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...
The paper outlines recent developments in using optical remote sensing (ORS) instruments for air quality monitoring both for gaseous pollutants and airborne particulate matter (PM). The U.S. Environmental Protection Agency (EPA) has been using open-path Fourier transform infrared...
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.
Wang, Huan-jiong; Fan, Wen-jie; Cui, Yao-kui; Zhou, Lei; Yan, Bin-yan; Wu, Dai-hui; Xu, Xi-ru
The distributing of China's grassland is abroad and the status of grassland degradation is in serious condition. So achieving real-time and exactly grassland ecological monitoring is significant for the carbon cycle, as well as for climate and on regional economies. With the field measured spectra data as data source, hyperspectral remote sensing monitoring of grassland degradation was researched in the present article. The warm meadow grassland in Hulunbeier was chosen as a study object. Reflectance spectra of leaves and pure canopies of some dominant grassland species such as Leymus chinensis, Stipa krylovii and Artemisia frigid, as well as reflectance spectra of mixed grass community were measured. Using effective spectral feature parametrization methods, the spectral feature of leaves and pure canopies were extracted, so the constructive species and degenerate indicator species can be exactly distinguished. Verification results showed that the accuracy of spectral identification was higher than 95%. Taking it as the foundation, the spectra of mixed grass community were unmixed using linear mixing models, and the proportion of all the components was calculated, and the errors were less than 5%. The research results of this article provided the evidence of hyperspectral remote sensing monitoring of grassland degradation.
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
The remote sensing technology has many practical applications in different fields of science and industry. There is also a need to examine its usefulness for the purpose of land border surveillance. This research started with analysis of potential direct use of Earth Observation technology for monitoring migrations of people and preventing smuggling. The research, however, proved that there are still many fields within which the EO technology needs to be improved. From that point the analysis focused on improving Border Permeability Index which utilizes EO techniques as a source of information. The result of BPI analysis with use of high resolution data provides new kind of information which can support and make more effective work of authorities from security domain.
I. Remote Sensing Basics
A. The electromagnetic spectrum demonstrates what we can see both in the visible and beyond the visible part of the spectrum through the use of various types of sensors.
B. Resolution refers to what a remote sensor can see and how often.
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
Yuanfu, S.; Quanan, Z.
In order to monitor marine pollution by airborne remote sensing techniques, some comprehensive test of airborne remote sensing, involving monitoring marine oil pollution, were performed at several bay areas of China. This paper presents some typical results of monitoring marine oil pollution. The features associated with the EM spectrum (visible, thermal infrared, and microwave) response of marine oil spills is briefly analyzed. It has been verified that the airborne oil surveillance systems manifested their advantages for monitoring the oil pollution of bay environments.
Epiphanio, J. C. N.; Vitorelli, I.
The use of remote sensing for irrigated areas, especially in the region of Guaira, Brazil (state of Sao Paulo), is examined. Major principles of utilizing LANDSAT data for the detection and mapping of irrigated lands are discussed. In addition, initial results obtained by computer processing of digital data, use of MSS (Multispectral Scanner System)/LANDSAT products, and the availability of new remote sensing products are highlighted. Future activities include the launching of the TM (Thematic Mapper)/LANDSAT 4 with 30 meters of resolution and SPOT (Systeme Probatorie d'Observation de la Terre) with 10 to 20 meters of resolution, to be operational in 1984 and 1986 respectively.
The application of remotely sensed data in conjunction with in situ data greatly enhances the ability of the USDA Forest Service to meet the demands of field staff, customers, and others for groundwater information. Generally, the use of remotely sensed data to inventory and monitor groundwater reso...
Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote s...
Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote se...
Summers, R. A.; Smith, W. L.; Short, N. M.
Exploration for uranium, thorium, oil, gas and geothermal activity through remote sensing techniques is considered; satellite monitoring of coal-derived CO2 in the atmosphere, and the remote assessment of strip mining and land restoration are also mentioned. Reference is made to color ratio composites based on Landsat data, which may aid in the detection of uranium deposits, and to computer-enhanced black and white airborne scanning imagery, which may locate geothermal anomalies. Other applications of remote sensing to energy resources management, including mapping of transportation networks and power plant siting, are discussed.
Heller, A. N.; Bryson, J. C.; Vasuki, N. C.
The applications of remote sensing in atmospheric monitoring programs are described. The organization, operations, and functions of an air quality monitoring network at New Castle County, Delaware is discussed. The data obtained by the air quality monitoring network ground stations and the equipment used to obtain atmospheric data are explained. It is concluded that correlation of the information obtained by the network will make it possible to anticipate air pollution problems in the Chesapeake Bay area before a crisis develops.
Bolton, W.; Lapp, M.; Vitko, J. Jr.; Phipps, G.
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.
Xie, Caixiang; Song, Jingyuan; Suo, Fengmei; Li, Xiwen; Li, Ying; Yu, Hua; Xu, Xiaolan; Luo, Kun; Li, Qiushi; Xin, Tianyi; Guan, Meng; Xu, Xiuhai; Miki, Eiji; Takeda, Osami; Chen, Shilin
Remote sensing has been extensively applied in agriculture for its objectiveness and promptness. However, few applications are available for monitoring natural medicinal plants. In the paper, a multilevel monitoring system, which includes satellite and aerial remote sensing, as well as ground investigation, was initially proposed to monitor natural Rheum tanguticum resource in Baihe Pasture, Zoige County, Sichuan Province. The amount of R. tanguticum from images is M = S*ρ and S is vegetation coverage obtained by satellite imaging, whereas ρ is R. tanguticum density obtained by low-altitude imaging. Only the R. tanguticum which coverages exceeded 1 m2 could be recognized from the remote sensing image because of the 0.1 m resolution of the remote sensing image (called effective resource at that moment), and the results of ground investigation represented the amounts of R. tanguticum resource in all sizes (called the future resource). The data in paper showed that the present available amount of R. tanguticum accounted for 4% to 5% of the total quantity. The quantity information and the population structure of R. tanguticum in the Baihe Pasture were initially confirmed by this system. It is feasible to monitor the quantitative distribution for natural medicinal plants with scattered distribution. PMID:25101134
“How can remote sensing address information needs and gaps in water quality and quantity management?” was a workshop convened during the biennial National Water Quality Monitoring Conference 2014, held in Cincinnati, OH. The focus of this workshop was to provide an o...
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...
Xie, Caixiang; Song, Jingyuan; Suo, Fengmei; Li, Xiwen; Li, Ying; Yu, Hua; Xu, Xiaolan; Luo, Kun; Li, Qiushi; Xin, Tianyi; Guan, Meng; Xu, Xiuhai; Miki, Eiji; Takeda, Osami; Chen, Shilin
Remote sensing has been extensively applied in agriculture for its objectiveness and promptness. However, few applications are available for monitoring natural medicinal plants. In the paper, a multilevel monitoring system, which includes satellite and aerial remote sensing, as well as ground investigation, was initially proposed to monitor natural Rheum tanguticum resource in Baihe Pasture, Zoige County, Sichuan Province. The amount of R. tanguticum from images is M = S*ρ and S is vegetation coverage obtained by satellite imaging, whereas ρ is R. tanguticum density obtained by low-altitude imaging. Only the R. tanguticum which coverages exceeded 1 m(2) could be recognized from the remote sensing image because of the 0.1 m resolution of the remote sensing image (called effective resource at that moment), and the results of ground investigation represented the amounts of R. tanguticum resource in all sizes (called the future resource). The data in paper showed that the present available amount of R. tanguticum accounted for 4% to 5% of the total quantity. The quantity information and the population structure of R. tanguticum in the Baihe Pasture were initially confirmed by this system. It is feasible to monitor the quantitative distribution for natural medicinal plants with scattered distribution.
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.
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...
Klemas, V. V.
Tracking and Monitoring Oil Slicks Using Remote Sensing Victor Klemas, Ph.D. , College of Earth, Ocean and Environment, University of Delaware, Newark, DE 19716 Abstract Oil spills can harm marine life in the ocean, estuaries and wetlands. To limit the damage by a spill and facilitate cleanup efforts, emergency managers need information on spill location, size and extent, direction and speed of oil movement, wind, current, and wave information for predicting oil drift and dispersion. The main operational data requirements are fast turn-around time and frequent imaging to monitor the dynamics of the spill. Radar and multispectral remote sensors on satellites and aircraft meet most of these requirements by tracking the spilled oil at various resolutions, over wide areas and at frequent intervals. They also provide key inputs to drift prediction models and facilitate targeting of skimming and booming efforts. Satellite data are frequently supplemented by information provided by aircraft, ships and remotely controlled underwater robots. The Sea Princess tanker grounding off the coast of Wales and the explosion on the Deepwater Horizon rig in the Gulf of Mexico provide two representative, yet different, scenarios for evaluating the effectiveness of remote sensors during oil spill emergencies. Session NH17: Remote Sensing of Natural Hazards Session Chair: Ramesh P. Singh Sponsor: Natural Hazards (NH)
Faisal, K.; AlAhmad, M.; Shaker, A.
The disposal of the solid wastes in landfill sites should be properly monitored by analyzing samples from soil, water, and landfill gases within the landfill site. Nevertheless, ground monitoring systems require intensive efforts and cost. Furthermore, ground monitoring may be difficult to be achieved in large geographic extent. Remote sensing technology has been introduced for waste disposal management and monitoring effects of the landfill sites on the environment. In this paper, two case studies are presented in the Trail Road landfill, Ottawa, Canada and the Al-Jleeb landfill, Al-Farwanyah, Kuwait to evaluate the use of multi-temporal remote sensing images to monitor the landfill sites. The work objectives are: 1) to study the usability of multi-temporal Landsat images for landfill site monitoring by studying the land surface temperature (LST) in the Trail Road landfill, 2) to investigate the relationship between the LST and the amount of the landfill gas emitted in the Trail Road landfill, and 3) to use the multi-temporal LST images to detect the suspicious dumping areas within the Al-Jleeb landfill site. Free archive of multi-temporal Landsat images are obtained from the USGS EarthExplorer. The Landsat images are then atmospherically corrected and the LST images are derived from the thermal band of the corrected Landsat images. In the Trail Road landfill, the results reveal that the LST of the landfill site is always higher than the air temperature by 10°C in average as well as the surroundings. A correlation is also observed between the recorded emitted methane (CH4) from the ground monitoring stations and the LST derived from the Landsat images. Based on the findings in the Al-Jleeb landfill, five locations are identified as suspicious dumping areas by overlaying the highest LST contours generated from the multi-temporal LST images. The study demonstrates that the use of multi-temporal remote sensing images can provide supplementary information for
Moya, I.; Guyot, G.; Goulas, Y.
For monitoring plant canopies, fluorescence signals emitted by plants underlaser or daylight excitation appear to be a promising tool among the various remote sensing techniques available. Chlorophyll fluorenscece is a nature emission exhibiting a broad inverse relation with the photosynthetic carbon assimilation of green plants. Besides this specific red fluorescence, a second emission with a comparable intensity is observed in the blue region of the spectrum, when the vegetation is excited by near-UV radiation. The origin of blue fluorescence is still under discussion, but increasing evidence is found to associate it with non-photosynthetic parts of the plant tissue including cellular wall components or precursors, skin waxes and vacuolar metabolites. Experimental results show that the blue fluorescence signal depends on the type of vegetation and is highly affected by stress. For a better characterization of vegetation, blue and red fluorescence should be considered simultaneously because they contain complementary information and are highly specific to vegetation. Two approaches, which are currently considered feasible for the remote detection of fluorescence signals, are analyzed and discussed: laser induced fluorescence (active remote sensing) and solar stimulated fluorescence (passive remote sensing).
Rothery, D. A.; Francis, P. W.; Wood, C. A.
The use of short wavelength IR Landsat TM data for volcano monitoring is examined. By determining the pixel-integrated from the TM data, it is possible to estimate the temperature and size of hot areas which occupy less than one complete pixel. Examples of volcano monitoring with remote sensing data are discussed. It is suggested that the entire volcanic temperature range (100-1200 C) could be accomplished by decreasing the band 6 gain by just one order of magnitude so that it was sensitive to radiance from 1 to 100 mW/sq cm/sr/micron.
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
Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.
Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project
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...
La Loggia, Goffredo; Capodici, Fulvio; Ciraolo, Giuseppe; Drago, Aldo; Maltese, Antonino
Human activities contaminate both coastal areas and open seas, even though impacts are different in terms of pollutants, ecosystems and recovery time. In particular, Mediterranean offshore pollution is mainly related to maritime transport of oil, accounting for 25% of the global maritime traffic and, during the last 25 years, for nearly 7% of the world oil accidents, thus causing serious biological impacts on both open sea and coastal zone habitats. This paper provides a general review of maritime pollution monitoring using integrated approaches of remote sensing and hydrodynamic modeling; focusing on the main results of the MAPRES (Marine pollution monitoring and detection by aerial surveillance and satellite images) research project on the synergistic use of remote sensing, forecasting, cleanup measures and environmental consequences. The paper also investigates techniques of oil spill detection using SAR images, presenting the first results of "Monitoring of marine pollution due to oil slick", a COSMO-SkyMed funded research project where X-band SAR constellation images provided by the Italian Space Agency are used. Finally, the prospect of using real time observations of marine surface conditions is presented through CALYPSO project (CALYPSO-HF Radar Monitoring System and Response against Marine Oil Spills in the Malta Channel), partly financed by the EU under the Operational Programme Italia-Malta 2007-2013. The project concerns the setting up of a permanent and fully operational HF radar observing system, capable of recording surface currents (in real-time with hourly updates) in the stretch of sea between Malta and Sicily. A combined use of collected data and numerical models, aims to optimize intervention and response in the case of marine oil spills.
Pirie, D. M.; Murphy, M. J.; Edmisten, J. R.
During the oceanic period from July to November, the southward flowing California current dominates the nearshore current patterns. Commencing about the middle of November and extending to mid-February, the Davidson current, a northward moving countercurrent, is the dominant inshore transporter of water and suspensates. The phenomenon of upwelling is prevalent during the period from the middle of February to the end of July. Thus, every year along the coast of California, there are three successive current seasons: the oceanic, the Davidson, and the upwelling. This paper is a discussion of the nature of these nearshore currents. In addition, the capabilities of various remote sensing platforms and systems for providing methods of monitoring the coastal processes associated with the current seasons of California are demonstrated herein.
Singh, Upendra N. (Editor); Itabe, Toshikazu (Editor); Sugimoto, Nobuo (Editor)
Contents include the following: 1. Keynote paper: Overview of lidar technology for industrial and environmental monitoring in Japan. 2. lidar technology I: NASA's future active remote sensing mission for earth science. Geometrical detector consideration s in laser sensing application (invited paper). 3. Lidar technology II: High-power femtosecond light strings as novel atmospheric probes (invited paper). Design of a compact high-sensitivity aerosol profiling lidar. 4. Lasers for lidars: High-energy 2 microns laser for multiple lidar applications. New submount requirement of conductively cooled laser diodes for lidar applications. 5. Tropospheric aerosols and clouds I: Lidar monitoring of clouds and aerosols at the facility for atmospheric remote sensing (invited paper). Measurement of asian dust by using multiwavelength lidar. Global monitoring of clouds and aerosols using a network of micropulse lidar systems. 6. Troposphere aerosols and clouds II: Scanning lidar measurements of marine aerosol fields at a coastal site in Hawaii. 7. Tropospheric aerosols and clouds III: Formation of ice cloud from asian dust particles in the upper troposphere. Atmospheric boundary layer observation by ground-based lidar at KMITL, Thailand (13 deg N, 100 deg. E). 8. Boundary layer, urban pollution: Studies of the spatial correlation between urban aerosols and local traffic congestion using a slant angle scanning on the research vessel Mirai. 9. Middle atmosphere: Lidar-observed arctic PSC's over Svalbard (invited paper). Sodium temperature lidar measurements of the mesopause region over Syowa Station. 10. Differential absorption lidar (dIAL) and DOAS: Airborne UV DIAL measurements of ozone and aerosols (invited paper). Measurement of water vapor, surface ozone, and ethylene using differential absorption lidar. 12. Space lidar I: Lightweight lidar telescopes for space applications (invited paper). Coherent lidar development for Doppler wind measurement from the International Space
Whelan, Matthew J; Fuchs, Michael P; Janoyan, Kerop D
Recent developments in wireless sensor technology afford the opportunity to rapidly and easily deploy large-scale, low-cost, and low-power sensor networks across relatively sizeable environmental regions. Furthermore, the advancement of increasingly smaller and less expensive wireless hardware is further complemented by the rapid development of open-source software components. These software protocols allow for interfacing with the hardware to program and configure the onboard processing and communication settings. In general, a wireless sensor network topology consists of an array of microprocessor boards, referred to as motes, which can engage in two-way communication among each other as well as with a base station that relays the mote data to a host computer. The information can then be either logged and displayed on the local host or directed to an http server for network monitoring remote from the site. A number of wireless sensor products are available that offer off-the-shelf network hardware as well as sensor solutions for environmental monitoring that are compatible with the TinyOS open-source software platform. This paper presents an introduction to wireless sensing and to the use of external antennas for increasing the antenna radiation intensity and shaping signal directivity for monitoring applications requiring larger mote-to-mote communication distances.
