the drought such as large migration; more than 15000 Somalia have fled to neighboring countries to escape the problems caused by the drought. These problems will only grow in the future to larger areas due to increase in extreme weather patterns due to global climate change. Monitoring drought impact and managing the drought effects are therefore of critical importance. The impact of a drought is hard to characterize as drought depends on several parameters, like precipitation, land use, irrigation. Consequently the effects of the drought vary spatially and range from short-term to long-term. For this reason a drought event can be characterized into four categories: meteorological, agricultural, hydrological and socio-economical. In terms of food production the agricultural drought, or short term dryness near the surface layer, is most important. This drought is usually characterized by low soil moisture content in the root zone, decreased evapotranspiration, and changes in vegetation vigor. All of these parameters can be detected with good accuracy from space. The advantage of remote sensing in Drought monitoring is evident. Drought monitoring is usually performed using drought indices, like the Palmer Index (PDSI), Crop Moisture Index (CMI), Standard Precipitation Index (SPI). With the introduction of remote sensing several indices of these have shown great potential for large scale application. These indices however all incorporate precipitation as the main surface parameter neglecting the response of the surface to the dryness. More recently two agricultural drought indices, the EvapoTranspiration Deficit
Prasad, Saurabh; Chanussot, Jocelyn
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
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
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...
Zhou, Ji; Chen, Yun H.; Li, Jing; Weng, Qi H.; Tang, Yan
Vegetation is a fundamental component of urban environment and its abundance is determinant of urban climate and urban ground energy fluxes. Based on the radiometric normalization of multitemporal ASTER imageries, the objectives of this study are: firstly, to estimate the vegetation abundance based on linear spectral mixture model (LSMM), and to compare it with NDVI and SDVI; secondly, to analyze the spatial distribution patterns of urban vegetation abundance in different seasons combined with some landscape metrics. The result indicates that both the vegetation abundance estimation based on LSMM and SDVI can reach high accuracy; however, NDVI is not a robust parameter for vegetation abundance estimation because there is significant non-linear effect between NDVI and vegetation abundance. This study reveals that the landscape characteristics of vegetation abundance is most complicated in summer, with spring and autumn less complicated and simplest in winter. This provides valuable information for urban vegetation abundance estimation and its seasonal change monitoring using remote sensing data.
Bernardo Machado Pires
Full Text Available The Soy Moratorium is a pledge agreed to by major soybean companies not to trade soybean produced in deforested areas after 24th July 2006 in the Brazilian Amazon biome. The present study aims to identify soybean planting in these areas using the MOD13Q1 product and TM/Landsat-5 images followed by aerial survey and field inspection. In the 2009/2010 crop year, 6.3 thousand ha of soybean (0.25% of the total deforestation were identified in areas deforested during the moratorium period. The use of remote sensing satellite images reduced by almost 80% the need for aerial survey to identify soybean planting and allowed monitoring of all deforested areas greater than 25 ha. It is still premature to attribute the recent low deforestation rates in the Amazon biome to the Soy Moratorium, but the initiative has certainly exerted an inhibitory effect on the soybean frontier expansion in this biome.
Full Text Available Phenology-driven events, such as spring wildflower displays or fall tree colour, are generally appreciated by tourists for centuries around the world. Monitoring when tourist seasons occur using satellite data has been an area of growing research interest in recent decades. In this paper, a valid methodology for detecting the grassland tourist season using remote sensing data was presented. On average, the beginning, the best, and the end of grassland tourist season of Inner Mongolia, China, occur in late June (±30 days, early July (±30 days, and late July (±50 days, respectively. In south region, the grassland tourist season appeared relatively late. The length of the grassland tourist season is about 90 days with strong spatial trend. South areas exhibit longer tourist season.
Meng, Qing-ye; Dong, Heng; Qin, Qi-ming; Wang, Jin-liang; Zhao, Jiang-hua
The chlorophyll content of plant has relative correlation with photosynthetic capacity and growth levels of plant. It affects the plant canopy spectra, so the authors can use hyperspectral remote sensing to monitor chlorophyll content. By analyzing existing mature vegetation index model, the present research pointed out that the TCARI model has deficiencies, and then tried to improve the model. Then using the PROSPECT+SAIL model to simulate the canopy spectral under different levels of chlorophyll content and leaf area index (LAI), the related constant factor has been calculated. The research finally got modified transformed chlorophyll absorption ratio index (MTCARI). And then this research used optimized soil background adjust index (OSAVI) to improve the model. Using the measured data for test and verification, the model has good reliability.
Becerril, R.; González Sosa, E.; Diaz-Delgado, C.; Mastachi-Loza, C. A.; Hernández-Tellez, M.
Desertification is defined as land degradation in arid, semi-arid and sub-humid areas due to climatic variations and human activities. Therefore there is a need to monitor the desertification process in the spatiotemporal scale in order to develop strategies to fight against desertification (Wu and Ci, 2002). In this sense, data provided by remote sensing is an important source for spatial and temporal information, which allows monitoring changes in the environment at low cost and high effectiveness. In Mexico, drylands hold 65% of the area, with about 1,280,494 km2 (UNESCO, 2010), where is located 46% of the national population (SEMARNAT, 2008). Given these facts, there is interest in monitoring the degradation of these lands, especially in Mexico because no specific studies have identified trends and progress of desertification in the country so far. However, it has been considered land degradation as an indicator of desertification process. Thus, it has been determined that 42% of soils in Mexico present some degradation degree. The aim of this study was to evaluate the spatial and temporal dynamics of desertification for 1993, 2000 and 2011 in the semiarid central plateau in Mexico based on demographic, climatic and satellite data. It took into consideration: 1) the Anthropogenic Impact Index (HII), based on the spatial population distribution and its influence on the use of resources and 2) the Aridity Index (AI), calculated with meteorological station records for annual rainfall and potential evapotranspiration. Mosaics were made with Landsat TM scenes; considering they are a data source that allows evaluate surface processes regionally and with high spectral resolution. With satellite information five indices were estimated to assess the vegetation and soil conditions: Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Weighted Difference Vegetation Index (WDVI), Grain Size Index (GSI) and Bare Soil Index (BSI). The rates
Liu, Anlin; Li, Xingmin; He, Yanbo; Deng, Fengdong
Based on the principle of energy balance, the method for calculating latent evaporation was simplified, and hence, the construction of the drought remote sensing monitoring model of crop water shortage index was also simplified. Since the modified model involved fewer parameters and reduced computing times, it was more suitable for the operation running in the routine services. After collecting the concerned meteorological elements and the NOAA/AVHRR image data, the new model was applied to monitor the spring drought in Guanzhong, Shanxi Province. The results showed that the monitoring results from the new model, which also took more considerations of the effects of the ground coverage conditions and meteorological elements such as wind speed and the water pressure, were much better than the results from the model of vegetation water supply index. From the view of the computing times, service effects and monitoring results, the simplified crop water shortage index model was more suitable for practical use. In addition, the reasons of the abnormal results of CWSI > 1 in some regions in the case studies were also discussed in this paper.
Full Text Available Monitoring of the atmosphere and determination of the types and amounts of pollutants is becoming more important issue in complex and global monitoring of the environment. On the geocomponent and geocomplex level problem of monitoring the environment is attracting the attention of the scientific experts of different profiles (chemists, physicists, geographers, biologists, meteorologists, both in the national and international projects. Because of the general characteristics of the Earth's atmosphere (Dynamically Ballanced Instability DBI and the potential contribution to climate change solutions air-pollution monitoring has become particularly important field of environmental research. Control of aerosol distribution over Europe is enabled by EARLINET systems (European Aerosol Lidar NETwork. Serbia’s inclusion into these European courses needs development of the device, the standardization of methods and direct activity in determining the type, quantity and location of aerosol. This paper is analyzing the first step in the study of air-pollution, which is consisted of the realization of a functional model of LIDAR remote sensing devices for the large particle pollutants.
Under contract to the US Air Force and Navy, Pacific Advanced Technology has developed a very sensitive hyperspectral imaging infrared camera that can perform remote imaging spectro-radiometry. One of the most exciting applications for this technology is in the remote monitoring of gas plume emissions. Pacific Advanced Technology (PAT) currently has the technology available to detect and identify chemical species in gas plumes using a small light weight infrared camera the size of a camcorder. Using this technology as a remote sensor can give advanced warning of hazardous chemical vapors undetectable by the human eye as well as monitor the species concentrations in a gas plume from smoke stack and fugitive leaks. Some of the gas plumes that have been measured and species detected using an IMSS imaging spectrometer are refinery smoke stacks plumes with emission of CO2, CO, SO2, NOx. Low concentration vapor unseen by the human eye that has been imaged and measured is acetone vapor evaporating at room temperature. The PAT hyperspectral imaging sensor is called 'Image Multi-spectral Sensing or IMSS.' The IMSS instrument uses defractive optic technology and exploits the chromatic aberrations of such lenses. Using diffractive optics for both imaging and dispersion allows for a very low cost light weight robust imaging spectrometer. PAT has developed imaging spectrometers that span the spectral range from the visible, midwave infrared (3 to 5 microns) and longwave infrared (8 to 12 microns) with this technology. This paper will present the imaging spectral data that we have collected on various targets with our hyperspectral imaging instruments as will also describe the IMSS approach to imaging spectroscopy.
Full Text Available The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre- and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.
Zhang, C., Sr.; Huang, J.; Li, L.; Wang, H.; Zhu, D.
Abstract: Cultivated Land Quality Grade monitoring and evaluation is an important way to improve the land production capability and ensure the country food safety. Irrigation guarantee capability is one of important aspects in the cultivated land quality monitoring and evaluation. In the current cultivated land quality monitoring processing based on field survey, the irrigation rate need much human resources investment in long investigation process. This study choses Beijing-Tianjin-Hebei as study region, taking the 1 km × 1 km grid size of cultivated land unit with a winter wheat-summer maize double cropping system as study object. A new irrigation capacity evaluation index based on the ratio of the annual irrigation requirement retrieved from MODIS data and the actual quantity of irrigation was proposed. With the years of monitoring results the irrigation guarantee capability of study area was evaluated comprehensively. The change trend of the irrigation guarantee capability index (IGCI) with the agricultural drought disaster area in rural statistical yearbook of Beijing-Tianjin-Hebei area was generally consistent. The average of IGCI value, the probability of irrigation-guaranteed year and the weighted average which controlled by the irrigation demand index were used and compared in this paper. The experiment results indicate that the classification result from the present method was close to that from irrigation probability in the gradation on agriculture land quality in 2012, with overlap of 73% similar units. The method of monitoring and evaluation of cultivated land IGCI proposed in this paper has a potential in cultivated land quality level monitoring and evaluation in China. Key words: remote sensing, evapotranspiration, MODIS cultivated land quality, irrigation guarantee capability Authors: Chao Zhang, Jianxi Huang, Li Li, Hongshuo Wang, Dehai Zhu China Agricultural University firstname.lastname@example.org
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.
Trescott, A; Park, M-H
Lake Champlain is significantly impaired by excess phosphorus loading, requiring frequent lake-wide monitoring for eutrophic conditions and algal blooms. Satellite remote sensing provides regular, synoptic coverage of algal production over large areas with better spatial and temporal resolution compared with in situ monitoring. This study developed two algal production models using Landsat Enhanced Thematic Mapper Plus (ETM(+)) satellite imagery: a single band model and a band ratio model. The models predicted chlorophyll a concentrations to estimate algal cell densities throughout Lake Champlain. Each model was calibrated with in situ data compiled from summer 2006 (July 24 to September 10), and then validated with data for individual days in August 2007 and 2008. Validation results for the final single band and band ratio models produced Nash-Sutcliffe efficiency (NSE) coefficients of 0.65 and 0.66, respectively, confirming satisfactory model performance for both models. Because these models have been validated over multiple days and years, they can be applied for continuous monitoring of the lake.
Emeis, Stefan; Schäfer, Klaus; Münkel, Christoph; Friedl, Roman; Suppan, Peter
Since 2006 different remote monitoring methods for mixing layer height have been operated in Augsburg. One method is based on eye-safe commercial mini-lidar systems (ceilometers). The optical backscatter intensities recorded with these ceilometers provide information about the range-dependent aerosol concentration; gradient minima within this profile mark the tops of mixed layers. A special software for these ceilometers provides routine retrievals of lower atmosphere layering. A second method, based on SODAR (Sound Detection and Ranging) observations, detects the height of a turbulent layer characterized by high acoustic backscatter intensities due to thermal fluctuations and a high variance of the vertical velocity component. This information is extended by measurements with a RASS (Radio-Acoustic Sounding System) which provide the vertical temperature profile from the detection of acoustic signal propagation and thus temperature inversions which mark atmospheric layers. These SODAR and RASS data are the input to a software-based determination of mixing layer heights developed with MATLAB. A comparison of results of the three remote sensing methods during simultaneous measurements was performed. The information content of the ceilometer data is assessed by comparing it to the results from the other two instruments and near-by radiosonde data.
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
LANYong－chao; MAQua－jie; 等
The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China.The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring .So snowmelt runoff forecast has importance for hydropower,flood prevention and water resources utilize-tion.The application of remote sensing and Geographic Information System(GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper.The key parame-ter-snow cover area can be computed by satellite images from multi-platform,multi-templral and multi-spectral.A clus-ter of snow-cover data can be yielded by means of the classification filter method.Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning .According to the typical samples extracting snow covered moun-tained in detail also.The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff,precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reser-voir,which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June.The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin.With the develop-ment of remote sensing technique and the progress of the interpretation method,the forecast accuracy of snowmelt runoff will be improved in the near future .Large scale extent and few stations are two objective reality situations in Chian,so they should be considered in simulation and forecast.Apart from dividing ,the derivation of
The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China. The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter- snow cover area can be computed by satellite images from multi-platform, multi-temporal and multi-spectral. A cluster of snow-cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two
Soares da Silva, Natália; Sánchez-Román, Rodrigo; Marchamalo Sacristán, Miguel; Rodriguez-Sinobas, Leonor
Nowadays, the concern of the effect of climate change on water availability on a global scale is getting bigger and bigger. In average, about 65 % of the world water consumption is devoted to irrigated agriculture. In countries such as Brazil, water scarcity has been a main issue in populated areas (i.e. São Paulo) in the last two years. This has affected not only water availability for the population but also irrigation water to maintain crop yield and Brazilian economy. Remote sensing is a tool broadly used in multiple fields of science such as water management in irrigated agriculture. Actually, there are several satellites moving around the earth, and they take images of every place in a weekly or biweekly basis. The images can be downloaded from the internet site at no cost by the users. Then, they are used to determine the vegetation index NDVI which is based in the energy reflected in red and infrared spectrum and it depends on the vegetation photosynthetic activity. Within the above context, this study focus on remote sensing monitoring of a bean crop located in the basin of Boi Branco, São Paulo - Brazil, which is irrigated by pivot center. The images from the Landsat and Modis satellites were downloaded throughout the bean growing period and then, they were processed and analyzed with the Qgis software. In addition, soil moisture was measured by several TDR probe sensors deployed in the irrigated area, and the leaf area index was measured as well in the field. Both variables were used to estimate the Normalized Difference Vegetation Index (NDVI) for each bean phenology state.
Doerffer, Roland; Murphy, Desmond
Interest in using remote sensing techniques, principally those involving satellite, in Wadden Sea research has centred on attempting a classification of the various sediment surface types present. Unlike most recent studies which have used mainly Landsat Multispectral Scanner data, we have assessed the feasibility of using Landsat Thematic Mapper data, which in conjunction with time series aerial photography, forms the basis of a strategy for remotely sensing the Wadden Sea. This paper focusses on an approach for extracting potentially “hidden” within-pixel information from multispectral data sets. A hierarchical (unsupervised) classification of a Thematic Mapper image successfully classified five different classes, including land, saltmarsh, water, cloud and tidal flat areas. This procedure thus enabled a “masking-out” of all classes other than those classified as tidal flat, following which a factor analysis was used to determine the minimum number of independent factors necessary to explain the observed variation in the signal received by the satellite. Three factors accounted for a total of 82% of the variation in all seven TM channels. Preliminary studies of the primary factor (score) image shows a good correlation with existing latterday cartographic data. Considering the proximate relationship between topography and other important biotic and abiotic sedimentary characteristics, this approach may prove valuable for future applications of satellite data for monitoring long-term change in physical and thus biological Wadden Sea characteristics. Ongoing research efforts are focussing on a classification and quantification of sub-pixel patchiness using aerial photography and ground surveys. The approaches taken and results obtained to date are discussed.
De Padova, Diana; Mossa, Michele; Adamo, Maria; De Carolis, Giacomo; Pasquariello, Guido
In case of oil spills due to disasters, one of the environmental concerns is the oil trajectories and spatial distribution. To meet these new challenges, spill response plans need to be upgraded. An important component of such a plan would be models able to simulate the behaviour of oil in terms of trajectories and spatial distribution, if accidentally released, in deep water. All these models need to be calibrated with independent observations. The aim of the present paper is to demonstrate that significant support to oil slick monitoring can be obtained by the synergistic use of oil drift models and remote sensing observations. Based on transport properties and weathering processes, oil drift models can indeed predict the fate of spilled oil under the action of water current velocity and wind in terms of oil position, concentration and thickness distribution. The oil spill event that occurred on 31 May 2003 in the Baltic Sea offshore the Swedish and Danish coasts is considered a case study with the aim of producing three-dimensional models of sea circulation and oil contaminant transport. The High-Resolution Limited Area Model (HIRLAM) is used for atmospheric forcing. The results of the numerical modelling of current speed and water surface elevation data are validated by measurements carried out in Kalmarsund, Simrishamn and Kungsholmsfort stations over a period of 18 days and 17 h. The oil spill model uses the current field obtained from a circulation model. Near-infrared (NIR) satellite images were compared with numerical simulations. The simulation was able to predict both the oil spill trajectories of the observed slick and thickness distribution. Therefore, this work shows how oil drift modelling and remotely sensed data can provide the right synergy to reproduce the timing and transport of the oil and to get reliable estimates of thicknesses of spilled oil to prepare an emergency plan and to assess the magnitude of risk involved in case of oil spills due
Coal exploitation inevitably damages the natural ecological environment through large scale underground exploitation which exhausts the surrounding areas and is the cause of surface subsidence and cracks.These types of damage seriously lower the underground water table.Deterioration of the environment has certainly an impact on and limits growth of vegetation, which is a very important indicator of a healthy ecological system.Dynamically monitoring vegetation growth under coal exploitation stress by remote sensing technology provides advantages such as large scale coverage, high accuracy and abundant information.A scatter plot was built by a TM (Thematic Mapper) infrared and red bands.A detailed analysis of the distributional characteristics of vegetation pixels has been carried out.Results show that vegetation pixels are affected by soil background pixels, while the distribution of soil pixels presents a linear pattern.Soil line equations were obtained mainly by linear regression.A new band, reflecting vegetation growth, has been obtained based on the elimination of the soil background.A grading of vegetation images was extracted by means of a density slice method.Our analysis indicates that before the exploitation of the Bulianta coal mining area, vegetation growth had gradually reduced; especially intermediate growth vegetation had been transformed into low vegetation.It may have been caused by the deterioration of the brittle environment in the western part of the mining area.All the same, after the start of coal production, vegetation growth has gradually improved, probably due to large scale aerial seeding.Remote sensing interpretation results proved to be consistent with the actual situation on the ground.From our research results we can not conclude that coal exploitation stress has no impact on the growth of vegetation.More detailed research on vegetation growth needs to be analyzed.
Shang, J.; Huang, X.; Liu, J.; Wang, J.
Information on agricultural land surface conditions is important for developing best land management practices to maintain the overall health of the fields. The climate condition supports one harvest per year for the majority of the field crops in Canada, with a relative short growing season between May and September. During the non-growing-season months (October to the following April), many fields are traditionally left bare. In more recent year, there has been an increased interest in planting cover crops. Benefits of cover crops include boosting soil organic matters, preventing soil from erosion, retaining soil moisture, and reducing surface runoff hence protecting water quality. Optical remote sensing technology has been exploited for monitoring cover crops. However limitations inherent to optical sensors such as cloud interference and signal saturation (when leaf area index is above 2.5) impeded its operational application. Radar remote sensing on the other hand is not hindered by unfavorable weather conditions, and the signal continues to be sensitive to crop growth beyond the saturation point of optical sensors. It offers a viable means for capturing timely information on field surface conditions (with or without crop cover) or crop development status. This research investigated the potential of using multi-temporal RADARSAT-2 C-band synthetic aperture radar (SAR) data collected in 2015 over multiple fields of winter wheat, corn and soybean crops in southern Ontario, Canada, to retrieve information on the presence of cover crops and their growth status. Encouraging results have been obtained. This presentation will report the methodology developed and the results obtained.
Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James
Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.
Torres, R. C.; Mouginis-Mark, P.; Wright, R.; Garbeil, H.; Craig, B.
The Philippines has one of the world's fastest disappearing forest cover, which is being lost to natural processes and landscape-modifying human activities. Currently, forested landscape covers 24% (i.e., 7.2 million hectares) of the Philippines' total land area, of which only 800,000 hectares are considered as old-growth forests. Occasionally, volcanic activities and earthquakes cause large-scale impacts on the forest cover, but the systematic reduction of the country's forest has been sustained through unregulated logging operations and other human-induced landscape modification. Reforestation and watershed protection have become important public policy programs as forest denudation is linked to recent devastating landslides, debris flows and flashfloods. However, many watershed areas that are at risk to deforestation are hardly accessible to ground-based monitoring. A spaced-based monitoring system facilitates an efficient and timely response to changes in the quality and extent of the Philippine forest cover. This monitoring system relies in the generation of Normalized Difference Vegetation Index (NDVI) products from the red and infrared bands of remote sensing data, which correlates with the amount of chlorophyll in the vegetation. Given the existing forest classification maps, non-forested regions are masked in the data analysis, so that only forest-related changes in the vegetation are shown in the NDVI image difference products. A combination of two MODIS-bearing satellites, i.e., Terra and Aqua, acquire high temporal and moderate spatial resolution data, enabling the countrywide detection of vegetation changes within a certain observation period. MODIS data are calibrated for setting the pixel quality thresholds, which minimize the artifact of clouds and haze in the analysis. Areas showing dramatic changes are further investigated using higher resolution data, such as ASTER and Landsat 7 ETM. Sequential NDVI products of remote sensing data provide
V. G. Konovalov
extrapolation of meteorological data. Examples are given of determining the spectral albedo of glacier surface, using ENVI software and remote sensing data from Landsat 7 ETM+ and TERRA. Application of the methods for determining the albedo on the one hand creates additional opportunities for remote monitoring of glaciers, on the other – provides calculation different types of melted glacier surface as a function of absorbed solar radiation.
Full Text Available Collecting vast amount of data does not solely help to fulfil information needs related to crowd monitoring, it is rather important to collect data that is suitable to meet specific information requirements. In order to address this issue, a prototype is developed to facilitate the combination of UAV-based RGB and thermal remote sensing datasets. In an experimental approach, image sensors were mounted on a remotely piloted aircraft and captured two video datasets over a crowd. A group of volunteers performed diverse movements that depict real world scenarios. The prototype is deriving the movement on the ground and is programmed in MATLAB. This novel detection approach using combined data is afterwards evaluated against detection algorithms that only use a single data source. Our tests show that the combination of RGB and thermal remote sensing data is beneficial for the field of crowd monitoring regarding the detection of crowd movement.
LI Liang-jun; WU Yan-bin
We discuss remote-sensing-image fusion based on a multi-band wavelet and RGB feature fusion method. The fused data can be used to monitor the dynamic evolution of mining induced subsidence. High resolution panchromatic image data and multi-spectral image data were first decomposed with a multi-ary wavelet method. Then the high frequency components of the high resolution image were fused with the features from the R, G, B bands of the multi-spectral image to form a new high frequency component. Then the newly formed high frequency component and the low frequency component were inversely transformed using a multi-ary wavelet method. Finally, color images were formed from the newly formed R, G, B bands. In our experiment we used images with a resolution of 10 m (SPOT), and TM30 images, of the Huainan mining area. These images were fused with a trinary wavelet method. In addition, we used four indexes-entropy, average gradient, wavelet energy and spectral distortion-to assess the new method. The result indicates that this new method can improve the clarity and resolution of the images and also preserves the information from the original images. Using the fused images for monitoring mining induced subsidence achieves a good effect.
James K. Lein
Full Text Available Regional sustainability encourages a re-examination of development programs in the context of environmental, social and economic policies and practices. However, sustainability remains a broadly defined concept that has been applied to mean everything from environmental protection, social cohesion, economic growth, neighborhood design, alternative energy, and green building design. To guide sustainability initiatives and assess progress toward more sustainable development patterns, a need exists to place this concept into a functional decision-centric context where change can be evaluated and the exploitation of resources better understood. Accepting the premise that sustainable development defines a set of conditions and trends in a given system that can continue indefinitely without contributing to environmental degradation, answers to four critical questions that direct sustainability over the long-term must be addressed: (1 What is the present state of the environmental system, (2 Is that pattern sustainable, (3 Are there indications that the environmental system is degrading, and (4 Can that information be incorporated into policy decisions to guide the future? Answers to these questions hinge on the development of tractable indices that can be employed to support the long-term monitoring required to assess sustainability goals and a means to measure those indices. In this paper, a solution based on the application of remote sensing technology is introduced focused on the development of land use intensity indices derived from earth-observation satellite data. Placed into a monitoring design, this approach is evaluated in a change detection role at the watershed scale.
Contreras, Sergio; Hunink, Johannes E.
We present a satellite-based Drought Monitoring System that provides weekly updates of maps and bulletins with vegetation drought indices over the Iberian Peninsula. The web portal InfoSequía (http://infosequia.es) aims to complement the current Spanish Drought Monitoring System which relies on a hydrological drought index computed at the basin level using data on river flows and water stored in reservoirs. Drought indices computed by InfoSequia are derived from satellite data provided by MODIS sensors (TERRA and AQUA satellites), and report the relative anomaly observed in the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and in an additive combination of both. Similar to the U.S. Drought Monitoring System by NOAA, the indices include the Vegetation Condition Index (VCI, relative NDVI anomaly), the Temperature Condition Index (TCI, relative LST anomaly) and the Vegetation Health Index (VHI, relative NDVI-LST anomaly). Relative anomalies are codified into four warning levels, and all of them are provided for short periods of time (8-day windows), or longer periods (e.g. 1 year) in order to capture the cumulative effects of droughts in the state variables. Additionally, InfoSequia quantifies the seasonal trajectories of the cumulative deviation of the observed NDVI in relation with the averaged seasonal trajectory observed over a reference period. Through the weekly bulletins, the Drought Monitoring System InfoSequia aims to provide practical information to stakeholders on the sensitivity and resilience of native ecosystems and rainfed agrosystems during drought periods. Also, the remote sensed indices can be used as drought impact indicator to evaluate the skill of seasonal agricultural drought forecasting systems. InfoSequia is partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant.
Lingli WANG; John J.QU
Surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/ atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. Recent technological advances in satellite remote sensing have shown that soil moisture can be measured by a variety of remote sensing techniques,each with its own strengths and weaknesses. This paper presents a comprehensive review of the progress in remote sensing of soil moisture, with focus on technique approaches for soil moisture estimation from optical,thermal, passive microwave, and active microwave measurements. The physical principles and the status of current retrieval methods are summarized. Limitations existing in current soil moisture estimation algorithms and key issues that have to be addressed in the near future are also discussed.
should be based on the integration of remotely-sensed data with semi-deterministic agrometeorological models. This approach will allow a...sensed data with semi-deterministic agrometeorological models. This approach will allow a regionalization of the production estimates. Keywords...successfully classified and discriminated fields of maize in Zambia based on a multitemporal analysis of a vegetation index calculated from Landsat Thematic
North, G. W.
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.
Okwu-Delunzu, V. U.; Enete, I. C.; Abubakar, A. S.; Lamidi, S.
Erosion is a natural, gradual and continuous process of earth surface displacement caused by various agents of denudation. It is also caused by some anthropogenic activities. Erosion rate of an area at any point in time is dependent mainly on climate and geological factors. Physical aspects of the erosive force experienced in gullies are mainly dependent on the local prevailing climate condition. In this study, remotely sensed data was used in the analysis of gully erosion progression at Nyaba River in Enugu Urban, aimed at mapping and monitoring gully erosion at the study site. Methodologies employed include; data acquisition from field observation and satellite images; data processing and analyses using ilwis 3.7 and Arc GIS 9.3 software. The result showed that gully progressed from 578,713,735 square meters in 1986 to 1, 002,819,723 in 2011. Prediction showed that the magnitude of the gully area is expected to increase as the years go by if measures are not taken to control the expansion rate. The forecast put the expected coverage of gully erosion at Nyaba River to be 45,210,440 square meters by the year 2040. Consequently, recommendations made include: constant monitoring to detect early stages of gully formation; regulation of grazing of pasture in the area; restriction of sand mining from the river bank and construction of water ways to stabilize river flow. In conclusion, monitoring clearly showed that there was a geometric progression in gully formation at Nyaba over years; the expansion was aided more by anthropogenic activities than natural factors.