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)
Fink, Jonathan; Wessels, Rick; Eisinger, Chris; Ramsey, Michael; Hellman, Melanie; Kuhn, Sally
This report details the final progress on the Solid Earth and Natural Hazards project: Monitoring of Hazards of Silicic Volcanoes with Remote Sensing (SENH99-0000-0159). The original award went to Arizona State University (ASU) with Dr. Jonathan Fink as the P.I. and Dr. Michael Ramsey as the Co-I. In May 2000, Dr. Ramsey left ASU to take a tenure-track faculty position at the University of Pittsburgh. The principle investigators and NASA Headquarters agreed to split the grant award at the HQ level and therefore avoid the double overhead charges that would arise from a university subcontract. The objectives of the science were divided, and coordinated yearly progress reports have been submitted from each University. This report details the final progress on work carried out at Arizona State. A report by Dr. Ramsey at the University of Pittsburgh has already been submitted. The work from both institutions is closely related and this report will reflect that connection.
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.
Gao, Z.; del Barrio, G.; Li, X.
The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired during the last two years could be summarized as follows:(1) Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) were estimated in Otindag sandy land by comparison of the pixel-invariant (Spectral Mixture Analysis, SMA) and pixel-variable (Multi-Endmember Spectral Mixture Analysis, MESMA, Automated Monte Carlo Unmixing Analysis, AutoMCU) methods, based on GF-1 data and field measured spectral library.(2) Based on GF-1 data, SMA was applied to solve vegetation cover and transitional sandy land detection in Zhenglan Banner, Inner Mongolia, China.(3) By defined a new indictor, Moisture-responded NPP(MNPP), a new method for identification of degraded lands was put forward, and the land degradation in Xinlin Gol league, Inner Mongolia Autonomous Region, China was assessed preliminarily. (4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China (PEDC) was assessed.
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.
Aten, Michelle L.
Lakes and reservoirs are important resources that provide water for critical needs, such as drinking water, agriculture, recreation, fisheries, wildlife, and other uses. However, there is increasing concern that anthropogenic eutrophication threatens the usability of these natural resources. Therefore, this research investigates these complex hydrologic ecosystems and recommends a methodology for monitoring the trophic state of lakes and reservoirs using remote sensing data. The Mississippi Department of Environmental Quality provided in situ data for seven Mississippi lakes including, Arkabutla, Bay Springs, Enid, Grenada, Okatibbee, Ross Barnett, and Sardis lakes. This research explored the relationships between the Secchi depth (SD), chlorophyll-a (CHL), and total phosphorus (TP) in situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) spectral reflectance data. This was accomplished by deriving Carlson Trophic State Index values for each in situ measurements and using these TSI(SD), TSI(CHL), and TSI(TP) values to evaluate potential predictive methods. Simple linear regression was performed to quantify the strength of the relationships between the in situ data and MODIS surface reflectance values. However, R-square values were too low and inconsistent to justify additional analyses. Therefore, machine learning models from the Waikato Environment for Knowledge Analysis (WEKA) software workbench were explored and tested. Optimal predictive models and settings were investigated for two meta-learner classifiers, three Bayesian classifiers and three decision tree classifiers. The Classification Via Regression yielded the best results when using large datasets, the all-but-one iteration setting, MODIS A1 individual bands as predictors, and TSI(SD) as targets. For this model and these settings, the percentages of correctly classified instances ranged from 77.74% to 81.98% and kappa values ranged from 0.41 to 0.48. The percentage of correctly classified
Xie, Yunlin; Peng, Mingjun
Rapid land use change has take place in Wuhan, the largest mega-city in central China during the last decade. Remotely sensed imagery together with geographical information system have long been utilized to monitor spatial and temporal land use change. The aim of this paper is to find out the land use change and the trend of urban growth in Wuhan, China using satellite images. The Landsat TM image acquired in 1991 and the Landsat ETM image acquired in 2002 were used to monitor land use change in Wuhan. The images were geo-referenced according to Gauss-Kruger projection with Krasovsky spheroid, by using 1:50, 000 topographical maps. The image processing is implemented by using Erdas Imagine package. The RMS error has been controlled under the limit of 1 pixel. The geo-referenced images were classified as seven land use types: cultivated land, forest land, grassland, urban and villages, transportation, water bodies and barren land. Two land use maps were produced for each date. The geo-referenced, classified images were compared pixel by pixel to locate and quantify land use changes that took place from 1991 to 2002 period. The further change detection analysis in a later stage is performed in ArcGIS. The transition matrix was produced and the quantitative information on the size of land use change from one type to another was compiles. The results of study indicate that the conversion of land use from cultivated land to urban was prominent, the rapid urban sprawl has occupied lots of cultivated land and water bodies, the urban area significantly increased 30%, most of which are converted from cultivated land. these valuable cultivated land need careful protection by providing land use plans to guide urban growth going toward the right directions. The results obtained from this application also indicate that the use of satellite imageries is very useful for mapping land use changes, and the monitoring land use change is essential for land use planning and urban
Simoniello, T.; Carone, M. T.; Loperte, A.; Satriani, A.; Imbrenda, V.; D'Emilio, M.; Guariglia, A.
Coastal areas are of great environmental, economic, social, cultural and recreational relevance; therefore, the implementation of suitable monitoring and protection actions is fundamental for their preservation and for assuring future use of this resource. Such actions have to be based on an ecosystem perspective for preserving coastal environment integrity and functioning and for planning sustainable resource management of both the marine and terrestrial components (ICZM-EU initiative). We implemented an integrated study based on remote sensing and geophysical techniques for monitoring a coastal area located along the Ionian side of Basilicata region (Southern Italy). This area, between the Bradano and Basento river mouths, is mainly characterized by a narrow shore (10-30 m) of fine sandy formations and by a pine forest planted in the first decade of 50's in order to preserve the coast and the inland cultivated areas. Due to drought and fire events and saltwater intrusion phenomena, such a forest is affected by a strong decline with consequent environmental problems. Multispectral satellite data were adopted for evaluating the spatio-temporal features of coastal vegetation and the structure of forested patterns. The increase or decrease in vegetation activity was analyzed from trends estimated on a time series of NDVI (Normalized Difference Vegetation Index) maps. The fragmentation/connection levels of vegetated patterns was assessed form a set of landscape ecology metrics elaborated at different structure scales (patch, class and landscape) on satellite cover classifications. Information on shoreline changes were derived form a multi-source data set (satellite data, field-GPS surveys and Aerial Laser Scanner acquisitions) by taking also into account tidal effects. Geophysical campaigns were performed for characterizing soil features and limits of salty water infiltrations. Form vertical resistivity soundings (VES), soil resistivity maps at different a deeps (0
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.
Haack, Barry; Messina, Joe
Environmental managers need current, accurate information upon which to base decisions. Viable information, especially in developing countries, is often unavailable. Satellite remote sensing is an appropriate and effective data source for mapping the surface of the earth including a variety of environmental features. Remote sensing derived information is enhanced by being one component within a Geographic Information System (GIS). These techniques were employed to study an expanding delta in East Africa. The Omo River flows from the Ethiopian Highlands into the northern end of Lake Turkana creating a large delta extending between Ethiopia and Kenya. This isolated and unique wetland feature has expanded by over 500 sq. km in the last fifteen years as measured by spaceborne remote sensing techniques and corroborated by low altitude aircraft reconnaissance flights. The growth of the delta appears to be a function of both increased sedimentation and decreased lake levels and river flows. Within the delta there has been a selective decline in wildlife and an increase in human activity, both pastoral and agricultural. The uniqueness of this isolated delta suggests that consideration be given to its possible protection and management.
Environmental managers need current, accurate information upon which to base decisions. Viable information, especially in developing countries, is often unavailable. Satellite remote sensing is an appropriate and effective data source for mapping the surface of the earth, including a variety of environmental features. Remote-sensing-derived information is enhanced by being one component within a geographic information system (GIS). These techniques were employed to study an expanding delta in East Africa. The Omo River flows from the Ethiopian Highlands into the northern end of Lake Turkana, creating a large delta extending between Ethiopia and Kenya. This isolated and unique wetland feature has expanded by over 500 sq km in the last 15 years as measured by space-borne remote sensing techniques and corroborated by low-altitude aircraft reconnaissance flights. The growth of the delta appears to be a function of both increased sedimentation and decreased lake levels and river flows. Within the delta there has been a selective decline in wildlife and an increase in human activity, both pastoral and agricultural. The uniqueness of this isolated delta suggests that consideration be given to its possible protection and management.
The applications are reported of new remote sensing techniques for earth resources surveys and environmental monitoring. Applications discussed include: vegetation systems, environmental monitoring, and plant protection. Data processing systems are described.
Active ground optical remote sensing (AGORS) devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and ...
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 tools available in the ENVI
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; Rollins, Katherine E.
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.
Stoms, D. M.; Estes, J. E.
A remote sensing research agenda designed to expand the knowledge of the spatial distribution of species richness and its ecological determinants and to predict its response to global change is proposed. Emphasis is placed on current methods of mapping species richness of both plants and animals, hypotheses concerning the biophysical factors believed to determine patterns of species richness, and anthropogenic processes causing the accelerating rate of extinctions. It is concluded that biodiversity should be incorporated more prominently into the global change and earth system science paradigms.
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
Bernardes, T.; Rosa, V. G.; Rudorf, B. F.; Adami, M.
Remote sensing studies applied to coffee crop have shown the complexity and difficulty to extract information from satellite imagery. The accuracy of automatic classification for coffee areas was considered only intermediate by several authors. The errors were attributed to topographic effects and low spatial resolution of Landsat images. Besides the difficulties to map coffee crop, there are few cloud cover free Landsat images over the growing season. Despite the low spatial resolution, high temporal coverage of MODIS data makes it possible to obtain cloud free images on several dates over the year providing additional information for monitoring coffee crops. Our hypothesis is that the range of foliar biomass of coffee plots over the growing season, assumed to be estimated through MODIS vegetation indices, is related to coffee yield. We assess the feasibility of monitoring coffee yield by using time-series of MODIS 250m normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) data. The study area is situated in the south of the Minas Gerais State which produces about thirty percent of the Brazilian coffee production. We used NDVI and EVI products from MODIS spanning from 2006 to 2009 to assess the feasibility of detecting relationships between vegetation indices and coffee yield. Landsat images were used to obtain a reference map of coffee areas and to identify MODIS 250m pure pixels overlapping homogeneous coffee crops. Only MODIS pixels with 100% coffee were included in the analysis. A wavelet-based filter was used to smooth NDVI and EVI time profiles. The next step was the acquisition of coffee yield data directly from farmers on the test site. Those data are being statistically related to vegetation indices and range values per year. The study region presents nearly 452.000 hectares of coffee mapped by on-screen digitalization of Landsat imagery from which about 10.000 hectares match plots likely to be monitored from 250 meters MODIS
Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna
'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).
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.
Allan, J. A.
Agriculture in semi-arid tracts of the world depends on water to sustain its irrigation systems. Such agricultural systems either derive from government investments in the control of surface flow or they have been developed through the exploitation of groundwater sometimes by a large community of unsupervised individuals seeking to maximise their own advantage without concern for the resource upon which they depend in the medium and long term. In both cases government agencies need data on the area irrigated and the volume of water used. In countries with highly developed scientific and agricultural institutions the contribution of remote sensing, though significant, may only provide between five and ten per cent of the data required to guide regional and national managers. In countries without such institutions the proportion contributed by remote sensing can be very much higher, as shown in a recent study in North Africa. The paper will emphasise the importance of carefully structured sampling procedures, both to improve the areal estimates from satellite imagery and the estimates of water use based upon them. The role of satellite imagery in providing information on the status of water resources, on trends in water use and in the implementation of policies to extend or diminish irrigated land are discussed.
Rader, M. L. (Principal Investigator)
Activities and results are reported of a project to investigate the application of remote sensing technology developed for the LACIE, AgRISTARS, Forestry and other NASA remote sensing projects for the environmental monitoring of strip mining, industrial pollution, and acid rain. Following a remote sensing workshop for EPA personnel, the EOD clustering algorithm CLASSY was selected for evaluation by EPA as a possible candidate technology. LANDSAT data acquired for a North Dakota test sight was clustered in order to compare CLASSY with other algorithms.
Brosius, C. A.; Gervin, J. C.; Ragusa, J. M.
A text book on remote sensing, as part of the earth resources Skylab programs, is presented. The fundamentals of remote sensing and its application to agriculture, land use, geology, water and marine resources, and environmental monitoring are summarized.
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.
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 se...
Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael
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. PMID:26437413
Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael
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.
Yuping, Ma; Shili, Wang; Li, Zhang; Yingyu, Hou; Liwei, Zhuang; Yanbo, He; Futang, Wang
Both of crop growth simulation models and remote sensing method have a high potential in crop growth monitoring and yield prediction. However, crop models have limitations in regional application and remote sensing in describing the growth process. Therefore, many researchers try to combine those two approaches for estimating the regional crop yields. In this paper, the WOFOST model was adjusted and regionalized for winter wheat in North China and coupled through the LAI to the SAIL-PROSPECT model in order to simulate soil adjusted vegetation index (SAVI). Using the optimization software (FSEOPT), the crop model was then re-initialized by minimizing the differences between simulated and synthesized SAVI from remote sensing data to monitor winter wheat growth at the potential production level. Initial conditions, which strongly impact phenological development and growth, and which are hardly known at the regional scale (such as emergence date or biomass at turn-green stage), were chosen to be re-initialized. It was shown that re-initializing emergence date by using remote sensing data brought simulated anthesis and maturity date closer to measured values than without remote sensing data. Also the re-initialization of regional biomass weight at turn-green stage led that the spatial distribution of simulated weight of storage organ was more consistent to official yields. This approach has some potential to aid in scaling local simulation of crop phenological development and growth to the regional scale but requires further validation.
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
Contents: Foundations of Remote Sensing : Data Acquisition and Interpretation; Availability of Remote Sensing Technology for Disaster Response...Imaging Systems, Current and Near Future Satellite and Aircraft Remote Sensing Systems; Utilization of Remote Sensing in Disaster Response: Categories of...Disasters, Phases of Monitoring Activities; Recommendations for Utilization of Remote Sensing Technology in Disaster Response; Selected Reading List.
Huang, He; Zhou, Hongjian; Wang, Ping; Wu, Wei; Yang, Siquan
Drought is one major nature disaster in the world. The affected population and agriculture loss caused by drought are the largest in all natural disasters. Drought has the characteristics of wide affected areas, long duration and periodic strong feature. Remote sensing has the advantages of large coverage, frequent observation, repeatable observation, reliable information source and low cost. These advantages make remote sensing a vital contributor for drought disaster monitoring and forecasting. So, remote sensing data have been widely used and delivered significant benefits in drought prevention and reduction in China. Three drought monitor models including Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Temperature Vegetation Dryness Index (TVDI) had been used to monitor southwest drought occurred in China from 2009 to 2011 based on the small satellite constellation for environment and disaster monitoring and forecasting A/B satellites (HJ-1AB) and Landsat remote sensing data. The results shown that five regions including Sichuan province, Chongqing, Guizhou province, Yunnan province, Guangxi province in southwest of China had suffered different degrees agricultural drought disaster in 2010 and 2011. The comprehensive agricultural disaster situation of five affected areas in 2010 was more serious than drought events occurred in 2011. The many regions in Guizhou province were hardest-hit areas cased by the two consecutive year drought events in southwest China.
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.
Understanding vegetation response to changing climate patterns is an important element of rangeland management and supports the use and development of ecological site descriptions. Monitoring of rangeland conditions with remote sensing can be misleading if ground measurements are not used to interpr...
Jones, John W.
Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management.
Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management. Copyright ?? 2011 Taylor & Francis Group, LLC.
Wu, Meng-quan; Wang, Zhou-long; Zhang, An-ding; Huang, Yong-qi; Cui, Qing-chun
Tobacco is one of important crops in our country, and brings the significant irreplaceable effect into playing in countrywide economic growth. So the monitoring and scientific management of tobacco fields show especially important to us. To monitor growing crops in a large scale is a complicated problem and a satisfied method to know what the way a crop is growing has been sought by the scientists in the field. At present, the study of tobacco remote sensing monitoring is less both at home and abroad. In this paper, we try to obtain tobacco field and area by remote sensing with Yunan Province Honghe State Tobacco County as example. We adopt rejecting interfering tobacco field information classification method of supervision while monitoring and get an ideal result. Simultaneity, we also offered the suggestion of further improving classification precision.
Johnson, R. W.; Ohlhorst, C. W.
Remotely sensed wide area synoptic data provides information on ocean dumping that is not readily available by other means. A qualitative approach has been used to map features, such as river plumes. Results of quantitative analyses have been used to develop maps showing quantitative distributions of one or more water quality parameters, such as suspended solids or chlorophyll a. Joint NASA/NOAA experiments have been conducted at designated dump areas in the U.S. coastal zones to determine the applicability of aircraft remote sensing systems to map plumes resulting from ocean dumping of sewage sludge and industrial wastes. A second objective is related to the evaluation of previously developed quantitative analysis techniques for studying dispersion of materials in these plumes. It was found that plumes resulting from dumping of four waste materials have distinctive spectral characteristics. The development of a technology for use in a routine monitoring system, based on remote sensing techniques, is discussed.
Ma, Yi; Zhang, Jie; Zhang, Jingyu
The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale
Recent developments in on-vehicle electronics makes practical remote monitoring of vehicle emissions compliance with CARB and EPA regulations. A system consisting of emission controls malfunction sensors, an on-board computer (OBC), and vehicle-to-roadside communications (VRC) would enable enforcement officials to remotely and automatically detect vehicle out-of-compliance status. Remote sensing could be accomplished at highway speeds as vehicles pass a roadside RF antenna and reader unit which would interrogate the on- vehicle monitoring and recording system. This paper will focus on the hardware system components require to achieve this goal with special attention to the VRC; a key element for remote monitoring. this remote sensing concept piggybacks on the development of inexpensive VRC equipment for automatic vehicle identification for electronic toll collection and intelligent transportation applications. Employing an RF transponder with appropriate interface to the OBC and malfunction sensors, a practical monitoring system can be developed with potentially important impact on air quality and enforcement. With such a system in place, the current -- and costly and ineffective -- emission control strategy of periodic smog checking could be replaced or modified.
Contents: Multi-sensors and systems in remote sensing ; Radar sensing systems over land; Remote sensing techniques in oceanography; Influence of...propagation media and background; Infrared techniques in remote sensing ; Photography in remote sensing ; Analytical studies in remote sensing .
Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin
There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.
Dowling, David R.; Sabra, Karim G.
Acoustic waves carry information about their source and collect information about their environment as they propagate. This article reviews how these information-carrying and -collecting features of acoustic waves that travel through fluids can be exploited for remote sensing. In nearly all cases, modern acoustic remote sensing involves array-recorded sounds and array signal processing to recover multidimensional results. The application realm for acoustic remote sensing spans an impressive range of signal frequencies (10-2 to 107 Hz) and distances (10-2 to 107 m) and involves biomedical ultrasound imaging, nondestructive evaluation, oil and gas exploration, military systems, and Nuclear Test Ban Treaty monitoring. In the past two decades, approaches have been developed to robustly localize remote sources; remove noise and multipath distortion from recorded signals; and determine the acoustic characteristics of the environment through which the sound waves have traveled, even when the recorded sounds originate from uncooperative sources or are merely ambient noise.
Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Suc...
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
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.
Lan, Guoxin; Ma, Long; Li, Ying; Liu, Bingxin
Remote Sensing surveillance constitutes an important component of oil spill disaster management system, but subject to monitoring accuracy and ability, which suffered from resolution, environmental conditions, and look-alikes. So this article aims to provide information of identification and distinguishing of look-alikes for optical sensors, and then improve the monitoring precision. Although limited by monitoring conditions of the atmosphere and night, optical satellite remote sensing can provide the intrinsic spectral information of the film and the background sea, then affords the potentiality for detailed identification of the film thickness, oil type classification (crude/light oil), trends, and sea surface roughness by multi-type data products. This paper focused on optical sensors and indicated that these false targets of sun glint, bottom feature, cloud shadow, suspend bed sediment and surface bioorganic are the main factors for false alarm in optical images. Based on the detailed description of the theory of oil spill detection in optical images, depending on the preliminary summary of the feature of look-alikes in visible-infrared bands, a discriminate criteria and work-flow for slicks identification are proposed. The results are helpful to improve the remote sensing monitoring ability and the contingency planning.
Al-Fahdawi, Ahmed A H; Rabee, Adel M; Al-Hirmizy, Shaheen M
The use of remote sensing and GIS in water monitoring and management has been long recognized. This paper, however discusses the application of remote sensing and GIS specifically in monitoring water quality parameters in Al-Habbaniyah Lake, and the results were compared with in situ measurements. Variations of different parameters under investigation were as follows: temperature (15-33°C), pH (7-9), dissolved oxygen (6-11 mg/L), BOD5 (0.5-1.8), electrical conductivity (200-2280 μS/cm), TDS (147-1520 mg/L), TSS (68-3200), turbidity (5-51), nitrate (0.7-20 mg/l), phosphate (77-220 μg/l), and chlorophyll-a (0.9-130 μg/l). Remote sensing results revealed that the band 5 was most likely significantly correlated with turbidity in the winter. Band 2 and 3 was most likely significantly correlated with TDS in autumn and summer, while band 2 was most likely significantly correlated with TSS in autumn, band 2 is most likely significantly correlated with chlorophyll-a in autumn. The current study results demonstrated convergence between in situ and remote sensing readings. The models were used to explore the values of each of chlorophyll-a, TSS,TDS, and turbidity did not deviate much from the values actually measured in the three seasons. Nevertheless, they were very useful in anticipating all seasons of the study due to the insignificant deviation between the remotely sensed values and actual measured values.
Howkins, John, Ed.
Four of the articles in this publication discuss the remote sensing of the Earth and its resources by satellites. Among the topics dealt with are the development and management of remote sensing systems, types of satellites used for remote sensing, the uses of remote sensing, and issues involved in using information obtained through remote…
Liu, Sanchao; Li, Wenbo
Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.
Tilton, James C.; Lawrence, William T.
NASA's Goddard Space Flight Center has developed a fast and effective method for generating image segmentation hierarchies. These segmentation hierarchies organize image data in a manner that makes their information content more accessible for analysis. Image segmentation enables analysis through the examination of image regions rather than individual image pixels. In addition, the segmentation hierarchy provides additional analysis clues through the tracing of the behavior of image region characteristics at several levels of segmentation detail. The potential for extracting the information content from imagery data based on segmentation hierarchies has not been fully explored for the benefit of the Earth and space science communities. This paper explores the potential of exploiting these segmentation hierarchies for the analysis of multi-date data sets, and for the particular application of change monitoring.
Jeong, Seungtaek; Ko, Jonghan; Kim, Mijeong; Kim, Jongkwon
We constructed a lightweight unmanned aerial vehicle (UAV) remote sensing system and determined the ideal method for equipment setup, image acquisition, and image processing. Fields of rice paddy (Oryza sativa cv. Unkwang) grown under three different nitrogen (N) treatments of 0, 50, or 115 kg/ha were monitored at Chonnam National University, Gwangju, Republic of Korea, in 2013. A multispectral camera was used to acquire UAV images from the study site. Atmospheric correction of these images was completed using the empirical line method, and three-point (black, gray, and white) calibration boards were used as pseudo references. Evaluation of our corrected UAV-based remote sensing data revealed that correction efficiency and root mean square errors ranged from 0.77 to 0.95 and 0.01 to 0.05, respectively. The time series maps of simulated normalized difference vegetation index (NDVI) produced using the UAV images reproduced field variations of NDVI reasonably well, both within and between the different N treatments. We concluded that the UAV-based remote sensing technology utilized in this study is potentially an easy and simple way to quantitatively obtain reliable two-dimensional remote sensing information on crop growth.
cyanobacteria , which is strongly influenced by the photosynthetic biomarker pigment, C-phycocyanin (C- PC), having an absorption maximum near 615 nm (Hunter...assemblages are dominated by phycocyanin-rich cyanobacteria using semi- analytical and semi-empirical approaches (Hunter et al. 2008; Simis et al...2005). These studies illustrate the wide range of capabilities of remote sensing to monitor cyanobacteria , ranging from the use of airborne
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.
during the agricultural season. Satellite remote sensing can contribute significantly to such a system by collecting information on crops and on...well as techniques to derive biophysical variables from remotely-sensed data. Finally, the integration of these remote - sensing techniques with crop
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%.
Rosen, Paul A.
This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.
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
Asante, K.O.; Macuacua, R.D.; Artan, G.A.; Lietzow, R.W.; Verdin, J.P.
This paper describes the application of remotely sensed precipitation to the monitoring of floods in a region that regularly experiences extreme precipitation and flood events, often associated with cyclonic systems. Precipitation data, which are derived from spaceborne radar aboard the National Aeronautics and Space Administration's Tropical Rainfall Measuring Mission and from National Oceanic and Atmospheric Administration's infrared-based products, are used to monitor areas experiencing extreme precipitation events that are defined as exceedance of a daily mean areal average value of 50 mm over a catchment. The remotely sensed precipitation data are also ingested into a hydrologic model that is parameterized using spatially distributed elevation, soil, and land cover data sets that are available globally from remote sensing and in situ sources. The resulting stream-flow is classified as an extreme flood event when flow anomalies exceed 1.5 standard deviations above the short-term mean. In an application in the Limpopo basin, it is demonstrated that the use of satellite-derived precipitation allows for the identification of extreme precipitation and flood events, both in terms of relative intensity and spatial extent. The system is used by water authorities in Mozambique to proactively initiate independent flood hazard verification before generating flood warnings. The system also serves as a supplementary information source when in situ gauging systems are disrupted. This paper concludes that remotely sensed precipitation and derived products greatly enhance the ability of water managers in the Limpopo basin to monitor extreme flood events and provide at-risk communities with early warning information. ?? 2007 IEEE.
Handcock, Rebecca N.; Swain, Dave L.; Bishop-Hurley, Greg J.; Patison, Kym P.; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J.
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. PMID:22412327
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.
Shen, Xuhui; Zhang, Xuemin; Hong, Shunying; Jing, Feng; Zhao, Shufan
In the last ten years, a few national research plans and scientific projects on remote sensing application in Earthquake monitoring research are implemented in China. Focusing on advancing earthquake monitoring capability searching for the way of earthquake prediction, satellite electromagnetism, satellite infrared and D-InSAR technology were developed systematically and some remarkable progress were achieved by statistical research on historical earthquakes and summarized initially the space precursory characters, which laid the foundation for gradually promoting the practical use. On the basis of these works, argumentation on the first space-based platform has been finished in earthquake stereoscope observation system in China, and integrated earthquake remote sensing application system has been designed comprehensively. To develop the space-based earthquake observational system has become a major trend of technological development in earthquake monitoring and prediction. We shall pay more emphasis on the construction of the space segment of China earthquake stereoscope observation system and Imminent major scientific projects such as earthquake deformation observation system and application research combined INSAR, satellite gravity and GNSS with the goal of medium and long term earthquake monitoring and forcasting, infrared observation and technical system and application research with the goal of medium and short term earthquake monitoring and forcasting, and satellite-based electromagnetic observation and technical system and application system with the goal of short term and imminent earthquake monitoring.
Bhat, Nagaraj; Gouda, Krushna Chandra; Vh, Manumohan; Bhat, Reshma
Water Reservoirs are the main source of water supply for many settlements as well as power generation. So the water volume and extent of the reservoirs needs to be monitored at regular time intervals for efficient usage as well as to avoid disasters like extreme rainfall events and flood etc. Generally the reservoirs are remotely located so it is difficult to well monitor the water volume and extent. But with growing of Remote sensing and GIS in HPC environment and modeling techniques it is possible to monitor, estimate even predict the reservoir water volumes in advance by using the numerical modeling and satellite Remote sensing data. In this work the monitoring and estimation of the volume of water in the Krishna Raja Sagar(KRS) water reservoir in Karnataka state of India. In this work multispectral images from different sources like Landsat TRS and Digital Elevation Model(DEM) using IRS LISS III (IRS- Indian Remote Sensing, LISS- Linear Imaging Self-Scanning) and ASTER(Advanced Spaceborne Thermal Emission and Reflectance Radiometer) are being used .The methodology involves GIS and image processing techniques such as mosaicing and georeferencing the raw data from satellite, identifying the reservoir water level, segmentation of waterbody using the pixel level analysis. Calculating area and depth per each pixel, the total water volume calculations are done based on the empirical model developed using the past validated data. The water spreaded area calculated by using water indexing is converted in to vector polygon using ArcGIS tools. Water volume obtained by this method is compared with ground based observed values of a reservoir and the comparison well matches for 80% of cases.
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.
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
Johnson, J. D.; Foster, K. E.; Mouat, D. A.; Miller, D. A.; Conn, J. S.
The activities and accomplishments of the Applied Remote Sensing Program during FY 1975-1976 are reported. The principal objective of the Applied Remote Sensing Program continues to be designed projects having specific decision-making impacts as a principal goal. These projects are carried out in cooperation and collaboration with local, state and federal agencies whose responsibilities lie with planning, zoning and environmental monitoring and/or assessment in the application of remote sensing techniques. The end result of the projects is the use by the involved agencies of remote sensing techniques in problem solving.
Guzzetti, F.; Candela, L.; Carlà, R.; Fornaro, G.; Lanari, R.; Mondini, A.; Ober, G.; Fiorucci, F.; Zeni, G.
MORFEO, an Italian acronym for Monitoring Landslide Risk exploiting Earth Observation Technology, is a 3-year research and development project of the Italian Space Agency, carried out in the framework of the Italian national earth observation programme. The project primary contract is Carlo Gavazzi Space, a leading enterprise in space technology and remote sensing applications in Italy. The project research team is composed by seven research institutes of the Italian National Research Council, and six university departments. The team has consolidated experience in landslide detection and mapping, landslide hazard assessment and risk evaluation, remote sensing technology (e.g., laser, optical, radar, GPS) for landslide detection, mapping and monitoring. MORFEO aims at the design, development and demonstration of a prototype system that exploits multiple satellite technologies to support the Italian national civil protection offices to manage landslide risk in Italy. Research activities conducted within the MORFEO project consist chiefly in testing, evaluating and improving EO technologies to increase the current capabilities to detect, map, monitor and forecast landslides in Italy. More precisely, the activities include: (i) detection and mapping landslides exploiting medium-resolution to very-high resolution satellite optical images, (ii) landslide monitoring, through the integration of ground based and satellite technologies, including GPS and DInSAR, (iii) landslide susceptibility, hazard and risk modelling using information obtained processing optical and radar data, (iv) vulnerability and damage assessment, exploiting optical and radar sensors, and (v) landslides forecasting, using thresholds, models and remote sensing data. We provide examples of some of the preliminary results obtained in the MOFEO project.
Wang, Difeng; Pan, Delu; Li, Ning
The State Development and Planning Commission has approved nuclear power projects with the total capacity of 23,000 MW. The plants will be built in Zhejiang, Jiangsu, Guangdong, Shandong, Liaoning and Fujian Province before 2020. However, along with the nuclear power policy of accelerated development in our country, the quantity of nuclear plants and machine sets increases quickly. As a result the environment influence of thermal discharge will be a problem that can't be slid over. So evaluation of the environment influence and engineering simulation must be performed before station design and construction. Further more real-time monitoring of water temperature need to be arranged after fulfillment, reflecting variety of water temperature in time and provided to related managing department. Which will help to ensure the operation of nuclear plant would not result in excess environment breakage. At the end of 2007, an airborne thermal discharge monitoring experiment has been carried out by making use of MAMS, a marine multi-spectral scanner equipped on the China Marine Surveillance Force airplane. And experimental subject was sea area near Qin Shan nuclear plant. This paper introduces the related specification and function of MAMS instrument, and decrypts design and process of the airborne remote sensing experiment. Experiment showed that applying MAMS to monitoring thermal discharge is viable. The remote sensing on a base of thermal infrared monitoring technique told us that thermal discharge of Qin Shan nuclear plant was controlled in a small scope, never breaching national water quality standard.
Zheng, You-Fei; Cheng, Jin-Xin; Wu, Rong-Jun; Guan, Fu-Lai; Yao, Shu-Ran
From the viewpoint of land surface evapotranspiration, and by using the semi-empirical evapotranspiration model based on the Priestley-Taylor equation and the land surface temperature-vegetation index (LST-VI) triangle algorithm, the current monitoring technology of agricultural drought based on remote sensing was improved, and a simplified Evapotranspiration Stress Index (SESI) was derived. With the application of the MODIS land products from March to November in 2008 and 2009, the triangle algorithm modeling with three different schemes was constructed to calculate the SESI to monitor the agricultural drought in the plain areas of Beijing, Tianjin, and Hebei, in comparison with the Temperature Vegetation Dryness Index (TVDI). The results showed that SESI could effectively simplify the remote sensing drought monitoring method, and there was a good agreement between SESI and surface soil (10 and 20 cm depth) moisture content. Moreover, the performance of SESI was better in spring and autumn than in summer, and the SESI during different periods was more comparable than TVDI. It was feasible to apply the SESI to the continuous monitoring of a large area of agricultural drought.
Chawira, M.; Dube, T.; Gumindoga, W.