Harb, Mostapha; De Vecchi, Daniele; Dell'Acqua, Fabio
The paper introduces a novel approach for the geometric co registration of optical remote sensing imagery. In the context of disaster mitigation and preparedness, a multi-temporal set of several remote sensing images often has to be processed separately to extract the required information. Then, a comparison among the obtained results would provide clues towards the time-evolving extent and distribution of risk. Therefore, it is of significant importance to achieve a proper geometric matching among the compared images. The traditional procedure of using manually-determined ground control points is not viable for large stacks of images, and automated methods may fail short of ensuring image conformity. The established method uses image data itself to effectively perform the co registration among the images relying on feature extraction and matching, without the necessity of using ground control points (GCPs). The approach has been tested using both high and medium resolution images on different test cases in a context of multi-risk vulnerability monitoring. The obtained results were highly promising in resolving the mismatching problem of objects in images taken from different dates and allowing smooth extraction of vulnerability proxies from multi-temporal moderate resolution optical satellite images. In conclusion, the methodology would be a useful contribution towards easing the tracking of temporal variation of ground features in the wide domain of risk-related application of remote sensing (e.g. urban development, deforestation, wild fire, damage assessment...) Keywords: Risk monitoring, remote sensing, optical imagery, geometric co registration
Yan, Hongxiang; Moradkhani, Hamid
Current two datasets provide spatial and temporal resolution of soil moisture at large-scale: the remotely-sensed soil moisture retrievals and the model-simulated soil moisture products. Drought monitoring using remotely-sensed soil moisture is emerging, and the soil moisture simulated using land surface models (LSMs) have been used operationally to monitor agriculture drought in United States. Although these two datasets yield important drought information, their drought monitoring skill still needs further quantification. This study provides a comprehensive assessment of the potential of remotely-sensed and model-simulated soil moisture data in monitoring agricultural drought over the Columbia River Basin (CRB), Pacific Northwest. Two satellite soil moisture datasets were evaluated, the LPRM-AMSR-E (unscaled, 2002-2011) and ESA-CCI (scaled, 1979-2013). The USGS Precipitation Runoff Modeling System (PRMS) is used to simulate the soil moisture from 1979-2011. The drought monitoring skill is quantified with two indices: drought area coverage (the ability of drought detection) and drought severity (according to USDM categories). The effects of satellite sensors (active, passive), multi-satellite combined, length of climatology, climate change effect, and statistical methods are also examined in this study.
Zhang, J.; Becker-Reshef, I.; Justice, C. O.
Although agricultural production has been rising in the past years, drought remains the primary cause of crop failure, leading to food price instability and threatening food security. The recent 'Global Food Crisis' in 2008, 2011 and 2012 has put drought and its impact on crop production at the forefront, highlighting the need for effective agricultural drought monitoring. Satellite observations have proven a practical, cost-effective and dynamic tool for drought monitoring. However, most satellite based methods are not specially developed for agriculture and their performances for agricultural drought monitoring still need further development. Wheat is the most widely grown crop in the world, and the recent droughts highlight the importance of drought monitoring in major wheat producing areas. As the largest wheat producing state in the US, Kansas plays an important role in both global and domestic wheat markets. Thus, the objective of this study is to investigate the capabilities of remotely sensed crop indicators for effective agricultural drought monitoring in Kansas wheat-grown regions using MODIS data and crop yield statistics. First, crop indicators such as NDVI, anomaly and cumulative metrics were calculated. Second, the varying impacts of agricultural drought at different stages were explored by examining the relationship between the derived indicators and yields. Also, the starting date of effective agricultural drought early detection and the key agricultural drought alert period were identified. Finally, the thresholds of these indicators for agricultural drought early warning were derived and the implications of these indicators for agricultural drought monitoring were discussed. The preliminary results indicate that drought shows significant impacts from the mid-growing-season (after Mid-April); NDVI anomaly shows effective drought early detection from Late-April, and Late-April to Early-June can be used as the key alert period for agricultural
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.
The world is suffering from rapid changes in both climate and land cover which are the main factors affecting global biodiversity. These changes may affect ecosystems by altering species distributions, population sizes, and community compositions, which emphasizes the need for a rapid assessment of biodiversity status for conservation and management purposes. Current approaches on monitoring biodiversity rely mainly on long term observations of predetermined sites, which require large amounts of time, money and personnel to be executed. In order to overcome problems associated with current field monitoring methods, the main objective of this dissertation is the development of framework for inferential monitoring of the impact of global change on biodiversity based on remotely sensed data coupled with species distribution modeling techniques. Several research pieces were performed independently in order to fulfill this goal. First, species distribution modeling was used to identify the ranges of 6362 birds, mammals and amphibians in South America. Chapter 1 compares the power of different presence-only species distribution methods for modeling distributions of species with different response curves to environmental gradients and sample sizes. It was found that there is large variability in the power of the methods for modeling habitat suitability and species ranges, showing the importance of performing, when possible, a preliminary gradient analysis of the species distribution before selecting the method to be used. Chapter 2 presents a new methodology for the redefinition of species range polygons. Using a method capable of establishing the uncertainty in the definition of existing range polygons, the automated procedure identifies the relative importance of bioclimatic variables for the species, predicts their ranges and generates a quality assessment report to explore prediction errors. Analysis using independent validation data shows the power of this
Kontoes, C.; Papoutsis, I.; Michail, D.; Herekakis, Th.; Koubarakis, M.; Kyzirakos, K.; Karpathiotakis, M.; Nikolaou, C.; Sioutis, M.; Garbis, G.; Vassos, S.; Keramitsoglou, I.; Kersten, M.; Manegold, S.; Pirk, H.
In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such
Jucker, T.; Caspersen, John; Chave, J.; Antin, C.; Barbier, N.; Bongers, F.; Dalponte, M.; Ewijk van, K.Y.; Poorter, L.; Sterck, F.J.
Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks an
Kontoes, C.; Papoutsis, I.; Michail, D.; Herekakis, T.; Koubarakis, M.; Kyzirakos, K.; Karpathiotakis, M.; Nikolaou, C.; Sioutis, M.; Garbis, G.; Vassos, S.; Keramitsoglou, I.; Manegold, S.; Kersten, M.L.; Pirk, H.
In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applicati
Full Text Available Whereas the tank volume and dehydrating digits from kinds of tanks are depended on repository sludge, so calculating the sediments is so important in tank planning and hydraulic structures. We are worry a lot about soil erosion in the basin area leading to deposit in rivers and lakes. It holds two reasons: firstly, because the surface soil of drainage would lose its fertility and secondly, the capacity of the tank decreases also it causes the decrease of water quality in downstream. Several studies have shown that we can estimate the rate of suspension sediments through remote sensing techniques. Whereas using remote sensing methods in contrast to the traditional and current techniques is faster and more accurate then they can be used as the effective techniques. The intent of this study has already been to estimate the rate of sediments in Karaj watershed through remote sensing and satellite images then comparing the gained results to the sediments data to use them in gauge-hydraulic station. We mean to recognize the remote sensing methods in calculating sediment and use them to determine the rate of river sediments so that identifying their accuracies. According to the results gained of the shown relations at this article, the amount of annual suspended sedimentary in KARAJ watershed have been 320490 Tones and in hydrologic method is about 350764 Tones .
required (common ones developed for land include HATCH, ACORN, FLAASH, ISDAS , and ATCOR, which are comparable although some include advanced spectral...Batzli, and D. L. Skole. 2003. Regional assessment of lake water clarity using satellite remote sensing. In Papers from Bolsena Conference (2002...information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing
Bridging various scales ranging from local to regional and global, remote sensing has facilitated extraordinary advances in modeling and mapping ecosystems and their functioning. Since forests are one of the most important natural resources on the terrestrial Earth surface, accurate and up-to-date i
C. Kontoes (Charalampos); I. Papoutsis (Ioannis); D. Michail (Dimitrios); T. Herekakis (Themistocles); M. Koubarakis (Manolis); K. Kyzirakos (Konstantinos); M. Karpathiotakis (Manos); C. Nikolaou (Charalampos); M. Sioutis (Michael); G. Garbis (George); S. Vassos (Stavros); I. Keramitsoglou; S. Manegold (Stefan); M.L. Kersten (Martin); H. Pirk (Holger)
textabstractIn the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum
SHEN RUNPING; I. KHEORUENROMNE
A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.
Li, Ying; Cui, Can; Liu, Zexi; Liu, Bingxin; Xu, Jin; Zhu, Xueyuan; Hou, Yongchao
Current marine oil spill detection and monitoring methods using high-resolution remote sensing imagery are quite limited. This study presented a new bottom-up and top-down visual saliency model. We used Landsat 8, GF-1, MAMS, HJ-1 oil spill imagery as dataset. A simplified, graph-based visual saliency model was used to extract bottom-up saliency. It could identify the regions with high visual saliency object in the ocean. A spectral similarity match model was used to obtain top-down saliency. It could distinguish oil regions and exclude the other salient interference by spectrums. The regions of interest containing oil spills were integrated using these complementary saliency detection steps. Then, the genetic neural network was used to complete the image classification. These steps increased the speed of analysis. For the test dataset, the average running time of the entire process to detect regions of interest was 204.56 s. During image segmentation, the oil spill was extracted using a genetic neural network. The classification results showed that the method had a low false-alarm rate (high accuracy of 91.42%) and was able to increase the speed of the detection process (fast runtime of 19.88 s). The test image dataset was composed of different types of features over large areas in complicated imaging conditions. The proposed model was proved to be robust in complex sea conditions.
Kaplan, G.; Avdan, U.
Snow cover is an important part of the Earth`s climate system so its continuous monitoring is necessary to map snow cover in high resolution. Satellite remote sensing can successfully fetch land cover and land cover changes. Although normalized difference snow index NDSI has quite good accuracy, topography shadow, water bodies and clouds can be easily misplaced as snow. Using Landsat TM, +ETM and TIRS/OLI satellite images, the NDSI was modified for more accurate snow mapping. In this paper, elimination of the misplaced water bodies was made using the high reflectance of the snow in the blue band. Afterwards, the modified NDSI (MNDSI) was used for estimating snow cover through the years on the highest mountains in Republic of Macedonia. The results from this study show that the MNDSI accuracy is bigger than the NDSI`s, totally eliminating the misplaced water bodies, and partly the one caused from topography and clouds. Also, it was noticed that the snow cover in the study area has been lowered through the years. For future studies, the MNDSI should be validated on different study areas with different characteristics.
Full Text Available A method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of cloud microphysical changes due to the changing aerosol concentration. We use high resolution measurements from lidar, radar and radiometer which allow to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example study cases were chosen from the Atmospheric Radiation Measurement (ARM Program deployment at Graciosa Island, Azores, Portugal in 2009 to present the method. We show the Pearson Product–Moment Correlation Coefficient, r, and the Coefficient of Determination, r2 for data divided into bins of LWP, each of 10 g m−2. We explain why the commonly used way of quantity aerosol cloud interactions by use of an ACI index (ACIr,τ = dln re,τ/dlnα is not the best way of quantifying aerosol–cloud interactions.
Robert Paul Breckenridge
Creeping environmental changes are impacting some of the largest remaining intact parcels of sagebrush steppe ecosystems in the western United States, creating major problems for land managers. The Idaho National Laboratory (INL), located in southeastern Idaho, is part of the sagebrush steppe ecosystem, one of the largest ecosystems on the continent. Scientists at the INL and the University of Idaho have integrated existing field and remotely sensed data with geographic information systems technology to analyze how recent fires on the INL have influenced the current distribution of terrestrial vegetation. Three vegetation mapping and classification systems were used to evaluate the changes in vegetation caused by fires between 1994 and 2003. Approximately 24% of the sagebrush steppe community on the INL was altered by fire, mostly over a 5-year period. There were notable differences between methods, especially for juniper woodland and grasslands. The Anderson system (Anderson et al. 1996) was superior for representing the landscape because it includes playa/bare ground/disturbed area and sagebrush steppe on lava as vegetation categories. This study found that assessing existing data sets is useful for quantifying fire impacts and should be helpful in future fire and land use planning. The evaluation identified that data from remote sensing technologies is not currently of sufficient quality to assess the percentage of cover. To fill this need, an approach was designed using both helicopter and fixed wing unmanned aerial vehicles (UAVs) and image processing software to evaluate six cover types on field plots located on the INL. The helicopter UAV provided the best system compared against field sampling, but is more dangerous and has spatial coverage limitations. It was reasonably accurate for dead shrubs and was very good in assessing percentage of bare ground, litter and grasses; accuracy for litter and shrubs is questionable. The fixed wing system proved to be
González-Dugo, Maria P.; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; José Polo, María
Drought is one of the major hazards faced by agroforestry systems in southern Europe, and an increase in frequency is predicted under the conditions of climate change for the region. Timely and accurate monitoring of vegetation water stress using remote sensing time series may assist early-warning services, helping to assess drought impacts and the design of management actions leading to reduce the economic and environmental vulnerability of these systems. A holm oak savanna, known as dehesa in Spain and montado in Portugal, is an agro-silvo-pastoral system occupying more than 3 million hectares the Iberian Peninsula and Greece. It consists of widely-spaced oak trees (mostly Quercus ilex L.), combined with crops, pasture and Mediterranean shrubs, and it is considered an example of sustainable land use, with great importance in the rural economy. Soil water dynamics is known to have a central role in current tree decline and the reduction of the forested area that is threatening its conservation. A two-source thermal-based evapotranspiration model (TSEB) has been applied to monitor the effect on vegetation water use of soil moisture stress in a dehesa located in southern Spain. The TSEB model separates the soil and canopy contributions to the radiative temperature and to the exchange of surface energy fluxes, so it is especially suited for partially vegetated landscapes. The integration of remotely sensed data in this model may support an evaluation of the whole ecosystem state at a large scale. During two consecutive summers, in 2012 and 2013, time series of optical and thermal MODIS images, with 250m and 1 km of spatial resolution respectively, have been combined with meteorological data provided by a ground station to monitor the evapotranspiration (ET) of the system. An eddy covariance tower (38°12' N; 4°17' W, 736 m a.s.l), equipped with instruments to measure all the components of the energy balance and 1 km of homogeneous fetch in the predominant wind
Mona, Lucia; Caggiano, Rosa; Donvito, Angelo; Giannini, Vincenzo; Papagiannopoulos, Nikolaos; Sarli, Valentina; Trippetta, Serena
The atmospheric aerosols have effects on climate, environment and health. Although the importance of the study of aerosols is well recognized, the current knowledge of the characteristics and their distribution is still insufficient, and there are large uncertainties in the current understanding of the role of aerosols on climate and the environment, both on a regional and local level. Overcoming these uncertainties requires a search strategy that integrates data from multiple platforms (eg, terrestrial, satellite, ships and planes) and the different acquisition techniques (for example, in situ measurements, remote sensing, modeling numerical and data assimilation) (Yu et al., 2006). To this end, in recent years, there have been many efforts such as the creation of networks dedicated to systematic observation of aerosols (eg, European Monitoring and Evaluation Programme-EMEP, European Aerosol Research Lidar NETwork-EARLINET, MicroPulse Lidar Network- MPLNET, and Aerosol Robotic NETwork-AERONET), the development and implementation of new satellite sensors and improvement of numerical models. The recent availability of numerous data to the ground, columnar and profiles of aerosols allows to investigate these aspects. An integrated approach between these different techniques could be able to provide additional information, providing greater insight into the properties of aerosols and their distribution and overcoming the limits of each single technique. In fact, the ground measurements allow direct determination of the physico-chemical properties of aerosols, but cannot be considered representative for large spatial and temporal scales and do not provide any information about the vertical profile of aerosols. On the other hand, the remote sensing techniques from the ground and satellite provide information on the vertical distribution of atmospheric aerosols both in the Planetary Boundary Layer (PBL), mainly characterized by the presence of aerosols originating from
Cammalleri, Carmelo; Vogt, Jürgen
Soil moisture anomalies (i.e., deviations from the climatology) are often seen as a reliable tool to monitor and quantify the occurrence of drought events and their potential impacts, especially in agricultural and naturally vegetated lands. Soil moisture datasets (or their proxy) can be derived from a variety of sources, including land-surface models and thermal and microwave satellite remote sensing images. However, each data source has different advantages and drawbacks that prevent to unequivocally prefer one dataset over the others, especially in global applications that encompass a wide range of soil moisture regimes. The analysis of the spatial reliability of the different datasets at global scale is further complicated by the lack of reliable long-term soil moisture records for a ground validation over most regions. To overcome this limitation, in recent years the Triple Collocation (TC) technique has been deployed in order to quantify the likely errors associated to three mutually-independent datasets without assuming that one of them represents the "truth". In this study, three global datasets of soil moisture anomalies are investigated: the first one derived from the runs of the Lisflood hydrological model, the second one obtained from the combined active/passive microwave dataset produced in the framework of the European Space Agency (ESA) Climate Change Initiative (CCI), and the last one derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) observations. A preliminary analysis of the three datasets aimed at detecting the areas where the TC technique can be successfully applied, hence the spatial distribution of the random error variance for each model is evaluated. This study allows providing useful advises for a robust combination of the three datasets into a single product for a more reliable global drought monitoring.
Bonifazi, Giuseppe; Serranti, Silvia
Mining activities, expecially those operated in open air (open pit), present a deep impact on the sourrondings. Such an impact, and the related problems, are directly related to the correct operation of the activities, and usually strongly interact with the environment. Impact can be mainly related to the following issues: high volumes of handled material, ii) generation of dust, noise and vibrations, water pollution, visual impact and, finally, mining area recovery at the end of exploitation activities. All these aspects can be considered very important, and must be properly evaluated and monitored. Environmental impact control is usually carried out during and after the end of the mining activities, adopting methods related to the detection, collection, analysis of specific environmental indicators and with their further comparison with reference thresholding values stated by official regulations. Aim of the study was to investigate, and critically evaluate, the problems related to development of an integrated set of procedures based on the collection and the analysis of remote sensed data in order to evaluate the effect of rehabilitation of land contaminated by extractive industry activities. Starting from the results of these analyses, a monitoring and registration of the environmental impact of such operations was performed by the application and the integration of modern information technologies, as the previous mentioned Earth Observation (EO), with Geographic Information Systems (GIS). The study was developed with reference to different dismissed mine sites in India, Thailand and China. The results of the study have been utilized as input for the construction of a knowledge based decision support system finalized to help in the identification of the appropriate rehabilitation technologies for all those dismissed area previously interested by extractive industry activities. The work was financially supported within the framework of the Project ASIA IT&C - CN
Ghosh, Manoj Kumer; Kumar, Lalit; Roy, Chandan
A large percentage of the world's population is concentrated along the coastal zones. These environmentally sensitive areas are under intense pressure from natural processes such as erosion, accretion and natural disasters as well as anthropogenic processes such as urban growth, resource development and pollution. These threats have made the coastal zone a priority for coastline monitoring programs and sustainable coastal management. This research utilizes integrated techniques of remote sensing and geographic information system (GIS) to monitor coastline changes from 1989 to 2010 at Hatiya Island, Bangladesh. In this study, satellite images from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) were used to quantify the spatio-temporal changes that took place in the coastal zone of Hatiya Island during the specified period. The modified normalized difference water index (MNDWI) algorithm was applied to TM (1989 and 2010) and ETM (2000) images to discriminate the land-water interface and the on-screen digitizing approach was used over the MNDWI images of 1989, 2000 and 2010 for coastline extraction. Afterwards, the extent of changes in the coastline was estimated through overlaying the digitized maps of Hatiya Island of all three years. Coastline positions were highlighted to infer the erosion/accretion sectors along the coast, and the coastline changes were calculated. The results showed that erosion was severe in the northern and western parts of the island, whereas the southern and eastern parts of the island gained land through sedimentation. Over the study period (1989-2010), this offshore island witnessed the erosion of 6476 hectares. In contrast it experienced an accretion of 9916 hectares. These erosion and accretion processes played an active role in the changes of coastline during the study period.
Miodrag D. Regodić
monitoring natural phenomena The images taken from Remote Sensing have helped men to use the environment and natural resources in a better way. It is expected that the developement of new technologies will spread the usage of satellite images for the welfare of mankind as well. Besides monitoring the surface of the Earth, the satellite monitoring of the processes inside the Earth itself is of great importance since these processes can cause different catastrophes such as earthquakes, volcano eruptions, floods, etc. Usage of satellite images in monitoring atmospheric phenomena The launch of artificial earth satellites has opened new possibilities for monitoring and studying atmospheric phenomena. A large number of meteorological satellites have been launched by now (Nimbus, Meteor, SNS, ESSA, Meteosat, Terra, etc.. Since these images are primarily used for weather forecast, meteorologists use them to get information about the characteristics of clouds related to their temperature, the temperature of the cloud layer, the degree of cloudness, the profiles of humidity content, the wind parameters, etc. Meteosat satellites Meteosat is the first European geostationary satellite designed for meteorological research. The use of these satellites enabled the surveying in the visible and the near IR part of the spectrum as well as in the infrared thermal and water steam track. Based on these images, it was possible to obtain data such as: height of clouds, cloud spreading and moving, sea surface temperature, speed of wind, distribution of the water steam, balance of radiation, etc. Usage of satellite images in monitoring floods Satellite images are an excellent background and an initial phase for preventing severe catastrophic events caused by floods. Due to satellite images, it is possible to manage overflown regions before, during and after floods. This enables prevention, forecasting, detection and elimination of consequences, i.e. demage. Satellite images are of great help
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.
Scipal, K.; Wagner, W.
The lack of global soil moisture observations is one of the most glaring and pressing deficiencies in current research activities of related fields, from climate monitoring and ecological applications to the quantification of biogeophysical fluxes. This has implications for important issues of the international political agenda like managing global water resources, securing food production and studying climate change. Currently it is held that only microwave remote sensing offers the potential to produce reliable global scale soil moisture information economically. Recognising the urgent need for a soil moisture mission several international initiatives are planning satellite missions dedicated to monitor the global hydrological cycle among them two European microwave satellites. ESA is planning to launch the Soil Moisture and Ocean Salinity Mission SMOS, in 2006. SMOS will measure soil moisture over land and ocean salinity over the oceans. The mission rests on a passive microwave sensor (radiometer) operated in L-band which is currently believed to hold the largest potential for soil moisture retrieval. One year before (2005) EUMETSAT will launch the Meteorological Operational satellite METOP which carries the active microwave system Advanced Scatterometer ASCAT on board. ASCAT has been designed to retrieve winds over the oceans but recent research has established its capability to retrieve soil moisture. Although currently it is hold that, using active microwave techniques, the effect of surface roughness dominates that of soil moisture (while the converse is true for radiometers), the ERS scatterometer was successfully used to derive global soil moisture information at a spatial resolution of 50 km with weekly to decadal temporal resolution. The quality of the soil moisture products have been assessed by independent experts in several pilot projects funded by the European Space Agency. There is evidence to believe that both missions will provide a flow of
The bibliography contains citations concerning the use of remote sensors to aid in the monitoring of air and water pollution. Citations address the use of lasers, optical radar systems, aerial photography, and satellite observations. (Contains 50-250 citations and includes a subject term index and title list.) (Copyright NERAC, Inc. 1995)
Trelogan, Jessica; Crawford, Melba; Carter, Joseph
In 1998 the University of Texas Institute of Classical Archaeology, in collaboration with the University of Texas Center for Space Research and the National Preserve of Tauric Chersonesos (Ukraine), began a collaborative project, funded by NASA's Solid Earth and Natural Hazards program, to investigate the use of remotely sensed data for the study and protection of the ancient a cultural territory, or chora, of Chersonesos in Crimea, Ukraine.
Deepak R. Mishra; Gould, Richard W.
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...
Pervez, M. S.; Budde, M. E.; Rowland, J.
We extract percent of basin snow covered areas above 2500m elevation from Moderate Resolution Imaging Spectroradiometer (MODIS) 500-meter 8-day snow cover composites to monitor accumulation and depletion of snow in the basin. While the accumulation and depletion of snow cover extent provides an indication of the temporal progression of the snow pack, it does not provide insight into available water for irrigation. Therefore, we use snow model results from the National Operational Hydrologic Remote Sensing Center to quantify snow water equivalent and volume of water available within the snowpack for irrigation. In an effort to understand how water availability, along with its inter-annual variability, relates to the food security of the country, we develop a simple, effective, and easy-to-implement model to identify irrigated areas across the country on both annual and mid-season basis. The model is based on applying thresholds to peak growing season vegetation indices—derived from 250-meter MODIS images—in a decision-tree classifier to separate irrigated crops from non-irrigated vegetation. The spatial distribution and areal estimates of irrigated areas from these maps compare well with irrigated areas classified from multiple snap shots of the landscape from Landsat 5 optical and thermal images over selected locations. We observed that the extents of irrigated areas varied depending on the availability of snowmelt and can be between 1.35 million hectares in a year with significant water deficit and 2.4 million hectares in a year with significant water surplus. The changes in the amount of available water generally can contribute up to a 30% change in irrigated areas. We also observed that the strong correlation between inter-annual variability of irrigated areas and the variability in the country's cereal production could be utilized to predict an annual estimate of cereal production, providing early indication of food security scenarios for the country.
Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt
Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
Lessel, J.; Ceccato, P.
Agriculture is a vital resource in the country of Uruguay. Here we propose new methods using remotely sensed data for assisting ranchers, land managers, and policy makers in the country to better manage their crops. Firstly, we created a drought severity index based on the climatological anomalies of land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), precipitation data from the Tropical Rainfall Monitoring Mission (TRMM), and normalized difference water index (NDWI) data also using MODIS. The use of the climatological anomalies on the variables has improved the ability of the index to correlate with known drought indices versus previously published indices, which had not used them. We applied various coefficient schemes and vegetation indices in order to choose the model which best correlated with the drought indices across 10 sites throughout Uruguay's rangelands. The model was tested over summer months from 2009-2013. In years where drought had indeed been a problem in the country (such as 2009) the model showed intense signals of drought. Secondly, we used Landsat images to identify winter and summer crops in Uruguay. We first classified them using ENVI and then used the classifications in an ArcMap model to identify specific crop areas. We first created a polygon of the classifications for soils and vegetation for each month (omitting cloud covered images). We then used the crop growing cycle to identify the times during the year for which specific polygons should be soil and which should be vegetation. By intersecting the soil polygons with the vegetation polygons during their respective time periods during the crop growing cycle we were able to create an accurately identify crops. When compared to a shapefile of proposed crops for the year the model obtained a kappa value of 0.60 with a probability of detection of 0.79 and a false alarm ratio of 0.31 for the south-western study area over the 2013-2014 summer.
Full Text Available This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1 the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2 the installation/innovation of the drainage system did help to control salinity; and (3 a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.
Webley, P. W.; Dehn, J.
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.
Thi Van Le, Khoa; Minkman, Ellen; Nguyen Thi Phuong, Thuy; Rutten, Martine; Bastiaanssen, Wim
Remote sensing and citizen science can be utilized to fulfill the gap of conventional monitoring methods. However, how to engage these techniques, principally taking advantage of local capacities and of globally accessible data for satisfying the continuous data requirements and uncertainties are exciting challenges. Previous studies in Vietnam showed that official documents regulated towards responding the vital need of upgrading national water monitoring infrastructures do not put the huge potentials of free satellite images and crowd-based data collection into account, this factor also limits publications related to these techniques. In this research, a new water monitoring approach will be developed friendly with areas suffering poor quality monitoring works. Particularly, algorithms respecting to the relationship between temperature, total suspended sediment (TSS), chlorophyll and information collected by sensors onboard Landsat-8 and Sentinel-2 MSI satellites are built in the study area in Northern Vietnam; additionally, undergraduate student volunteers were sent to the sites with all the measurement activities are designed to coincide with the time when the study area captured by the satellites to compare the results. While conventional techniques are proving their irreplaceable role in the water monitoring network, the utilization of remote sensing techniques and citizen science in this study will demonstrate highly supportive values, saving monitoring costs and time; advantaging local human resources to science; providing an inclusive assessment of water quality changes along with land-use change in the study area, these approaches are excellent alternatives to meet the demand of real-time, continuous data nationwide.
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...
comprehensively the fluctuation of large water bodies based entirely on remote sensing data.
Butler, James J.; Johnson, B. Carol; Barnes, Robert A.
The use of remote sensing instruments on orbiting satellite platforms in the study of Earth Science and environmental monitoring was officially inaugurated with the April 1, 1960 launch of the Television Infrared Observation Satellite (TIROS) . The first TIROS accommodated two television cameras and operated for only 78 days. However, the TIROS program, in providing in excess of 22,000 pictures of the Earth, achieved its primary goal of providing Earth images from a satellite platform to aid in identifying and monitoring meteorological processes. This marked the beginning of what is now over four decades of Earth observations from satellite platforms. reflected and emitted radiation from the Earth using instruments on satellite platforms. These measurements are input to climate models, and the model results are analyzed in an effort to detect short and long-term changes and trends in the Earth's climate and environment, to identify the cause of those changes, and to predict or influence future changes. Examples of short-term climate change events include the periodic appearance of the El Nino-Southern Oscillation (ENSO) in the tropical Pacific Ocean  and the spectacular eruption of Mount Pinatubo on the Philippine island of Luzon in 1991. Examples of long term climate change events, which are more subtle to detect, include the destruction of coral reefs, the disappearance of glaciers, and global warming. Climatic variability can be both large and small scale and can be caused by natural or anthropogenic processes. The periodic El Nino event is an example of a natural process which induces significant climatic variability over a wide range of the Earth. A classic example of a large scale anthropogenic influence on climate is the well-documented rapid increase of atmospheric carbon dioxide occurring since the beginning of the Industrial Revolution . An example of the study of a small-scale anthropogenic influence in climate variability is the Atlanta Land
Kilpatrick, Adam D; Lewis, Megan M; Ostendorf, Bertram
A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural
Adam D Kilpatrick
Full Text Available A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2 area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction and maintenance of full 100% stocking regime (Full Stocking Maintained (P = 0.00000132. While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling
Campbell, James B
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
Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea
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
Katsuhama, N.; Ikeda, K.; Imai, M.; Watanabe, K.; Marpaung, F.; Yoshii, T.; Naruse, N.; Takahashi, Y.