Lakes Chivero and Manyame are amongst Zimbabwe’s most polluted inland water bodies. MEdium Resolution Imaging Spectrometry level 1b full resolution imagery for 2011 and 2012 were used to derive chlorophyll-a (chl_a) and phycocyanin (blue-green algae) concentrations using a semi-empirical band ratio model; total suspended matter (TSM) concentrations were derived from the MERIS processor. In-situ measured chl_a was used to validate the remotely sensed values. Results indicate that remote sensing measurements are comparable with in situ measurements. A strong positive correlation (R2 = 0.91; MAE = 2.75 mg/m3 (8.5%)) and p < 0.01 (highly significant)) between measured and modeled chl_a concentrations was obtained. Relationships between optically active water constituents were assessed. Measured chl_a correlated well with MERIS modeled phycocyanin (PC) concentration (R2 = 0.9458; p < 0.01 (highly significant)) whilst chl_a and TSM gave (R2 = 0.7344; p < 0.05 (significant)). Modeled TSM and PC concentrations manifested a good relationship with each other (R2 = 9047; p < 0.001 (very highly significant)). We conclude that remote sensing data allow simultaneous retrieval of different water quality parameters as well as providing near real time and space results that can be used by water managers and policy makers to monitor water bodies.
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.
Paska, Eva Petra
The widespread use of digital technologies, combined with rapid sensor advancements resulted in a paradigm shift in geospatial technologies the end of the last millennium. The improved performance provided by the state-of-the-art airborne remote sensing technology created opportunities for new applications that require high spatial and temporal resolution data. Transportation activities represent a major segment of the economy in industrialized nations. As such both the transportation infrastructure and traffic must be carefully monitored and planned. Engineering scale topographic mapping has been a long-time geospatial data user, but the high resolution geospatial data could also be considered for vehicle extraction and velocity estimation to support traffic flow analysis. The objective of this dissertation is to provide an assessment on what state-of-the-art remote sensing technologies can offer in both areas: first, to further improve the accuracy and reliability of topographic, in particular, roadway corridor mapping systems, and second, to assess the feasibility of extracting primary data to support traffic flow computation. The discussion is concerned with airborne LiDAR (Light Detection And Ranging) and digital camera systems, supported by direct georeferencing. The review of the state-of-the-art remote sensing technologies is dedicated to address the special requirements of the two transportation applications of airborne remotely sensed data. The performance characteristics of the geospatial sensors and the overall error budget are discussed. The error analysis part is focused on the overall achievable point positioning accuracy performance of directly georeferenced remote sensing systems. The QA/QC (Quality Assurance/Quality Control) process is a challenge for any airborne direct georeferencing-based remote sensing system. A new method to support QA/QC is introduced that uses the road pavement markings to improve both sensor data accuracy as well as the
Keafer, L. S., Jr. (Editor)
The long term role of airborne/spaceborne passive remote sensing systems for tropospheric air quality research and the identification of technology advances required to improve the performance of passive remote sensing systems were discussed.
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
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.
Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Husak, G. J.; Magadzire, T.; Verdin, J. P.
Global agriculture monitoring is a crucial aspect of monitoring food security in the developing world. The Famine Early Warning Systems Network (FEWS NET) has a long history of using remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and climate change. In recent years, it has become apparent that FEWS NET requires the ability to apply monitoring and modeling frameworks at a global scale to assess potential impacts of foreign production and markets on food security at regional, national, and local levels. Scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the University of California Santa Barbara (UCSB) Climate Hazards Group have provided new and improved data products as well as visualization and analysis tools in support of the increased mandate for remote monitoring. We present our monitoring products for measuring actual evapotranspiration (ETa), normalized difference vegetation index (NDVI) in a near-real-time mode, and satellite-based rainfall estimates and derivatives. USGS FEWS NET has implemented a Simplified Surface Energy Balance (SSEB) model to produce operational ETa anomalies for Africa and Central Asia. During the growing season, ETa anomalies express surplus or deficit crop water use, which is directly related to crop condition and biomass. We present current operational products and provide supporting validation of the SSEB model. The expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) production system provides FEWS NET with an improved NDVI dataset for crop and rangeland monitoring. eMODIS NDVI provides a reliable data stream with a relatively high spatial resolution (250-m) and short latency period (less than 12 hours) which allows for better operational vegetation monitoring. We provide an overview of these data and cite specific applications for crop monitoring. FEWS NET uses satellite rainfall estimates as inputs for
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
Keskin, Göksu; Teutsch, Caroline D.; Lenz, Andreas; Middelmann, Wolfgang
Areas occupied by oil pipelines and storage facilities are prone to severe contamination due to leaks caused by natural forces, poor maintenance or third parties. These threats have to be detected as quickly as possible in order to prevent serious environmental damage. Periodical and emergency monitoring activities need to be carried out for successful disaster management and pollution minimization. Airborne remote sensing stands out as an appropriate choice to operate either in an emergency or periodically. Hydrocarbon Index (HI) and Hydrocarbon Detection Index (HDI) utilize the unique absorption features of hydrocarbon based materials at SWIR spectral region. These band ratio based methods require no a priori knowledge of the reference spectrum and can be calculated in real time. This work introduces a flexible airborne pipeline monitoring system based on the online quasi-operational hyperspectral remote sensing system developed at Fraunhofer IOSB, utilizing HI and HDI for oil leak detection on the data acquired by an SWIR imaging sensor. Robustness of HI and HDI compared to state of the art detection algorithms is evaluated in an experimental setup using a synthetic dataset, which was prepared in a systematic way to simulate linear mixtures of selected background and oil spectra consisting of gradually decreasing percentages of oil content. Real airborne measurements in Ettlingen, Germany are used to gather background data while the crude oil spectrum was measured with a field spectrometer. The results indicate that the system can be utilized for online and offline monitoring activities.
Wang, Fu-tao; Wang, Shi-xin; Zhou, Yi; Wang, Li-tao; Yan, Fu-li; Li, Wen-jun; Liu, Xiong-fei
The secondary geological disasters triggered by the Lushan earthquake on April 20, 2013, such as landslides, collapses, debris flows, etc., had caused great casualties and losses. We monitored the number and spatial distribution of the secondary geological disasters in the earthquake-hit area from airborne remote sensing images, which covered areas about 3 100 km2. The results showed that Lushan County, Baoxing County and Tianquan County were most severely affected; there were 164, 126 and 71 secondary geological disasters in these regions. Moreover, we analyzed the relationship between the distribution of the secondary geological disasters, geological structure and intensity. The results indicate that there were 4 high-hazard zones in the monitored area, one focused within six kilometers from the epicenter, and others are distributed along the two main fault zones of the Longmen Mountain. More than 97% secondary geological disasters occurred in zones with a seismic intensity of VII to IX degrees, a slope between 25 A degrees and 50 A degrees, and an altitude of between 800 and 2 000 m. At last, preliminary suggestions were proposed for the rehabilitation and reconstruction planning of Lushan earthquake. According to the analysis result, airborne and space borne remote sensing can be used accurately and effectively in almost real-time to monitor and assess secondary geological disasters, providing a scientific basis and decision making support for government emergency command and post-disaster reconstruction.
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.
Goettelman, R. C.; Grass, L. B.; Millard, J. P.; Nixon, P. R.
The following multispectral remote-sensing techniques were compared to determine the most suitable method for routinely monitoring agricultural subsurface drain conditions: airborne scanning, covering the visible through thermal-infrared (IR) portions of the spectrum; color-IR photography; and natural-color photography. Color-IR photography was determined to be the best approach, from the standpoint of both cost and information content. Aerial monitoring of drain conditions for early warning of tile malfunction appears practical. With careful selection of season and rain-induced soil-moisture conditions, extensive regional surveys are possible. Certain locations, such as the Imperial Valley, Calif., are precluded from regional monitoring because of year-round crop rotations and soil stratification conditions. Here, farms with similar crops could time local coverage for bare-field and saturated-soil conditions.
El Vilaly, Mohamed Abd salam M.
Droughts are a recurrent part of our climate, and are still considered to be one of the most complex and least understood of all natural hazards in terms of their impact on the environment. In recent years drought has become more common and more severe across the world. For more than a decade, the US southwest has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources. The focus of this work is achieving a better understanding of the impact of drought on the lands of the Hopi Tribe and Navajo Nation, situated in the Northeastern corner of Arizona. This research explores the application of remote sensing data and geospatial tools in two studies to monitor drought impacts on vegetation productivity. In both studies we used land surface phenometrics as the data tool. In a third related study, I have compared satellite-derived land surface phenology (LSP) to field observations of crop stages at the Maricopa Agricultural Center to achieve a better understanding of the temporal sensitivity of satellite derived phenology of vegetation and understand their accuracy as a tool for monitoring change. The first study explores long-term vegetation productivity responses to drought. The paper develops a framework for drought monitoring and assessment by integrating land cover, climate, and topographical data with LSP. The objective of the framework is to detect long-term vegetation changes and trends in the Normalized Difference Vegetation Index (NDVI) related productivity. The second study examines the major driving forces of vegetation dynamics in order to provide valuable spatial information related to inter-annual variability in vegetation productivity for mitigating drought impacts. The third study tests the accuracy of remote sensing-derived LSP by comparing them to the actual seasonal phases of crop growth. This provides a way to compare and validate the various LSP algorithms, and more crucially, helps to
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.
Savastano, K. J.; Leming, T. D.
An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.
di, L.; Yu, G.; Han, W.; Deng, M.
Group on Earth Observations (GEO) is a voluntary partnership of governments and international organizations. GEO is coordinating the implementation of the Global Earth Observation System of Systems (GEOSS), a worldwide effort to make Earth observation resources more useful to the society. As one of the important technical contributors to GEOSS, the Center for Spatial Information Science and Systems (CSISS), George Mason University, is implementing a remote sensing-based global agricultural drought monitoring and forecasting system (GADMFS) as a GEOSS societal benefit areas (agriculture and water) prototype. The goals of the project are 1) to establish a system as a component of GEOSS for providing global on-demand and systematic agriculture drought information to users worldwide, and 2) to support decision-making with improved monitoring, forecasting, and analyses of agriculture drought. GADMFS has adopted the service-oriented architecture and is based on standard-compliant interoperable geospatial Web services to provide online on-demand drought conditions and forecasting at ~1 km spatial and daily and weekly temporal resolutions for any part of the world to world-wide users through the Internet. Applicable GEOSS recommended open standards are followed in the system implementation. The system’s drought monitoring relies on drought-related parameters, such as surface and root-zone soil moisture and NDVI time series derived from remote sensing data, to provide the current conditions of agricultural drought. The system links to near real-time satellite remote sensing data sources from NASA and NOAA for the monitoring purpose. For drought forecasting, the system utilizes a neural-network based modeling algorithm. The algorithm is trained with inputs of current and historic vegetation-based and climate-based drought index data, biophysical characteristics of the environment, and time-series weather data. The trained algorithm will establish per-pixel model for
Albright, Thomas 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.
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
Cuomo, V.; Lasaponara, R.; Macchiato, F. M.; Simoniello, T.
Remote sensing provides useful data for environmental monitoring nevertheless, efforts are required to test and evaluate methods and techniques to be applied for operational applications. Since 1994, in the context of several projects founded by the Italian Environment Protection Agency (ANPA) and Environmental Department of Basilicata Region, we have experienced the use of remote sensing for environmental monitoring in operative contexts. Particularly, we have developed and tested methodologies based on the integration of remote sensed data aimed at: estimations of space/temporal dynamics of surface parameters (such as temperature and vegetation indexes), forest fire detection and danger estimation, risk assessment, change detection, desertification, alpine ice monitoring, etc. Some examples are briefly summarized below. The action C of Timoran projects was devoted to forest fire monitoring. We devised a dynamic short time fire forecasting based on the integration of remote sensing and GIS. A daily fire susceptibility assessment was performed, from NOAA-AVHRR exploiting the cross analysis of the temporal evolution of NDVI and the middle-infrared channel. Four danger classes have been obtained (low, moderate, high and very high). We also estimated the expected fire severity combining and integrating different danger variables, such as: (1) fire susceptibility (water stress) performed using satellite AVHRR data, (2) fuel type, (3) incidence of topography, (4) wind forecast, obtained from meteorological models. Potential and limitations of AVHRR for fire detection were evaluated in the Italian ecosystems. At present we are working on evaluating the effectiveness of Landsat-TM imagery for mapping burned area in heterogeneous regions, characterized by different cover types, rough topography and complex ecosystems. In the context of "Devising of environmental indicators based on remote sensing data" project, funded by ANPA, we investigated on an AVHRR time series from
Tappan, G. Gray; Moore, Donald G.; Knauseberger, Walter I.
Development programmes in Sahelian Africa are beginning to use geographic information system (GIS) technology. One of the GIS and remote sensing programmes introduced to the region in the late 1980s was the use of seasonal vegetation maps made from satellite data to support grasshopper and locust control. Following serious outbreaks of these pests in 1987, the programme addressed a critical need, by national and international crop protection organizations, to monitor site-specific dynamic vegetation conditions associated with grasshopper and locust breeding. The primary products used in assessing vegetation conditions were vegetation index (greenness) image maps derived from National Oceanic and Atmospheric Administration satellite imagery. Vegetation index data were integrated in a GIS with digital cartographic data of individual Sahelian countries. These near-real-time image maps were used regularly in 10 countries for locating potential grasshopper and locust habitats. The programme to monitor vegetation conditions is currently being institutionalized in the Sahel.
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
Gadallah, Fawziah L.
Human environmental impact has occurred on a global scale. Effective management of problems occurring over broad regions requires monitoring and intervention over large extents of space and time. Remote sensing provides an attractive data source, particularly as satellite data have been consistently collected over both space and time and present a readily available, inexpensive archive. At best, however, remote sensing provides proxy data for the underlying variables of interest. Here remotely sensed data are used to measure habitat degradation at a lesser snow goose colony. An increase in goose numbers has led to a loss of forage vegetation in the arctic and sub-arctic marshes where the geese nest and raise their young. In particular, isostatic rebound has generated extensive coastal marshes along the west coast of Hudson Bay, and lesser snow geese colonized such a marsh at La Perouse Bay in the late 1950's. This well-studied colony is used to assess the feasibility of mapping decadal change with Landsat imagery. A baseline map is developed using satellite data, aerial photography, and a knowledge of vegetation dynamics at the site. Calibration equations, relating the quantity of above-ground vegetation and its reflectance, are developed using cross-validation and goodness-of-prediction measures for field data collected on-site. To detect changes in vegetation state, tree-classification and cross-validation were applied to ground data. Using satellite imagery, changes in vegetation quantity and type could be detected against a background of mineral soil, but not against a background of mosses. Even in this site with low topographic variability, few species and few strong driving forces (i.e. isostatic rebound and herbivory), multiple change trajectories are possible. As different trajectories have different influences on both the reflectance of the surface and the expected behaviour and functioning of the system, each must be accounted for separately. Failure to
Li, Fei; Zhao, Ying; Zheng, Jiajia; Luo, Juhua; Zhang, Xiaoqiang
The quantification of grassland grazing intensity (GI) and its detailed spatial distribution are important for grassland management and ecological protection. Remote sensing has great potential in these areas, but its use is still limited. This study analyzed the impacts of grazing on biophysical properties of vegetation and suggested using biomass to quantify GI because of its stability and interpretability. In comparison to a single spectral index, such as the red edge index (REI), combining REI and a cellulose absorption ratio index calculated from hyperspectral data performs better for biomass estimation. Further, an auxiliary spectral index, called the grazing monitoring index (GMI), was developed based on differences in spectral reflectance in the infrared range. Experiments in a grazing area of the Inner Mongolia grassland indicated that GMI can identify GI, with three range intervals (GMI <0, 0-1, and ≥1) used to describe the biomass distribution. The results showed that combining GMI and biomass was more successful than existing approaches for identifying the grassland variability resulting from the spatial heterogeneity of grazing behavior. The thresholds of biomass for four GI levels (ungrazed, lightly grazed, moderately grazed, and heavily grazed) could be determined by the intersections of biomass distributions. In addition, the approach developed at the on-ground canopy scale was extended to remotely sensed Hyperion data. The results showed that the approach could successfully identify the grazing treatments of blocks in the experimental grazing area. Overall, our study provides inspiration and ideas for using satellite remote sensing for evaluating plant production, standing biomass, and livestock impacts.
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
Matinfar, Hamid Reza
The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. Change detection is a technique in remote sensing for detecting the changes which have occurred in the existing phenomena over two or more periods of time in a particular area. In this paper, Khoramabad a city in Lorestan province of Iran, was examined in a case study via three techniques of remote sensing: (1) NDVI comparison, (2) Principle Component Analysis, and (3) the Post Classification. To carry out these three techniques, TM and ETM+ data obtained from Landsat Satellite within the years 1991 to 2002was used to monitor environmental changes especially the physical development of the area and its devastating effects on the green space. In this research, one of the capabilities of Thematic Mapper of Landsat Satellite is presented which is oriented towards determining land use changes and methodology in comparison to the change detection techniques via the standard method.. The result presented here indicates that the farming land area decreased between 1991 and 2002 by 14% from 4975 to 3672 ha. Also the urban and non arable land area increased from 5376 to 6678 ha. We may conclude any land use/land cover change must be permitted by land management expert
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.
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.
Huang, Ming-Fang; Plant, Genevieve; Tanaka, Akihiro; Cvijetic, Neda; Tian, Yue; Wysocki, Gerard; Wang, Ting
We propose an optical gas sensing network directly overlaid onto optical access networks, hybrid TDM/WDM-PONs. Centralized remote gas monitoring is demonstrated using three different sensing technologies: Chirp Laser Dispersion Spectroscopy (CLaDS), Direct Laser Absorption Spectroscopy (DLAS) and tunable diode laser absorption spectroscopy (TDLS). DLAS performs fast threshold detection while CLaDS provides quantitative information about the gas. Additionally, TDLS utilizes a cost-effective solution for multiple gases detection. The results confirm that centralized remote gas sensing can be realized in optical communication networks using standard single-mode fiber (SMF), which provides a real time, low cost, and maintenance-free solution.
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
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
Ozbey, Burak; Unal, Emre; Ertugrul, Hatice; Kurc, Ozgur; Puttlitz, Christian M.; Erturk, Vakur B.; Altintas, Ayhan; Demir, Hilmi Volkan
We propose and demonstrate a wireless, passive, metamaterial-based sensor that allows for remotely monitoring submicron displacements over millimeter ranges. The sensor comprises a probe made of multiple nested split ring resonators (NSRRs) in a double-comb architecture coupled to an external antenna in its near-field. In operation, the sensor detects displacement of a structure onto which the NSRR probe is attached by telemetrically tracking the shift in its local frequency peaks. Owing to the NSRR's near-field excitation response, which is highly sensitive to the displaced comb-teeth over a wide separation, the wireless sensing system exhibits a relatively high resolution (<1 μm) and a large dynamic range (over 7 mm), along with high levels of linearity (R2 > 0.99 over 5 mm) and sensitivity (>12.7 MHz/mm in the 1–3 mm range). The sensor is also shown to be working in the linear region in a scenario where it is attached to a standard structural reinforcing bar. Because of its wireless and passive nature, together with its low cost, the proposed system enabled by the metamaterial probes holds a great promise for applications in remote structural health monitoring. PMID:24445416
This volume contains the proceedings of SPIE`s remote sensing symposium which was held September 22--24, 1998, in Barcelona, Spain. Topics of discussion include the following: calibration techniques for soil moisture measurements; remote sensing of grasslands and biomass estimation of meadows; evaluation of agricultural disasters; monitoring of industrial and natural radioactive elements; and remote sensing of vegetation and of forest fires.
Nagy, Attila; Tamás, János; Fehér, János
The World Meteorological Organization (WMO) and Global Water Partnership (GWP) have launched a joint Integrated Drought Management Programme (IDMP) to improve monitoring and prevention of droughts. In the frame of this project this study focuses on identification of agricultural drought characteristics and elaborates a monitoring method (with application of remote sensing data), which could result in appropriate early warning of droughts before irreversible yield loss and/or quality degradation occur. The spatial decision supporting system to be developed will help the farmers in reducing drought risk of the different regions by plant specific calibrated drought indexes. The study area was the Tisza River Basin, which is located in Central Europe within the Carpathian Basin. For the investigations normalized difference vegetation index (NDVI) was used calculated from 16 day moving average chlorophyll intensity and biomass quantity data. The results offer concrete identification of remote sensing and GIS data tools for agricultural drought monitoring and forecast, which eventually provides information on physical implementation of drought risk levels. In the first step, we statistically normalized the crop yield maps and the MODIS satellite data. Then the drought-induced crop yield loss values were classified. The crop yield loss data were validated against the regional meteorological drought index values (SPI), the water management and soil physical data. The objective of this method was to determine the congruency of data derived from spectral data and from field measurements. As a result, five drought risk levels were developed to identify the effect of drought on yields: Watch, Early Warning, Warning, Alert and Catastrophe. In the frame of this innovation such a data link and integration, missing from decision process of IDMP, are established, which can facilitate the rapid spatial and temporal monitoring of meteorological, agricultural drought phenomena and its
Nádor, G.; Fényes, D.; Vasas, L.; Surek, G.
The gradual dispersion of western corn rootworm (WCR) is becoming a serious maize pest in Europe, and all over the world. In 2008 using remote sensing data, the Remote Sensing Centre of Institute of Geodesy, Cartography and Remote Sensing (FÖMI RSC) carried out this project to identify WCR larval damage. Our goal with the present project is to assess and identify the disorder and structural changes caused by WCR larvae using optical (IRS-P6 AWiFS, IRS-P6 LISS, SPOT4 and SPOT5) and polarimetic radar (ALOS PALSAR) satellite images. We used 3 different individual features (Mono-maize feature, Optical feature, Radar feature) derived from remote sensing data to accomplish this goal. Findings were tested against on-the-spot ground assessments. Using radar polarimetry increased the accuracy significantly. The final results have implications for plant protection strategy, farming practices, pesticide producers, state authorities and research institutes.
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
Pencheva, Vasilka H.; Penchev, S.; Naboko, Vassily N.; Naboko, Sergei V.
We report new aspects of application of pulsed GaAs diode lasers, concerning absorption spectroscopy of water vapor of third oscillatory molecular overtone 8990 - 9012 angstroms, and Mie-scattering lidar signal in the 15 km range. It is accessible by the power characteristics of a system utilizing the powerful `chip-stack' GaAs diode lasers, employing optimal photodetection technique based on an analyzing system with computer operated boxcar. Data on atmospheric aerosol backscatter signal acquired by DL lidar are presented with relevance to the potential of complex atmospheric remote sensing. GaAs diode lasers, with radiation matching water vapor spectrum of absorption- coefficients of 0.5 - 5 km-1 in Beer's law, are shown feasible for DIAL monitoring of atmospheric humidity.
Eitel, Jan U. H.; Keefe, Robert F.; Long, Dan S.; Davis, Anthony S.; Vierling, Lee A.
Active ground optical remote sensing (AGORS) devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and do not require spectral reference readings. Besides measuring red (590–670 nm) and near-infrared (>760 nm) reflectance AGORS devices have recently become available that also measure red-edge (730 nm) reflectance. We tested the hypothesis that the additional availability of red-edge reflectance information would improve AGORS of plant stress induced chlorophyll breakdown in Scots pine (Pinus sylvestris). Our results showed that the availability of red-edge reflectance information improved AGORS estimates of stress induced variation in chlorophyll concentration (r2 > 0.73, RMSE < 1.69) when compared to those without (r2 = 0.57, RMSE = 2.11). PMID:22319275
Song, Yu; Song, Xiao-dong; Guo, Qing-hai; Tang, Li-na
The explosive growth of algae in inland water bodies is one of the major water environmental problems in China, and it's very important to monitor the dynamic of algae in both temporal and spatial scales. In the present paper, a model, which was used to extract the algae information from the water body of Taihu Lake using MODIS data, was established based on the remote sensing index and image false color composite methods. Using this model, we studied the algae explosive growth formation process between March and May in 2007. Through the analysis of the temporal and spatial distribution features of the algae outbreak between the spring and summer seasons, an early warning method of algal blooms was proposed, that is, when the MODIS green index mainly concentrated in the range between 0. 6 and 0. 8, the water body of Taihu Lake can be considered to have been in the early alarming stage of algal blooms.
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.
Zeng, Linglin; Shan, Jie; Xiang, Daxiang
Various drought monitoring models have been developed from different perspectives, as drought is impacted by various factors (precipitation, evaporation, runoff) and usually reflected in various aspects (vegetation condition, temperature). Cloud not only plays an important role in the earth's energy balance and climate change, but also directly impacts the regional precipitation and evaporation. As a result, the change of cloud cover and cloud type can be used to monitor drought. This paper proposes a new drought composite index, the Drought Composite Index (DCI), for drought monitoring based on multi-sensor remote sensing data in cropland of Gansu Province. This index combines the cloud classification data (CLS) from FY satellite and Vegetation Condition Index (VCI) which was calculated using the maximum and minimum NDVI values for the same time period from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson correlation was performed to correlate NDVI, VCI, CLS and DCI values to precipitation data and soil moisture (SM) data collected from 20 meteorological stations during the growing season of 2011 and 2012. Better agreement was observed between DCI and precipitation as compared with that between NDVI/VCI and precipitation, especially the one-month precipitation, and there is an obvious time lag in the response of vegetation to precipitation. In addition, the results indicated that DCI well reflected precipitation fluctuations in the study area promising a possibility for early drought awareness necessary and near real-time drought monitoring.
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.
Hepner, George F.
The University of Utah, Department of Geography has developed a research and instructional program in satellite remote sensing and image processing. The University requested funds for the purchase of software licenses, mass storage for massive hyperspectral imager data sets, upgrades for the central data server to handle the additional storage capacity, a spectroradiometer for field data collection. These purchases have been made. This equipment will support research in one of the newest and most rapidly expanding areas of remote sensing.
Kayanne, H.; Matsunaga, T.; Kanbara, H.; Kato, M.
Coral reefs in the world are under the crisis of degradation both by increasing human activities in coastal zone and by the global changes. All the factors of the global change scenario would bring serious impact on coral reefs. Increase in CO2 suppress calcification in coral reefs. The world-wide bleaching event in 1997-1998 was supposed to be at least partly resulted from global warming. Coral reefs would submerge by sea level rise in this century. To conserve and manage coral reefs against these threats, monitoring of coral reef by satellite remote sensing is important. ASTER has provided effective data for mapping coral reef landforms and benthic communities. The most basic geomorphological and ecological zonation was successfully classified using ASTER data. For example, coral reef flat with its zonation of algai rim, rubble bank, back reef was clearly identified by ASTER by decision tree method and bottom index using VNIR bands data. For the basis of effective monitoring of coral reefs, we have constructed coral reef remote sensing database, which contains more than 1,100,000 data. Tropical and subtropical oceans (40N-40S) were gridded by 0.5 x 0.5 degrees and the grids with coral reefs were identified. The grids with coral reefs correspond to path/rows of the satellite (MOS1, JERS-1, ADEOS, LANDSAT, SPOT and TERRA) and basic information (existence of data, satellite and sensor, path/row, lat/log, aquisition date, cloud cover, type of coral reef) of so-far obtained satellite data until 2000 was input in the database. Status of data aquisition at specific coral reefs can be listed up by this database.
Macomber, S.A.; Woodcock, C.E. )
A prolonged drought in the western US has resulted in alarming levels of mortality in conifer forests. Satellite remote sensing holds the potential for mapping and monitoring the effects of such environmental changes over large geographic areas in a timely manner. Results from the application of a forest canopy reflectance model using multitemporal Landsat TM imagery and field measurements, indicate conifer mortality can be effectively mapped and inventoried. The test area for this project is the Lake Tahoe Basin Management Unit in the Sierra Nevada of California. The Landsat TM images are from the summers of 1988 and 1991. The Li-Strahler canopy model estimates several forest stand parameters, including tree size and canopy cover for each conifer stand, from reflectance values in satellite imagery. The difference in cover estimates between the dates forms the basis for stratifying stands into mortality classes, which are used as both themes in a map and the basis of the field sampling design. Field measurements from 61 stands collected in the summer of 1992 indicate 15% of the original timber volume in the true fir zone died between 1988 and 1992. The resulting low standard error of 11% for this estimate indicates the utility of these mortality classes for detecting areas of high mortality. Also, the patterns in the estimated mean timber volume loss for each class follow the expected trends. The results of this project are immediately useful for fire hazard management, by providing both estimates of the degree of overall mortality and maps showing its location. They also indicate current remote sensing technology may be useful for monitoring the changes in vegetation that are expected to result from climate change.
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.
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 email@example.com
Huang, He; Yang, Siquan; Li, Suju; He, Haixia; Liu, Ming; Xu, Feng; Lin, Yueguan
Earthquake is one major nature disasters in the world. At 8:02 on 20 April 2013, a catastrophic earthquake with Ms 7.0 in surface wave magnitude occurred in Sichuan province, China. The epicenter of this earthquake located in the administrative region of Lushan County and this earthquake was named the Lushan earthquake. The Lushan earthquake caused heavy casualties and property losses in Sichuan province. After the earthquake, various emergency relief supplies must be transported to the affected areas. Transportation network is the basis for emergency relief supplies transportation and allocation. Thus, the road losses of the Lushan earthquake must be monitoring. The road losses monitoring results for Lushan earthquake disaster utilization multisource remote sensing images were reported in this paper. The road losses monitoring results indicated that there were 166 meters' national roads, 3707 meters' provincial roads, 3396 meters' county roads, 7254 meters' township roads, and 3943 meters' village roads were damaged during the Lushan earthquake disaster. The damaged roads mainly located at Lushan County, Baoxing County, Tianquan County, Yucheng County, Mingshan County, and Qionglai County. The results also can be used as a decision-making information source for the disaster management government in China.
The activities of the Mississippi Remote Sensing Center are described in addition to technology transfer and information dissemination, remote sensing topics such as timber identification, water quality, flood prevention, land use, erosion control, animal habitats, and environmental impact studies are also discussed.
A general overview of the USGS land remote sensing program is presented. The contents include: 1) Brief overview of USGS land remote sensing program; 2) Highlights of JACIE work at USGS; 3) Update on NASA/USGS Landsat Data Continuity Mission; and 4) Notes on alternative data sources.
Thomas, J. P.
Some of the findings of the Superflux program relative to fishery research and monitoring are reviewed. The actual and potential influences of the plume on the shelf ecosystem contiguous to the mouth of Chesapeake Bay are described and insights derived from the combined use of in situ and remotely sensed data are presented.
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.
Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation
Soil water sensing methods are widely used to characterize the rhizosphere and below, but only a few are capable of delivering water content data with accuracy for the entire soil profile such that evapotranspiration (ET) can be determined by soil water balance with minimal error. One such is the ne...
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.
Piscini, Alessandro; Lombardo, Valerio
Neural networks are an effective and well-established technique for the classification of satellite images. In addition, once well trained, they prove to be very fast in the application stage. Furthermore satellite remote sensing is a very effective and safe way to monitor volcanic eruptions in order to safeguard the environment and the people affected by such natural hazards. In our study a Back Propagation Neural Network was used for the recognition of thermal anomalies affecting hot lava pixels in multispectral remote sensed images. The network was trained using the three thermal channels of the Advanced Very High Resolution Radiometer (AVHHR) sensor as inputs and the corresponding values of heat flux, estimated using a two thermal component model, as reference outputs. As a case study the volcano Etna (Eastern Sicily, Italy) was chosen and the neural network was trained with a time series of AVHRR images belonging to an effusive eruption which took place during the month of July 2006, and validated on three independent data sets of images of the same eruption and on two relative to an eruption occurred the following month. Whilst for both night-time and day-time validation images the neural network identified the image pixels affected by hot lava with a 100% success rate, for the daytime images also adjacent pixels were included, apparently not interested by lava flow. Despite these performance differences under different illumination conditions, the proposed method can be considered effective both in terms of classification accuracy and generalization capability. In particular our approach proved to be robust in the rejection of false positives, often corresponding to noisy or cloudy pixels, whose presence in multispectral images can often undermine the performance of traditional classification algorithms. Future work shall address application of the proposed method to data from different eruptions provided by the MODIS sensor aboard the Terra and Aqua
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
Zhang, Yuanzhi; Chen, Zhengyi; Zhu, Boqin; Luo, Xiuyue; Guan, Yanning; Guo, Shan; Nie, Yueping
The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.
This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. We argue that satellite observations not currently used for operational drought monitoring, such as near-surface air relative humidity data from the Atmospheric Infrared Sounder (AIRS) mission, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. While there are immense opportunities, there are major challenges including data continuity, unquantified uncertainty, sensor changes, and community acceptability. One of the major limitations of many of the currently available satellite observations is their short length of record. A number of relevant satellite missions and sensors (e.g., the Gravity Recovery and Climate Experiment, GRACE) provide only a decade of data, which may not be sufficient to study droughts from a climate perspective. However, they still provide valuable information about relevant hydrologic and ecological processes linked to this natural hazard. Therefore, there is a need for models and algorithms that combine multiple datasets and/or assimilate satellite observations into model simulations to generate long-term climate data records. Finally, the study identifies a major gap in indicators for describing drought impacts on the carbon and nitrogen cycle, which are fundamental to assessing drought impacts on ecosystems.
D'Sa, E. J.; Ko, D. S.; Stone, G.; Walker, N. D.
The northern Gulf of Mexico is strongly influenced by the discharge of water, nutrients, dissolved and suspended particulate matter from the Mississippi-Atchafalaya River system, the largest in North America. It is also frequently impacted by energetic meteorological events that cause storm surge, high waves and affects water quality along its coastal waters. We describe the components of an integrated web-based Gulf Coast Information System (GCIS) (http://gulf-coast.lsu.edu) developed to serve remotely sensed products from a number of NASA satellite sensors such as the SeaWiFS and MODIS ocean color and the QuikSCAT wind sensors. GCIS also serves high-resolution nowcast and 48-hour forecast outputs (sea level variations, temperature, salinity and currents) from a 3-dimensional NCOM coastal circulation model for the coastal states of Mississippi, Louisiana and Texas. The GCIS is coupled to the near real-time outputs of a field monitoring and satellite receiving system, the Wave-Current Information System (WAVCIS) (http://www.wavcis.lsu.edu) and Earth Scan Laboratory (ESL) (www.esl.lsu.edu), respectively that provide critical decision support during hurricanes to the Gulf Coast. We present results on the use of the combined field, satellite and model outputs to monitor the effects of fronts, hurricanes, oil spill and the potential to study longer term climate impacts along the Gulf coast.