Since 2008, coffee leaf rust fungus (Hemileia vastatrix) has expanded its infection in Latin America, and early trimming and burning infected trees have been only effective countermeasures to prevent spreading infection. Although some researchers reported a case about the monitoring of coffee leaf rust using satellite remote sensing in 1970s, the spatial resolution was unsatisfied, and therefore, further technological development has been required. The purpose of this research is to develop effective method of discovering coffee leaf rust infected areas using satellite remote sensing. Annual changes of vegetation indices, i.e. Normalized Difference Vegetation Index (NDVI) and Modified Structure Insensitive Pigment Index (MSIPI), around Cuchumatanes Mountains, Republic of Guatemala, were analyzed by Landsat 7 images. Study fields in the research were limited by the coffee farm areas based on a previous paper about on site surveys in different damage areas. As the result of the analysis, the annual change of NDVI at the coffee farm areas with damages tended to be lower than those without damages. Moreover, the decline of NDVI appear from 2008 before the damage was reported. On the other hand, the change of MSIPI had no significant difference. NDVI and MSIPI are mainly related to the amount of chlorophyll and carotenoid in the leaves respectively. This means that the infected coffee leaves turned yellow without defoliation. This situation well matches the symptom of coffee leaf rust. The research concluded that the property of infected leaves turning yellow is effective to monitoring of infection areas by satellite remote sensing.
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.
Li, Xiuhong; Cheng, Xiao; Yang, Rongjin; Liu, Qiang; Qiu, Yubao; Zhang, Jialin; Cai, Erli; Zhao, Long
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.
Chen, Chuqun; Shi, Ping; Mao, Qingwen
This article introduces a practical method to investigate thermal pollution in coastal water from satellite data. The intensity and distribution areas of thermal pollution by the heated effluent discharge from the nuclear power plant on Daya Bay, southern China were investigated by using Landsat-5 Thematic Mapper (TM) thermal band data from 1994 to 2001. A local algorithm was developed, based on sea-truth data of water surface temperature measured when the satellite passed over the study area. The local algorithm was then applied to estimate water temperature from TM data. It shows that the remote sensing technique provides an effective means to quantitatively monitor the intensity of thermal pollution and to retrieve a very detailed distribution pattern of thermal pollution in coastal waters. The remotely-sensed results of the thermal pollution can be used for environmental management of coastal waters.
Pettry, D. E.; Powell, N. L.; Newhouse, M. E.
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.
Deepak R. Mishra; Eurico J. D’Sa; Sachidananda Mishra
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.
Full Text Available This research is an application of remote sensing technology for monitoring and evaluation of watershed management, which was conducted is Solo Watershed, Central and East Java. The research objectives were 1 to investigate the capability of photomorphic analysis of Landsat Thematic Mapper (TM and Enhanced Themmatic Mapper (ETM + imagery as the basic for analyzes of landforms, landuse, and morphometry of the land surface; 2 to calculate the overland flow – peak discharge and erosion – sediment yield as indicators of land degradation of the area; 3 to use the indicators as set of instrument for monitoring and evaluation of watershed management. In this study, visual interpretation by means of on-screen digilization of the digital imagery was carried out in order to identify and to delineate land parameters using photomorphic approach. Based on the photomorphic analysis, several image – based parameters such as relief topography, physical soil characteristic, litho – stratigraphy, and vegetation cover were integrated with other themati maps in a geographic information system (GIS environment. Estimation of overland flow (C based on Cook methods (1942 and calculation of peak disccharge (Qmax based on rational method (Qmax = C. I. A were applied. Meanwhile, estimation of surface erosion was carried out using Universal Soil Loss Equation (USLE, A = R. K. L. S. CP. The sediment yield (Sy was estimated using seddiment delivery ratio ( SDR based on the following formula: Sy = [A + (25% x A] x SDR. Both pairs of C – Qmax and A – Sy, were utilized as the basis for monitoring and evaluation of the watershed. The combination of C – Qmax and A – Sy were also used as the basis for selection of stream gauge setting / AWLR within particular sub – catchment. It was found that the photomorphic analysis is only color/tone, slope aspects, pattern, and texture, unit boundaries between volcanic – origin landscape (Wilis volcanic complex and folded
Nansen, Christian; Elliott, Norman
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.
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...
Brown, Gareth [Sgurr Energy (Canada)
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.
Carroll, Mark L.; Brown, Molly E.; Elders, Akiko; Johnson, Kiersten
Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.
Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco
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.
Champollion, N; Benveniste, J; Chen, J
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...
Quinteros Casaverde, N. L.; McDonald, K.
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.
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
Akbar, M. S.; Sarker, M. H.; Sattar, M. A.; Sarwar, G. M.; Rahman, S. M. M.; Rahman, M. M.; Khan, Z. U.
Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp) cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.
Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Mohd. Saleh, N.
Total suspended solid (TSS) is a major factor affecting water quality in aquatic ecosystem. An investigation has been conducted to test the feasibility of using SPOT 5 data for estimating TSS in the coastal waters of Penang Island, Malaysia. Atmospheric correction of the satellite measurements is critical for aquatic remote sensing. Atmospheric correction of the remotely sensed image was performed using the ENVI FLAASH. Water samples were collected simultaneously with the satellite image acquisition and later analyzed in the laboratory. The digital numbers for each band corresponding to the sea-truth locations were extracted and then converted into reflectance values. The variables of the reflectance were used for calibration of the water quality algorithm. Regression technique was employed to calibrate the algorithm using the SPOT multispectral signals. An algorithm was developed based on the reflectance model, which is a function of the inherent optical properties of water that can be related to the concentration of its constituents. Spatial distribution map of the water quality parameter was produced using the calibrated algorithm. The efficiency of the present algorithm, in comparison to other forms of algorithm, was also investigated. Finally, the TSS map was generated using the proposed algorithm.
Remote sensing technology has great potential for mapping weed distributions. Fine-scale weed distribution maps can provide means to evaluate the success of weed control methods, to guide selection of future control methods, and to examine factors that influence the creation and persistence of monotypic weed patches. Here I examined the effectiveness of different classification approaches in detecting dense monotypic patches of the late-phenology weeds Taeniatherum caput-medusae (medusahead) and Aegilops triuncialis (barbed goatgrass), among cool-season forage grasses (Bromus spp. and Avena spp.) across multiple years in semi-arid rangelands in northern California (USA). I found that color infrared photographs acquired at two key phenological periods produced more accurate classifications than those based on one image alone, and that inclusion of training sites did not improve the overall accuracy of a classification. I also examined the association of remnant litter with transitions in species dominance in medusahead, goatgrass or forage patches. Persistence of goatgrass-dominated patches was correlated with the amount of remnant litter present, but surprisingly that of medusahead was not, suggesting a potential need for different strategies in control of these two noxious species. Overall, this study shows that remote sensing can be used to create weed distribution maps of phenologically distinct species, and help us further understand community response to invasion and evaluate the effectiveness of management treatments.
Direk, S.; Seker, D. Z.; Musaoglu, N.; Gazioglu, C.
great flexibility for the display and visualization of data to a wider audience. Today GIS, plays a key role in monitoring and management procedures and re-shaping the environment. The capability of GIS in handling spatial data, presented new opportunities for adaptation of more cost-effective and efficient procedures. By using remote sensing and GIS, coastal zone could be monitored and managed more easily. The map/chart of interested coastal areas could be done more accurately and rapidly. Maps/charts of areas before and after flooding could be done by using satellites or areal images and the effect of damage could be analyzed in a short time.
Garb, Yaakov; Friedlander, Lonia
Electronic waste (e-waste) is one of today's fastest growing waste streams, and also one of the more problematic, as this end-of-life product contains precious metals mixed with and embedded in a variety of low value and potentially harmful plastic and other materials. This combination creates a powerful incentive for informal value chains that transport, extract from, and dispose of e-waste materials in far-ranging and unregulated ways, and especially in settings where regulation and livelihood alternatives are sparse, most notably in areas of India, China, and Africa. E-waste processing is known to release a variety of contaminants, such as heavy metals and persistent organic pollutants, including flame retardants, dioxins and furans. In several sites, where the livelihoods of entire communities are dependent on e-waste processing, the resulting contaminants have been demonstrated to enter the hydrological system and food chain and have serious health and ecological effects. In this paper we demonstrate for the first time the usefulness of multi-spectral remote sensing imagery to detect and monitor the release and possibly the dispersal of heavy metal contaminants released in e-waste processing. While similar techniques have been used for prospecting or for studying heavy metal contamination from mining and large industrial facilities, we suggest that these techniques are of particular value in detecting contamination from the more dispersed, shifting, and ad-hoc kinds of release typical of e-waste processing. Given the increased resolution and decreased price of multi-spectral imagery, such techniques may offer a remarkably cost-effective and rapidly responsive means of assessing and monitoring this kind of contamination. We will describe the geochemical and multi-spectral image-processing principles underlying our approach, and show how we have applied these to an area in which we have a detailed, multi-temporal, spatially referenced, and ground
Index (NDVI) average values in the adjacent uplands also decreased over thirty years and were correlated with the previous year's annual precipitation. Hence an increase in ET in the uplands did not appear to be responsible for the decrease in river flows in this study, leaving increased regional groundwater pumping as a feasible alternative explanation for decreased flows and deterioration of the riparian forest. The second research objective was to develop a new method of classification using very high-resolution aerial photo to map riparian vegetation at the species level in the Colorado River Ecosystem, Grand Canyon area, Arizona. Ground surveys have showed an obvious trend in which non-native saltcedar (Tamarix spp.) has replaced native vegetation over time. Our goal was to develop a quantitative mapping procedure to detect changes in vegetation as the ecosystem continues to respond to hydrological and climate changes. Vegetation mapping for the Colorado River Ecosystem needed an updated database map of the area covered by riparian vegetation and an indicator of species composition in the river corridor. The objective of this research was to generate a new riparian vegetation map at species level using a supervised image classification technique for the purpose of patch and landscape change detection. A new classification approach using multispectral images allowed us to successfully identify and map riparian species coverage the over whole Colorado River Ecosystem, Grand Canyon area. The new map was an improvement over the initial 2002 map since it reduced fragmentation from mixed riparian vegetation areas. The most dominant tree species in the study areas is saltcedar (Tamarix spp.). The overall accuracy is 93.48% and the kappa coefficient is 0.88. The reference initial inventory map was created using 2002 images to compare and detect changes through 2009. The third objective of my research focused on using multiplatform of remote sensing and ground calibration
Shen, Xin; Zhang, Jing; Yao, Huang
Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.
Lu, Anxin; Wang, Lihong; Chen, Xianzhang
A major monitoring area, a part of the middle reaches of Heihe basin, was selected. The Landsat TM data in summer of 1990 and 2000 were used with interpretation on the computer screen, classification and setting up environmental investigation database (1:100000) combined with DEM, land cover/land use, land type data and etc., according to the environmental classification system. Then towards to the main problems of environment, the spatial statistical analysis and dynamic comparisons were carried out using the database. The dynamic monitoring results of 1999 and 2000 show that the changing percentage with the area of 6 ground objects are as follows: land use and agriculture land use increased by 34.17% and 19.47% respectively, wet land and water-body also increased by 6.29% and 8.03% respectively; unused land increased by 1.73% and the biggest change is natural/semi-natural vegetation area, decreased by 42.78%, the main results above meat with the requirements of precise and practical conditions by the precise exam and spot check. With the combinations of using TM remote sensing data and rich un-remote sensing data, the investigations of ecology and environment and the dynamic monitoring would be carried out efficiently in the arid area. It is a dangerous signal of large area desertification if the area of natural/semi-natural vegetation is reduced continuously and obviously.
Greenberg, Jonathan Asher
Uncertainties in our understanding of the basic inputs and dynamics at work in the global carbon cycle severely restrict our ability to address why climate change is happening and how best to mitigate it. I focused on advances in regional and global climate change model inputs, addressing two major uncertainties: (1) what are the anthropogenic factors influencing deforestation and (2) what is the carbon load of an ecosystem? Analysis of anthropogenic factors leading to land use changes are presented in an evaluation of deforestation at the UNESCO Biosphere Reserve, Parque National Yasuni, located in the rainforest of eastern Ecuador, using multitemporal Landsat satellite imagery. Using survival analysis, I assessed current and future trends in deforestation rates and investigated the impact of spatial, cultural, and economic factors on deforestation. I found the annual rate of deforestation is currently only 0.11%, but is increasing with time, so that by 2063, 50% of the forest within 2 km of a major oil access road will be lost due to unhindered colonization and anthropogenic conversion. To improve accuracy in estimating landscape level carbon sequestration, I developed a new approach to generating regional aboveground biomass estimates for tree species of the Lake Tahoe Basin, California using hyperspatial (<1m2) remote sensing imagery. I demonstrate how, with accurate classification maps and allometric equations relating DBH or crown area to biomass, that crown parameters can be used to estimate regional biomass. I show that biomass estimated with fine-scale optical sensors does not saturate at high biomass levels as does coarse-scale optical and RADAR sensors. Finally, I address a technical problem to improve quantitative comparison of remote sensing datasets. I present a modification of the empirical line method for normalizing the radiance or reflectance scales of two images. Radiometric normalization of multitemporal remote sensing datasets is a critical
Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark
Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.
Langran, K. J.
Accurate estimates of soil erosion and its effects on soil productivity are essential in agricultural decision making and planning from the field scale to the national level. Erosion models have been primarily developed for designing erosion control systems, predicting sediment yield for reservoir design, predicting sediment transport, and simulating water quality. New models proposed are more comprehensive in that the necessary components (hydrology, erosion-sedimentation, nutrient cycling, tillage, etc.) are linked in a model appropriate for studying the erosion-productivity problem. Recent developments in remote sensing systems, such as Landsat Thematic Mapper, Shuttle Imaging Radar (SIR-B), etc., can contribute significantly to the future development and operational use of these models.
Kirschbaum, Dalia; Fukuoka, Hiroshi
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.
Kirschbaum, Dalia; Fukuoka, Hiroshi
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.
Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson; Ryan C. Hruska
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).
Schultz, J.; Czuchlewski, S.; Karl, R. [and others
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.
M. S. Akbar
Full Text Available Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.
Song, Xiaoyu; Li, Ting; Wang, Jihua; Gu, Xiaohe; Xu, Xingang
This work aims at quantifying the winter wheat growth spatial heterogeneity captured by hyperspectral airborne images. The field experiment was conducted in 2001 and 2002 and airborne hyperspectral remote-sensing data was acquired at noon on 11 April 2001 using an operational modular imaging spectrometer (OMIS). Totally 12 winter fields which covered by both dense and sparse winter wheat canopies were selected to analysis the winter wheat growth heterogeneity. The experimental semi-variograms for bands covered from invisible to mid-infrared were computed for each field then the theoretical models were be fitted with least squares algorithm for spherical model, exponential model. The optimization model was selected after evaluated by R-square. Three key terms in each model, the sill, the range, and nugget variance were then calculated from the models. The study results show that the sill, range and nugget for same field wheat were varied with the wavelength from blue to mid infrared bands. Although wheat growth in different fields showed different spatial heterogeneity, they all showed an obvious sill pattern. The minimum of mean range value was 7.52 m for mid-infrared bands while the maximum value was 91.71 m for visible bands. The minimum of mean sill value ranged from 1.46 for visible bands to 39.76 for NIR bands, the minimum of mean nugget value ranged from 0.06 for visible bands to5.45 for mid-infrared bands. This study indicate that remote sensing image is important for crop growth spatial heterogeneity study. But it is necessary to explore the effect of different wavelength of image data on crop growth semi-variogram estimation and find out which band data could be used to estimate crop semi-variogram reliably.
Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.
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.. The MODIS time series NDVI data are modeled by TIMESAT , 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
Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.
Sagebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change - adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush ( Artemisia spp.), percent big sagebrush ( Artemisia tridentata), percent Wyoming sagebrush ( Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.
Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.
agebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change – adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.
Zilberman, Arkadi; Ben Asher, Jiftah; Kopeika, Norman S.
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.
"… 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...
Hariz, Alex; Mehmood, Nasir; Voelcker, Nico
Chronic wounds, such as venous leg ulcers, can be monitored non-invasively by using modern sensing devices and wireless technologies. The development of such wireless diagnostic tools may improve chronic wound management by providing evidence on efficacy of treatments being provided. In this paper we present a low-power portable telemetric system for wound condition sensing and monitoring. The system aims at measuring and transmitting real-time information of wound-site temperature, sub-bandage pressure and moisture level from within the wound dressing. The system comprises commercially available non-invasive temperature, moisture, and pressure sensors, which are interfaced with a telemetry device on a flexible 0.15 mm thick printed circuit material, making up a lightweight biocompatible sensing device. The real-time data obtained is transmitted wirelessly to a portable receiver which displays the measured values. The performance of the whole telemetric sensing system is validated on a mannequin leg using commercial compression bandages and dressings. A number of trials on a healthy human volunteer are performed where treatment conditions were emulated using various compression bandage configurations. A reliable and repeatable performance of the system is achieved under compression bandage and with minimal discomfort to the volunteer. The system is capable of reporting instantaneous changes in bandage pressure, moisture level and local temperature at wound site with average measurement resolutions of 0.5 mmHg, 3.0 %RH, and 0.2 °C respectively. Effective range of data transmission is 4-5 m in an open environment.
Allison, Robert S.; Johnston, Joshua M.; Craig, Gregory; Jennings, Sion
For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. PMID:27548174
Robert S. Allison
Full Text Available For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites. Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context.
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.…
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.…
Zheng, Xiangyu; Gao, Zhiqiang; Ning, Jicai; Xu, Fuxiang; Liu, Chaoshun; Sun, Zhibin
In this paper, the green tide (Large green algae-Ulva prolifera) in the Yellow Sea in 2015 is monitored which is based on remote sensing and geographic information system technology, using GF-1 WFV data, combined with the virtual baseline floating algae height index (VB-FAH) and manual assisted interpretation method. The results show that GF-1 data with high spatial resolution can accurately monitoring the Yellow Sea Ulva prolifera disaster, the Ulva prolifera was first discovered in the eastern waters of Yancheng in May 12th, afterwards drifted from the south to the north and affected the neighboring waters of Shandong Peninsula. In early July, the Ulva prolifera began to enter into a recession, the coverage area began to decrease, by the end of August 6th, the Ulva prolifera all died.
Department of Transportation — The Remote Maintenance and Monitoring System (RMMS) is a collection of subsystems that includes telecommunication components, hardware, and software, which serve to...
Kayendeke, Ellen; French, Helen K.; Kansiime, Frank; Bamutaze, Yazidhi
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.
Global forests are experiencing a variety of stresses in response to climate change and human activities. The broad objective of this dissertation is to improve understanding of how temperate and boreal forests are changing by using remote sensing to develop new techniques for detecting change in forest ecosystems and to use these techniques to investigate patterns of change in North American forests. First, I developed and applied a temporal segmentation algorithm to an 11-year time series of MODIS data for a region in the Pacific Northwest of the USA. Through comparison with an existing forest disturbance map, I characterized how the severity and spatial scale of disturbances affect the ability of MODIS to detect these events. Results from these analyses showed that most disturbances occupying more than one-third of a MODIS pixel can be detected but that prior disturbance history and gridding artifacts complicate the signature of forest disturbance events in MODIS data. Second, I focused on boreal forests of Canada, where recent studies have used remote sensing to infer decreases in forest productivity. To investigate these trends, I collected 28 years of Landsat TM and ETM+ data for 11 sites spanning Canada's boreal forests. Using these data, I analyzed how sensor geometry and intra- and inter-sensor calibration influence detection of trends from Landsat time series. Results showed systematic patterns in Landsat time series that reflect sensor geometry and subtle issues related to inter-sensor calibration, including consistently higher red band reflectance values from TM data relative to ETM+ data. In the final chapter, I extended the analyses from my second chapter to explore patterns of change in Landsat time series at an expanded set of 46 sites. Trends in peak-summer values of vegetation indices from Landsat were summarized at the scale of MODIS pixels. Results showed that the magnitude and slope of observed trends reflect patterns in disturbance and land
Hamada, Yuki [Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division; Grippo, Mark A. [Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division; Smith, Karen P. [Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
In anticipation of increased utility-scale solar energy development over the next 20 to 50 years, federal agencies and other organizations have identified a need to develop comprehensive long-term monitoring programs specific to solar energy development. Increasingly, stakeholders are requesting that federal agencies, such as the U.S. Department of the Interior Bureau of Land Management (BLM), develop rigorous and comprehensive long-term monitoring programs. Argonne National Laboratory (Argonne) is assisting the BLM in developing an effective long-term monitoring plan as required by the BLM Solar Energy Program to study the environmental effects of solar energy development. The monitoring data can be used to protect land resources from harmful development practices while at the same time reducing restrictions on utility-scale solar energy development that are determined to be unnecessary. The development of a long-term monitoring plan that incorporates regional datasets, prioritizes requirements in the context of landscape-scale conditions and trends, and integrates cost-effective data collection methods (such as remote sensing technologies) will translate into lower monitoring costs and increased certainty for solar developers regarding requirements for developing projects on public lands. This outcome will support U.S. Department of Energy (DOE) Sunshot Program goals. For this reason, the DOE provided funding for the work presented in this report.
环境污染遥感监测技术具有监测范围广、速度快、成本低，且便于进行长期的动态监测等优点，是实现宏观、快速、连续、动态地监测环境污染的有效高新技术手段。介绍了应用于环境污染监测的可见光、反射红外遥感技术、热红外遥感技术、高光谱技术以及微波遥感监测技术，并着重阐述了遥感监测技术在水环境污染、大气环境污染中的应用。最后，指出了我国环境污染遥感监测技术存在的问题和发展趋势，建议尽快发展我国的环境污染遥感监测技术，以满足我国环境污染监测的需要。%Remote sensing technology is an effective way to continually， rapidly and dynamically monitor the large-scale environmental pollution since the technology possess the advantages of low-cost， regional and global， long-term monitoring， and of real-time or timely prediction. This paper summarizes the achievements of visible， reflected and thermal infrared， hyper-spectral and microwave remote sensing technology applied to environmental pollution monitoring. The applications of remote sensing technology to water and atmosphere environment pollution monitoring are illustrated， including water turbidity analysis， oil pollution， urban sewage， water-body thermal pollution and eutrophication. Finally， it is pointed out that the remote sensing technology of environment pollution monitoring exists much deficiency in China. And some suggestions on developing the technology are given as follows: (1) Utilizing remote sensing technology， it is necessitated to construct largescale real-time monitoring and predicting system of environment pollution accidents. (2) Developing new remote sensing sensors and improving their performances in pollution monitoring. (3) Developing quantitative remote sensing monitoring technology for environment pollutants. (4) Integrating environment pollution remote sensing monitoring
Copenhaver, K.; Glaser, J. A.; Fridgen, J.; Carroll, M.
During the 2004 and 2005 growing seasons, a study was conducted by the Environmental Protection Agency and United States Department of Agriculture's Agricultural Research Service at several sites across the Corn Belt to evaluate the use of the remotely sensed imagery for the detection of transgenic and European corn borer infested corn hybrids. A number of statistical and image analysis techniques were used to evaluate the imagery's ability to distinguish the transgenic corn hybrids from non-transgenic hybrids and delineate infested plots. Analysis techniques varied in complexity from simple band thresholds to wavelet transforms and neural networks. Accuracies greater than 90% were obtained using these methods. Accuracies typically improved with increasing algorithm complexity and were highest when comparing individual transgenic hybrids to multiple non-transgenic hybrids. Efforts in 2006 focused on the rapid production of infestation and transgenic delineation maps from the imagery using algorithms developed from the 2004 and 2005 plot level experiments. Throughout the season, the Institute for Technology Development delivered maps identifying potential infestation sites and transgenic/non- transgenic field delineations to the EPA in a pseudo-operational manner. Scouts visited locations identified and test for accurate delineation using assays and infestation measurements.
Baliarsingh, S K; Dwivedi, R M; Lotliker, Aneesh A; Sahu, K C; Kumar, T Srinivasa; Shenoi, S S C
An ecosystem disruptive bloom of red Noctiluca scintillans (hereafter Noctiluca) was observed in coastal waters of the north-western Bay of Bengal during April 2014. Based on the principle of phytoplankton group/species specific remote sensing reflectance (Rrs), a technique of detecting green Noctiluca and diatom was developed earlier using Rrs at 443, 488, and 531 nm of Moderate Imaging Spectroradiometer-Aqua (MODIS). This was appropriately modified to detect bloom of red Noctiluca in coastal waters of the Bay of Bengal. Additional Rrs data at longer wavelengths viz. 667 and 678 nm were included in the existing algorithm, and the spectral shapes were accounted to detect the bloom of red Noctiluca. The classification scheme discriminates red Noctiluca from the green form of the same species and diatom. Phytoplankton group/species products were generated using the modified approach and validated with the reported events of red and green Noctiluca blooms in the Indian coastal waters. The present study also highlights two specific results based on MODIS retrieved time-series phytoplankton group/species image analysis: first, the observation of coexistence of diatom, red, and green Noctiluca in coastal waters of the north-western Bay of Bengal, and the second, phytoplankton community shift resulting in red/green Noctiluca proliferation following diatom.
Samseemoung, Grianggai; Jayasuriya, Hemantha P. W.; Soni, Peeyush
Timely detection of pest or disease infections is extremely important for controlling the spread of disease and preventing crop productivity losses. A specifically designed radio-controlled helicopter mounted low altitude remote sensing (LARS) platform can offer near-real-time results upon user demand. The acquired LARS images were processed to estimate vegetative-indices and thereby detecting upper stem rot (Phellinus Noxius) disease in both young and mature oil palm plants. The indices helped discriminate healthy and infested plants by visualization, analysis and presentation of digital imagery software, which were validated with ground truth data. Good correlations and clear data clusters were obtained in characteristic plots of normalized difference vegetation index (NDVI)LARS and green normalized difference vegetation indexLARS against NDVISpectro and chlorophyll content, by which infested plants were discriminated from healthy plants in both young and mature crops. The chlorophyll content values (μmol m-2) showed notable differences among clusters for healthy young (972 to 1100), for infested young (253 to 400), for healthy mature (1210 to 1500), and for infested mature (440 to 550) oil palm. The correlation coefficients (R2) were in a reasonably acceptable range (0.62 to 0.88). The vegetation indices based on LARS images, provided satisfactory results when compared to other approaches. The developed technology showed promising scope for medium and large plantations.
Alex Okiemute Onojeghuo
Full Text Available Despite their importance, available information on the dynamics of forest protected areas and their management in the Niger delta are insufficient. We present results showing the distribution and structure of forest landscapes across protected areas in two states (Cross River and Delta within the Niger Delta using multi-temporal remote sensing. Satellite images were classified and validated using ground data, existing maps, Google Earth, and historic aerial photographs over 1986, 2000 and 2014. The total area of forest landscape for 1986, 2000 and 2014 across the identified protected areas were 535,671 ha, 494,009 ha and 469,684 ha (Cross River and 74,631 ha, 68,470 ha and 58,824 ha (Delta respectively. The study showed annual deforestation rates for protected areas across both states from 1986 to 2000 were 0.8%. However, the overall annual deforestation rate between 2000 and 2014 was higher in Delta (1.9% compared to Cross River (0.7%. This study shows accelerated levels of forest fragmentation across protected areas in both states as a side effect of the prevalence of agricultural practices and unsupervised urbanisation. The results show the need for government intervention and policy implementation, in addition to efforts by local communities and conservation organisations in protected area management across ecologically fragile areas of Nigeria.
Deepak R. Mishra
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.
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
Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.
The increase of urban atmospheric pollution due to particulate matters (PM) in different fraction sizes affects seriously not only human health and environment, but also city climate directly and indirectly. In the last decades, with the economic development and the increased emissions from industrial, traffic and domestic pollutants, the urban atmospheric pollution with remarkable high PM2.5 (particulate matters with aerodynamic diameter less than 2.5 μm) and PM10 (particulate matters with aerodynamic diameter less than 10 μm) concentration levels became serious in the metropolitan area of Bucharest in Romania. Both active as well as satellite remote sensing are key applications in global change science and urban climatology. The aerosol parameters can be measured directly in situ or derived from satellite remote sensing observations. All these methods are important and complementary. The current study presents a spatiotemporal analysis of the aerosol concentrations in relation with climate parameters in two size fractions (PM10 and PM2.5) in Bucharest metropolitan area. Daily average particle matters concentrations PM10 and PM2.5 for Bucharest metropolitan area have been provided by 8 monitoring stations belonging to air pollution network of Environmental Protection Agency. The C005 (version 5.1) Level 2 and Level 3 Terra and Aqua MODIS AOD550 time-series satellite data for period 01/01/2011- 31/12/2012 have been also used. Meteorological variables (air temperature, relative humidity, sea level atmospheric pressure) have been provided by in-situ measurements. Both in-situ monitoring data as well as MODIS Terra/Aqua time-series satellite data for 2011-2012 period provided useful tools for particle matter PM2.5 and PM10 monitoring.
ZHANG Liang; ZHANG bing; CHEN Zhengchao; ZHENG Lanfen; TONG Qingxi
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.
Deepak R. Mishra
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.
Zhu, Li; Zhao, Li-Min; Wang, Qiao; Zhang, Ai-Ling; Wu, Chuan-Qing; Li, Jia-Guo; Shi, Ji-Xiang
Thermal plume from coastal nuclear power plant is a small-scale human activity, mornitoring of which requires high-frequency and high-spatial remote sensing data. The infrared scanner (IRS), on board of HJ-1B, has an infrared channel IRS4 with 300 m and 4-days as its spatial and temporal resolution. Remote sensing data aquired using IRS4 is an available source for mornitoring thermal plume. Retrieval pattern for coastal sea surface temperature (SST) was built to monitor the thermal plume from nuclear power plant. The research area is located near Guangdong Daya Bay Nuclear Power Station (GNPS), where synchronized validations were also implemented. The National Centers for Environmental Prediction (NCEP) data was interpolated spatially and temporally. The interpolated data as well as surface weather conditions were subsequently employed into radiative transfer model for the atmospheric correction of IRS4 thermal image. A look-up-table (LUT) was built for the inversion between IRS4 channel radiance and radiometric temperature, and a fitted function was also built from the LUT data for the same purpose. The SST was finally retrieved based on those preprocessing procedures mentioned above. The bulk temperature (BT) of 84 samples distributed near GNPS was shipboard collected synchronically using salinity-temperature-deepness (CTD) instruments. The discrete sample data was surface interpolated and compared with the satellite retrieved SST. Results show that the average BT over the study area is 0.47 degrees C higher than the retrieved skin temperature (ST). For areas far away from outfall, the ST is higher than BT, with differences less than 1.0 degrees C. The main driving force for temperature variations in these regions is solar radiation. For areas near outfall, on the contrary, the retrieved ST is lower than BT, and greater differences between the two (meaning > 1.0 degrees C) happen when it gets closer to the outfall. Unlike the former case, the convective heat
González-Dugo, Maria P.; Carpintero, Elisabet; Andreu, Ana
A holm oak savanna, known as dehesa in Spain and montado in Portugal, is the largest agroforest ecosystem in Europe, covering about 3 million hectares in the Iberian Peninsula and Greece (Papanastasis et al., 2004). It is considered an example of sustainable land use, supporting a large number of species and diversity of habitats and for its importance in rural development and economy (Plieninger et al., 2001). It is a combination between an agricultural and a naturally vegetated ecosystem, consisting of widely-spaced oak trees (mostly Quercus Ilex and Quercus suber) combined with a sub-canopy composed by crops, annual grassland and/or shrubs. It has a Mediterranean climate with severe periodic droughts. In the last decades, this system is being exposed to multiple threats derived from socio-economic changes and intensive agricultural use, which have caused environmental degradation, including tree decline, changes in soil properties and hydrological processes, and an increase of soil erosion (Coelho et al., 2004). Soil water dynamics plays a central role in the current decline and reduction of forested areas that jeopardizes the preservation of the system. In this work, a series of remotely sensed images since 1990 to present was used to evaluate the effect of several drought events occurred in the study area (1995, 2009, 2010/2011) on the tree density and water status. Data from satellites Landsat and field measurements have been combined in a spectral mixture model to assess separately the evolution of tree, dry grass and bare soil ground coverage. Only summer images have been used to avoid the influence of the green herbaceous layer on the analysis. Thermal data from the same sensors and meteorological information are integrated in a two source surface energy balance model to compute the Evaporative Stress Index (ESI) and evaluate the vegetation water status. The results have provided insights about the severity of each event and the spatial distribution of
Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike
Soil moisture content (SMC) is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of SMC in mountain catchments is an essential step towards improving quantitative predictions of catchment hydrological processes and related ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on SMC and the influence of SMC patterns on runoff generation processes have been extensively investigated (Vereecken et al., 2014). However, in mountain areas, obtaining reliable SMC estimations is still challenging, because of the high variability in topography, soil and vegetation properties. In the last few years, there has been an increasing interest in the estimation of surface SMC at local scales. On the one hand, low cost wireless sensor networks provide high-resolution SMC time series. On the other hand, active remote sensing microwave techniques, such as Synthetic Aperture Radars (SARs), show promising results (Bertoldi et al. 2014). As these data provide continuous coverage of large spatial extents with high spatial resolution (10-20 m), they are particularly in demand for mountain areas. However, there are still limitations related to the fact that the SAR signal can penetrate only a few centimeters in the soil. Moreover, the signal is strongly influenced by vegetation, surface roughness and topography. In this contribution, we analyse the spatial and temporal dynamics of surface and root-zone SMC (2.5 - 5 - 25 cm depth) of alpine meadows and pastures in the Long Term Ecological Research (LTER) Area Mazia Valley (South Tyrol - Italy) with different techniques: (I) a network of 18 stations; (II) field campaigns with mobile ground sensors; (III) 20-m resolution RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model (Rigon et al
Kaipov, I. V.
Anthropogenic and natural factors have increased the power of wildfires in massive Siberian woodlands. As a consequence, the expansion of burned areas and increase in the duration of the forest fire season have led to the release of significant amounts of gases and aerosols. Therefore, it is important to understand the impact of wildland fires on air quality, atmospheric composition, climate and accurately describe the distribution of combustion products in time and space. The most effective research tool is the regional hydrodynamic model of the atmosphere, coupled with the model of pollutants transport and chemical interaction. Taking into account the meteorological parameters and processes of chemical interaction of impurities, complex use of remote sensing techniques for monitoring massive forest fires and mathematical modeling of long-range transport of pollutants in the atmosphere, allow to evaluate spatial and temporal scale of the phenomenon and calculate the quantitative characteristics of pollutants depending on the height and distance of migration.
Zhu, Li; Yin, Shoujing; Wu, Chuanqing; Ma, Wandong; Hou, Haiqian; Xu, Jing
In this paper, the method of monitoring coastal areas affected by thermal discharge of nuclear plant by using remote sensing techniques was introduced. The proposed approach was demonstrated in Daya Bay nuclear plant based on HJ-B IRS data. A single channel water temperature inversion algorithm was detailed, considering the satellite zenith angle and water vapor. Moreover the reference background temperature was obtained using the average environmental temperature method. In the case study of Daya Bay nuclear plant, the spatial distribution of thermal pollution was analyzed by taking into account the influence of tidal, wind and so on. According to the findings of this study, the speed and direction of the ebb tide, is not conducive to the diffusion of thermal discharge of DNNP. The vertically thermal diffusion was limited by the shallow water depth near the outlet.
Full Text Available In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.
Roffer, M. A.; Gawlikowski, G.; Muller-Karger, F.; Schaudt, K.; Upton, M.; Wall, C.; Westhaver, D.
Thermal infrared (TIR) and ocean color remote sensing data (1.1 - 4.0 km) are being used as the primary data source in decision making systems for fisheries management, commercial and recreational fishing advisory services, fisheries research, environmental monitoring, oil and gas operations, and ship routing. Experience over the last 30 years suggests that while ocean color and other remote sensing data (e.g. altimetry) are important data sources, TIR presently yields the most useful data for studying ocean surface circulation synoptically on a daily basis. This is due primarily to the greater temporal resolution, but also due to one's better understanding of the dynamics of sea surface temperature compared with variations in ocean color and the spatial limitations of altimeter data. Information derived from commercial operations and research is being used to improve the operational efficiency of fishing vessels (e.g. reduce search time and increase catch rate) and to improve our understanding of the variations in catch distribution and rate needed to properly manage fisheries. This information is also being used by the oil and gas industry to minimize transit time and thus, save costs (e.g., tug charter, insurance), to increase production and revenue up to 500K dollars a day. The data are also be used to reduce the risk of equipment loss, loss of time and revenue to sudden and unexpected currents such as eddies. Sequential image analysis integrating TIR and ocean color provided near-real time, synoptic visualization of the rapid and wide dispersal of coastal waters from the northern Gulf of Mexico following Hurricanes Katrina and Rita in September 2005. The satellite data and analysis techniques have also been used to monitor the effects and movement of other potential environmentally damaging substances, such as dispersing nutrient enriched waste water offshore. A review of our experience in several commercial applications and research efforts will reinforce the
Hotchkiss, Rose; Dickerson, Daniel
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…
Hotchkiss, Rose; Dickerson, Daniel
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…
Coates, Austin Reece
A drought persisting since the winter of 2011-2012 has resulted in severe impacts on shrublands and forests in southern California, USA. Effects of drought on vegetation include leaf wilting, leaf abscission, and potential plant mortality. These impacts vary across plant species, depending on differences in species' adaptations to drought, rooting depth, and edaphic factors. During 2013 and 2014, Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data were acquired seasonally over the Santa Ynez Mountains and Santa Ynez Valley north of Santa Barbara, California. To determine the impacts of drought on individual plant species, spectral mixture analysis was used to model a relative green vegetation fraction (RGVF) for each image date in 2013 and 2014. A July 2011 AVIRIS image acquired during the last nondrought year was used to determine a reference green vegetation (GV) endmember for each pixel. For each image date in 2013 and 2014, a three-endmember model using the 2011 pixel spectrum as GV, a lab nonphotosynthetic vegetation (NPV) spectrum, and a photometric shade spectrum was applied. The resulting RGVF provided a change in green vegetation cover relative to 2011. Reference polygons collected for 14 plant species and land cover classes were used to extract the RGVF values from each date. The deeply rooted tree species and tree species found in mesic areas appeared to be the least affected by the drought, whereas the evergreen chaparral showed the most extreme signs of distress. Coastal sage scrub had large seasonal variability; however, each year, it returned to an RGVF value only slightly below the previous year. By binning all the RGVF values together, a general decreasing trend was observed from the spring of 2013 to the fall of 2014. This study intends to lay the groundwork for future research in the area of multitemporal, hyperspectral remote sensing. With proposed plans for a hyperspectral sensor in space (HyspIRI), this type of research will prove to
Aquatic vegetation plays an important role in the ecological interactions and processes within a water body. However, the presence of the invasive exotic aquatic plant species, waterhyacinth [Eichhornia crassipes (Mart.) Solms], negatively affects those interactions as well as interfering with water use for recreation and navigation. An implemented management plan for waterhyacinth control relies on the use of herbicides. Efficacy is commonly assessed using visual injury and control ratings as well as estimating biomass. The problem is that those approaches are labor intensive only assessing single points throughout the entire water body. Therefore, technology like remote sensing, which is the focus of this research, is recommended as an additional tool to assess implemented management plans. Studies were conducted in a mesocosm research facility to evaluate the relationship between simulated spectral bands 3, 4, 5, and 7 Landsat 5 TM and waterhyacinth treated with the herbicides imazapyr and glyphosate. Results indicate that injury is better detected and predicted with band 4 and that relationship is negative when either herbicide was used. However, prediction is better when plants have developed sufficient injury to influence the spectral response of band 4. In the second study, the biomass of waterhyacinth was estimated using the Normalized Difference Vegetation Index (NDVI) using simulated data from Landsat 5 TM. This study was conducted over natural populations of waterhyacinth in Lakes Columbus and Aberdeen, MS over two growing seasons. Results indicate that the use of NDVI alone is a weak predictor of biomass; however, its combination with morphometric parameters like leaf area index enhanced predictive capabilities. In order to assess field herbicide treatments for waterhyacinth control and its consequent impact on native aquatic vegetation, lake-wide surveys were performed in Lake Columbus, MS using a point-intercept method. The herbicide assessed was 2
Karan, Shivesh Kishore; Samadder, Sukha Ranjan; Maiti, Subodh Kumar
The objective of the present study is to monitor reclamation activity in mining areas. Monitoring of these reclaimed sites in the vicinity of mining areas and on closed Over Burden (OB) dumps is critical for improving the overall environmental condition, especially in developing countries where area around the mines are densely populated. The present study evaluated the reclamation success in the Block II area of Jharia coal field, India, using Landsat satellite images for the years 2000 and 2015. Four image processing methods (support vector machine, ratio vegetation index, enhanced vegetation index, and normalized difference vegetation index) were used to quantify the change in vegetation cover between the years 2000 and 2015. The study also evaluated the relationship between vegetation health and moisture content of the study area using remote sensing techniques. Statistical linear regression analysis revealed that Normalized Difference Vegetation Index (NDVI) coupled with Normalized Difference Moisture Index (NDMI) is the best method for vegetation monitoring in the study area when compared to other indices. A strong linear relationship (r(2) > 0.86) was found between NDVI and NDMI. An increase of 21% from 213.88 ha in 2000 to 258.9 ha in 2015 was observed in the vegetation cover of the reclaimed sites for an open cast mine, indicating satisfactory reclamation activity. NDVI results indicated that vegetation health also improved over the years. Copyright © 2016 Elsevier Ltd. All rights reserved.
张渊智; 聂跃平; 蔺启忠; 荆林海; 张兵
主要讨论了应用多种传感器遥感技术进行表面水质监测研究的有效性。首先论述了纯水和不同水质的波谱特性，然后以芬兰海湾和芬兰南部湖泊为应用实例，进行多种遥感数据和主要水质参数之间的相关性分析，从而确定不同波谱段是否可以有效地监测表面水质的变化情况。本研究为新一代传感器的设计提供水质监测的重要参数，进一步的试验研究仍在进行之中。%This paper describes the possibility of surface water quality monitoring using remote sensing technolo gy and the spectral signatures of pure water and other types of water quality. Using airborne and spacebornedata (TM and ERS-2) analysed with in situ measurements of ground truth points for water quality parameters， some major factors of surface water quality can be derived from remote sensing data by case studies. Concurrent in situ surface water quality measurments， Landsat TM data and ERS-2 SAR data were obtained in the selected locations in August1997. In situ data included measurements of chlorophyll-a， total dissolved organic carbon and turbidity， Secchi disk depth， color index， estimated wave height， salinity and surface temperature. The Landsat TM and ERS-2 SAR data from locations of water samples were extracted and the digital data were examined in their raw states as well as numerous transformations. Significant correlations were observed between digital numbers and surface water quality parameters. The results indicate that it may be possible to derive surface water quality parameters using remote sensing data in our case study area. However， the technique still needs to be refined to detect differences within the range of water quality which is typically found in the area under study.
El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.
The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary
Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf
Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was
Boschetti, Mirco; Holectz, Francesco; Manfron, Giacinto; Collivignarelli, Francesco; Nelson, Andrew
Updated information on crop typology and status are strongly required to support suitable action to better manage agriculture production and reduce food insecurity. In this field, remote sensing has been demonstrated to be a suitable tool to monitor crop condition however rarely the tested system became really operative. The ones today available, such as the European Commission MARS, are mainly based on the analysis of NDVI time series and required ancillary external information like crop mask to interpret the seasonal signal. This condition is not always guarantied worldwide reducing the potentiality of the remote sensing monitoring. Moreover in tropical countries cloud contamination strongly reduce the possibility of using optical remote sensing data for crop monitoring. In this framework we focused our analysis on the rice production monitoring in Asian tropical area. Rice is in fact the staple food for half of the world population (FAO 2004), in Asia almost 90% of the world's rice is produced and consumed and Rice and poverty often coincide. In this contest the production of reliable rice production information is of extreme interest. We tried to address two important issue in terms of required geospatial information for crop monitoring: rice crop detection (rice map) and seasonal dynamics analysis (phenology). We use both SAR and Optical data in order to exploit the potential complementarity of this system. Multi-temporal ASAR Wide Swath data are in fact the best option to deal with cloud contamination. SAR can easily penetrate the clouds providing information on the surface target. Temporal analysis of archive ASAR data allowed to derived accurate map, at 100m spatial resolution, of permanent rice cultivated areas. On the other and high frequency revisiting optical data, in this case MODIS, have been used to extract seasonal information for the year under analysis. MOD09A1 Surface Reflectance 8-Day L3 Global 500m have been exploited to derive time series of
夏传福; 李静; 柳钦火
We reviewed and analyzed the monitoring methods, the validation methods and the error sources of remote sensing phenology. First, the monitoring methods, including the threshold-based, delayed-moving-average and curve-fitting methods, etc., were introduced and inter-compared. Second, the primary validation methods were analyzed, including sensor-network-monitoring, simulation model, etc. The error sources of remote sensing phenology products were further analyzed from the monitoring methods and the remote sensing data. At last, we made prospects for the future development of vegetation phenology monitoring by remote sensing: (1) To develop the new monitoring methodology by coupling the physiological and ecological respond mechanisms of vegetation phenology with the spectral response of remote sensing data. (2) To establish the standardized validation dataset for remote sensing phenology. (3) To improve the temporal resolution and the accuracy of remote sensing data for phenology monitoring by multi-satellite data.%植被物候是研究植被与气候、环境变化间关系的重要参量.本文针对目前常用的阈值法、拟合法和延迟滑动平均法等植被物候遥感监测方法进行比较分析；介绍了传感器网络法、物候模型法等物候遥感监测验证方法；从遥感监测方法和数据源两方面分析物候遥感监测的误差来源；针对目前研究中存在的问题,讨论了遥感物候的主要研究方向:从机理层面,应创新植被物候遥感监测方法；建立标准化地面验证数据源；利用多源遥感数据,组成高时间分辨率的原始遥感数据源,提高植被物候遥感监测的时间分辨率和测算精度.
Full Text Available In Arctic regions, a major concern is the release of carbon from melting permafrost that could greatly exceed current human carbon emissions. Arctic rivers drain these organic-rich watersheds (Ob, Lena, Yenisei, Mackenzie, Yukon but field measurements at the outlets of these great Arctic rivers are constrained by limited accessibility of sampling sites. In particular, the highest dissolved organic carbon (DOC fluxes are observed throughout the ice breakup period that occurs over a short two to three-week period in late May or early June during the snowmelt-generated peak flow. The colored fraction of dissolved organic carbon (DOC which absorbs UV and visible light is designed as chromophoric dissolved organic matter (CDOM. It is highly correlated to DOC in large arctic rivers and streams, allowing for remote sensing to monitor DOC concentrations from satellite imagery. High temporal and spatial resolutions remote sensing tools are highly relevant for the study of DOC fluxes in a large Arctic river. The high temporal resolution allows for correctly assessing this highly dynamic process, especially the spring freshet event (a few weeks in May. The high spatial resolution allows for assessing the spatial variability within the stream and quantifying DOC transfer during the ice break period when the access to the river is almost impossible. In this study, we develop a CDOM retrieval algorithm at a high spatial and a high temporal resolution in the Yenisei River. We used extensive DOC and DOM spectral absorbance datasets from 2014 and 2015. Twelve SPOT5 (Take5 and Landsat 8 (OLI images from 2014 and 2015 were examined for this investigation. Relationships between CDOM and spectral variables were explored using linear models (LM. Results demonstrated the capacity of a CDOM algorithm retrieval to monitor DOC fluxes in the Yenisei River during a whole open water season with a special focus on the peak flow period. Overall, future Sentinel2/Landsat8
Isaacson, Sivan; Blumberg, Dan G.; Rachmilevitch, Shimon; Ephrath, Jhonathan E.; Maman, Shimrit
Trees play a significant role in the desert ecosystem by moderating the extreme environmental conditions including radiation, temperature, low humidity and small amount of precipitation. Trees In arid environments such an Acacia are considered to be `keystone species', because they have major influence over both plants and animal species. Long term monitoring of acacia tree population in those areas is thus essential tool to estimate the overall ecosystem condition. We suggest a new remote sensing data analysis technique that can be integrated with field long term monitoring of trees in arid environments and improve our understanding of the spatial and temporal changes of these populations. In this work we have studied the contribution of remote sensing methods to long term monitoring of acacia trees in hyper arid environments. In order to expand the time scope of the acacia population field survey, we implemented two different approaches: (1) Trees individual based change detection using Corona satellite images and (2) Spatial analysis of trees population, converting spatial data into temporal data. A map of individual acacia trees that was extracted from a color infra-red (CIR) aerial photographs taken at 2010 allowed us to examine the distribution pattern of the trees size and foliage health status (NDVI). Comparison of the tree sizes distribution and NDVI values distribution enabled us to differentiate between long-term (decades) and short-term (months to few years) processes that brought the population to its present state. The spatial analysis revealed that both tree size and NDVI distribution patterns were significantly clustered, suggesting that the processes responsible for tree size and tree health status (i.e., flash-floods spatial spreading) have a spatial expression. The distribution of the trees in the Wadi (ephemeral river) was divided into three distinct parts: large trees with high NDVI values, large trees with low NDVI values and small trees with
Scafutto, Rebecca Del'Papa Moreira; de Souza Filho, Carlos Roberto; de Oliveira, Wilson José
Remote detection and mapping of hydrocarbons (PHCs) in situ in continental areas is still an operational challenge due to the small scale of the occurrences and the mix of spectral signatures of PHCs and mineral substrates in imagery pixels. Despite the increasing development of new technologies, the use of hyperspectral remote sensing data as a complementary tool for both oil exploration and environmental monitoring is not standard in the oil industry, despite its potential. The high spectral resolution of hyperspectral images allows the direct identification of PHCs on the surface and provides valuable information regarding the location and spread of oil spills that can assist in containment and cleanup operations. Combining the spectral information with statistical techniques also offers the potential to improve exploration programs focused on the discovery of new exploration fields through the qualitative and quantitative characterization of oil occurrences in onshore areas. In this scenario, the aim of this work was to develop methods that can assist the detection of continental areas affected by natural oil seeps or leaks (crude oils and fuels). A field experiment was designed by impregnating several mineral substrates with crude oils and fuels in varying concentrations. Simultaneous measurements of soil-PHC combinations were taken using both a hand-held spectrometer and an airborne hyperspectral imager. Classification algorithms were used to directly map the PHCs on the surface. Spectral information was submitted to a PLS (partial least square regression) to create a prediction model for the estimation of the concentrations of PHCs in soils. The developed model was able to detect three impregnation levels (low, intermediate, high), predicting values close to the concentrations used in the experiment. Given the quality of the results in controlled experiments, the methods developed in this research show the potential to support the oil industry in the
Rangeland comprises as much as 70% of the Earth’s land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satel...
Lam, N.; Qiu, H.-I.; Quattrochi, Dale A.; Zhao, Wei
With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.
Kara, Can; Akçit, Nuhcan
Land-cover change is considered one of the central components in current strategies for managing natural resources and monitoring environmental changes. It is important to manage land resources in a sustainable manner which targets at compacting and consolidating urban development. From 2005 to 2015,urban growth in Kyrenia has been quite dramatic, showing a wide and scattered pattern, lacking proper plan. As a result of this unplanned/unorganized expansion, agricultural areas, vegetation and water bodies have been lost in the region. Therefore, it has become a necessity to analyze the results of this urban growth and compare the losses between land-cover changes. With this goal in mind, a case study of Kyrenia region has been carried out using a supervised image classification method and Landsat TM images acquired in 2005 and 2015 to map and extract land-cover changes. This paper tries to assess urban-growth changes detected in the region by using Remote Sensing and GIS. The study monitors the changes between different land cover types. Also, it shows the urban occupation of primary soil loss and the losses in forest areas, open areas, etc.
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
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...
Eisele, Andreas; Chabrillat, Sabine; Lau, Ian; Hecker, Christoph; Hewson, Robert; Carter, Dan; Wheaton, Buddy; Ong, Cindy; Cudahy, Thomas John; Kaufmann, Hermann
Digital soil mapping with the means of passive remote sensing basically relies on the soils' spectral characteristics and an appropriate atmospheric window, where electromagnetic radiation transmits without significant attenuation. Traditionally the atmospheric window in the solar-reflective wavelength region (visible, VIS: 0.4 - 0.7 μm; near infrared, NIR: 0.7 - 1.1 μm; shortwave infrared, SWIR: 1.1 - 2.5 μm) has been used to quantify soil surface properties. However, spectral characteristics of semi-arid soils, typically have a coarse quartz rich texture and iron coatings that can limit the prediction of soil surface properties. In this study we investigated the potential of the atmospheric window in the thermal wavelength region (long wave infrared, LWIR: 8 - 14 μm) to predict soil surface properties such as the grain size distribution (texture) and the organic carbon content (SOC) for coarse-textured soils from the Australian wheat belt region. This region suffers soil loss due to wind erosion processes and large scale monitoring techniques, such as remote sensing, is urgently required to observe the dynamic changes of such soil properties. The coarse textured sandy soils of the investigated area require methods, which can measure the special spectral response of the quartz dominated mineralogy with iron oxide enriched grain coatings. By comparison, the spectroscopy using the solar-reflective region has limitations to discriminate such arid soil mineralogy and associated coatings. Such monitoring is important for observing potential desertification trends associated with coarsening of topsoil texture and reduction in SOC. In this laboratory study we identified the relevant LWIR wavelengths to predict these soil surface properties. The results showed the ability of multivariate analyses methods (PLSR) to predict these soil properties from the soil's spectral signature, where the texture parameters (clay and sand content) could be predicted well in the models
Horion, Stéphanie Marie Anne F; Kurnik, Blaz; Barbosa, Paulo
distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy...... of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different...
Full Text Available Soil salinization is one of the most widespread soil degradation processes on Earth, especially in arid and semi-arid areas. The salinized soil in arid to semi-arid Xinjiang Uyghur Autonomous Region in China accounts for 31% of the area of cultivated land, and thus it is pivotal for the sustainable agricultural development of the area to identify reliable and cost-effective methodologies to monitor the spatial and temporal variations in soil salinity. This objective was accomplished over the study area (Keriya River Basin, northwestern China by adopting technologies that heavily rely on, and integrate information contained in, a readily available suite of remote sensing datasets. The following procedures were conducted: (1 a selective principle component analysis (S-PCA fusion image was generated using Phased Array Type L-band SAR (PALSAR backscattering coefficient (σ° and Landsat Enhanced Thematic Mapper Plus (ETM+ multispectral image of Keriya River Basin; and (2 a support vector machines (SVM classification method was employed to classify land cover types with a focus on mapping salinized soils; (3 a cross-validation method was adopted to identify the optimum classification parameters, and obtain an optimal SVM classification model; (4 Radarsat-2 (C band and PALSAR polarimetric images were used to analyze polarimetric backscattering behaviors in relation to the variation in soil salinization; (5 a decision tree (DT scheme for multi-source optical and polarimetric SAR data integration was proposed to improve the estimation and monitoring accuracies of soil salinization; and (6 detailed field observations and ground truthing were used for validation of the adopted methodology, and quantity and allocation disagreement measures were applied to assess classification outcome. Results showed that the fusion of passive reflective and active microwave remote sensing data provided an effective tool in detecting soil salinization. Overall accuracy of
Full Text Available Spartina alterniflora is one of the most hazardous invasive plant species in China. Monitoring the changes in dominant plant species can help identify the invasion mechanisms of S. alterniflora, thereby providing scientific guidelines on managing or controlling the spreading of this invasive species at Jiuduansha Wetland in Shanghai, China. However, because of the complex terrain and the inaccessibility of tidal wetlands, it is very difficult to conduct field experiments on a large scale in this wetland. Hence, remote sensing plays an important role in monitoring the dynamics of plant species and its distribution on both spatial and temporal scales. In this study, based on multi-spectral and high resolution (<10 m remote sensing images and field observational data, we analyzed spectral characteristics of four dominant plant species at different green-up phenophases. Based on the difference in spectral characteristics, a decision tree classification was built for identifying the distribution of these plant species. The results indicated that the overall classification accuracy for plant species was 87.17%, and the Kappa Coefficient was 0.81, implying that our classification method could effectively identify the four plant species. We found that the area of Phragmites australi showed an increasing trend from 1997 to 2004 and from 2004 to 2012, with an annual spreading rate of 33.77% and 31.92%, respectively. The area of Scirpus mariqueter displayed an increasing trend from 1997 to 2004 (12.16% per year and a decreasing trend from 2004 to 2012 (−7.05% per year. S. alterniflora has the biggest area (3302.20 ha as compared to other species, accounting for 51% of total vegetated area at the study region in 2012. It showed an increasing trend from 1997 to 2004 and from 2004 to 2012, with an annual spreading rate of 130.63% and 28.11%, respectively. As a result, the native species P. australi was surrounded and the habitats of S. mariqueter were
Handcock, Rebecca N; Swain, Dave L; Bishop-Hurley, Greg J; Patison, Kym P; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J
...). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor...
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.
Full Text Available This paper is based on using DMSP-OLS data from satellites nighttime light observations to detect both sources of light emissions in Algeria from human settlement areas and gas flaring from oil-extraction and natural gas production. We used the time series of data from DMSP-OLS images to examine the spatial and temporal characteristics of urban development in 48 Algerian provinces from 1993 to 2012. A systematic nighttime light calibration method was used to improve the consistency and comparability of the DSMPOSL images and then a separation is made between light detected from human settlements and light detected from gas flaring in order to allow us to study human settlements without other light emissions and then assess the suitability of using DMSP data in southern Algeria and its ability to monitor gas flaring. Linear regression methods were developed to identify the dynamic change of nighttime light and estimated its growth directions at pixel level. This work is the first to use nighttime light observations to detect and monitor the growth of human settlements in North Africa. In this study, we made use of DMSP-OLS data as a return ticket to the years of crises and we found the most affected provinces during that period. The DMSP-OLS data proved to be an index of growth in the economy during the period of stability in Algeria expressed by positive dynamic changes in the lighted area in all Algerian provinces. We used NTL data as an alternative to annual growth indexes for each province, which are unavailable, and its help as a monitoring system for socioeconomic parameters to fill the gap of data availability. We also proposed nighttime light remote sensing data as a useful tool to control and reduce CO2 emissions in Algeria’s petroleum sector.