Roller, N. E. G.
The concept of using remote sensing to inventory wetlands and the related topics of proper inventory design and data collection are discussed. The material presented shows that aerial photography is the form of remote sensing from which the greatest amount of wetlands information can be derived. For extensive, general-purpose wetlands inventories, however, the use of LANDSAT data may be more cost-effective. Airborne multispectral scanners and radar are, in the main, too expensive to use - unless the information that these sensors alone can gather remotely is absolutely required. Multistage sampling employing space and high altitude remote sensing data in the initial stages appears to be an efficient survey strategy for gathering non-point specific wetlands inventory data over large areas. The operational role of remote sensing insupplying inventory data for application to several typical wetlands management problems is illustrated by summary descriptions of past ERIM projects.
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.
Partial Contents: Short Introduction to Nation’s Remote Sensing Units, Domestic Airborne Remote - Sensing System, Applications in Monitoring Natural...Disasters, Applications of Imagery From Experimental Satellites Launched in 1985, 1986, Current Status, Future Prospects for Domestic Remote - Sensing -Satellite...Ground Station, and Radar Remote - Sensing Technology Used to Monitor Yellow River Delta,
Remote sensing is one of the best ways to be able to monitor and see changes in the Earth. The use of satellite images in the classroom can be a practical way to help students understand the importance and use of remote sensing and Geographic Information Systems (GIS). It is essential in helping students to understand that underlying individual data points are converted to a broad spatial form. The use of actual remote sensing data makes this more understandable to the students e.g. an online map of recent earthquake events, geologic maps, satellite imagery. For change detection, images of years ten or twenty years apart of the same area can be compared and observations recorded. Satellite images of different places can be available on the Internet or from the local space agency. In groups of mixed abilities, students can observe changes in land use over time and also give possible reasons and explanations to those changes. Students should answer essential questions like, how does satellite imagery offer valuable information to different faculties e.g. military, weather, environmental departments and others. Before and after images on disasters for example, volcanoes, floods and earthquakes should be obtained and observed. Key questions would be; how can scientists use these images to predict, or to change the future outcomes over time. How to manage disasters and how the archived images can assist developers in planning land use around that area in the future. Other material that would be useful includes maps and aerial photographs of the area. A flight should be organized over the area for students to acquire aerial photographs of their own; this further enhances their understanding of the concept "remote sensing". Environmental issues such as air, water and land pollution can also be identified on satellite images. Key questions for students would include causes, effects and possible solutions to the problem. Conducting a fieldwork exercise around the area would
Philipson, W. R. (Principal Investigator)
Built on Cornell's thirty years of experience in aerial photographic studies, the NASA-sponsored remote sensing program strengthened instruction and research in remote sensing, established communication links within and beyond the university community, and conducted research projects for or with town, county, state, federal, and private organizations in New York State. The 43 completed applied research projects are listed as well as 13 spinoff grants/contracts. The curriculum offered, consultations provided, and data processing facilities available are described. Publications engendered are listed including the thesis of graduates in the remote sensing program.
Dardanelli, Gino; La Loggia, Goffredo; Perfetti, Nicola; Capodici, Fulvio; Puccio, Luigi; Maltese, Antonino
deformations monitoring of the Castello dam. Displacements of different sections of the dam reveal different behaviour (in time and periodicity) that looks to be related with water surface (and level) retrieved from remote sensing.
Lie, Penny; Mowry, Mychelle; Nettle, Jeremy
Wireless technology enables clinicians to continuously monitor their patients' conditions remotely. This allows doctors to leverage data to make informed decisions and interventions with immediacy, thereby reducing or eliminating hospital stays, driving down costs and improving outcomes. Remote monitoring initiatives rely on a sophisticated end-to-end IT infrastructure that encompasses wireless sensors and mobile telecommunications devices as well as middleware and business intelligence capabilities to provide a faster response loop, greater visibility and an extensible and scalable framework. This article explores the potential of wireless remote monitoring to improve care and reduce the cost of chronic disease management in an aging and mobile population. The article will also discuss the IT infrastructure and operational requirements needed to ensure that data from remote sensors can be quickly translated into actionable information.
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.
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.
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
Abd Salam El Vilaly, Mohamed; El Vilaly, Audra; Badiane, Ousmane
Understanding the complex feedbacks between climate, environmental change, and human activities is essential to the development of sustainable agricultural systems. A key aspect of crop production that shows immediate response to climate change is crop phenology, which defines the shape and progress of the growing season and is an integrator of all environmental factors controlling crop production. This research aims to characterize remote sensing-based land surface phenology of cropped areas and compare them to the actual crop growing seasons recorded by farmers: planting, emergences, flowering, fruiting, and harvest date. We use the 2000-2013 MODIS Terra 16-day record of vegetation index to extract 4 phenometrics (Start and Length of Growing Season, Date of Growing Season Peak, and the Growing Season Cumulative Signal). Most of these metrics are simple time-related phenometrics. A spatiotemporal phenological characterization of cropped/managed lands in the basin already shows distinct response patterns and trajectories along climate gradients. This permits us to monitor cropped lands and their responses to disturbances, such as drought, fire, flooding, and human activities. In turn, interviewing farmers in the basin and consulting their phenological records. This study will allow for robust validation of remote sensing LSP algorithms, and more crucially, will help characterize any remote sensing-based metrics that contrast with the actual biological phenophases of monitored crops. In terms of its larger significance, this study demonstrates the fundamental role that remote sensing plays in global agriculture in informing conservation and management practices.
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
Rickman, Douglas L.
This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.
Perry, Cortes L.
The objective of this project is to evaluate remote hydrogen sensing methodologies utilizing metal oxide semi-conductor field effect transistors (MOS-FET) and mass spectrometric (MS) technologies and combinations thereof.
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.
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
The Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET), highlighting areas with anomalously high or low rates of water use across the land surface. ET is retrieved via energy balance using remotely sensed land-surface temperature (LST) time-change signals. LST ...
Remote sensing technology has the potential to inform and accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long...
Cheng, Peng-gen; Tong, Cheng-zhuo; Chen, Xiao-yong; Nie, Yun-ju
At present, the dynamic change monitoring of urban ecological environment has became an important guarantee measure for urban management, planning and construction. In this paper, taking Nanchang city as a case study, the remote sensing ecological index (RSEI) which is based on the natural factors is used to study the changes of the urban ecological environment. The Landsat images in the three different time periods of 1996, 2005, and 2013 in Nanchang were selected. To extract the four factors of green level, moisture, dryness and heat respectively as sub-indexs of the ecological assessment, in which the single window algorithm was used to calculate the heat. Based on the four factors, the RSEI in each year was finally calculated. The results show that the ecological environment in Nanchang deteriorated in the past 17 years, the value of the RSEI has decreased from 0.385 in 1996 to 0.267 in 2005, falling by 30.65%, but the ecological environment has improved in the later period, with the value of RSEI value rising to 0.413, increased by 54.68% compared with the results in 2005. It is indicates that the urban ecological environment of Nanchang has been significantly improved after some effective measures such as urban greening, pollution control, environmental protection were taken.
Wu, Weicheng; Courel, Marie-Francoise; Le Rhun, Jeannine
Since the construction of a harbour, Port de l'Amitie, an important importation gate for Nouakchott in 1987, the previous coast dynamic equilibrium had been destroyed and thus a significant littoral geomorphological change has occurred, which has produced a severe degradation of the littoral and urban environment. Our research is focused on this coastal environmental change monitoring and its potential evolution estimation by remote sensing techniques using multi-temporal SPOT images and Markov chain analysis. The objectives of this study are to understand coastline evolution particularities, measure geomorphological change rates, evaluate life-span of the harbour, produce useful data for the government to control the environment degradation and provide reference for the future similar coastal engineering. According to our research, the north beach of the harbour has extended by 0.92km2 (91.6ha) from 1989 to 2001 and the accretion will probably reach its maximum limit in about 13.4 +/- 0.5 years (in 2014-2015) and the harbour will arrive at the end of service. The south sandbar has been eroded by 1.34km2 (134ha) and the coastline has landward retreated at the maximum by 362m. Another 0.91km2 of land will be nibbled by seawater in the next 10 years. This erosion has caused several times inundation into the suburb and urban areas, provoking a deterioration of the urban environment.
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 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.
Gao, Zhihai; del Barrio, Gabriel; Li, Xiaosong; Wang, Wengyu; Puigdefabregas, Juan; Sanjuan, Maria E.; Bai, Lina; Wu, Junjun; Sun, Bin; Li, Changlong
The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired since 2012 could be summarized as follows:(1) Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) fraction were retrieved separately through utilizing Auto Monte Carlo Unmixing technique (AutoMCU), based on BJ-1 data and field measured spectral library.(2) The accuracy of sandy land classification was as high as 81.52% when the object-oriented method and Support Vector Machine (SVM) classifiers were used.(3) A new Monthly net primary productivity (NPP) dataset from 2002 to 2010 for the whole China were established with Envisat-MERIS fraction of absorbed photosynthetically active radiation (FPAR) data.(4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China (PEDC) was assessed preliminarily.
Gao, Zhihai; del Barrio, Gabriel; Li, Xiaosong; Wang, Bengyu; Puigdefabregas, Juan; Sanjuan, Maria E.; Bai, Lina; Wu, Junjun; Sun, Bin; Li, Changlong
The objective of Dragon 3 Project 10367 is the development of techniques research for desertification assessment and monitoring in China using remote sensing data in combination with climate and environmental-related data. The main achievements acquired since2012could be summarized as follows: (1)Photosynthetic vegetation(PV)and non-photosynthetic vegetation(NPV)fraction were retrieved separately through utilizing Auto Monte Carlo Unmixing technique (AutoMCU), based on BJ-1 data and field measured spectral library. (2) The accuracy of sandy land classification was as high as81.52%when the object-oriented method and Support Vector Machine (SVM) classifiers were used. (3) A new Monthly net primary productivity (NPP)dataset from 2002 to 2010 for the whole China were established with Envisat-MERIS fraction of absorbed photosynthetically active radiation (FPAR) data. (4) The 2dRUE proved to be a good indicator for land degradation, based on which, land degradation status in the general potential extent of desertification in China(PEDC) was assessed preliminarily.
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
Huang, He; Fan, Yida; Yang, Siquan; Wen, Qi; Pan, Donghua; Fan, Chunbo; He, Haixia
Drought is one kind of nature disasters in the world. It has characteristics of temporal-spatial inhomogeneity, wide affected areas and periodic happening. The economic loss and affected population caused by different droughts are the largest in all natural disasters. Remote sensing has the advantages of large coverage, frequent observation, repeatable observation, reliable information source and low cost. These advantages make remote sensing a vital contributor for drought disaster risk assessment and monitoring. In this paper, three drought monitoring models, such as Vegetation Condition Index (VCI), Temperature Vegetation Dryness Index (TVDI), and Water Supplying Vegetation Index (WSVI) had been selected to monitor the drought occurred from January 2012 to June 2012 in Hubei province, China. Two kinds of remote sensing data, including HJ-1A/B CCD/IRS and ZY-3, had been employed to assess the integrated risk of Hubei drought based on three drought monitoring models. The results shown that the risk of northwest regions and middle regions in Hubei province were higher than that in the other regions. The results also indicated that the extreme risk regions were located in Shiyan, Xiangyang, Suizhou and Jingmen.
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
Tourre, Y. M.; Lacaux, J.
Presence (density) of mosquitoes linked to Rift Valley Fever (RVF) epidemics in the Ferlo (Senegal) is evaluated by monitoring the environment from space. Using five SPOT-5 high-resolution images (~10m spatial resolution, on August 17th, 2006) a meridional transect of 290 x 60 km2 is analyzed for the first time. Four major ecozones are thus identified: Senegal River valley; sandy Ferlo; sandy-clayey Ferlo; and steppe/cultivated areas, from north to south, respectively. An integrated/multidisciplinary approach using remote-sensing leads to a composited Zones Potentially Occupied by Mosquitoes (or ZPOMs, with extrema). It is found that at the peak of the rainy season, the area occupied by ponds is of 12,817 ha ± 10% (i.e., ~ 0.8 % of the transect) with a mean ZPOM 17 times larger i.e.: 212,813 ha ± 10 % (or ~14 % of the transect). ZPOMs characteristics (minimum and maximum) at the ecozones levels with different hydrological mechanisms, are presented. Ponds and ZPOMs inter-annual variabilities and RVF risks, are subsequently highlighted by comparing statistics in the so-called Barkedji zone (sandy-clayey Ferlo with a hydrofossil riverbed), for the very humid year of 2003, and the near normal rainfall year of 2006. It is shown that at the end of August 2003/2006, ponds (ZPOMs) areas, were already ~22 (~5) times larger. The key roles played by isolated ponds for animals' exposure to RVF risks are thus identified. These results highlight the importance of monitoring the changing environment when linkages with public health exist. The ZPOM approach is to be adapted for other vector-borne diseases such as malaria, dengue fever, in different places of the world. Results are meant to be included into Health Information Systems (HIS) on an operational basis, in order to minimize socio-economical impacts from epidemics.
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
Ramoelo, A.; Cho, M. A.; Madonsela, S.; Mathieu, R.; van der Korchove, R.; Kaszta, Z.; Wolf, E.
Global change consisting of land use and climate change could have huge impacts on food security and the health of various ecosystems. Leaf nitrogen (N) is one of the key factors limiting agricultural production and ecosystem functioning. Leaf N can be used as an indicator of rangeland quality which could provide information for the farmers, decision makers, land planners and managers. Leaf N plays a crucial role in understanding the feeding patterns and distribution of wildlife and livestock. Assessment of this vegetation parameter using conventional methods at landscape scale level is time consuming and tedious. Remote sensing provides a synoptic view of the landscape, which engenders an opportunity to assess leaf N over wider rangeland areas from protected to communal areas. Estimation of leaf N has been successful during peak productivity or high biomass and limited studies estimated leaf N in dry season. The objective of this study is to monitor leaf N as an indicator of rangeland quality using WorldView 2 satellite images in the north-eastern part of South Africa. Series of field work to collect samples for leaf N were undertaken in the beginning of May (end of wet season) and July (dry season). Several conventional and red edge based vegetation indices were computed. Simple regression was used to develop prediction model for leaf N. Using bootstrapping, indicator of precision and accuracy were analyzed to select a best model for the combined data sets (May and July). The may model for red edge based simple ratio explained over 90% of leaf N variations. The model developed from the combined data sets with normalized difference vegetation index explained 62% of leaf N variation, and this is a model used to estimate and map leaf N for two seasons. The study demonstrated that leaf N could be monitored using high spatial resolution with the red edge band capability.
Feng, Wei; Zhu, Yan; Yao, Xia; Tian, Yong-Chao; Yao, Xin-Feng; Cao, Wei-Xing
In a two-year field experiment with wheat cultivars under different application rates of fertilizer N, the wheat leaf pigment concentrations were monitored with hyper-spectral remote sensing, and quantitative monitoring models were established. The results showed that the pigment concentrations in wheat leaves increased with increasing N application rate, and differed significantly among test cultivars. With the growth of wheat, the relative concentration of chlorophyll a + b varied more obviously than those of chlorophyll b and carotenoid (Car), and the sensitive bands of the pigments occurred mostly within visible light range, especially in red-edge district. The analyses on the relationships between eight existing vegetation indices and leaf pigment concentrations indicated that the concentrations of chlorophyll a, chlorophyll b, and chlorophyll a + b were highly correlated with red edge position, and the relationships to REP(LE) were better than to REP(IG), giving the determination coefficient R2 as 0.835, 0.841 and 0.840, and standard error SE as 0.264, 0.095 and 0.353, respectively. However, the R2 values between Car and different spectral indices decreased significantly, and the differences among the spectrum indices were very small. The tests of the monitoring models with independent datasets indicated that REP(LE) and REP(IG) were the best to predict leaf pigment concentrations. The R2 of chlorophyll a, chlorophyll a + b, and Car for REP(LE) were 0.805, 0.744 and 0.588, with the RE being 9.0%, 9.7% and 14.6%, respectively, and the R2 and RE of chlorophyll b for REP(IG) were 0.632 and 18.2%, respectively. It was suggested that the red-edge parameters of hyper-spectral reflectance had stable relationships with the pigment concentrations in wheat leaves, and especially, REP(LE) could be used to reliably estimate the concentrations of leaf chlorophyll a and chlorophyll a + b.
Miller, W. L.
Nonpoint pollution of streams with sediment as a result of runoff from alternative uses of land has become a socially unacceptable product of economic activity. This report describes a research approach to economically achieve correction of the nonpoint pollution problem. The research approach integrates the economic model with those data which may be obtainable from remotely sensed sources. The economic problem involves measurement of the direct benefits and costs associated with the changes in land management activities necessary to reduce the level of nonpoint pollution. Remotely sensed data from ERTS-1 may provide some of the information required for the economic model which indicates efficient solutions to the nonpoint pollution problem. Three classes of data (i.e., soil categories, vegetative cover, and water turbidity) have the potential to be measured by ERTS-1 systems. There is substantial research which indicates the ability of ERTS-1 to measure these classes of data under selected conditions.