Weng, Songgan; Zhai, Duo; Yang, Xing; Hu, Xiaodong
Hydrological monitoring is recognized as one of the most important factors in hydrology. Particularly, investigation of the tempo-spatial variation patterns of water-level and their effect on hydrological research has attracted more and more attention in recent. Because of the limitations in both human costs and existing water-level monitoring devices, however, it is very hard for researchers to collect real-time water-level data from large-scale geographical areas. This paper designs and implements a real-time water-level data monitoring system (MCH) based on ZigBee networking, which explicitly serves as an effective and efficient scientific instrument for domain experts to facilitate the measurement of large-scale and real-time water-level data monitoring. We implement a proof-of-concept prototype of the MCH, which can monitor water-level automatically, real-timely and accurately with low cost and low power consumption. The preliminary laboratory results and analyses demonstrate the feasibility and the efficacy of the MCH.
Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Reiche, Johannes
The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral
Horion, Stéphanie Marie Anne F; Kurnik, Blaz; Barbosa, Paulo
distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy...
Du, Peijun; Xia, Junshi; Feng, Li
Impervious surface area (ISA) plays an important role in monitoring urbanization and related environmental changes, and has become a hotspot in urban and environmental studies. Xuzhou City, located in northwest Jiangsu Province, China, is chosen as the study area, and two scenes of China-Brazil Earth Resources Satellites images and one scene of HJ-1 image are employed to estimate ISA percentage and analyze the change trend from 2001 to 2009. Using a linear spectral mixture model (LSMM) and nonlinear backpropagation neural network (BPNN) method, all pixels are decomposed to derive four fraction images representing the abundance of four endmembers: vegetation, high-albedo objects, low-albedo objects, and soil. The ISA percentage is then derived by the combination of high- and low-albedo fraction images after removing the influence of water. Some high spatial resolution images are selected to validate the ISA estimation results, and the experimental results indicate that the accuracy of BPNN is higher than LSMM. By comparing the urban ISA abundances derived by BPNN from three dates, it is found that the ISA of Xuzhou City has increased rapidly from 2001 to 2009, especially in the northeast and southeast regions, corresponding to the urban planning scheme and fast urbanization. Compared to other medium remote sensing images, the revisit cycle of HJ-1 multispectral image is only two days, demonstrating the potential of such data for ISA extraction in urbanization, disaster, and other related applications.
Nikolakopoulos, Konstantinos; Pavlopoulos, Kosmas; Chalkias, Christos; Manou, Dora
During the last thirty-five years the capital of Greece has suffered from an enormous internal immigration. Its population has overpassed the five millions and today almost the half population of Greece is squeezed in Athens metropolitan area. Because of the significant increase of population, the urban expansion in the basin of Athens was also excessive and in some cases catastrophic. Buildings have covered all the free places, new roads have been constructed, the drainage networks have been covered or disappeared and a lot of changes have been occurred to the landforms. The construction of the new airport (Elefterios Venizelos) at the beginning of this decade created a new commercial and urban pole at the eastern part of Athens and the constructive activity has been moved to new areas around the airport. Our aim was to detect and map all the changes that occurred in the urban area, estimate the urban expansion rate and the human interferences in the natural landscape, using GIS and remote sensing techniques. We have used satellite images from three different periods (1973, 1992, 2002) and topographic maps of 1:25.000 scale. The spatial resolution of all the satellite images ranges from 5 to 10 meters and is it acceptable for the monitoring and mapping of the urban growth. Supervised classification and on screen digitizing methods have been used in order to map the changes. Finally the qualitative and quantitative results of this study are presented in this paper.
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.
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).
Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)
This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)
With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynamics monitoring and database updating techniques. With the pressure on nature environment from increasing population and decreasing farmland becoming significant more and more in China, the farmland urban dynamics in historical and current times, even the change trends in the future, should be monitored and analyzed serving for regional and national social, economic and environmental sustainable development in the long future. Based on spatial and temporal series of land -use/land-cover database resources, Chinese Academy of Sciences designed a sampling framework for monitoring farmland and urban area dynamics in regional and national level. In order to test the accuracy of the sampling schema for national and regional level, we took two provinces area into overall covered change detecting process with TM images data through being interpreted by digitalization on the screen. The result shows that our stratified random sampling schema is suitable for monitoring land -use/land-cover change at national and regional level with quick response, high accuracy and low expenses. The land-use/land-cover change (LUCC) information can update the LUTEA database for global change research during certain period so that the forecasting process and evaluating analysis on land resources and environment under human and natural driving force will get essential data and produce valuable conclusions.
Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moist...
Vanden Borre, J.; Paelinckx, D.; Mücher, C.A.; Kooistra, L.; Haest, B.; Blust, De G.; Schmidt, A.M.
Monitoring and reporting on the state of nature gained increasing importance in the European Union with the implementation of the Habitats Directive and the Natura 2000 network. Reporting habitat conservation status requires detailed knowledge on many aspects of habitats at different spatial levels.
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.
Asner, Gregory P. (Inventor)
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.
尹京苑; 沈迪; 李成范
A large volcanic eruption can produce large amounts of volcanic ash,water vapor and heat,and form the volcanic ash cloud.The volcanic ash cloud is mainly composed of volcanic ash debris in diameter less than 2mm and gases including SO2,H2S,CO2,the mixture of the two can form acidic aerosols which can stay in the atmosphere for a long time.It not only destructs the balance of earth's surface solar radiation and causes the depletion of the ozone layer,the greenhouse effect,air pollution,acid rain,anomalies of air temperature and precipitation,and other major global climate and environmental changes,but also damages and corrodes the structure of an aircraft,reduces the visibility and jams the radio communication system.The most serious problem is that the volcanic ash debris particles are capable of cooling and adhering to the aircraft engine blades after high-temperature melting,resulting in the flameout of aircraft engine.Under the background of globalization and the boom of air-transport industry,the volcanic ash cloud is a serious threat to aviation safety.Remote sensing technology can quickly and accurately obtain the information of the surface's and the atmosphere's changes,therefore it is playing an important role in monitoring volcanic activity.In recent years,with the advancement of sensor technology,the thermal infrared remote sensing technology has become an important means of monitoring the volcanic ash cloud.Currently,there have been a variety of remote sensors for volcanic ash cloud monitoring.Meanwhile,based on that,a series of volcanic ash cloud monitoring algorithms have also been developed for different remote sensors.However,most of the volcanic ash cloud monitoring algorithms have limitations of a low accuracy and a narrow scope.This paper tries to conduct a more comprehensive overview of the different types of remote sensors and the different algorithms for volcanic ash cloud monitoring.First,the damage of volcanic ash cloud to the natural
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...
Initialization and opportunistic targets are chosen that represent the MTF on the spatial domain. Ideal targets have simple mathematical relationships. Determine the MTF of an on-orbit satellite using in-scene targets: Slant-Edge, Line Source, point Source, and Radial Target. Attempt to facilitate the MTF calculation by automatically locating targets of opportunity. Incorporate MTF results into a product quality monitoring architecture.
Full Text Available In this work, we present the results of a low-cost optical monitoring station designed for monitoring the kinematics of glaciers in an Alpine environment. We developed a complete hardware/software data acquisition and processing chain that automatically acquires, stores and co-registers images. The system was installed in September 2013 to monitor the evolution of the Planpincieux glacier, within the open-air laboratory of the Grandes Jorasses, Mont Blanc massif (NW Italy, and collected data with an hourly frequency. The acquisition equipment consists of a high-resolution DSLR camera operating in the visible band. The data are processed with a Pixel Offset algorithm based on normalized cross-correlation, to estimate the deformation of the observed glacier. We propose a method for the pixel-to-metric conversion and present the results of the projection on the mean slope of the glacier. The method performances are compared with measurements obtained by GB-SAR, and exhibit good agreement. The system provides good support for the analysis of the glacier evolution and allows the creation of daily displacement maps.
Tamassoki, E.; Amiri, H.; Soleymani, Z.
Shoreline change is one of the most common natural processes that prevail upon coastal areas. The most important aspect of managing coastal areas is identifying the location and change over time of shoreline. This requires frequent monitoring of the shoreline using satellite imagery over time. We have used imagery from the Landsat TM-5 sensor from 1984,1998 and 2009 in order to monitor shoreline changes using the Max Likelihood Classification method (MLC) in Bandar Abbas city. Monitoring showed that during the period from 1984 to 1998 the area of coastline of Bandar Abbas increased 804.09 hectares. The increase over the next 11-year period was as less, at only 140.81 hectares. In 2009 there was a drastic decrease in shoreline, with the total length of shoreline decreasing from 330 km to 271 km during the period from 1984 to 2009.Results showed that in each period in which the area of coastline advanced, changes in length of shoreline had been less prominent.
Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.
Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and
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
Chen, H S
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
Hao, Cui; Zhang, Jiahua; Yao, Fengmei
Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed
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....
Budde, Michael E.; Rowland, James; Funk, Christopher C.
For one-sixth of the world’s population - roughly 1 billion children, women and men - growing, buying or receiving adequate, affordable food to eat is a daily uncertainty. The World Monetary Fund reports that food prices worldwide increased 43 percent in 2007-2008, and unpredictable growing conditions make subsistence farming, on which many depend, a risky business. Scientists with the U.S. Geological Survey (USGS) are part of a network of both private and government institutions that monitor food security in many of the poorest nations in the world.
Kunte, P.D.; Aswini, M.A.
Browse Images for Production Release [V3.20] were downloaded (Fig. 4b) from http://www- calipso.larc.nasa.gov/products/lidar. The footprint of CALIPSO overlaid over the MODIS scene to validate the presence of dust (Fig. 4c). In absence of any other..., the clouds are seen floating between 7000m-13000m over the Arabian Sea during March 2012 event (Fig. 4b). 3.4. Super Sand Storm migration monitoring Aqua and terra MODIS scenes captured during 2nd half of March, 2012 were downloaded, enhanced...
Wylie, Bruce K.; Boyte, Stephen P.; Major, Donald J.
Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance (P<0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.
Scopélitis, Julie; Andréfouët, Serge; Phinn, Stuart; Arroyo, Lara; Dalleau, Mayeul; Cros, Annick; Chabanet, Pascale
Most current coral reef management is supported by mapping and monitoring limited in record length and spatial extent. These deficiencies were addressed in a multidisciplinary study of cyclone impacts on Aboré Reef, New-Caledonia. Local knowledge, high thematic-resolution maps, and time-series satellite imagery complemented classical in situ monitoring methods. Field survey stations were selected from examination of pre- and post-cyclone images and their post-cyclone coral communities documented in terms of substrata, coral morphologies, live coral cover, and taxonomy. Time-series maps of hierarchically defined coral communities created at spatial scales documenting the variability among communities (29-45 classes) and suggesting the processes that affected them. The increased spatial coverage and repeatability of this approach significantly improved the recognition and interpretation of coral communities' spatio-temporal variability. It identified precise locations of impacted areas and those exhibiting coral recovery and resilience. The approach provides a comprehensive suite of information on which to base reef-scale conservation actions.
Pavelka, K.; Šedina, J.; Matoušková, E.; Faltýnová, M.; Hlaváčová, I.
Since 2002, German low-cost scientific expeditions to Greenland have been performed. The objective was a geodetic survey and glaciology with GNSS technology - mainly the measurement of glacier profiles (height). The same glacier profiles along the route were measured during German expeditions in 2006, 2010, 2012 and 2015. The last international expedition was supplemented with RPAS (UAV) measurement, the testing of small corner reflectors for Terra SAR X satellite measurement and the use of image based modelling technology for historical monuments documentation, all in specific arctic conditions. The RPAS measurement was focused on the documentation of existing valuable archaeological sites near Ilulissat city and the testing of RPAS technology for the monitoring of the face of the moving glacier. Two typical church wooden constructions were documented by simple photogrammetric technology based on image correlation. Both experiments were evaluated as successfully case projects. The last part of the experiments deals with the monitoring of a moving inland glacier using SAR technology; four corner reflectors were installed on the glacier and on a massive nearby rock. Two ascending and two descending overflights of the Terra SAR X satellite in fine resolution mode were performed. The InSAR technology give inconclusive results, but some movements were detected; small and inexpensive corner reflectors of our own production have proven suitable. Experience and expertise from the measurement such as the first outputs from the expedition are the content of the present article.
This paper examines the potential of microwave radar interferometry for monitoring the dynamic behaviour of large civil engineering works. It provides an overview of the method, its principles of operation with particular emphasis given on the IBIS-S system. Two areas of application are considered and the results of the analyses are presented and discussed. The first experimental study involves the monitoring of the dynamic response of a tall power plant chimney due to wind load. The second example examines the dynamic behaviour of a long cable-stayed bridge. In this case, the focus is placed on the effects that individual traffic events impose on the vibration response of the main span of the bridge deck and the bridge pylons. Analysis of the results provides detailed displacement time-histories and the dominant frequencies observed at the top of the chimney and along the bridge deck and the top of the towers. Also, cross-comparisons and discussions with the results obtained at the same structures using different sensor configurations are provided.
Labazuy, Philippe; Gouhier, Mathieu; Hervo, Maxime; Freville, Patrick; Quehennen, Boris; Donnadieu, Frank; Guehenneux, Yannick; Cacault, Philippe; Colomb, Aurélie; Gayet, Jean-François; Pichon, Jean-Marc; Rivet, Sandrine; Schwarzenböck, Alfons; Sellegri, Karine
OPGC (Observatoire de Physique du Globe de Clermont-Ferrand) presents a unique combination of knowledge in volcanology and atmosphere physics, for the tracking and the monitoring of volcanic plumes. These competences interact through the combination of the mastering of Lidar and radar techniques; gas and aerosol measurement (in-situ and airborne) by the Laboratoire de Météorologie Physique (LaMP,OPGC) and the expertise of the Laboratoire Magmas et Volcans (LMV,OPGC) in eruption dynamics and spatial remote sensing. Platforms for observations benefit from the technical support and expertise of the OPGC staff. HOTVOLC group is dedicated to the near-real-time monitoring of thermal anomalies related to the eruptive activity of volcanoes. The main goal of HOTVOLC deals with estimation of quantitative parameters that give stringent constraints on ash plumes dynamics, from the vent to the atmosphere. Datas from HOTVOLC give near -real time monitoring of ash plume, and its height, crucial parameter for predictive models and risk assessment. The height of the plume of Eyjafjöll on April 15 2010 at 12:00 UTC was estimated at 5000-6500 m, in accordance with ground observations and Lidar data. TERRA MODIS and AURA OMI sensors were used for the daily quantitative estimation of ash and SO2 burden , respectively. Two peaks of ash and SO2 emissions occurring on April 15 (100 kt and 8 kt) and 19 (170 kt and 12 kt) were determined. HOTVOLC is involved in the monitoring of the eruption at Eyjafjöll(Iceland) and belongs to a volcano alert group, at the request of the MEEDDM (French Ministry for ecology, energy, sustainable development and sea). LIDAR at the OPGC, is a Rayleigh-Mie LIDAR emitting at 355nm, with parallel and crossed polarization channels. On April 19, a layer of depolarizing particles i.e.non-spherical particles was observed at 3000 m a.s.l, with maximum thickness of 500m. The instrumented station at the top of the Puy de Dôme allows measurements of gas-phase and of
Gat, N.; Subramanian, S. [Opto-Knowledge Systems, Inc. (United States); Barhen, J. [Oak Ridge National Lab., TN (United States); Toomarian, N. [Jet Propulsion Lab., Pasadena, CA (United States)
This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.
Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.
This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.
Ye, Baoying; Liu, Ling
This paper monitored the coal mine exploitation in Donglutian coal mine, Shuozhou city, Shanxi Province. Landsat satellite images from 2008 to 2016 were selected, and then 15m color composite images were obtained through data processing and image fusion. On this basis, the land use map from 2008 to 2016 was obtained using visual interpretation method. Results showed that the main land use type in this area was cropland, unused land and coalmine. Area of cropland and unused land kept decreasing year by year, while coal mine expanded rapidly. The expansion of coal mine concentrated on two time periods: from 2009 to 2010 and from 2012 to 2013. During these two time periods, topsoil stripping was the main exploitation type, while deep mining was the main type for other times. Results also presented that the exploitation number of small coals kept increasing year by year, from the initial number of 26 at 2008 to 42 at 2016.
Polidori, A.; Tisopulos, L.; Pikelnaya, O.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Robinson, R. A.; Innocenti, F.; Finlayson, A.; Hashmonay, R.
Despite great advances in reducing air pollution, the South Coast Air Basin (SCAB) still faces challenges to attain federal health standards for air quality. Refineries are large sources of ozone precursors and, hence contribute to the air quality problems of the region. Additionally, petrochemical facilities are also sources of other hazardous air pollutants (HAP) that adversely affect human health, for example aromatic hydrocarbons. In order to assure safe operation, decrease air pollution and minimize population exposure to HAP the South Coast Air Quality Management District (SCAQMD) has a number of regulations for petrochemical facilities. However, significant uncertainties still exist in emission estimates and traditional monitoring techniques often do not allow for real-time emission monitoring. In the fall of 2015 the SCAQMD, Fluxsense Inc., the National Physical Laboratory (NPL), and Atmosfir Optics Ltd. conducted a measurement study to characterize and quantify gaseous emissions from the tank farm of one of the largest oil refineries in the SCAB. Fluxsense used a vehicle equipped with Solar Occultation Flux (SOF), Differential Optical Absorption Spectroscopy (DOAS), and Extractive Fourier Transform Infrared (FTIR) spectroscopy instruments. Concurrently, NPL operated their Differential Absorption Lidar (DIAL) system. Both research groups quantified emissions from the entire tank farm and identified fugitive emission sources within the farm. At the same time, Atmosfir operated an Open Path FTIR (OP-FTIR) spectrometer along the fenceline of the tank farm. During this presentation we will discuss the results of the emission measurements from the tank farm of the petrochemical facility. Emission rates resulting from measurements by different ORS methods will be compared and discussed in detail.
Wang, Weimin; Hong, Liang; Yang, Lijun; He, Lihuan; Dong, Guihua
In the past three decades, the Shenzhen city, which is located in south of China, has experienced a rapid urbanization process characterized by sharp decrease in farmland and increases in urban area. This rapid urbanization is one of the main causes of many environmental and ecological problems including urban heat island (UHI). Therefore, the monitoring of rapid urbanization regions and the environment is of critical importance for their sustainable development. In this study, Landsat-8 OLI and TIR images, which were acquired on 2013, are used to monitor urban heat island. After radiometric calibration and atmospheric correction with a simplified method for the atmospheric correction (SMAC) are applied to OLI image, an index-based build-up index (IBI), which is based on the soil adjusted vegetation index (SAVI), the modified normalized difference water index (MNDWI) and the normalized difference built-up index (NDBI), is employed to extract the build-up land features with a given thresholds. A single-channel algorithm is used to retrieve land surface temperature while the land surface emissivity is derived from a normalized differential vegetation index (NDVI) thresholds method. Surface urban heat island index (SUHII) and urban heat island ratio index (URI) are computed for ten districts of Shenzhen based on build-up land distribution and land surface temperature data. A correlation analysis is conducted between heat island index (including SUHII and URI) and socio-economic statistics (including total population and population density) also are included in this analysis. The results show that, a weak relationship between urban heat island and socio-economic statistics are found.
Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir
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.
Lazaridou, M. A.; Patmio, E. N.
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.
Wang, Zhen; He, Lei; Zhang, Shengwei; Lei, Yuping
Lake Baiyangdian, a largest wetland ecosystem in North China Plain, has dried up on seven occasions since the 1960s. In recent years, more than one billion of cubic meters of water from upstream reservoirs and Yellow river have been transported to the lake to rescue the shrinking wetlands. Since the Lake Baiyangdian was actually composed of 143 small lakes and more than 70 villages with large or small area of cropland, dynamic distribution of aquatic plants in wetland such as reed and associated growth condition of these allowed to monitor the changes of wetland landscape and water quality to support the policy applications of water conveyance and wetland environmental treatment and control. Assisted with ground survey analyses and Landsat TM image, the MODIS 250 m time series Normalized Difference Vegetation Index (NDVI), given its combination of medium spatial and high temporal resolution, were applied to detect the unique rapid growth stage of reed in the spring from adjacent crops such as winter wheat, cotton, and spring maize, of which has a similar phenology in development of leaf area index, and dynamic reed areas were mapped in recent decade. Landscape changes of the wetland were analyzed using maps of reed area and hydrological data.
Anderson, M. C.; Hain, C.; Gao, F.; Yang, Y.; Sun, L.; Dulaney, W.; Sharifi, A.; Holmes, T. R.; Kustas, W. P.
Across the U.S. and globally there are ever increasing and competing demands for freshwater resources in support of food production, ecosystems services and human/industrial consumption. Recent studies using the GRACE satellite have identified severely stressed aquifers globally, which are being unsustainably depleted due to over-extraction primarily in support of irrigated agriculture. In addition, historic droughts and ongoing political conflicts threaten food and water security in many parts of the world. To facilitate wise water management, and to develop sustainable agricultural systems that will feed the Earth's growing population into the future, there is a critical need for robust assessments of daily water use, or evapotranspiration (ET), over a wide range in spatial scales - from field to globe. While Earth Observing (EO) satellites can play a significant role in this endeavor, no single satellite provides the combined spatial, spectral and temporal characteristics required for actionable ET monitoring world-wide. In this presentation we discuss new methods for combining information from the current suite of EO satellites to address issues of water use, water quality and water security, particularly as they pertain to agricultural production. These methods fuse multi-scale diagnostic ET retrievals generated using shortwave, thermal infrared and microwave datasets from multiple EO platforms to generate ET datacubes with both high spatial and temporal resolution. We highlight several case studies where such ET datacubes are being mined to investigate changes in water use patterns over agricultural landscapes in response to changing land use, land management, and climate forcings.
Zhan, Xiwu; Gao, Wei; Pan, Xiaoling; Ma, Yingjun
Terrestrial ecosystems, in which carbon is retained in live biomass, play an important role in the global carbon cycling. Among these ecological systems, vegetation and soils in deserts and semi deserts control significant proportions in the total carbon stocks on the land surface and the carbon fluxes between the land surface and the atmosphere (IPCC special report: Land Use, Land Use Change and Forestry, June 2000). Therefore, accurate assessment of the carbon stocks and fluxes of the desert and semi desert areas at regional scales is required in global carbon cycle studies. In addition, vegetative ecosystem in semi-arid and arid land is strongly dependent on the water resources. Monitoring the hydrologic processes of the land is thus also required. This work explores the methodology for the sequential continuous estimation of the carbon stocks, CO2 flux, evapotranspiration, and sensible heat fluxes over desert and semidesert area using data from the Jornada desert in New Mexico, USA. A CO2 and energy flux coupled model is used to estimate CO2, water vapor and sensible heat fluxes over the desert area. The model is driven by the observed meteorological data. Its input land surface parameters are derived from satellite images. Simulated energy fluxes are validated for specific sites with eddy covariance observations. Based on the output of spatially distributed CO2 fluxes, carbon accumulations over the desert area during a period of time is calculated and the contribution of the desert ecosystem to the atmospheric carbon pool is discussed.
Boschetti, Mirco; Mauri, Emanuela; Gadda, Chiara; Busetto, Lorenzo; Confalonieri, Roberto; Bocchi, Stefano; Brivio, Pietro A.
Rice is one of the most important crops in the whole world, providing staple food for more than 3000 million people. For this reason FAO declared the year 2004 as The International Year of Rice promoting initiatives and researches on this valuable crop. Assessing the Net Primary Production (NPP) is fundamental to support a sustainable development and to give crop yield forecast essential to food security policy. Crop growth models can be useful tools for estimating growth, development and yield but require complex spatial distributed input parameters to produce valuable map. Light use efficiency (LUE) models, using satellite-borne data to achieve daily surface parameters, represent an alternative approach able to monitor differences in vegetation compound providing spatial distributed NPP maps. An experiment aimed at testing the capability of a LUE model using daily MODIS data to estimate rice crop production was conducted in a rice area of Northern Italy. Direct LAI measurements and indirect LAI2000 estimation were collected on different fields during the growing season to define a relationship with MODIS data. An hyperspectral MIVIS image was acquired in early July on the experimental site to provide high spatial resolution information on land cover distribution. LUE-NPP estimations on several fields were compared with CropSyst model outputs and field biomass measurements. A comparison of different methods performance is presented and relative advantages and drawbacks in spatialization are discussed.
Anderson, Martha; Hain, Christopher; Feng, Gao; Yang, Yun; Sun, Liang; Yang, Yang; Dulaney, Wayne; Sharifi, Amir; Kustas, William; Holmes, Thomas
Across the globe there are ever-increasing and competing demands for freshwater resources in support of food production, ecosystems services and human/industrial consumption. Recent studies using the GRACE satellite have identified severely stressed aquifers that are being unsustainably depleted due to over-extraction, primarily in support of irrigated agriculture. In addition, historic droughts and ongoing political conflicts threaten food and water security in many parts of the world. To facilitate wise water management, and to develop sustainable agricultural systems that will feed the Earth's growing population into the future, there is a critical need for robust assessments of daily water use, or evapotranspiration (ET), over a wide range in spatial scales - from field to globe. While Earth Observing (EO) satellites can play a significant role in this endeavor, no single satellite provides the combined spatial, spectral and temporal characteristics required for actionable ET monitoring world-wide. In this presentation we discuss new methods for combining information from the current suite of EO satellites to address issues of water quality, water use and water security, particularly as they pertain to agricultural production. These methods fuse multi-scale diagnostic ET retrievals generated using shortwave, thermal infrared and microwave datasets from multiple EO platforms to generate ET datacubes with both high spatial and temporal resolution. We highlight several case studies where such ET datacubes are being mined to investigate changes in water use patterns over agricultural landscapes in response to changing land use, land management, and climate forcings.
Full Text Available Urban forest ecosystems provide a range of social and ecological services, but due to the heterogeneity of these canopies their spatial extent is difficult to quantify and monitor. Traditional per-pixel classification methods have been used to map urban canopies, however, such techniques are not generally appropriate for assessing these highly variable landscapes. Landsat imagery has historically been used for per-pixel driven land use/land cover (LULC classifications, but the spatial resolution limits our ability to map small urban features. In such cases, hyperspatial resolution imagery such as aerial or satellite imagery with a resolution of 1 meter or below is preferred. Object-based image analysis (OBIA allows for use of additional variables such as texture, shape, context, and other cognitive information provided by the image analyst to segment and classify image features, and thus, improve classifications. As part of this research we created LULC classifications for a pilot study area in Seattle, WA, USA, using OBIA techniques and freely available public aerial photography. We analyzed the differences in accuracies which can be achieved with OBIA using multispectral and true-color imagery. We also compared our results to a satellite based OBIA LULC and discussed the implications of per-pixel driven vs. OBIA-driven field sampling campaigns. We demonstrated that the OBIA approach can generate good and repeatable LULC classifications suitable for tree cover assessment in urban areas. Another important finding is that spectral content appeared to be more important than spatial detail of hyperspatial data when it comes to an OBIA-driven LULC.
Piccard, Isabelle; Gobin, Anne; Curnel, Yannick; Goffart, Jean-Pierre; Planchon, Viviane; Wellens, Joost; Tychon, Bernard; Cattoor, Nele; Cools, Romain
Potato processors, traders and packers largely work with potato contracts. The close follow up of contracted parcels is important to improve the quantity and quality of the crop and reduce risks related to storage, packaging or processing. The use of geo-information by the sector is limited, notwithstanding the great benefits that this type of information may offer. At the same time, new sensor-based technologies continue to gain importance and farmers increasingly invest in these. The combination of geo-information and crop modelling might strengthen the competitiveness of the Belgian potato chain in a global market. The iPot project, financed by the Belgian Science Policy Office (Belspo), aims at providing the Belgian potato processing sector, represented by Belgapom, with near real time information on field condition (weather-soil), crop development and yield estimates, derived from a combination of satellite images and crop growth models. During the cropping season regular UAV flights (RGB, 3x3 cm) and high resolution satellite images (DMC/Deimos, 22m pixel size) were combined to elucidate crop phenology and performance at variety trials. UAV images were processed using a K-means clustering algorithm to classify the crop according to its greenness at 5m resolution. Vegetation indices such as %Cover and LAI were calculated with the Cyclopes algorithm (INRA-EMMAH) on the DMC images. Both DMC and UAV-based cover maps showed similar patterns, and helped detect different crop stages during the season. A wide spread field monitoring campaign with crop observations and measurements allowed for further calibration of the satellite image derived vegetation indices. Curve fitting techniques and phenological models were developed and compared with the vegetation indices during the season, both at trials and farmers' fields. Understanding and predicting crop phenology and canopy development is important for timely crop management and ultimately for yield estimates. An
Kanniah, K. D.; Kamarul Zaman, Nurul Amalin Fatihah; Lim, H. Q.; Reba, Mohd Nadzri Md.
Monitoring particulate matter less than 10 μm (PM10) near the ground routinely is critical for Malaysia for emergency management because Malaysia receives considerable amount of pollutants from both local and trans-boundary sources. Nevertheless, aerosol data covering major cities over a large spatial extent and on a continuous manner are limited. Thus, in the present study we aimed to estimate PM10 at 5 km spatial scale using AOD derived from MERIS sensor at 3 metropolitan cities in Malaysia. MERIS level 2 AOD data covering 5 years (2007-2011) were used to develop an empirical model to estimate PM10 at 11 locations covering Klang valley, Penang and Johor Bahru metropolitan cities. This study is different from previous studies conducted in Malaysia because in the current study we estimated PM10 by considering meteorological parameters that affect aerosol properties, including atmospheric stability, surface temperature and relative humidity derived from MODIS data and our product will be at ~5 km spatial scale. Results of this study show that the direct correlation between monthly averaged AOD and PM10 yielded a low and insignificant relationship (R2= 0.04 and RMSE = 7.06μg m-3). However, when AOD, relative humidity, land surface temperature and k index (atmospheric stability) were combined in a multiple linear regression analysis the correlation coefficient increased to 0.34 and the RMSE decreased to 8.91μg m-3. Among the variables k- index showed highest correlation with PM 10 (R2=0.35) compared to other variables. We further improved the relationship among PM10 and the independent variables using Artificial Neural Network. Results show that the correlation coefficient of the calibration dataset increased to 0.65 with low RMSE of 6.72μg m-3. The results may change when we consider more data points covering 10 years (2002- 2011) and enable the construction of a local model to estimate PM10 in urban areas in Malaysia.
Dye, Dennis G.; Bogle, Rian C.
Scientists at the U.S. Geological Survey are improving and developing new ground-based remote-sensing instruments and techniques to study how Earth’s vegetation responds to changing climates. Do seasonal grasslands and forests “green up” early (or late) and grow more (or less) during unusually warm years? How do changes in temperature and precipitation affect these patterns? Innovations in ground-based remote-sensing instrumentation can help us understand, assess, and mitigate the effects of climate change on vegetation and related land resources.
Silvestro, Paolo Cosmo; Casa, Raffaele; Pignatti, Stefano; Castaldi, Fabio; Yang, Hao; Guijun, Yang
The aim of this work was to develop a tool to evaluate the effect of water stress on yield losses at the farmland and regional scale, by assimilating remotely sensed biophysical variables into crop growth models. Biophysical variables were retrieved from HJ1A, HJ1B and Landsat 8 images, using an algorithm based on the training of artificial neural networks on PROSAIL.For the assimilation, two crop models of differing degree of complexity were used: Aquacrop and SAFY. For Aquacrop, an optimization procedure to reduce the difference between the remotely sensed and simulated CC was developed. For the modified version of SAFY, the assimilation procedure was based on the Ensemble Kalman Filter.These procedures were tested in a spatialized application, by using data collected in the rural area of Yangling (Shaanxi Province) between 2013 and 2015Results were validated by utilizing yield data both from ground measurements and statistical survey.
沈文娟; 蒋超群; 侍昊; 王春红; 李明诗
本文总结了基于样点地面实测光谱分析和基于遥感影像的多光谱和高光谱定量化监测方法在土壤重金属污染中应用的优劣势，分析出现有研究数据和方法的不足与需改进之处，并指出整合多源数据和多变量方法用于连续动态监测并制图土壤重金属污染将是遥感定量化监测新的发展趋势。尺度的变化和定量遥感的不确定性影响土壤重金属污染遥感监测的精度。%How to map the pollution quality and severity in an accurate,timely,and large scale manner has definitely been recognized as the crux of bringing the pollution under control.Remote sensing technology,with the monitoring advantages of wide coverage,expeditiousness,affordable price and suitable revisit frequency remains irreplaceable in monitoring large-scale soil pollution.In this paper,the advantages and disadvantages of monitoring methods for soil heavy metal pollution evaluation based on the measured spectral analysis of the samples as well as the quantitative detection by the multispectral and hyperspectral remote sensing imagery were summarized and the deficiency of the existing research data and methods and which need to be improved were analyzed.Finally,it pointed out that the continuous dynamic monitoring and mapping soil heavy metal pollution by the integration of multi-source data and multivariate methods will be the new development trend of quantitative monitoring via remote sensing technology.Scale changes in detection and the uncertainty of quantitative remote sensing affect the accuracy of remote sensing monitoring on soil heavy metal pollution.
对国内外遥感监测土壤盐渍化发展情况作了介绍，对土壤盐渍化及其动态变化遥感监测方法进行了总结，数字图像处理将成为区域土壤盐渍化遥感监测研究的主要手段。土壤盐渍化是一个世界性的问题，应将遥感及遥感图像处理技术的最新成果充分运用到盐渍土监测研究中，为盐渍土治理与农业可持续发展提供信息保障。%Globally, an estimated 9.5×108 hm2 of land are affected bysalinity and sodicity. Soil salinization is the major land degradation problem of the world. The information on saline soil is prerequisite for saline soil amelioration and sustainable development of agriculture. By virtue of synoptic view of large area in discrete bands of the electromagnetic spectrum, multi-spectral data acquired from spaceborne platforms, remote sensing has been found to be useful in detection, mapping and monitoring of salt-affected soils. The international and national development of soil salinization monitoring based on remote sensing is introduced. Overseas, satellite remote sensing has been used to monitor salt-affected soil since 1970's. Multi-spectral and multi-temporal data was been widely used in the 1980's. During the time, visual interpretation approach was generally used. Since the 1990's, data has been enriched. Research category becomes wider than before. But visual interpretation is still the major approach used to extract information on saline soil. In China, satellite remote sensing has been used to monitor saline soil since 1980's. It is 10 years latter than overseas. Fundamental technical, monetary and data handling limits act collectively to constrain the information extraction on saline soils. The methods of regional soil salinization monitoring are visual interpretation and digital image processing. The approaches of saline soil dynamic detecting are pixel-by-pixel comparison and post-classification comparison. The digital image processing will be
Yi, Lim J.; Sarker, Md Latifur Rahman; Zhang, Lei; Siswanto, Eko; Mubin, Ahmad; Sabarudin, Saadah
Oceans play a significant role in the global carbon cycle and climate change, and the most importantly it is a reservoir for plenty of protein supply, and at the center of many economic activities. Ocean health is important and can be monitored by observing different parameters, but the main element is the phytoplankton concentration (chlorophyll-a concentration) because it is the indicator of ocean productivity. Many methods can be used to estimate chlorophyll-a (Chl-a) concentration, among them, remote sensing technique is one of the most suitable methods for monitoring the ocean health locally, regionally and globally with very high temporal resolution. In this research, long term ocean health monitoring was carried out at the Bay of Bengal considering three facts i.e. i) very dynamic local weather (monsoon), ii) large number of population in the vicinity of the Bay of Bengal, and iii) the frequent natural calamities (cyclone and flooding) in and around the Bay of Bengal. Data (ten years: from 2001 to 2010) from SeaWiFS and MODIS were used. Monthly Chl-a concentration was estimated from the SeaWiFS data using OC4 algorithm, and the monthly sea surface temperature was obtained from the MODIS sea surface temperature (SST) data. Information about cyclones and floods were obtained from the necessary sources and in-situ Chl-a data was collected from the published research papers for the validation of Chl-a from the OC4 algorithm. Systematic random sampling was used to select 70 locations all over the Bay of Bengal for extracting data from the monthly Chl-a and SST maps. Finally the relationships between different aspects i.e. i) Chl-a and SST, ii) Chl-a and monsoon, iii) Chl-a and cyclones, and iv) Chl-a and floods were investigated monthly, yearly and for long term (i.e 10 years). Results indicate that SST, monsoon, cyclone, and flooding can affect Chl-a concentration but the effect of monsoon, cyclone, and flooding is temporal, and normally reduces over time
Ross, Robert P.; Grams, Paul E.
Closure of Glen Canyon Dam in 1963 dramatically changed discharge and sediment supply to the downstream Colorado River in Marble and Grand Canyons. Magnitudes of seasonal flow variation have been suppressed, while daily fluctuations have increased because of hydropower generation. Lake Powell, the upstream reservoir, traps all sediment, leaving the Paria and Little Colorado Rivers as the main suppliers of fine sediment to the system below Glen Canyon Dam. The reduction in sediment supply, along with changes in discharge, have resulted in finesediment deficit (Topping et al., 2000), leading to a decrease in the size and number of alluvial sandbars (Schmidt and Graf, 1990; Schmidt et al., 2004). However, the understanding of these important spatial and temporal changes in sandbars located along the banks of the river have been limited to infrequent measurements mostly made by direct visitation and topographic surveying (Hazel et al., 2010). Aerial photographs are the only data available from which it is possible to evaluate changes in alluvial deposits at a large number of sites and compare recent conditions with those that existed prior to the initiation of ground-based monitoring in the early 1990s. Previous studies have evaluated the effects of Glen Canyon Dam on sandbars by analysis of comprehensive maps of surficial geology that are based on seven sets of aerial imagery taken between 1935 and 1996 for selected reaches in the first 120 km downstream from Lees Ferry, Arizona (Figure 1). These studies showed that the area of exposed sand in eddy-deposition zones was less in the post-dam period than in the pre-dam period (Leschin and Schmidt, 1995; Schmidt et al., 1999b; Sondossi, 2001, Sondossi and Schmidt, 2001, Schmidt et al., 2004). In this study, we extend these analyses to encompass a 74-year period by including maps of sand deposits visible in aerial imagery taken in 2002, 2005, and 2009 for the same reaches that were mapped in the earlier studies. Results
Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.
Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to
Shagarova, Lyudmila; Muratova, Mira; Abuova, Sholpan
The impact of oil-producing facilities on the environment is caused by toxicity of hydrocarbons and by-products, a variety of chemicals used in industrial processes, as well as specificity of production, treatment, transportation and storage of oil and oil products. To predict the state of the geological environment, scientists carry out investigations, which help to choose the optimal strategy for creation of the expert system taking into account simulations and to provide efficient use of available environmentally relevant information related to the current state of the geological environment. The expert system is a complex of interconnected blocks, one of which is the information on the presence of oil pollution, which can be identified using satellite imagery. The satellite imagery has practical application in monitoring of oil pollution, as it allows specialists to identify oil spills remotely and to determine their characteristics based on the differentiation of the surface reflectance spectra. Snapshots are used to estimate the area of oil-contamination and location of spills. To detect contaminants it is necessary to perform the following steps in processing of the remote sensing data: - Identify and isolate all the dark deformations in the satellite images, as a result of processing of segmentation and threshold processing; - Calculate statistical parameters of dark deformations, i.e., signs similar to areas prone to contamination. These signs are related to the geometry of formation, their physical changes (backscattering value) and the image context; - Classify the selected spectral anomalies as oil pollution and oil sludge. On the basis of classification of satellite imagery, the objects of oil pollution are detected and deciphering signs are analyzed in order to refer classified objects to implicit or explicit contaminations. To detect oil pollution, pixels are classified into categories with learning on the given areas with creation of the
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....
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....
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....
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....
Davis, Bruce A.; Schmidt, Nicholas; Jensen, John R.; Cowen, Dave J.; Halls, Joanne; Narumalani, Sunil; Burgess, Bryan
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.
吕玉凤; 修晓龙; 郭玉斌; 陈哲锋
The maturity and development of remote sensing technology provides a scientific method and means for mine environmental monitoring and management.This paper,by taking the high spatial resolution re-mote sensing data (QuickBird) as the main information source,and through the computer image processing,uses the man-machine interactive interpretation method to extract the mine development area condition,mine geologi-cal hazard and mine environment restoration management,among other remote sensing information.The paper makes the work area mine environment remote sensing monitoring chart,and with the appropriate field verifica-tion,finally achieves the goal of mine environment monitoring.%遥感技术的不断成熟与发展,为矿山环境监测治理提供了科学的方法和手段.本文以高空间分辨率遥感数据(QuickBird影像)为主要信息源,通过计算机图像处理,采用人机交互解译方式,提取矿山开发占地状况、矿山地质灾害及矿山环境恢复治理等遥感信息,制作工作区矿山环境遥感监测图,配合适当的野外验证,最终达到对矿山环境进行监测的目的.
Schott, John R
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
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
结合国际碳排放气体浓度遥感监测最新研究进展,介绍了碳排放监测方法,以及碳排放气体浓度遥感监测技术(包括热红外、太阳波谱、主动遥感监测技术).并详细介绍了目前已在使用和未来将采用的监测主要碳排放气体的几种星载传感器,并对这些传感器已获取的监测结果进行了详细分析.%Global climate warming has become the focus question of international global climate change research, and is an important factor influencing world economy, political situation, and ecological environment Produced carbon emission gases such as CO2, CH4, N2O, etc. caused by human activity are the main reason for global warming. In order to forecast future climate change and construct accurate carbon cycle model, monitoring accuracy of gas concentration from carbon emission must be improved. In the present paper, the newest progress in the international research results about monitoring gas concentration from carbon emissions by remote sensing was considered, monitoring method for carbon emissions was introduced, and remotely sensed monitoring technology about gas concentration from carbon emissions (including thermal infrared, sun spectrum, active remote sensing monitoring technology) was stated. In detail, several present and future satellite sensors were introduced (including TOVS, AIRS, IASI, SCIAMACHY, GOSAT, OCO, A-SCOPE and ASCENDS), and monitoring results achieved by these sensors were analyzed.
周进生; 牛建英; 张旭; 于艳蕊
矿山遥感监测评估是通过遥感监测手段获得对矿产资源开发利用状况、矿山环境和矿产资源规划执行情况的评判,为改进矿产资源规划、整顿矿业秩序、治理矿山环境等提供依据。根据矿山遥感监测实施效果评估的对象多、内容多、应用面广及难度大等特点,提出了矿产资源监管效果、效率和效益3个一级指标,9个二级指标的评估体系,并根据实验性评估结论提出简化指标体系、侧重连续监测区动态评估等建议。%Remote sensing monitoring is used by mine remote sensing monitoring and assessment so as to understand the situation of mineral resources development, mining environment and evaluate mineral resource planning implementation, thus providing the basis for mineral resources planning, mining order rectifying and mine environment governing. The authors analyzed the situation of evaluating the implementation effect of the mine remote sensing monitoring, which is characterized by numerous objects and contents, wide applications and considerable difficulties. In view of such a complex situation, this paper puts forward the index evaluation system for the mineral resources monitoring result, benefit and efficiency, which consists of three primary and nine secondary indexes. According to the experimental evaluation conclusion, some constructive suggestions, such as simplification of the index system and emphasis on the dynamic assessment of continuous monitoring area, have been put forward in this paper.
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
White, P. G.
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.
Hawat, Toufic-Michel; Camy-Peyret, Claude; Torguet, Roger J.
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.
Barrios, M.; Verstraeten, W. W.; Amipour, S.; Wambacq, J.; Aerts, J.-M.; Maes, P.; Berckmans, D.; Lagrou, K.; van Ranst, M.; Coppin, P.
Lyme disease and Hanta virus infection are the result of the conjunction of several climatic and ecological conditions. Although both affections have different causal agents, they share an important characteristic which is the fact that rodents play an important role in the contagion. One of the most important agents in the dispersion of these diseases is the bank vole (Clethrionomys glareoulus). The bank vole is a common host for both, the Borrelia bacteria which via the ticks (Ixodes ricinus) reaches the human body and causes the Lyme disease, and the Nephropatia epidemica which is caused by Puumala Hantavirus and affects kidneys in humans. The prefered habitat of bank voles is broad-leaf forests with an important presence of beeches (Fagus sylvatica) and oaks (Quercus sp.) and a relatively dense low vegetation layer. These vegetation systems are common in West-Europe and their dynamics have a great influence in the bank voles population and, therefore, in the spreading of the infections this study is concerned about. The fact that the annual seed production is not stable in time has an important effect in bank voles population and, as it has been described in other studies, in the number of reported cases of Hanta virus infections and Lyme disease. The years in which an abundant production of seeds is observed are referred to as mast years which are believed to obey to cyclic patterns and to certain climatologically characteristics of the preceding years. Statistical analysis have confirmed the correlation in the behaviour of the number of infected cases and the presence of mast years. This project aims at the design of a remote sensing based system (INFOPRESS - INFectious disease Outbreak Prediction REmote Sensing based System) that should enable local and national health care instances to predict and locate the occurrence of infection outbreaks and design policies to counteract undesired effects. The predictive capabilities of the system are based on the
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
Leben, R. R.; Shannon, M. R.
Whale sharks, Rhincodon Typus, congregate annually in the coastal waters northeast of the Yucatán Peninsula from May through mid-September, with peak abundance in occurring between late July and the middle of August. This coincides with seasonal upwelling along the northern Yucatán coast and the eastern margin of the Yucatán shelf. Remote sensing data, including ocean color, sea surface temperature, ocean vector winds, and satellite altimetry, are used to characterize the physical environment supporting this unique coastal ecology, which also has important economic ramifications for the region because of increasing ecotourism activities focused on whale shark aggregations.
Large-scale urban development is likely to be one of the primary sources of environmental change over the next decades, and more of this development will take place in India and China than in any other two countries. Rapid urban growth can have severe consequences for environmental sustainability creating an urgent need for alternative pathways to development. Satellite data and further geo-information data are used for landscape ecological evaluations, e.g. to predict structural diversity in landscape, to derive quantitative data on open space fragmentation and on interlink of biotope structures. Satellite images are just as much used to identify compensational areas for planning of building land in conurbations or to quantify landscape metrics by means of derived medium and high resolution satellite parameters in order to calculate neighbourhood relations of objects. Within the last two decades landscape structure indices or metrics have been implemented on remote sensing image data for different mapping scales. As original input data topographic maps, aerial photographic data as well as satellite images have been used. Thus the analysis of historical samples represents the base for the comparison of current as well as of future landscape structures and enables predicates to evaluate the dynamics of the landscape. Nature, in particular in the suburban cultural landscape is described regarding indicators such as structure (line or planar expansion, cutting, island areas, etc.), dynamics (entry of the modification processes) and texture (neighbourhood relations to other land use forms). This is based on the identification and computation of static and dynamic indicators that help providing a synthetic assessment of suburban landscapes. The indicators will also allow the comparison of the environment's condition in different conurbations. The static indicator includes proportion of urban land uses at different points in time, of road network cutting land uses, but
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.
Voronov, Nikolai; Dikinis, Alexandr
Modern technologies of remote sensing (RS) open wide opportunities for monitoring and increasing the accuracy and forecast-time interval of forecasts of hazardous hydrometeorological phenomena. The RS data do not supersede ground-based observations, but they allow to solve new problems in the area of hydrological and meteorological monitoring and forecasting. In particular, the data of satellite, aviation or radar observations may be used for increasing of special-temporal discreteness of hydrometeorological observations. Besides, what seems very promising is conjunctive use of the data of remote sensing, ground-based observations and the "output" of hydrodynamical weather models, which allows to increase significantly the accuracy and forecast-time interval of forecasts of hazardous hydrometeorological phenomena. Modern technologies of monitoring and forecasting of hazardous of hazardous hydrometeorological phenomena on the basis of conjunctive use of the data of satellite, aviation and ground-based observations, as well as the output data of hydrodynamical weather models are considered. It is noted that an important and promising method of monitoring is bioindication - surveillance over response of the biota to external influence and behavior of animals that are able to be presentient of convulsions of nature. Implement of the described approaches allows to reduce significantly both the damage caused by certain hazardous hydrological and meteorological phenomena and the general level of hydrometeorological vulnerability of certain different-purpose objects and the RF economy as a whole.
Full Text Available Stone pine stand of Castel Fusano (Rome burnt on July the 4th 2000 during a huge wildfire. As a consequence of the fire an intensive natural sexual and asexual regeneration began. In order to monitor such a regeneration field surveys were carried out in 2003 and 2006 in sample plots. Remotely sensed high resolution images from Ikonos and Quick Bird were acquired for the same years. The purpose of this work is to test different methodologies for modeling existing relationships between remotely sensed images and ground collected data in order to estimate and to map both sexual and asexual regeneration. For such a purpose different methodologies were tested: step-wise Muliple Linear Regression, Neural Networks (Relevance-Vector-Machine and the Multi-Layered-Perceptron and the k-Nearest-Neighbors. These activities were carried out within the framework of the GRINFOMED-MEDIFIRE also developing a specific software named Spatial Forest Modeler (SFM able to analyze existing relationships between remotely sensed variables and data collected in the field in order to identify the best available models to map and estimate the studied variables acquired on the basis of a field sampling design. The present paper presents data collected in the field, analysis and modeling methods and achieved results. The SFM software is also presented.
Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip
Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.
郭永旺; 金晓华; 杨建国; 李国强
Based on the theory of remote sensing technology, comparative studies were carried out between the analysis of satellite remote sensing data and the application of the 4 wavelength infrared radiator (Model EXOTECH - 100, made in USA) on the monitoring of wheat aphid infestation. Results indicated that the 4 wavelength infrared radiator was applicable, a system appliance was developed through the renovation of EXOTECH-100, and it was successfully used on the monitoring of wheat aphid infestation with appropriate efficiency and accuracy. Results also showed that it was impractical for the monitoring of wheat aphid infestation by the analysis of satellite remote sensing data due to the limitation on its accession and high costs.%根据遥感技术原理，对卫星遥感与四波段野外辐射计(EXOTECH-100美国)在麦蚜灾害监测中的使用情况进行了研究比较。结果表明，四波段野外辐射计具有很好的适用性。并在此基础上，通过对四波段野外辐射计EXOTECH-100进行改造，自制了病虫害监测仪，在麦蚜灾害遥感监测中成功使用，提高监测效率和测量的准确率。卫星遥感由于成本高、可用数据有限，不便于在麦蚜灾害监测中应用。
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.
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.
Ustinov, Eugene A
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...
周磊; 武建军; 张洁
Drought is a serious natural disaster. It is doing increasingly damage to the human environment as the drought events occur more frequently. Real-time and effective drought monitoring is an effective means to reduce the losses caused by drought. Since the beginning of 20th century, a lot of drought indices have been de-veloped for monitoring the occurrence and variation of drought. Drought is a complex natural disaster. Howev-er, each drought index has its own advantages and weaknesses in drought monitoring. Almost all the drought indices are based on specific geographical and temporal scales;it is difficult to spread its applicability all over the world. Because of the meteorological drought indices using discrete, point-based meteorological measure-ments collected at weather station locations, the results have restricted level of spatial precision for monitoring drought patterns. Remote sensing technology provides alternative data for operational drought monitoring, with advanced temporal and spatial characteristics. However, additional information still needs to be incorpo-rated so as to thoroughly explain the anomaly in vegetation caused by drought. Besides, to achieve a more ac-curate description of drought characteristics, drought intensity differences caused by vegetation type, tempera-ture, elevation, manmade irrigation, and other factors under the same water condition must be considered. Therefore, effective drought monitoring indicator should both reflect soil moisture, vegetation condition and take into account vegetation type, temperature, and man-made factors leading to regional drought differences. Aiming at the problem mentioned above, the satellite based drought indices, and integrated meteorological and remote sensed drought indices was reviewed in our research. Firstly, this paper summarized the widely used drought monitoring models which were based on remote sensing data. The remote sensing drought monitoring approach was summarized by dividing
Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin
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.
Esaias, W. E.
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.
This study focused on the water quality of the Guanting Reservoir,a possible auxiliary drinking water source for Beijing.Through a remote sensing (RS)approach and using Landsat 5 Thematic Mapper (TM)data,water quality retrieval models were established and analyzed for eight common water quality variables,including algae content,turbidity,and concentrations of chemical oxygen demand,total nitrogen,ammonia nitrogen,nitrate nitrogen,total phosphorus,and dissolved phosphorus.The results show that there exists a statistically significant correlation between each water quality variable and remote sensing data in a slightly-polluted inland water body with fairly weak spectral radiation.With an appropriate method of sampling pixel digital numbers and multiple regression algorithms,retrieval of the algae content,turbidity,and nitrate nitrogen concentration was achieved within 10% mean relative error,concentrations of total nitrogen and dissolved phosphorus within 20%,and concentrations of ammonia nitrogen and total phosphorus within 30%.On the other hand,no effective retrieval method for chemical oxygen demand was found.These accuracies were acceptable for the practical application of routine monitoring and early warning on water quality safety with the support of precise traditional monitoring.The results show that performing the most traditional routine monitoring of water quality by RS in relatively clean inland water bodies is possible and effective.
Pena, A.; Bay Hasager, C.; Lange, J. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark) (and others
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)
Yu, Kegen; Rizos, Chris; Burrage, Derek; Dempster, Andrew G.; Zhang, Kefei; Markgraf, Markus
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.
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
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
Fingas, Merv; Brown, Carl
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.
Benoit, Lionel; Pham, Ha-Thai; Trouvé, Emmanuel; Vernier, Flavien; Moreau, Luc; Martin, Olivier; Thom, Christian; Briole, Pierre
The Argentière glacier in the French Alps (Mont-Blanc massif) is a 10 km long glacier covering 19 km². Its flow on a large scale has been studied for over a hundred years by glaciologists, but the time and space fluctuations of its flow are still poorly documented. We selected a small area of the glacier, about 1 km upstream of the Lognan serac fall to measure the glacier flow with in-situ GPS measurements combined with time series of ground based pictures and time series of synthetic aperture radar images from the TerreSAR-X satellite. The experiment took place during two months between September and November 2013 with a network of thirteen single-frequency GPS receivers (eleven set up on the glacier and two on the nearby bedrock) deployed in the field with a sampling rate of 30s. Our data processing allows us to estimate epoch by epoch coordinates of each GPS site with a centimetric precision. The main interest of this approach is twofold : the monitoring of the temporal evolution of the flow and the providing of ground control points for the local and satellite remote sensing imagery. The average velocities of the stations is around 15 cm/day with peaks reaching 25cm/day lasting a few hours to one day after rainfalls or cooling periods. We explain these accelerations as the consequence of an increased basal water pressure. The strain tensor analysis shows a good consistency between the main strain axis and the orientation of the cracks on both sides of the glacier. However, available only at eleven points, the GPS data can not in any case give a picture of the overall deformation of the glacier. In order to map the glacier flow as a whole, including crevasse areas or serac falls, two automatic digital cameras were installed during the experiment on the bedrock on the shore of the glacier with acquisitions every three hours during day time. The processing of the stereo pairs produces maps in which the pixels coordinates (and their changes) are estimated with a
Tsalyuk, M.; Kelly, M.; Getz, W.
Rangeland ecosystems cover more than fifty percent of earth's land surface, host considerable biodiversity and provide vital ecosystem services. However, rangelands around the world face degradation due to climate change, land use change and overgrazing. Human-driven changes to fire and grazing regimes enhance degradation processes. The purpose of this research is to develop a remote sensing methodology to characterize the structure and composition of savanna vegetation, in order to improve the ability of conservation managers to monitor and address such degradation processes. Our study site, Etosha National Park, is a 22,270 km^2 semi-arid savanna located in north-central Namibia. Fencing and provision of artificial water sources for wildlife have changed the natural grazing patterns, which has caused bush encroachment and vegetation degradation across the park. We used MODIS and Landsat ETM+ 7 satellite imagery to map the vegetation type, dominant species, density, cover and biomass of herbaceous and woody vegetation in Etosha. We used imagery for 2007-2012 together with extensive field sampling, both in the wet and the dry seasons. At each sampling point, we identified the dominant species and measured the density, canopy size, height and diameter of the trees and shrubs. At only 31% of the sampling points, the identified vegetation type matched the class assigned at the 1996 classification. This may indicate significant habitat modifications in Etosha. We used two parallel analytical approaches to correlate between radiometric and field data. First, we show that traditional supervised classification identifies well five classes: bare soil, grassland, steppe, shrub savanna and tree savanna. We then refined this classification to enable us to identify the species composition in an area utilizing the phenological differences in timing and duration of greenness of the dominant tree and shrub species in Etosha. Specifically, using multi-date images we were able to
Shukla, S.; Khire, M. V.; Gedam, S. S.
Faster pace of urbanization, industrialization, unplanned infrastructure developments and extensive agriculture result in the rapid changes in the Land Use/Land Cover (LU/LC) of the sub-tropical river basins. Study of LU/LC transformations in a river basin is crucial for vulnerability assessment and proper management of the natural resources of a river basin. Remote sensing technology is very promising in mapping the LU/LC distribution of a large region on different spatio-temporal scales. The present study is intended to understand the LU/LC changes in the Upper Bhima river basin due to urbanization using modern geospatial techniques such as remote sensing and GIS. In this study, the Upper Bhima river basin is divided into three adjacent sub-basins: Mula-Mutha sub-basin (ubanized), Bhima sub-basin (semi-urbanized) and Ghod sub-basin (unurbanized). Time series LU/LC maps were prepared for the study area for a period of 1980, 2002 and 2009 using satellite datasets viz. Landsat MSS (October, 1980), Landsat ETM+ (October, 2002) and IRS LISS III (October 2008 and November 2009). All the satellite images were classified into five LU/LC classes viz. built-up lands, agricultural lands, waterbodies, forests and wastelands using supervised classification approach. Post classification change detection method was used to understand the LU/LC changes in the study area. Results reveal that built up lands, waterbodies and agricultural lands are increasing in all the three sub-basins of the study area at the cost of decreasing forests and wastelands. But the change is more drastic in urbanized Mula-Mutha sub-basin compared to the other two sub-basins.
Full Text Available This research is focused on gully erosion mapping and monitoring at multiple spatial scales using multi-source remote sensing data of the Sancha River catchment in Northeast China, where gullies extend over a vast area. A high resolution satellite image (Pleiades 1A, 0.7 m was used to obtain the spatial distribution of the gullies of the overall basin. Image visual interpretation with field verification was employed to map the geometric gully features and evaluate gully erosion as well as the topographic differentiation characteristics. Unmanned Aerial Vehicle (UAV remote sensing data and the 3D photo-reconstruction method were employed for detailed gully mapping at a site scale. The results showed that: (1 the sub-meter image showed a strong ability in the recognition of various gully types and obtained satisfactory results, and the topographic factors of elevation, slope and slope aspects exerted significant influence on the gully spatial distribution at the catchment scale; and (2 at a more detailed site scale, UAV imagery combined with 3D photo-reconstruction provided a Digital Surface Model (DSM and ortho-image at the centimeter level as well as a detailed 3D model. The resulting products revealed the area of agricultural utilization and its shaping by human agricultural activities and water erosion in detail, and also provided the gully volume. The present study indicates that using multi-source remote sensing data, including satellite and UAV imagery simultaneously, results in an effective assessment of gully erosion over multiple spatial scales. The combined approach should be continued to regularly monitor gully erosion to understand the erosion process and its relationship with the environment from a comprehensive perspective.