Shumate, M. S.
An instrument capable of remotely monitoring trace atmospheric constituents is described. The instrument, called a laser absorption spectrometer, can be operated from an aircraft or spacecraft to measure the concentration of selected gases in three dimensions. This device will be particularly useful for rapid determination of pollutant levels in urban areas.
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.
Ling, Feng; Cai, Xiaobin; Li, Wenbo; Xiao, Fei; Li, Xiaodong; Du, Yun
River discharge is an important parameter in understanding water cycles, and consistent long-term discharge records are necessary for related research. In practice, discharge records based on in situ measurement are often limited because of technological, economic, and institutional obstacles. Satellite remote sensing provides an attractive alternative way to measure river discharge by constructing an empirical rating curve between the parameter provided by remote sensing techniques and simultaneous ground discharge data. River width is a popular parameter for constructing the empirical curve, since change in river discharge can be represented by a change in river width. In some rectangular channels, however, river width does not change significantly with river discharge, so an alternative parameter is necessary. We analyze a novel technique using river island area as an indicator of discharge. A river island often has a flat terrain, and its area decreases with higher discharge. This technique is validated by three river islands in the Yangtze River in China. All 61 remotely sensed images acquired by the HuanJing (HJ) satellites from 2009 to 2010 were correlated with corresponding in situ discharge of the nearby Zhicheng hydrological station. The performance of fitted curves for inferring river discharge is validated using 36 HJ images taken in 2011, and the influence of remotely sensed imagery and river islands is discussed. All three river islands can be used as indicators of river discharge, although their performances are much different. For the river island with the best result, the mean accuracy of the estimates is less than 10% of the observed discharge, and all relative errors are within 20%, validating the effectiveness of the proposed method.
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.
Trees, Charles C.; Bissett, Paul W.; Dierssen, Heidi; Kohler, David D. R.; Moline, Mark A.; Mueller, James L.; Pieper, Richard E.; Twardowski, Michael S.; Zaneveld, J. Ronald V.
Diver visibility analyses and predictions, and water transparency in general, are of significant military and commercial interest. This is especially true in our current state, where ports and harbors are vulnerable to terrorist attacks from a variety of platforms both on and below the water (swimmers, divers, AUVs, ships, submarines, etc.). Aircraft hyperspectral imagery has been previously used successfully to classify coastal bottom types and map bathymetry and it is time to transition this observational tool to harbor and port security. Hyperspectral imagery is ideally suited for monitoring small-scale features and processes in these optically complex waters, because of its enhanced spectral (1-3 nm) and spatial (1-3 meters) resolutions. Under an existing NOAA project (CICORE), a field experiment was carried out (November 2004) in coordination with airborne hyperspectral ocean color overflights to develop methods and models for relating hyperspectral remote sensing reflectances to water transparency and diver visibility in San Pedro and San Diego Bays. These bays were focused areas because: (1) San Pedro harbor, with its ports of Los Angeles and Long Beach, is the busiest port in the U.S. and ranks 3rd in the world and (2) San Diego Harbor is one of the largest Naval ports, serving a diverse mix of commercial, recreational and military traffic, including more than 190 cruise ships annual. Maintaining harbor and port security has added complexity for these Southern California bays, because of the close proximity to the Mexican border. We will present in situ optical data and hyperspectral aircraft ocean color imagery from these two bays and compare and contrast the differences and similarities. This preliminary data will then be used to discuss how water transparency and diver visibility predictions improve harbor and port security.
Song, Xiaoyu; Cui, Fangnin; Gu, Xiaohe; Xu, Xingang; Wang, Jihua
Winter wheat is one of the most important crops planted in Beijing suburb. In recent 20 years, winter wheat planted area decreased obviously in Beijing area owning to the urbanization process. This study focuses on the winter wheat planted area transformation monitoring of Beijing suburb from 1992 to 2009 through remote sensing technique. Multi-temporal Landsat- TM images are collected during the winter wheat growth season of 1992-2000 and 2009 and used to analyze the trend and characteristics of winter wheat field variation in Beijing suburb in recent two decades years. The PCA analysis and Tasseled Cap transform technique are adopted in this study for feature classification. The study result shows that the winter wheat planted area in 1992-2000 and 2009 in Beijing is 113671 ha - 84322 ha and 61529 ha, respectively. It indicates that winter wheat planting area in Beijing has a significantly decreasing trend and the total reduced area is 52143 ha from 1992 to 2009. Winter wheat planted area is decreased by 29349 ha from 1992 to 2000. Most of reduced wheat fields are transformed into bare land or used for urban land accounting for 42.8% and 39.7%. Others wheat fields are used for greenhouse and water bodies (fish ponds and water fields), accounting for 13.3% and 3%. The winter wheat field decreased by 22794 ha from 2000 to 2009, more than 41.93% of wheat field is turned into bare land. Reduce field for greenhouse land and water bodies (ponds or water fields) are account for21.61% and 7.79%, respectively.
Murthy, A.; Gouda, K. C.; Bhat, R.; Laxmikantha, B. P.; Prabhuraj, D. K.
The Krishna River Basin in the south India experienced a major flood during October 2009, which is the second largest Eastward draining River in Peninsular India covering vast area in the States of Maharashtra, Karnataka and Andhra Pradesh. This River drains approximately 2,58,948 km2 , which is about 8 % of the total geographical area of India. In the present study the lateral extent of river resulted by the flood is monitored and analyzed using the MODIS remote sensing satellite data. The extension of river is derived by processing the data before, during and after the flood event in the river basin. Associated meteorological parameters like rainfall, river run off, rise in water column are also discussed using multi-source satellite (TMI/TRMM, SRTM DEM etc) and observed data. The land cover and Land use analysis of the basin is also carried out for the pre flood and post flood scenarios. It is observed that the elevation tends to decrease from the western part to the eastern part of the basin. The variations of lateral extent is well captured by the GIS analysis, which indicates the extent pattern are different at east and west part of basin due to different topographical features in the river basin. Figure 1 presents the increase in the lateral extent of river due to the flood event. This information can be used by the disaster managers for pro-active disaster mitigation. Figure 1: Increase in the lateral extent of Krishna river due to the October 2009 flood.
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.
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.
Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain
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. PMID:27873914
Consoli, Simona; Cirelli, Giuseppe Luigi; Toscano, Attilio
The structure of vegetation is paramount in regulating the exchange of mass and energy across the biosphereatmosphere interface. In particular, changes in vegetation density affected the partitioning of incoming solar energy into sensible and latent heat fluxes that may result in persistent drought through reductions in agricultural productivity and in the water resources availability. Limited research with citrus orchards has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigation when crop coefficient (Kc) estimate, derived from remotely sensed multispectral vegetation indices (VIs), are incorporated into irrigation-scheduling algorithms. The purpose of this article is the application of an empirical reflectance-based model for the estimation of Kc and evapotranspiration fluxes (ET) using ground observations on climatic data and high-resolution VIs from ASTER TERRA satellite imagery. The remote sensed Kc data were used in developing the relationship with the normalized difference vegetation index (NDVI) for orange orchards during summer periods. Validation of remote sensed data on ET, Kc and vegetation features was deal through ground data observations and the resolution of the energy balance to derive latent heat flux density (λE), using measures of net radiation (Rn) and soil heat flux density (G) and estimate of sensible heat flux density (H) from high frequency temperature measurements (Surface Renewal technique). The chosen case study is that of an irrigation area covered by orange orchards located in Eastern Sicily, Italy) during the irrigation seasons 2005 and 2006.
Chen, Qiaoling; Zhang, Yuanzhi; Hallikainen, Martti
Water quality monitoring using remote sensing has been studied in Finland for many years. But there are still few discussions on water quality monitoring using remote sensing technology in support of water policy and legislation in Finland under the WFD. In this study, we present water quality monitoring using remote sensing in the Gulf of Finland, and focus on the spatial distribution of water quality information from satellite-based observations in support of water policy by a case study of nitrate concentrations in surface waters. In addition, we briefly describe instruments using a system of river basin districts (RBD), highlighting the importance of integrated water resources and river-basin management in the WFD, and discuss the role of water quality monitoring using remote sensing in the implementation of water policy in Finland under the WFD.
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.
Xiao, Zhongyong; Jiang, Hong; Song, Xiaodong; Zhang, Xiuying
Measurements from the Ozone Monitoring Instrument are used to investigate the temporal and spatial dynamics of global nitrogen dioxide (NO2). The results show that the global tropospheric column NO2 increased by 11.10% during 2005 to 2010 at a 1.76% annual growth rate. The largest tropospheric and total NO2 columns are mainly concentrated in the industrialized regions of North America, Europe, and east Asia. The large values of column NO are also observed and scattered in South America, Africa, and Indonesia due to biomass burning and savannah fires. Average tropospheric column NO increased by 32.62% at a 4.82% annual rate over eastern Asia. On the contrary, the trend decreased by 35.47% at a 7.04% annual rate over eastern America. The trend was not significant over Europe as a whole, where a decrease was observed over western and southern Europe and an increase was observed over eastern and northern Europe. Over the polluted urban areas, the ratios of tropospheric to total column NO2 are larger than 0.6 and the correlation coefficients are larger than 0.8. This can be mainly attributed to the anthropogenic NOx emissions over land, and it is noteworthy that the ratios are higher than 0.8 (correlation coefficients >0.95) over northern China.
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 22,672km2 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 spatio
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
Shah-Hosseini, Reza; Homayouni, Saeid; Safari, Abdolreza
In the event of a natural disaster, such as a flood or earthquake, using fast and efficient methods for estimating the extent of the damage is critical. Automatic change mapping and estimating are important in order to monitor environmental changes, e.g., deforestation. Traditional change detection (CD) approaches are time consuming, user dependent, and strongly influenced by noise and/or complex spectral classes in a region. Change maps obtained by these methods usually suffer from isolated changed pixels and have low accuracy. To deal with this, an automatic CD framework-which is based on the integration of change vector analysis (CVA) technique, kernel-based C-means clustering (KCMC), and kernel-based minimum distance (KBMD) classifier-is proposed. In parallel with the proposed algorithm, a support vector machine (SVM) CD method is presented and analyzed. In the first step, a differential image is generated via two approaches in high dimensional Hilbert space. Next, by using CVA and automatically determining a threshold, the pseudo-training samples of the change and no-change classes are extracted. These training samples are used for determining the initial value of KCMC parameters and training the SVM-based CD method. Then optimizing a cost function with the nature of geometrical and spectral similarity in the kernel space is employed in order to estimate the KCMC parameters and to select the precise training samples. These training samples are used to train the KBMD classifier. Last, the class label of each unknown pixel is determined using the KBMD classifier and SVM-based CD method. In order to evaluate the efficiency of the proposed algorithm for various remote sensing images and applications, two different datasets acquired by Quickbird and Landsat TM/ETM+ are used. The results show a good flexibility and effectiveness of this automatic CD method for environmental change monitoring. In addition, the comparative analysis of results from the proposed method
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
Siddiqui, M. N.; Jamil, Z.; Afsar, J.
Depletion in the forest area threatens the sustainability of agricultural production systems and en-dangers the economy of the country. Every year extensive areas of arable agricultural and forestlands are degraded and turned into wastelands over time, due to natural causes or human interventions. Depletion in forest cover, therefore, has an important impact on socio-economic development and ecological balance. High population growth rate in Pakistan is one of the main causes for rapid deterioration of the physical environment and natural resource base. In view of this, it was felt necessary to carryout landuse studies focusing on mapping the past and present conditions and the extent of forests and rangelands using satellite remote sensing (SRS) and Geographic Information System (GIS) technologies. The SRS and GIS technologies provide a possible means of monitoring and mapping the changes occurring in natural resources and the environment on a continuous basis. The riverine forests of Sindh mostly growing along the river Indus in the flood plains are spread over an area of 241,000 ha but are disappearing very rapidly. Construction of dams/barrages on the upper reaches of the river Indus for hydroelectric power and irrigation works have significantly reduced the discharge of fresh water into the lower Indus basin and as a result 100,000 acres of forests have disappeared. Furthermore, heavy floods that occurred in 1978, 1988, 1992 and 1997, altered the course of the River Indus in many places, especially in the lower reaches, this has also damaged the riverine forests of Sindh. An integrated approach involving analysis of SRS data from 1977 to 1998 and GIS technique have been used to evaluate the geographic extent and distribution of the riverine forests of Sindh and to monitor temporal changes in the forest cover between 1977 and 1990; 1990 and 1998; and 1977 and 1998. The integrated landuse forest cover maps have shown not only the temporal changes that occur in
The author presents selected case studies to demonstrate theories and practices of remote sensing and its value to the study of the terrestrial environment. Begins with an overview of sensor types and electromagnetic remote sensing, continuing with an examination of photographic and non-photographic systems in the study of the radiation budget, temperature structure and weather conditions of the atmosphere. Includes thorough coverage of the lithosphere, biosphere and hydrosphere, as well as the cartographic problems involved in land use/land cover and topographic mapping. Concludes with a discussion of the impact of electromagnetic computers in the development of geographic information systems.
Lenoble, Jacqueline (Editor); Remer, Lorraine (Editor); Tanre, Didier (Editor)
This book gives a much needed explanation of the basic physical principles of radia5tive transfer and remote sensing, and presents all the instruments and retrieval algorithms in a homogenous manner. For the first time, an easy path from theory to practical algorithms is available in one easily accessible volume, making the connection between theoretical radiative transfer and individual practical solutions to retrieve aerosol information from remote sensing. In addition, the specifics and intercomparison of all current and historical methods are explained and clarified.
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.
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. PMID:27869668
Lillesand, T. M.; Kiefer, R. W. (Principal Investigator)
A textbook prepared primarily for use in introductory courses in remote sensing is presented. Topics covered include concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; airphoto interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.
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.
Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.
Roughgarden, J.; Running, S. W.; Matson, P. A.
The application of remote sensing to ecological investigations is briefly discussed. Emphasis is given to the recruitment problem in marine population dynamics, the regional analysis of terrestrial ecosystems, and the monitoring of ecological changes. Impediments to the use of remote sensing data in ecology are addressed.
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.
Graff, W. J. (Compiler)
Remote sensing and aerial photographic interpretation are discussed along with the specific imagery techniques used for this research. The method used to select sites, the results of data analyses for the Houston metropolitan area, and the location of dredging sites along the Houston Ship Channel are presented. The work proposed for the second year of the project is described.
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...
This volume contains abstracts that have been accepted for presentation at the symposium on Solar System Remote Sensing, September 20-21, 2002, in Pittsburgh, Pennsylvania. Administration and publications support for this meeting were provided by the staff of the Publications and Program Services Departments at the Lunar and Planetary Institute.
Zhizhin, M.; Poyda, A.; Velikhov, V.; Novikov, A.; Polyakov, A.
All Most of the remote sensing applications rely on the daytime visible and infrared images of the Earth surface. Increase in the number of satellites, their spatial resolution as well as the number of the simultaneously observed spectral bands ensure a steady growth of the data volumes and computational complexity in the remote sensing sciences. Recent advance in the night time remote sensing is related to the enhanced sensitivity of the on-board instruments and to the unique opportunity to observe “pure” emitters in visible infrared spectra without contamination from solar heat and reflected light. A candidate set of the night-time emitters observable from the low-orbiting and geostationary satellites include steady state and temporal changes in the city and traffic electric lights, fishing boats, high-temperature industrial objects such as steel mills, oil cracking refineries and power plants, forest and agricultural fires, gas flares, volcanic eruptions and similar catastrophic events. Current satellite instruments can detect at night 10 times more of such objects compared to daytime. We will present a new data-intensive workflow of the night time remote sensing algorithms for map-reduce processing of visible and infrared images from the multispectral radiometers flown by the modern NOAA/NASA Suomi NPP and the USGS Landsat 8 satellites. Similar radiometers are installed on the new generation of the US geostationary GOES-R satellite to be launched in 2016. The new set of algorithms allows us to detect with confidence and track the abrupt changes and long-term trends in the energy of city lights, number of fishing boats, as well as the size, geometry, temperature of gas flares and to estimate monthly and early flared gas volumes by site or by country. For real-time analysis of the night time multispectral satellite images with global coverage we need gigabit network, petabyte data storage and parallel compute cluster with more than 20 nodes. To meet the
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.
Torres, R. C.; Torres, R. C.; Mouginis-Mark, P.; Kallianpur, K.; Garbeil, H.; Self, S.; Quiambao, R.