Shanjun Liu; Han Wang; Jianwei Huang; Lixin Wu
Landslide is one of the multitudinous serious geological hazards. The key to its control and reduction lies on dynamic monitoring and early warning. The article points out the insufficiency of traditional measuring means applied for large-scale landslide monitoring and proposes the method for extensive landslide displacement field monitoring using high-resolution remote images. Matching of cognominal points is realized by using the invariant features of SIFT algorithm in image translation, rotation, zooming, and affine transformation, and through recognition and comparison of characteristics of high-resolution images in different landsliding periods. Following that, landslide displacement vector field can be made known by measuring the distances and directions between cognominal points. As evidenced by field application of the method for landslide monitoring at West Open Mine in Fushun city of China, the method has the attraction of being able to make areal measurement through satellite observation and capable of obtaining at the same time the information of large-area intensive displacement field, for facilitating automatic delimitation of extent of landslide displacement vector field and sliding mass. This can serve as a basis for making analysis of laws governing occurrence of landslide and adoption of countermeasures.
Geymen, Abdurrahman; Baz, Ibrahim
The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation.
Rodríguez-González, Patricia María; Albuquerque, António; Martínez-Almarza, Miguel; Díaz-Delgado, Ricardo
Implementing long-term monitoring programs that effectively inform conservation plans is a top priority in environmental management. In floodplain forests, historical pressures interplay with the complex multiscale dynamics of fluvial systems and require integrative approaches to pinpoint drivers for their deterioration and ecosystem services loss. Combining a conceptual framework such as the Driver-Pressure-State-Impact-Response (DPSIR) with the development of valid biological indicators can contribute to the analysis of the driving forces and their effects on the ecosystem in order to formulate coordinated conservation measures. In the present study, we evaluate the initial results of a decade (2004-2014) of floodplain forest monitoring. We adopted the DPSIR framework to summarize the main drivers in land use and environmental change, analyzed the effects on biological indicators of foundation trees and compared the consistency of the main drivers and their effects at two spatial scales. The monitoring program was conducted in one of the largest and best preserved floodplain forests in SW Europe located within Doñana National Park (Spain) which is dominated by Salix atrocinerea and Fraxinus angustifolia. The program combined field (in situ) surveys on a network of permanent plots with several remote sensing sources. The accuracy obtained in spectral classifications allowed shifts in species cover across the whole forest to be detected and assessed. However, remote sensing did not reflect the ecological status of forest populations. The field survey revealed a general decline in Salix populations, especially in the first five years of sampling -a factor probably associated with a lag effect from past human impact on the hydrology of the catchment and recent extreme climatic episodes (drought). In spite of much reduced seed regeneration, a resprouting strategy allows long-lived Salix individuals to persist in complex spatial dynamics. This suggests the beginning
李崇贵; 斯林; 赵宪文
The components and functions of all parts of forest volume dynamic monitoring system based on remote sensing (RS), geographic information system (GIS) and the global positioning system (GPS) are presented. The various volume estimate models included in the system are sketched. The action and application of the system in forest resource quantitative monitoring is analyzed through practical example.
Peterson, D. L.
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.
The main environmental issues affecting the broad acceptability of nuclear power plant are the emission of radioactive materials, the generation of radioactive waste, and the potential for nuclear accidents. All nuclear fission reactors, regardless of design, location, operator or regulator, have the potential to undergo catastrophic accidents involving loss of control of the reactor core, failure of safety systems and subsequent widespread fallout of hazardous fission products. Risk is the mathematical product of probability and consequences, so lowprobability and high-consequence accidents, by definition, have a high risk. NPP environment surveillance is a very important task in frame of risk assessment. Satellite remote sensing data had been applied for dosimeter levels first time for Chernobyl NPP accident in 1986. Just for a normal functioning of a nuclear power plant, multitemporal and multispectral satellite data in complementarily with field data are very useful tools for NPP environment surveillance and risk assessment. Satellite remote sensing is used as an important technology to help environmental research to support research analysis of spatio-temporal dynamics of environmental features nearby nuclear facilities. Digital processing techniques applied to several LANDSAT, MODIS and QuickBird data in synergy with in-situ data are used to assess the extent and magnitude of radiation and non-radiation effects on the water, near field soil, vegetation and air. As a test case the methodology was applied for for Nuclear Power Plant (NPP) Cernavoda, Romania. Thermal discharge from nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Canal and Danube River. Water temperatures captured in thermal IR imagery are correlated with meteorological parameters. If during the winter thermal plume is localized to an area of a few km of NPP, the temperature difference between the plume and non-plume areas being about 1.5 oC, during summer and fall , is
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.
Jiang, Shu; Wen, Bao-Ping; Zhao, Cheng; Li, Rui-Dong; Li, Zhi-Heng
Slow-moving landslides generally are long-lived and characterized by continuous movement with some fluctuation in sliding rate following changes of environmental factors, such as rainfall and earthquake. Analysis on kinematics of this type of landslide is essential for understanding its mechanism and identifying causal factors controlling its movement behavior. This paper presents a study on kinematics of a giant slow-moving landslide in northwest China, called the Xieliupo landslide, which is about 72 × 106 m3 in volume and has been slowly moving for more than 100 years. This study is conducted using archival high resolution remote sensing images from multi-sources over a period about 43 years and the data from 15-month GPS monitoring. Six sets of multi-source remote sensing images in 1969, 1971, 2004, 2008, 2010 and 2012 with spatial resolution higher than 2.5 m were used, and GPS monitoring data were recorded from September 2012 to December 2013. Obvious geomorphologic changes identified from the images in 1971 and 2004 confirm that this landslide did move slowly in the past. Quantitative analysis reveals that movement of the landslide was persistent and behaved in a block by block mode with the greatest and the least velocities in its middle and lower parts, respectively. Distance measurement between the homologous point pairs on the orthorectified images in 2005, 2010 and 2012 indicates that annual ground displacement of the landslide ranged from 0.52 m to 6.54 m in the seven years. GPS monitoring data shows that the landslide ground displacement in the 15 months varied from 0.49 m to 2.91 m, and annually between 0.39 m and 2.33 m, with a rather uniform movement pattern as identified using the remote sensing images. GPS monitoring results also reveal that the landslide movement is intermittent inter-annually. It is further discussed that movement behavior of the landslide is largely controlled by its topography with great influence of the active fault along
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.
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
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
TIAN Xiao-rui; Douglas J. Mcrae; SHU Li-fu; WANG Ming-yu; LI Hong
Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.
Full Text Available The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.
Vannah, Benjamin; Chang, Ni-Bin
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.
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.
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.
Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.
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.
Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...
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.
Duggin, M. J.; Whitehead, V.
Although considerable progress has been made in applying remote sensing technology to vegetation monitoring, considerable problems still exist in the improvement of techniques for crop type discrimination, stress detection on a large scale, and stress quantification. In this paper, some of the problems remaining in the operational use of remote sensing technology for vegetation stress detection are discussed, and directions in which some of these problems might be solved are proposed.
Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu
Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.
Sáenz, N. A.; Paez, D. E.; Arango, C.
An empirical relationship of Total Suspended Sediments (TSS) concentrations and reflectance values obtained with Drones' aerial photos and processed using remote sensing tools was set up as the main objective of this research. A local mathematic algorithm for the micro-watershed of the Teusacá River at La Calera, Colombia, was developed based on the computing of four component of bands from consumed-grade cameras obtaining from each their corresponding reflectance values from procedures for correcting digital camera imagery and using statistical analysis for study the fit and RMSE of 25 regressions. The assessment was characterized by the comparison of reflectance values and 34 in-situ data measurements concentrations between 1.6 and 33 mg L-1 taken from the superficial layer of the river in two campaigns. A large data set of empirical and referenced algorithm from literature were used to evaluate the accuracy and precision of the relationship. For estimation of TSS, a higher accuracy was achieved using the Tassan's algorithm with the BAND X/ BANDX ratio. The correlation coefficient with R2 = X demonstrate the feasibility of use remote sensed data with consumed-grade cameras as an effective tool for a frequent monitoring and controlling of water quality parameters such as Total Suspended Solids of watersheds, these being the most vulnerable and less compliance with environmental regulations.
N. A. Sáenz
Full Text Available An empirical relationship of Total Suspended Sediments (TSS concentrations and reflectance values obtained with Drones’ aerial photos and processed using remote sensing tools was set up as the main objective of this research. A local mathematic algorithm for the micro-watershed of the Teusacá River at La Calera, Colombia, was developed based on the computing of four component of bands from consumed-grade cameras obtaining from each their corresponding reflectance values from procedures for correcting digital camera imagery and using statistical analysis for study the fit and RMSE of 25 regressions. The assessment was characterized by the comparison of reflectance values and 34 in-situ data measurements concentrations between 1.6 and 33 mg L−1 taken from the superficial layer of the river in two campaigns. A large data set of empirical and referenced algorithm from literature were used to evaluate the accuracy and precision of the relationship. For estimation of TSS, a higher accuracy was achieved using the Tassan’s algorithm with the BAND X/ BANDX ratio. The correlation coefficient with R2 = X demonstrate the feasibility of use remote sensed data with consumed-grade cameras as an effective tool for a frequent monitoring and controlling of water quality parameters such as Total Suspended Solids of watersheds, these being the most vulnerable and less compliance with environmental regulations.
Academy of Natural Sciences, Philadelphia, PA.
This publication identifies some of the general concepts of remote sensing and explains the image collection process and computer-generated reconstruction of the data. Monitoring the ecological collapse in coral reefs, weather phenomena like El Nino/La Nina, and U.S. Space Shuttle-based sensing projects are some of the areas for which remote…
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
LIANG Zong-bao; CHEN Wei-min; ZHU Yong; FU Yu-mei; XU Mou; YANG Hong
The research for remote monitoring of bridges is expected to develop methodologies and tools for collecting state data, monitoring the real-time status of the bridge from distance, and more importantly seeking a best way for remote transmission of bridge monitoring system by comparing the characteristics of each scheme. This paper focuses on the solutions to remote transmission for state monitoring of bridges, which deals with the remote transmission system based on PSTN (Public Service Telephone Network), wireless sensor monitoring system and remote transmission using SDH (Synchronous Digital Hierarchy) network. As a result, a combination of wireless sensor monitoring system and the remote sensing system using SDH network is proposed to be the considered way for remote state monitoring of bridges.
R. A., Majdaldin; Osunmadewa, B. A.; Csaplovics, E.; Aralova, D.
Land degradation, a phenomenon referring to (drought) in arid, semi-arid and dry sub-humid regions as a result of climatic variations and anthropogenic activities most especially in the semi-arid lands of Sudan, where vast majority of the rural population depend solely on agriculture and pasture for their daily livelihood, the ecological pattern had been greatly influenced thereby leading to loss of vegetation cover coupled with climatic variability and replacement of the natural tree composition with invasive mesquite species. The principal aim of this study is to quantitatively examine the vigour of vegetation in Sudan through different vegetation indices. The assessment was done based on indicators such as soil adjusted vegetation index (SAVI). Cloud free multi-spectral remotely sensed data from LANDSAT imagery for the dry season periods of 1984 and 2009 were used in this study. Results of this study shows conversion of vegetation to other land use type. In general, an increase in area covered by vegetation was observed from the NDVI results of 2009 which is a contrast of that of 1984. The results of the vegetation indices for NDVI in 1984 (vegetated area) showed that about 21% was covered by vegetation while 49% of the area were covered with vegetation in 2009. Similar increase in vegetated area were observed from the result of SAVI. The decrease in vegetation observed in 1984 is as a result of extensive drought period which affects vegetation productivity thereby accelerating expansion of bare surfaces and sand accumulation. Although, increase in vegetated area were observed from the result of this study, this increase has a negative impact as the natural vegetation are degraded due to human induced activities which gradually led to the replacement of the natural vegetation with invasive tree species. The results of the study shows that NDVI perform better than by SAVI.
Kim, Min-Kook; Daigle, John J.
Cadillac Mountain—the highest peak along the eastern seaboard of the United States—is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies—based on placing physical barriers and educational messages for visitors—have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to
Kim, Min-Kook; Daigle, John J
Cadillac Mountain--the highest peak along the eastern seaboard of the United States--is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies--based on placing physical barriers and educational messages for visitors--have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.
N A Sáenz; D E Paez; C Arango
An empirical relationship of Total Suspended Sediments (TSS) concentrations and reflectance values obtained with Drones' aerial photos and processed using remote sensing tools was set up as the main objective of this research...
Sabins, Floyd F., Jr.; Bailey, G. Bryan; Abrams, Michael J.
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.
Moore, H.J.; Boyce, J.M.; Schaber, G.G.; Scott, D.H.
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
Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.
A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.
Muralidharan, Govindarajan [Knoxville, TN; Britton, Charles L [Alcoa, TN; Pearce, James [Lenoir City, TN; Jagadish, Usha [Knoxville, TN; Sikka, Vinod K [Oak Ridge, TN
A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interface circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitter with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.
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…
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...
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.
JIANG Jingshan; DONG Xiaolong; LIU Heguang
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.
Vélez-Reyes, Miguel; Goodman, James A.; Castrodad-Carrau, Alexey; Jiménez-Rodriguez, Luis O.; Hunt, Shawn D.; Armstrong, Roy
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.
Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6e10% increases in respiratory and allergic health outcomes per interquartile range (3.97 mg m3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20e64) in the national study population. Risk estimates for air pollution and respiratory/ allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05).
Kegen, Yu; Rizos, Chris; Burrage, Derek; Dempster, Andrew; Zhang, Kefei; Markgraf, Markus
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 ...
Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasilki; Themistocleous, Kyriacos; Cuca, Branka; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter
Remote sensing science is increasingly being used to support archaeological and cultural heritage research in various ways. Satellite sensors either passive or active are currently used in a systematic basis to detect buried archaeological remains and to systematic monitor tangible heritage. In addition, airborne and low altitude systems are being used for documentation purposes. Ground surveys using remote sensing tools such as spectroradiometers and ground penetrating radars can detect variations of vegetation and soil respectively, which are linked to the presence of underground archaeological features. Education activities and training of remote sensing archaeology to young people is characterized of highly importance. Specific remote sensing tools relevant for archaeological research can be developed including web tools, small libraries, interactive learning games etc. These tools can be then combined and aligned with archaeology and cultural heritage. This can be achieved by presenting historical and pre-historical records, excavated sites or even artifacts under a "remote sensing" approach. Using such non-form educational approach, the students can be involved, ask, read, and seek to learn more about remote sensing and of course to learn about history. The paper aims to present a modern didactical concept and some examples of practical implementation of remote sensing archaeology in secondary schools in Cyprus. The idea was built upon an ongoing project (ATHENA) focused on the sue of remote sensing for archaeological research in Cyprus. Through H2020 ATHENA project, the Remote Sensing Science and Geo-Environment Research Laboratory at the Cyprus University of Technology (CUT), with the support of the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR) aims to enhance its performance in all these new technologies.
叶娜; 贾建军; 田静; 苏红波; 雒伟民; 张峰; 肖康
综述了目前国内外浒苔遥感监测方法,阐述了单波段阈值分割法、多波段比值法和辐射传输模型法的优缺点,指出多波段比值法是应用最广和有效的方法,主要有双波段比值法、归一化植被指数法、浮游植物指数法和归一化藻类指数法4种.辐射传输模型法主要用于水下悬浮浒苔的监测,目前应用较少,还处于起步阶段.而研究浒苔与其他浮游植物的差异,深入研究水下悬浮浒苔的遥感监测方法,发展解决现有监测能力不足与监测信息使用者需求之间矛盾的手段和方法是未来浒苔遥感监测的主要研究方向.%The massive bloom of the green macroalgae Ulvaprolifera is called "green tide". The "green tide" event frequently happens in the world and is known as an oceanic disaster due to its bad effects on the marine ecological environment, coastal scene, seashore tourism and water sports. Remote sensing has the advantages over the conventional methods in oceanic monitoring because of its great capabilities of large - area, multi - resolution, multi - spectrum, quick and dynamic observations. Remote sensing has become a necessary method in the study of the origin, spatial pattern, evolution, size and movement of "green tide". At present, 3 main approaches detecting Ulvaprolifera have been developed, which are single band threshold image segmentation method, multi - band ratio method and radiation transmission model method. The multi - band ratio method is most widely used, which includes two - band ratio algorithm, normalized differential vegetation index, floating algae index and normalized difference algae index. The method of radiation transmission model is mainly used to monitor Ulvaprolifera suspended in water, and its study is just in the initial stage. Further researches on distinguishing the difference between the spectrum of Ulvaprolifera and other type of floating algae, monitoring Ulvaprolifera suspended in water, solving
Luther, Joan E.; Carroll, Allen L.
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.
Rosenqvist, Ake; Imhoff, Marc; Milne, Anthony; Dobson, Craig
The Kyoto Protocol to the United Nations Framework Convention on Climate Change contains quantified, legally binding commitments to limit or reduce greenhouse gas emissions to 1990 levels and allows carbon emissions to be balanced by carbon sinks represented by vegetation. The issue of using vegetation cover as an emission offset raises a debate about the adequacy of current remote sensing systems and data archives to both assess carbon stocks/sinks at 1990 levels, and monitor the current and future global status of those stocks. These concerns and the potential ratification of the Protocol among participating countries is stimulating policy debates and underscoring a need for the exchange of information between the international legal community and the remote sensing community. On October 20-22 1999, two working groups of the International Society for Photogrammetry and Remote Sensing (ISPRS) joined with the University of Michigan (Michigan, USA) to convene discussions on how remote sensing technology could contribute to the information requirements raised by implementation of, and compliance with, the Kyoto Protocol. The meeting originated as a joint effort between the Global Monitoring Working Group and the Radar Applications Working Group in Commission VII of the ISPRS, co-sponsored by the University of Michigan. Tile meeting was attended by representatives from national government agencies and international organizations and academic institutions. Some of the key themes addressed were: (1) legal aspects of transnational remote sensing in the context of the Kyoto Protocol; (2) a review of the current and future and remote sensing technologies that could be applied to the Kyoto Protocol; (3) identification of areas where additional research is needed in order to advance and align remote sensing technology with the requirements and expectations of the Protocol; and 94) the bureaucratic and research management approaches needed to align the remote sensing
Woodcock, Curtis E.; Strahler, Alan H.; Franklin, Janet
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
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.
Remote Sensing is a scientific discipline of non-contact monitoring. It includes a range of technologies that span from aerial photography to advanced spectral imaging and analytical methods. This Session is designed to demonstrate contemporary practical applications of remote ...
S. K. Saha
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.
Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Murali Krishna Gumma,; Venkateswarlu Dheeravath,
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.
Helm, Neil R.; Edelson, Burton I.
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.
Rush, M.; Vernon, S.
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.
Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E. O. C.; Arai, Egidio; Simonetti, Dario; Achard, Frédéric
Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the
Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnett, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; van Donkelaar, Aaron; Peters, Paul A.; Johnson, Markey
Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6-10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m-3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20-64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is
Xiaoming Cao; Yiming Feng; Juanle Wang
This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981–2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981–2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.
Full Text Available This paper presents latest results from the combined use of SAR (Synthetic Aperture Radar remote sensing and GIS providing detailed insights into recent volcanic activity under Vatnajökull ice cap (Iceland. Glaciers atop active volcanoes pose a constant potential danger to adjacent inhabited regions and infrastructure. Besides the usual volcanic hazards (lava flows, pyroclastic clouds, tephra falls, etc., the volcano-ice interaction leads to enormous meltwater torrents (icelandic: jökulhlaup, devastating large areas in the surroundings of the affected glacier. The presented monitoring strategy addresses the three crucial questions: When will an eruption occur, where is the eruption site and which area is endangered by the accompanying jökulhlaup. Therefore, sufficient early-warning and hazard zonation for future subglacial volcanic eruptions becomes possible, as demonstrated for the Bardárbunga volcano under the northern parts of Vatnajökull. Seismic activity revealed unrest at the northern flanks of Bardárbunga caldera at the end of September 2006. The exact location of the corresponding active vent and therefore a potentially eruptive area could be detected by continuous ENVISAT-ASAR monitoring. With this knowledge a precise prediction of peri-glacial regions prone to a devastating outburst flood accompanying a possible future eruption is possible.
Cao, Xiaoming; Feng, Yiming; Wang, Juanle
This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981-2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981-2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.
O'Connor, Edel; Smeaton, Alan F.; O'Connor, Noel E.; Regan, Fiona
In this paper it is investigated how conventional in-situ sensor networks can be complemented by the satellite data streams available through numerous platforms orbiting the earth and the combined analyses products available through services such as MyOcean. Despite the numerous benefits associated with the use of satellite remote sensing data products, there are a number of limitations with their use in coastal zones. Here the ability of these data sources to provide contextual awareness, redundancy and increased efficiency to an in-situ sensor network is investigated. The potential use of a variety of chlorophyll and SST data products as additional data sources in the SmartBay monitoring network in Galway Bay, Ireland is analysed. The ultimate goal is to investigate the ability of these products to create a smarter marine monitoring network with increased efficiency. Overall it was found that while care needs to be taken in choosing these products, there was extremely promising performance from a number of these products that would be suitable in the context of a number of applications especially in relation to SST. It was more difficult to come to conclusive results for the chlorophyll analysis.
湿地是地球上最具生产力和最富生物多样性的生态系统之一。湿地具有很高的资源价值、经济价值、环境效益和多种生态功能。湿地研究己成为当前地理科学、环境科学和生态科学等多学科交汇研究的一个热门领域。目前国内外在对湿地研究过程中，采用遥感技术的关注焦点已逐渐从光学遥感转移到雷达遥感上。采用雷达遥感数据监测湿地的研究，经过了20—30年的研究历程，虽取得了一定的研究成果，但是面对复杂性较为突出的湿地生态系统来说，仍有诸多问题需要深入研究。本文从雷达遥感系统的主要参数波长、极化、入射角，以及湿地雷达遥感监测的主要相关专题时相、环境影响和采用的分析技术方面，回顾了国内外主要地理科学文献上发表的相关研究成果，并总结分析了研究结论和研究发展趋势。%Wetlands is important ecosystems with high productivity and abundant biology diversity. Wetlands have high resource values, economic values, environmental values and a variety of ecological functions. Wetlands research has become a highlighted domain that associates with geography, environment and ecology. The earliest article about wetlands monitoring by radar remote sensing appeared around 1970. Afterwards, many satellites radar sensors were launched, such as SEASAT, ERS, JERS-1, Radarsat, Envisat, ALOS and TerraSAR-X; many space shuttle radar sensors were used, such as SIR-A, SIR-B, SIR-C/X-SAR and SRTM; many airplane sensors were applied, such as AIRSAR, EMISAR and E-SAR. Researchers have published a lot of papers about wetlands and radar data. Monitoring wetlands by radar remote sensing have undergone for 20-30 years and yielded many achievements. But a great number of problems for complicated wetlands still need to be further researched. In this paper, main radar parameters including wave length, polarization, and incident angle were
Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.
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.
Crippen, Robert E.
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.
Jin, Shuanggen; Xie, Feiqin
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.
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...
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.
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.
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
Sai Kiran, M P R; Rajalakshmi, P; Acharyya, Amit
In hyperconnectivity scenario, managing the amount of data acquired from sensors in the Body Area Networks (BANs) is one of the major issues. In this paper we propose an on-chip context predictor based sparse sensing technology with smart transmission architecture which makes use of confidence interval calculation from the features that present in the data, thereby achieving statistical guarantee. The proposed architecture uses intelligent sparse sensing, which eradicates the collection of redundant data, thereby reducing the amount of data generated. For the performance analysis, we considered ECG data acquisition and transmission system. The proposed architecture when applied on the data collected from 10 patients reduces the duty cycle of the sensing unit to 27.99%, by achieving an energy saving of 72% and the mean deviation of sampled data from the original data is 2%.
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.
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.
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
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...
Monitoring the seasonal snow cover is important for several purposes. This report describes user requirements for hydrological models utilizing remotely sensed snow data. The information is mainly provided by operational users through a questionnaire. The report is primarily intended as a basis for other work packages within the Snow Tools project which aim at developing new remote sensing products for use in hydrological models. The HBV model is the only model mentioned by users in the questionnaire. It is widely used in Northern Scandinavia and Finland, in the fields of hydroelectric power production, flood forecasting and general monitoring of water resources. The current implementation of HBV is not based on remotely sensed data. Even the presently used HBV implementation may benefit from remotely sensed data. However, several improvements can be made to hydrological models to include remotely sensed snow data. Among these the most important are a distributed version, a more physical approach to the snow depletion curve, and a way to combine data from several sources. 1 ref.
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.
Richards, John A
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...
Lo, Shi-Wei; Wu, Jyh-Horng; Lin, Fang-Pang; Hsu, Ching-Han
With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.
Full Text Available With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.
李云; 徐伟; 吴玮
以汶川8.0级地震灾害中民政部门使用无人机采集数据、评估灾情、监测灾后恢复苇建进展情况为例,总结灾害监测无人机技术在灾害救助过程中的积极作用,归纳其技术范围,分析其应用方法以及在地震灾害监测评估中的突出应用,指出其技术应用优势和不足.最后,从该技术发展现状、应用程度和减灾救灾应用需求角度出发,指出灾害监测无人机技术在灾害预警监测、快速评估、恢复重建等方面广泛应用前景,并提出建立与完善重大自然灾害应急无人机监测体系.%Taking an example of Aviation Remote Sensing Unmanned Aerial Vehicle (ARS-UAV) applied for data collecting, assessment and monitoring of post-disaster rehabilitation by Ministry of Civil Affairs for the “M8. 0 Wenchuan earthquake”, the paper firstly summarizes the role, advantages and disadvantages of ARS-UAV for disaster rescue and restoration. Then, the prospect of ARS-UAV are discussed in the area of disaster management,especially in hazard monitoring, loss rapid assessment and victims relocation based on its technical features and disaster management demand. Finally, the monitoring system of using ARA-UAV ia proposed to be established and improved for large-scale disaster risk management.
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
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.
Liang, T.; Philipson, W. R. (Principal Investigator); Stanturf, J. A.
High altitude, color infrared aerial photography as well as imagery from Skylab and LANDSAT were used to inventory timber and assess potential sites for industrial development in New York State. The utility of small scale remotely sensed data for monitoring clearcutting in hardwood forests was also investigated. Consultation was provided regarding the Love Canal Landfill as part of environment protection efforts.
This paper, presented in poster form addresses the use of radar remote sensing in coastal zone management. Current and future applications in The Netherlands are highlighted with an outlook to technology and models that are involved. Applications include monitoring of the environment, oil spills, sh
Alistair M. S. Smith; Crystal A. Kolden; Wade T. Tinkham; Alan F. Talhelm; John D. Marshall; Andrew T. Hudak; Luigi Boschetti; Michael J. Falkowski; Jonathan A. Greenberg; John W. Anderson; Andrew Kliskey; Lilian Alessa; Robert F. Keefe; James R. Gosz
Climate change is altering the species composition, structure, and function of vegetation in natural terrestrial ecosystems. These changes can also impact the essential ecosystem goods and services derived from these ecosystems. Following disturbances, remote-sensing datasets have been used to monitor the disturbance and describe antecedent conditions as a means of...
This paper, presented in poster form addresses the use of radar remote sensing in coastal zone management. Current and future applications in The Netherlands are highlighted with an outlook to technology and models that are involved. Applications include monitoring of the environment, oil spills,
Leifer, Ira; Tratt, David M.; Realmuto, Vincent J.; Gerilowski, Konstantin; Burrows, John P.
Atmospheric pollution affects human health, food production, and ecosystem sustainability, causing environmental and climate change. Species of concern include nitrogen oxides, sulfur dioxide (SO2 ), and the greenhouse gases (GHG) methane (CH4 ) and carbon dioxide (CO2 ). Trace gas remote sensing can provide source detection, attribution, monitoring, hazard alerts, and air quality evaluation.
Yan; ZHANG; Baoguo; WU; Dong; WANG
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.
Oil pollution belongs to the most widespread man-caused emergency situations considerably harming natural ecosystems and different types of economic activity fishing tourism and other About 50 of oil pollution of the World Ocean is on transportation where 75 is on the ordinary process of transportation related to the illicit vessel discharges such as ballasts water tank washings flowing of engine-room and other But this type of pollution can be considerably decreased due to the effective monitoring and penalty system For monitoring of marine pollution the state inspections as a rule use marine or aviation facilities which are quite expensive limited by a day light and weather conditions and cover only a territorial waters The satellites SAR Synthetic Aperture Radar images instead can be used for studding the large equatorials and does not depend on cloud coverage season and daytime Oil discharged in the water damps gravity-capillary waves and changes the slope angle Thus oil spills could be viewed on the SAR images as black spots on an unpolluted sea surface However one of the problems in odder to create an operational integrated space-based monitoring system is an absence of various pilot researches to develop methodological principles for the unified algorithm of monitoring on international level To contribute to this need a pilot research on Oil Spills Monitoring in the Black and Azov Seas was conducted by SSPC Pryroda with a support of European Space Agency under the ERUNET project within the framework of
黄友昕; 刘修国; 沈永林; 刘诗诗; 孙飞
在利用遥感数据进行长时间、大范围农业干旱遥感监测过程中，如何针对不同区域、不同作物生长阶段选取最合适的监测指标，对于及时、准确地评估干旱对作物生长的影响，实现合理水资源调度和有效抗旱减灾决策都具有重要意义。该文以遥感监测农业干旱的适应性为论述主线，对常用的农业干旱遥感监测指标及其适应性评价方法，从4个方面进行了系统归纳总结：1）国内外农业干旱监测适用的遥感卫星数据源；2）监测农业干旱适用的光谱敏感波段；3）农业干旱遥感监测指标自身的适用性与局限性；4）农业干旱遥感监测指标适应性的评价方法。在此基础上，指出今后在农业干旱遥感监测指标及其区域适应性研究中，需综合考虑作物与其生长环境之间的关系；增加光谱信息，降低遥感数据获取过程中的信噪比；选择农业干旱遥感监测指标适宜的时空尺度；重点解决部分植被覆盖时，如何选择合适的监测指标；加强高光谱技术在精细农业干旱遥感监测指标反演中的研究；进一步在机理上发掘监测指标自身的敏感性和适应性等6个方面的问题及发展趋势。%Remote sensing technology is a promising means for agricultural drought monitoring in large area, and can continuously obtain long-term time series of crop drought information. Currently, quite a few agricultural drought monitoring indices based on remote sensing technology have been developed from different perspectives. However, different agricultural drought monitoring indices derived from remote sensing have obviously different temporal and spatial adaptability. Selecting the appropriate drought monitoring indices based on different regions and crop growth stages is vital for timely and accurate evaluation of drought impact on crops. It is also important for effective water resource management and drought
Teta, Roberta; Romano, Vincenza; Della Sala, Gerardo; Picchio, Stefano; De Sterlich, Carlo; Mangoni, Alfonso; Di Tullio, Giacomo; Costantino, Valeria; Lega, Massimiliano
Cyanobacterial blooms (CBs) are generally triggered by eutrophic conditions due to anthropogenic nutrient inputs to local waters (wastewater or contaminated waters). During the bloom, some species produce toxic secondary metabolites (cyanotoxins) that are dangerous for humans and animals. Here, a multidisciplinary strategy for an early detection and constant monitoring is proposed. This strategy combines remote/proximal sensing technology with analytical/biotechnological analyses. To demonstrate the applicability of this strategy, four anthropogenically-impacted sites were selected along the Campania coast of southwestern Italy, in the so called ‘Land of Fires’. The sites were observed using satellite and aircraft images during summer, 2015. Algal community composition was determined using spectrophotometric analysis for the detection of the cyanobacterial pigment phycocyanin (PC). Complementary metagenomic analysis revealed the taxonomic presence of cyanobacteria belonging to genera associated with strong eutrophic conditions. Key elements of this strategy are the combination and integration of applying different methodological approaches such as the parallel and combined use of satellite, aerial and in-situ data, the simplified multispectral image indexing and classification for a truly efficient method in detecting early blooms of cyanobacteria. The effectiveness of the strategy has been validated also by the specific taxa of cyanobacteria found in the examined areas that confirm the assumption that cyanobacterial blooms may serve as useful bioindicators of degraded water quality in coastal ecosystems. To our knowledge this is the first time that the presence of cyanobacteria has been observed in water bodies along the Campania coast.
Liu, L.; Zhou, J. S.
Mining activity has strongly impacted the sustainable socioeconomic development of resource-based cities. The systematic monitoring of the change in mining activity can provide evidence for the transition and future development of resource-based cities. This paper chose Qitaihe, one of the four coal mining cities in northeastern China as the study area. Remote sensing and Geographical Information Systems (GIS) technique, as well as methods on landscape pattern analysis were used to study the evolution of mining activity from 4 different periods over 58 years’ time. Results showed that the area of land used in mining increased by about six times during the study period with cultivated land the main type that contributed to this increase. Mining activity showed an eastward trend, developing from one concentration circle to four circles, from a disordered system to a relatively integrated system. It was also suggested that differentiated policies should be adopted in different mining circles. This study also provides a framework for future city planning and sustainable development.
Powers, W. F.
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.
Levine, J. S.; Allario, F.
The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions are reviewed. Future thrusts in remote sensing of the troposphere are also considered.
Schowengerdt, Robert A
Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa
Levine, J. S.; Allario, F.
The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions are reviewed. Future thrusts in remote sensing of the troposphere are also considered.
Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit
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
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.
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.
Henderson, Frederick B.
Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources
Full Text Available Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC. The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation. Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.
崔凯; 蒙继华; 左廷英
The paper analyzed the advantages and defects of the existing RS phenology monitoring methods, including threshold method, Logistic function fitting method, harmonic analysis method, moving average method, the maximum slope method, etc. , and then discussed the improving measures, finally forecasted the RS phenology monitoring method in the future.%分析了阈值法、Logistic函数拟合法、谐波分析法、滑动平均法、斜率最大值法等目前遥感物候监测方法的优点及存在的不足,并讨论了相应改进措施,对遥感作物物候监测方法进行了展望.
Remote sensing for land use dynamic monitoring to provide a large-scale, multi-temporal land use information, use remote sensing information in real time, efficient utilization of land resources, dynamic monitoring and timely control of land use change. Remote sensing of land use dynamic monitoring is an important research field of iaformation science, this paper describes a comprehensive method of dynamic monitoring of land use, and some common methods by analyzing the theory that these methods in the problems to be solved.%遥感技术为土地利用动态监测提供了大范围、多时相的土地利用信息，利用这些遥感信息可以实时、有效地对土地资源利用进行动态监测，及时掌握土地利用的变化。土地利用动态监测是遥感信息科学的重要研究领域，本文全面阐述了土地利用动态监测的方法，并通过分析一些常见的方法理论，指出这些方法中的有待解决的问题。
李宏科; 王万玉; 冯旭祥; 王永华
伺服系统是遥感卫星地面接收系统的重要组成部分，可靠性和安全性要求高。采用单进程、多线程、并行多模块的结构，设计伺服系统监控软件，实现了天线控制、设备监视、信息显示、数据处理、通信及伺服性能指标自动化测试等功能，具有实时性强，自动化程度高，容错性、可靠性及扩展性好等特点。该设计已用于实际工程项目中，实际使用结果表明该设计是合理可行的。%The sever system is an important component in the ground receiving system of the remote sensing satellite,and has high reliability and security. The structures of single process,multi⁃thread,and parallel multi⁃module are adopted to design the monitoring software for servo system. The functions of antenna control,equipment monitoring,information display,data pro⁃cessing,communications and automatic test of servo performance index were implemented. The software has the characteristics of good real⁃time performance,high automation level,good fault tolerance,excellent reliability and extensibility. This design was applied to the practical engineering projects. The practical use result shows that the design is reasonable and feasible.
Full Text Available Although, the threat posed by Typha invasion to wetland utilization has been widely acknowledged in Hadejia Nguru wetland, yet little or no monitoring has been done to quantify the extent and time analysis of the threat. Remote sensing and GIS techniques were used in this study to monitor the Spatio-temporal dynamics of Typha spp. invasion in the dry environment of Hadejia Nguru Wetlands of NE Nigeria. Satellites images of Band 1, 2, 3, and 4 from Landsat ETM+ were acquired between 2003 and 2015 and natural color from GeoEye-1 in 2016 where image classification, change detection and spatial statistics were performed. To evaluate the impact of Typha grass on the livelihood of the people, a field investigation involving administration of 200 questionnaires was conducted among the two major wetland users: the farmers and the fishermen. The result from the RS/GIS revealed that Typha grass recorded an astronomical growth of 1013 % between 2003 and 2009 and another incremental of 32 % in 2015. The ANOVA test on land cover change in 2003, 2009 and 2015 showed a significant variation in land cover and use changes at p<0.05. The findings from field survey showed that Typha grass accounted for 70% decrease in land available for farmland and subsequent reduction in crop output by 90%. It also accounted for 80% reduction in total fish caught as compared to non Typha infested land and open water. Strategic and selective weeding by mechanical and manual techniques was therefore suggested as control measures to save the wetland ecosystem and wetland users livelihood.
Choi, Y.; Kim, J.; Lin, S. Y.; Chen, W. C.
The changes of ice sheet in Greenland have been traced through various remote sensing observations. However, it was realised that the uncertainties in the observed change of ice sheet were not fully addressed. Therefore, we devised and tested a scheme employing multiple sensor satellite data and the data fusion to spatially and temporally monitor the migration of glacier with high accuracy. The test area was established in Russell glacier in western Greenland where the change of glacier has been obvious for the last century. Firstly, differential interferometric SAR (D-InSAR) campaigns using ALOS PALSAR pairs were applied to monitor the glacial change. In terms of data fusion aspect, we then employed pixel tracing method by co-registration of ALOS PRISM optical images over target area to compensate for any line-of-sight glacial movement resulted by the D-InSAR analysis. To securely trace individual pixel, high accuracy sub-pixel co-registration algorithm was developed. Meanwhile, PALSAR pairs were also applied to test the amplitude tracking method in the same manner. To address the temporal difference between the acquisition of SAR and optical images, the velocity vectors considering seasonal mean migration were interpolated. At last, the outputs from analyses were incorporated to build an effective 3D movement tracing over Russell glacier. Furthermore, in order to investigate the glacial migration process, the hydrodynamic simulations employing optical stereo pairs and InSAR DTMs over meltwater outflow channels, such as Akuliarusiarsuup Kuua and Qinnguata Kuussua from Russell glacier, were conducted simultaneously with the tracking of the geometric movement of glacier. The overall results were anticipated to be incorporated for the understanding of long term change of Russell glacier. Based on the output of this case study, the proposed method will be extended into a comprehensive scheme to tackle the issues of ice sheet change occurred in the Greenland.
Washington-Allen, R. A.; Twidwell, D. L., Jr.; Mendieta, V. P.; Delgado, A.; Redman, B.; Trollope, W. S.; Trollope, L.; Govender, N.; Smit, I.; Popescu, S. C.; de Bruno Austin, C.; Reeves, M. C.
The status and trend of degradation in the world’s Drylands, that support over 1.2 billion people, is unknown because monitoring & assessment has not occurred on a globally consistent basis and skilled personnel with a cultivated interest in natural resource science and management are lacking. A major monitoring dataset is the 37-year Landsat data archive that has been released free to the world, but this dataset requires persons who understand how to process and interpret this and similar datasets applicable to the desertification problem. The College of Agriculture & Life Sciences (COALS) at Texas A&M University (TAMU) has an initiative to provide undergraduates with both international and research experiences. The lead author used start-up money, USFS project funds for livestock footprint studies in the US, and seed money from COALS to 1) develop academic mentor contacts in Mozambique, Namibia, Botswana, South Africa, and Tunisia to prepare a National Science Foundation Research Experience for Undergraduates (NSF-REU) Site proposal and 2) launch a pilot REU for two TAMU undergraduate students. Mr. Delgado and Mr. Redman received lidar processing and visualization, field survey training on global positioning systems (GPS), terrestrial LIDAR, and ground penetrating radar technologies and conducted carbon change studies by collecting pre- and post-fire laser scans on experimental burn (EPB) sites in Texas and South Africa. Mr. Redman also developed GIS databases of Landsat timeseries for these EPBs and others in southern Africa. Mr. Delgado participated in the Savanna Fire Ignition Research Experiment (SavFIRE) in Kruger National Park (KNP) by collected laser scan data on 3 EPBs. He also received mentoring from Dr. Winston Trollope, a prominent fire ecologist, and Mr. Chris Austin both of Working with Fire International and Navashni Govender, KNP’s Fire Ecologist. He also was an active participant in a NASA sponsored workshop on remote sensing of global
Silva, Thiago S F; Costa, Maycira P F; Melack, John M; Novo, Evlyn M L M
Aquatic vegetation is an important component of wetland and coastal ecosystems, playing a key role in the ecological functions of these environments. Surveys of macrophyte communities are commonly hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. Also, many vegetation characteristics can be estimated from reflectance measurements, such as species composition, vegetation structure, biomass, and plant physiological parameters. However, proper use of these methods requires an understanding of the physical processes behind the interaction between electromagnetic radiation and vegetation, and remote sensing of aquatic plants have some particular difficulties that have to be properly addressed in order to obtain successful results. The present paper reviews the theoretical background and possible applications of remote sensing techniques to the study of aquatic vegetation.
Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola
The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best
H S Negi; N K Thakur; Rajeev Kumar; Manoj Kumar
Seasonal snow cover is a vital natural resource in the Himalaya. Monitoring of the areal extent of seasonal snow cover is important for both climatological studies as well as hydrological applications. In the present paper, snow cover monitoring was carried out to evaluate the region-wise accumulation and ablation pattern of snow cover in Pir Panjal and Shamshawari ranges of Kashmir valley. The study was carried out for the winter period between November and April of 2004–05, 2005–06 and 2006–07, using multi-temporal WiFS sensor data of IRS-1C/1D satellites. The study shows reduction in the areal extent of seasonal snow cover and rising trend of maximum temperature in three winters for the entire Kashmir valley. This has been validated with 20 years (1988– 89 to 2007–08) climatic conditions prevailed in both ranges of Kashmir valley. Region-wise study shows the spatial and temporal variability in seasonal snow cover within Kashmir valley. Advance melting was observed in Banihal and Naugam/Tangdhar regions than Gurez and Machhal regions. Different geographical parameters of these regions were studied to evaluate the influence on snow cover and it was observed that altitude and position of region with respect to mountain range are the deciding factors for retaining the seasonal snow cover for longer duration. Such region-wise study of snow cover monitoring, can provide vital inputs for planning the hydropower projects, development in habitat areas, recreational and strategic planning in the region.
Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling
In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.
Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton
Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.
Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc
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).
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.
Aparna, N.; Ramani, A. V.; Nagaraja, R.
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).
Velez-Rodriguez, Linda L. (Principal Investigator)
Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.
Bagli, Stefano; Pistocchi, Alberto; Mazzoli, Paolo; Borga, Marco; Bertoldi, Giacomo; Brenner, Johannes; Luzzi, Valerio
Climate change, increasing pressure on farmland to satisfy the growing demand, and need to ensure environmental quality for agriculture in order to be competitive require an increasing capacity of water management. In this context, web-based for forecasting and monitoring the hydrological conditions of topsoil can be an effective means to save water, maximize crop protection and reduce soil loss and the leaching of pollutants. Such tools need to be targeted to the users and be accessible in a simple way in order to allow adequate take up in the practice. IASMHYN "Improved management of Agricultural Systems by Monitoring and Hydrological evaluation" is a web mapping service designed to provide and update on a daily basis the main water budget variables for farmland management. A beta version of the tool is available at www.gecosistema.com/iasmhyn . IASMHYN is an instrument for "second level monitoring" that takes into account accurate hydro-meteorological information's from ground stations and remote sensing sources, and turns them into practically usable decision variables for precision farming, making use of geostatistical analysis and hydrological models The main routines embedded in IASMYHN exclusively use open source libraries (R packages and Python), to perform following operations: (1) Automatic acquisition of observed data, both from ground stations and remote sensing, concerning precipitation (RADAR) and temperature (MODIS-LST) available from various sources; (2) Interpolation of acquisitions through regression kriging in order to spatially map the meteorological data; (3) Run of hydrological models to obtain spatial information of hydrological soil variables of immediate interest in agriculture. The real time results that are produced are available trough a web interface and provide the user with spatial maps and time series of the following variables, supporting decision on irrigation, soil protection from erosion, pollution risk of groundwater and
Hernandez, B. C. B.
Degrading groundwater quality due to saltwater intrusion is one of the key challenges affecting many island aquifers. These islands hold limited capacity for groundwater storage and highly dependent on recharge due to precipitation. But its ease of use, natural storage and accessibility make it more vulnerable to exploitation and more susceptible to encroachment from its surrounding oceanic waters. Estimating the extent of saltwater intrusion and the state of groundwater resources are important in predicting and managing water supply options for the community. In Guimaras island, central Philippines, increasing settlements, agriculture and tourism are causing stresses on its groundwater resource. Indications of saltwater intrusion have already been found at various coastal areas in the island. A Geographic Information Systems (GIS)-based approach using the GALDIT index was carried out. This includes six parameters assessing the seawater intrusion vulnerability of each hydrogeologic setting: Groundwater occurrence, Aquifer hydraulic conductivity, Groundwater Level above sea, Distance to shore, Impact of existing intrusion and Thickness of Aquifer. To further determine the extent of intrusion, Landsat images of various thematic layers were stacked and processed for unsupervised classification and electrical resistivity tomography using a 28-electrode system with array lengths of 150 and 300 meters was conducted. The GIS index showed where the vulnerable areas are located, while the geophysical measurements and images revealed extent of seawater encroachment along the monitoring wells. These results are further confirmed by the measurements collected from the monitoring wells. This study presents baseline information on the state of groundwater resources and increase understanding of saltwater intrusion dynamics in island ecosystems by providing a guideline for better water resource management in the Philippines.
Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.
Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to
Reddy, C Sudhakar; Jha, C S; Dadhwal, V K
Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924-1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km(2) (52.5 %), 56,661.1 km(2) (36.4 %), 51,642.3 km(2) (33.2 %), 49,773 km(2) (32 %) and 48,669.4 km(2) (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 % year(-1) during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km(2)) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.
Piccard, Isabelle; Nackaerts, Kris; Gobin, Anne; Goffart, Jean-Pierre; Planchon, Viviane; Curnel, Yannick; Tychon, Bernard; Wellens, Joost; Cools, Romain; Cattoor, Nele
Belgian potato processors, traders and packers are increasingly working with potato contracts. The close follow up of contracted parcels on the land as well as from above is becoming an important tool to improve the quantity and quality of the potato crop and reduce risks in order to plan the storage, packaging or processing and as such to strengthen the competitiveness of the Belgian potato chain in a global market. At the same time, precision agriculture continues to gain importance and progress. Farmers are obligated to invest in new technologies. Between mid-May and the end of June 2014 potato fields in Gembloux were monitored from emergence till canopy closure. UAV images (RGB) and digital (hemispherical) photographs were taken at ten-daily intervals. Crop emergence maps show the time (date) and degree of crop emergence and crop closure (in terms of % cover). For three UAV flights during the growing season RGB images at 3 cm resolution were processed using a K-means clustering algorithm to classify the crop according to its greenness. Based on the greenness %cover and daily cover growth were derived for 5x5m pixels and 25x25m pixels. The latter resolution allowed for comparison with high resolution satellite imagery. Vegetation indices such as %Cover and LAI were calculated with the Cyclopes algorithm (INRA-EMMAH) from high resolution satellite images (DMC/Deimos, 22m pixel size). DMC based cover maps showed similar patterns as compared with the UAV-based cover maps, and allows for further applications of the data in crop management. Today the use of geo-information by the (private) agricultural sector in Belgium is rather limited, notwithstanding the great benefits this type of information may offer, as recognized by the sector. The iPot project, financed by the Belgian Science Policy Office (BELSPO), aims to provide the Belgian potato sector, represented by Belgapom, with near real time information on field condition (weather-soil) and crop development and
Camps, Adriano; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Marchán-Hernández, Juan F.; Rodríguez, Nereida; Valencia, Enric; Tarongi, Jose M.; Aguasca, Albert; Acevo, René
Lack of frequent and global observations from space is currently a limiting factor in many Earth Observation (EO) missions. Two potential techniques that have been proposed nowadays are: (1) the use of satellite constellations, and (2) the use of Global Navigation Satellite Signals (GNSS) as signals of opportunity (no transmitter required). Reflectometry using GNSS opportunity signals (GNSS-R) was originally proposed in 1993 by Martin-Neira (ESA-ESTEC) for altimetry applications, but later its use for wind speed determination has been proposed, and more recently to perform the sea state correction required in sea surface salinity retrievals by means of L-band microwave radiometry (TB). At present, two EO space-borne missions are currently planned to be launched in the near future: (1) ESA's SMOS mission, using a Y-shaped synthetic aperture radiometer, launch date November 2nd, 2009, and (2) NASA-CONAE AQUARIUS/SAC-D mission, using a three beam push-broom radiometer. In the SMOS mission, the multi-angle observation capabilities allow to simultaneously retrieve not only the surface salinity, but also the surface temperature and an “effective” wind speed that minimizes the differences between observations and models. In AQUARIUS, an L-band scatterometer measuring the radar backscatter (σ0) will be used to perform the necessary sea state corrections. However, none of these approaches are fully satisfactory, since the effective wind speed captures some sea surface roughness effects, at the expense of introducing another variable to be retrieved, and on the other hand the plots (TB-σ0) present a large scattering. In 2003, the Passive Advance Unit for ocean monitoring (PAU) project was proposed to the European Science Foundation in the frame of the EUropean Young Investigator Awards (EURYI) to test the feasibility of GNSS-R over the sea surface to make sea state measurements and perform the correction of the L-band brightness temperature. This paper: (1) provides an
Camps, Adriano; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Marchán-Hernández, Juan F; Rodríguez, Nereida; Valencia, Enric; Tarongi, Jose M; Aguasca, Albert; Acevo, René
Lack of frequent and global observations from space is currently a limiting factor in many Earth Observation (EO) missions. Two potential techniques that have been proposed nowadays are: (1) the use of satellite constellations, and (2) the use of Global Navigation Satellite Signals (GNSS) as signals of opportunity (no transmitter required). Reflectometry using GNSS opportunity signals (GNSS-R) was originally proposed in 1993 by Martin-Neira (ESA-ESTEC) for altimetry applications, but later its use for wind speed determination has been proposed, and more recently to perform the sea state correction required in sea surface salinity retrievals by means of L-band microwave radiometry (T(B)). At present, two EO space-borne missions are currently planned to be launched in the near future: (1) ESA's SMOS mission, using a Y-shaped synthetic aperture radiometer, launch date November 2nd, 2009, and (2) NASA-CONAE AQUARIUS/SAC-D mission, using a three beam push-broom radiometer. In the SMOS mission, the multi-angle observation capabilities allow to simultaneously retrieve not only the surface salinity, but also the surface temperature and an "effective" wind speed that minimizes the differences between observations and models. In AQUARIUS, an L-band scatterometer measuring the radar backscatter (σ(0)) will be used to perform the necessary sea state corrections. However, none of these approaches are fully satisfactory, since the effective wind speed captures some sea surface roughness effects, at the expense of introducing another variable to be retrieved, and on the other hand the plots (T(B)-σ(0)) present a large scattering. In 2003, the Passive Advance Unit for ocean monitoring (PAU) project was proposed to the European Science Foundation in the frame of the EUropean Young Investigator Awards (EURYI) to test the feasibility of GNSS-R over the sea surface to make sea state measurements and perform the correction of the L-band brightness temperature. This paper: (1
Full Text Available Lack of frequent and global observations from space is currently a limiting factor in many Earth Observation (EO missions. Two potential techniques that have been proposed nowadays are: (1 the use of satellite constellations, and (2 the use of Global Navigation Satellite Signals (GNSS as signals of opportunity (no transmitter required. Reflectometry using GNSS opportunity signals (GNSS-R was originally proposed in 1993 by Martin-Neira (ESA-ESTEC for altimetry applications, but later its use for wind speed determination has been proposed, and more recently to perform the sea state correction required in sea surface salinity retrievals by means of L-band microwave radiometry (TB. At present, two EO space-borne missions are currently planned to be launched in the near future: (1 ESA’s SMOS mission, using a Y-shaped synthetic aperture radiometer, launch date November 2nd, 2009, and (2 NASA-CONAE AQUARIUS/SAC-D mission, using a three beam push-broom radiometer. In the SMOS mission, the multi-angle observation capabilities allow to simultaneously retrieve not only the surface salinity, but also the surface temperature and an “effective” wind speed that minimizes the differences between observations and models. In AQUARIUS, an L-band scatterometer measuring the radar backscatter (σ0 will be used to perform the necessary sea state corrections. However, none of these approaches are fully satisfactory, since the effective wind speed captures some sea surface roughness effects, at the expense of introducing another variable to be retrieved, and on the other hand the plots (TB-σ0 present a large scattering. In 2003, the Passive Advance Unit for ocean monitoring (PAU project was proposed to the European Science Foundation in the frame of the EUropean Young Investigator Awards (EURYI to test the feasibility of GNSS-R over the sea surface to make sea state measurements and perform the correction of the L-band brightness temperature. This paper: (1
Vanderbilt, Vern; Daughtry, Craig; Dahlgren, Robert
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.
Hasager, Charlotte Bay
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...
Pickles, W L; Kasameyer, P W; Martini, B A; Potts, D C; Silver, E A
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.
Meier, G.A.; Brown, J.F.
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.
Fountain, Glen H.; Gold, Robert E.; Jenkins, Robert E.; Lew, Ark L.; Raney, R. Keith
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.
Parker, I. E.
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.
Sallee, Jeff; Meier, Lesley R.
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…
Sallee, Jeff; Meier, Lesley R.
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…
Ionosphere is a temporally and spatially varying, dispersive, anisotropic and inhomogeneous medium that is characterized primarily by its electron density distribution. Electron density is a complex function of spatial and temporal variations of solar, geomagnetic, and seismic activities. Ionosphere is the main source of error for navigation and positioning systems and satellite communication. Therefore, characterization and constant monitoring of variability of the ionosphere is of utmost importance for the performance improvement of these systems. Since ionospheric electron density is not a directly measurable quantity, an important derivable parameter is the Total Electron Content (TEC), which is used widely to characterize the ionosphere. TEC is proportional to the total number of electrons on a line crossing the atmosphere. IONOLAB is a research group is formed by Hacettepe University, Bilkent University and Kastamonu University, Turkey gathered to handle the challenges of the ionosphere using state-of-the-art remote sensing and signal processing techniques. IONOLAB group provides unique space weather services of IONOLAB-TEC, International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model based IRI-Plas-MAP, IRI-Plas-STEC and Online IRI-Plas-2015 model at www.ionolab.org. IONOLAB group has been working for imaging and monitoring of ionospheric structure for the last 15 years. TEC is estimated from dual frequency GPS receivers as IONOLAB-TEC using IONOLAB-BIAS. For high spatio-temporal resolution 2-D imaging or mapping, IONOLAB-MAP algorithm is developed that uses automated Universal Kriging or Ordinary Kriging in which the experimental semivariogram is fitted to Matern Function with Particle Swarm Optimization (PSO). For 3-D imaging of ionosphere and 1-D vertical profiles of electron density, state-of-the-art IRI-Plas model based IONOLAB-CIT algorithm is developed for regional reconstruction that employs Kalman Filters for state
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.
Kroutil, Robert T.; Shen, Sylvia S.; Lewis, Paul E.; Miller, David P.; Cardarelli, John; Thomas, Mark; Curry, Timothy; Kudaraskus, Paul
On April 28, 2010, the Environmental Protection Agency's (EPA) Airborne Spectral Photometric Environmental Collection Technology (ASPECT) aircraft was deployed to Gulfport, Mississippi to provide airborne remotely sensed air monitoring and situational awareness data and products in response to the Deepwater Horizon oil rig disaster. The ASPECT aircraft was released from service on August 9, 2010 after having flown over 75 missions that included over 250 hours of flight operation. ASPECT's initial mission responsibility was to provide air quality monitoring (i.e., identification of vapor species) during various oil burning operations. The ASPECT airborne wide-area infrared remote sensing spectral data was used to evaluate the hazard potential of vapors being produced from open water oil burns near the Deepwater Horizon rig site. Other significant remote sensing data products and innovations included the development of an advanced capability to correctly identify, locate, characterize, and quantify surface oil that could reach beaches and wetland areas. This advanced identification product provided the Incident Command an improved capability to locate surface oil in order to improve the effectiveness of oil skimmer vessel recovery efforts directed by the US Coast Guard. This paper discusses the application of infrared spectroscopy and multispectral infrared imagery to address significant issues associated with this national crisis. More specifically, this paper addresses the airborne remote sensing capabilities, technology, and data analysis products developed specifically to optimize the resources and capabilities of the Deepwater Horizon Incident Command structure personnel and their remediation efforts.
Xia, Qing; Zuo, Hong-Fu; Li, Shao-Cheng; Wen, Zhen-Hua; Li, Yao-Hua
The traditional method of measuring the aeroengine exhausts is intrusive gas sampling analysis techniques. The disadvantages of the techniques include complex system, difficult operation, high costs and potential danger because of back-pressure effects. The non-intrusive methods have the potential to overcome these problems. So the remote FTIR passive sensing is applied to monitor aeroengine exhausts and determine the concentration of the exhausts gases of aeroengines. The principle of FTIR remote passive sensing is discussed. The model algorithm for the calibration of FTIR system, the radiance power distribution and gas concentration are introduced. TENSOR27 FTIR-system was used to measure the spectra of infrared radiation emitted by the hot gases of exhausts in a test rig. The emission spectra of exhausts were obtained under different thrusts. By analyzing the spectra, the concentrations of CO2, CO and NO concentration were calculated under 4 thrusts. Researches on the determination of concentration of the exhausts gases of aeroengines by using the remote FTIR sensing are still in early stage in the domestic aeronautics field. The results of the spectra and concentration in the aeroengine test are published for the first time. It is shown that the remote FTIR passive sensing techniques have a great future in monitoring the hot gas of the aeroengines exhausts.
Rutzinger, Martin; Zieher, Thomas; Pfeiffer, Jan; Schlögel, Romy; Darvishi, Mehdi; Toschi, Isabella; Remondino, Fabio
In the recent past, studies on the monitoring of deep-seated landslides included a multitude of measuring tech