Since the 1991 climatic eruption of Pinatubo, various hazards have affected the surrounding areas. The most significant of these involve the re-deposition of pyroclastic flow and fall deposits as lahars, deposit-derived pyroclastic flows, and phreatic explosion ash fall. Many of these processes occurred in areas that are inaccessible for ground observation and monitoring. A case in point is the potential hazard that currently threatens the low-lying areas along the Maraunot-Bucao river system should a significant lake breakout occur from the 1991 crater. Sequential remote sensing (RS) data sets, which include multi-temporal ERS, SIR-C, SPOT, TOPSAR/AIRSAR, Landsat 7 and Ikonos scenes, provide an unparalleled perspective to reconstruct the sequential development of the Pinatubo landscape and map the areas of the ignimbrite sheets that are being eroded as well as the encroachment of lahar fans. Multiple acquisition using different imaging techniques over the same area yields different surface albedos that can be compared with the actual ground observation. We have utilized the ENVI software package to apply principal component analysis, image subtraction, band ratio, and density slice on these data. These analytical techniques provide measurable parameters to track down the changes in the post-eruption landscape, calculate rates of erosion and deposition, and allow hazard vulnerability prediction along the timeline establish by the series of RS data sets. The RS-derived maps agree reasonably well with the field derived maps and provide important large-area coverage and show details that unobtainable from conventional ground-based mapping. Image subtraction between scenes yields image-difference maps that show cumulative aggradation within the lahar fans of the Pasig-Potrero River and erosion and development of the drainage systems in the upstream regions. Co-registered multi-temporal scenes can also allow changes in the settlement patterns of local population to be
Price, Kevin P.; Nellis, M. Duane
The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of
Middleton, E. M.; Marcell, R. F.
References relevant to remote sensing of water quality were compiled, organized, and cross-referenced. The following general categories were included: (1) optical properties and measurement of water characteristics; (2) interpretation of water characteristics by remote sensing, including color, transparency, suspended or dissolved inorganic matter, biological materials, and temperature; (3) application of remote sensing for water quality monitoring; (4) application of remote sensing according to water body type; and (5) manipulation, processing and interpretation of remote sensing digital water data.
A wide range of remote sensing methods have been used to study the climates of Venus, Earth, and Mars. In some cases, techniques pioneered for Earth were subsequently used to study the climates of Venus and Mars. For example, the thermal infrared limb sounders used on NIMBUS 7 (LIMS, SAMS) and UARS (ISAMS, CLAES) were the precursors of the Mars Reconnaissance Orbiter Mars Climate Sounder (MRO MCS). In other cases, methods first used to study planetary environments, were then used to study the Earth's climate. The Pioneer Venus Orbiter Cloud Photopolarimeter (PV OCPP) was a precursor to the POLDER instruments on ADEOS and PARASOL, and the Aerosol Polarimetry Sensor (APS) on the Glory spacecraft. Similarly, hyperspectral imagers that have long been used for studying planetary environments (NIMS, VIMS, OMEGA, VIRTIS) have only recently been used for studying the Earth (EO1 Hyperion). High spectral resolution solar remote sensing methods like those being developed for measuring CO2 and other greenhouse gases, such as those on the NASA Orbiting Carbon Observatory (OCO) and the Japanese Greenhouse Gases Observing Satellite (GOSAT) provide new tools for measuring surface pressures, trace gas abundances, and the dust and ice distributions in the Martian atmosphere. Active radar and lidar sounders, like those deployed on the CloudSat and CALIPSO spacecraft, provide new methods for studying the vertical structures of the H2SO4 clouds of Venus as well as dust and ice clouds on Mars. These and other opportunities will be reviewed here.
Hashim, M.; Pour, A. B.; Chong, K. W.
This study was undertaken in order to test the use of remote sensing technology to assess forest degradation in the Peninsular Malaysia. In order to analyse the effect of spatial resolution on forest degradation assessment, course and moderate spatial resolution remote sensing data were examined in this study. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used as coarse spatial resolution data, while Landsat Enhanced Thematic Mapper+ (ETM+) imagery was used as moderate spatial resolution to compare the accuracy. Geometric and radiometric correction and re-sampling were performed in preprocessing section to enhance the analysis and results. Canopy fractional cover was used as an approach to assess the forest degradation in this study. Then, an optimum vegetation index was selected to apply on canopy fractional cover to enhance the detection of forest canopy damage. At the same time, accuracy assessment for the approach was referred to the location of Neobalanocarpus Heimii and correlate with global evapotranspiration rate. The forest degradation analysis was also applied and compared for all of the states in the Peninsular Malaysia. In conclusion, Landsat ETM+ imagery obtained higher accuracy compare to MODIS using canopy fractional cover approach for forest degradation assessment, and can be more broadly applicable to use for forest degradation investigation.
Li, Xiao-Ming; Lehner, Susanne; Rosenthal, Wolfgang
Safety of shipping is a growing concern. The causes of shipping casualties are various, while over 30% of the casualties are due to bad weather. Heavy sea state and severe weather conditions have caused the loss of more than 200 large cargo vessels within 20 years between 1981 and 2000. Remote sensing techniques, particularly the active microwave radar provides global sea surface observations for detecting heavy sea state and bad weather independent of clouds and sunlight and therefore it can contribute to shipping safety. We have collected several cases of ship casualties occurred in the Chinese and European coasts as well as in the open sea, mainly on the global shipping routes. Sea state parameters and wind situation under these causalities are derived from SAR wide swath, image mode and wave mode data, as well as from other radar measurements, e.g., radar altimeter and scatterometer. In the present paper, based on a case analysis of ship accidents caused by adverse weather situation, we demonstrated the potential of using spaceborne remote sensing supporting for shipping security.
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
What would you do if you were faced with organizing 30 years of remote sensing projects that had been haphazardly stored at two separate locations for years then combined? The EPA Remote Sensing Archive, currently located in Las Vegas, Nevada. contains the remote sensing data and...
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
Evans, Richard D.; Murray, Kathy L.; Field, Stuart N.; Moore, James A. Y.; Shedrawi, George; Huntley, Barton G.; Fearns, Peter; Broomhall, Mark; McKinna, Lachlan I. W.; Marrable, Daniel
Technological advancements in remote sensing and GIS have improved natural resource managers’ abilities to monitor large-scale disturbances. In a time where many processes are heading towards automation, this study has regressed to simple techniques to bridge a gap found in the advancement of technology. The near-daily monitoring of dredge plume extent is common practice using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and associated algorithms to predict the total suspended solids (TSS) concentration in the surface waters originating from floods and dredge plumes. Unfortunately, these methods cannot determine the difference between dredge plume and benthic features in shallow, clear water. This case study at Barrow Island, Western Australia, uses hand digitising to demonstrate the ability of human interpretation to determine this difference with a level of confidence and compares the method to contemporary TSS methods. Hand digitising was quick, cheap and required very little training of staff to complete. Results of ANOSIM R statistics show remote sensing derived TSS provided similar spatial results if they were thresholded to at least 3 mg L−1. However, remote sensing derived TSS consistently provided false-positive readings of shallow benthic features as Plume with a threshold up to TSS of 6 mg L−1, and began providing false-negatives (excluding actual plume) at a threshold as low as 4 mg L−1. Semi-automated processes that estimate plume concentration and distinguish between plumes and shallow benthic features without the arbitrary nature of human interpretation would be preferred as a plume monitoring method. However, at this stage, the hand digitising method is very useful and is more accurate at determining plume boundaries over shallow benthic features and is accessible to all levels of management with basic training. PMID:23240055
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.
Liu, Ming; Yang, Siquan; Huang, He; He, Haixia; Li, Suju; Cui, Yan
Remote sensing is one of important methods on the agricultural drought monitoring for its long-term and wide-area observations. The detection of soil moisture and vegetation growth condition are two widely used remote sensing methods on that. However, because of the time lag in the impact of water deficit on the crop growth, it is difficulty to indicate the severity of drought by once monitoring. It also cannot distinguish other negative impact on crop growth such as low temperature or solar radiation. In this paper, the joint use of soil moisture and vegetation growth condition detections was applied on the drought management during the summer of 2013 in Liaoning province, China, in which 84 counties were affected by agricultural drought. MODIS vegetation indices and land surface temperature (LST) were used to extract the drought index. Vegetation Condition Index (VCI), which only contain the change in vegetation index, and Vegetation Supply Water Index (VSWI), which combined the information of vegetation index and land surface temperature, were selected to compare the monitoring ability on drought during the drought period in Liaoning, China in 2014. It was found that VCI could be a good method on the loss assessment. VSWI has the information on the change in LST, which can indicate the spatial pattern of drought and can also be used as the early warning method in the study.
Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Pedreros, D.; Husak, G. J.; Bohms, S.
monitoring and modeling. We also present two new monitoring tools, the Early Warning eXplorer (EWX) and the Decision Support Interface (DSI). The EWX is a data analysis tool which provides the ability to rapidly visualize multiple remote sensing datasets and compare standardized anomaly maps and time series. The DSI uses remote sensing data in an automated fashion to map areas of drought concern and ranks their severity at both crop zone and administrative levels. New and improved data products and more targeted analysis tools are a necessity as food security monitoring requirements expand and resources become limited.
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
Schmugge, T. J.; Gurney, R.
There are three things required for evapotranspiration to occur: (1) energy (580 cal/gm) for the change of phase of the water; (2) a source of the water, i.e., adequate soil moisture in the surface layer or in the root zone of the plant; and (3) a sink for the water, i.e., a moisture deficit in the air above the ground. Remote sensing can contribute information to the first two of these conditions by providing estimates of solar insolation, surface albedo, surface temperature, vegetation cover, and soil moisture content. In addition there have been attempts to estimate precipitation and shelter air temperature from remotely sensed data. The problem remains to develop methods for effectively using these sources of information to make large area estimates of evapotranspiration.
One of the primary resources supporting homeland security is the Remote Sensing Laboratory, or RSL. The Laboratory creates advanced technologies for emergency response operations, radiological incident response, and other remote sensing activities. RSL emergency response teams are on call 24-hours a day, and maintain the capability to deploy domestically and internationally in response to threats involving the loss, theft, or release of nuclear or radioactive material. Such incidents might include Nuclear Power Plant accidents, terrorist incidents involving nuclear or radiological materials, NASA launches, and transportation accidents involving nuclear materials. Working with the US Department of Homeland Security, RSL personnel equip, maintain, and conduct training on the mobile detection deployment unit, to provide nuclear radiological security at major national events such as the super bowl, the Indianapolis 500, New Year's Eve celebrations, presidential inaugurations, international meetings and conferences, just about any event where large numbers of people will gather.
One of the primary resources supporting homeland security is the Remote Sensing Laboratory, or RSL. The Laboratory creates advanced technologies for emergency response operations, radiological incident response, and other remote sensing activities. RSL emergency response teams are on call 24-hours a day, and maintain the capability to deploy domestically and internationally in response to threats involving the loss, theft, or release of nuclear or radioactive material. Such incidents might include Nuclear Power Plant accidents, terrorist incidents involving nuclear or radiological materials, NASA launches, and transportation accidents involving nuclear materials. Working with the US Department of Homeland Security, RSL personnel equip, maintain, and conduct training on the mobile detection deployment unit, to provide nuclear radiological security at major national events such as the super bowl, the Indianapolis 500, New Year's Eve celebrations, presidential inaugurations, international meetings and conferences, just about any event where large numbers of people will gather.
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.
Campbell, J. W.; Esaias, W. E.; Hypes, W. D.
The Chesapeake Bay plume study called Superflux is described. The study was initiated to incorporate the disciplines of both resources management and remote sensing in accomplishing the following objectives: (1) process oriented research to understand the impact of estuarine outflows on continental shelf ecosystems; (2) monitoring and assessment to delineate the role of remote sensing in future monitoring and assessment programs; and (3) remote sensing research: to advance the state of the art in remote sensing systems as applied to sensing of the marine environment, thereby hastening the day when remote sensing can be used operationally for monitoring and assessment and for process oriented research.
conducted studies of the sediments, seagrass and corals . The objective is to correlate the hyperspectral imagery with the detailed in-situ measurements...seagrass and coral reefs (Mazel, 1998). In addition to the basic science there is a directed effort in remote sensing for seafloor imaging and...area includes different bottom types – coral , sand, seagrass – sometimes within the same local area, at a variety of depths. Most of the region is quite
Schultz, J.; Czuchlewski, S.; Karl, R.
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.
This report discusses work done to investigate the feasibility of using non-contact optical absorption to remotely sense the surface moisture content of salt cake materials. Optical measurements were made in a dimensionally scaled setup to investigate this technique for in-situ waste tank applications. Moisture measurements were obtained from BY-104 simulant samples with 0 wt%, 10 wt%, and 20 wt% moisture content using the back-scattered light from a pulsed infrared optical parametric converter (OPC) laser source operating from 1.51 to 2.12 micron. An InGaAs detector, with 0.038 steradian solid angle (hemisphere = 6.28 steradians) collection angle was used to detect the back-scattered light. This work indicated that there was sufficient back-scatter from the BY-104 material to provide an indication of the surface moisture content.
Ni, S.; Zhang, J.; Ma, Y.; Ren, G.
Based on the extraction of coastline information by selecting 5 remotely sensed images of HJ-1B CCD and Landsat-7 ETM+ in the year of 2000, 2005 and 2010, change of coastline of Bohai bay in the first decade of 21st Century is analyzed. Results reveal that: (1) The whole coastline of Bohai Bay kept lengthening and moving seaward; (2) Among the littoral cities of Bohai Bay, the lengths of coastlines between Tangshan and Tianjin increased continuously; (3) Harbor coastline was the only one that continues to lengthen among 6 types of coastline; (4) The coastline types transformed mutually mainly in Binhai Developing Park of Tianjin, Caofeidian Developing Park of Tangshan, Tao-er River estuary and Yellow River estuary in Yellow River Delta. Construction and extension of saline, cultivated fields and harbors were the main driving factors causing the change of Bohai Bay coastline.
Khan, Sadiq Ibrahim
Study of hydroclimatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data combined with the recently available satellite remote sensing data, the hydroclimatology of Nzoia basin, one of the contributing sub-catchments of Lake Victoria in the East African highlands is analyzed. The basin, with a semi-arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the primary cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990s have had high peak discharges despite having relatively less annual rain. The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE) of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6) is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to early June.The spatially distributed model inputs, states, and outputs, were found to be useful for
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).
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.
Kong, J. A.
Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.
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.
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.
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.
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.
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.
Archer, Reginald S.
This research focuses on measuring and monitoring long term recovery progress from the impacts of Hurricane Katrina on New Orleans, LA. Remote sensing has frequently been used for emergency response and damage assessment after natural disasters. However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored. With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits. In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied. This dissertation addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators. Maximum likelihood classification and post-classification change detection were applied to multi-temporal high resolution aerial images to quantitatively measure the progress of recovery. Images were classified to automatically identify disaster recovery indicators and exploit the indicators that are visible within each image. The spectral analysis demonstrated that employing maximum likelihood classification to high resolution true color aerial images performed adequately and provided a good indication of spectral pattern recognition, despite the limited spectral information. Applying the change detection to the classified images was effective for determining the temporal trajectory of indicators categorized as blue tarps, FEMA trailers, houses, vegetation, bare earth and pavement. The results of the post classification change detection revealed a dominant change trajectory from bluetarp to house, as damaged houses became permanently repaired. Specifically, the level of activity of blue tarps, housing, vegetation, FEMA trailers (temporary housing) pavement and bare earth were derived from aerial image processing to
Shao, Honglan; Xie, Feng; Liu, Chengyu; Liu, Zhihui; Zhang, Changxing; Yang, Gui; Wang, Jianyu
The cooling water discharged from the coastal plants flow into the sea continuously, whose temperature is higher than original sea surface temperature (SST). The fact will have non-negligible influence on the marine environment in and around where the plants site. Hence, it's significant to monitor the temporal and spatial variation of the warm-water discharge for the assessment of the effect of the plant on its surrounding marine environment. The paper describes an approach for the dynamic monitoring of the warm-water discharge of coastal plants based on the airborne high-resolution thermal infrared remote sensing technology. Firstly, the geometric correction was carried out for the thermal infrared remote sensing images acquired on the aircraft. Secondly, the atmospheric correction method was used to retrieve the sea surface temperature of the images. Thirdly, the temperature-rising districts caused by the warm-water discharge were extracted. Lastly, the temporal and spatial variations of the warm-water discharge were analyzed through the geographic information system (GIS) technology. The approach was applied to Qinshan nuclear power plant (NPP), in Zhejiang Province, China. In considering with the tide states, the diffusion, distribution and temperature-rising values of the warm-water discharged from the plant were calculated and analyzed, which are useful to the marine environment assessment.
Yao, Yuan; Ding, Jian-Li; Zhang, Fang; Wang, Gang; Jiang, Hong-Nan
Soil salinization is one of the most important eco-environment problems in arid area, which can not only induce land degradation, inhibit vegetation growth, but also impede regional agricultural production. To accurately and quickly obtain the information of regional saline soils by using remote sensing data is critical to monitor soil salinization and prevent its further development. Taking the Weigan-Kuqa River Delta Oasis in the northern Tarim River Basin of Xinjiang as test object, and based on the remote sensing data from Landsat-TM images of April 15, 2011 and September 22, 2011, in combining with the measured data from field survey, this paper extracted the characteristic variables modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), and the third principal component from K-L transformation (K-L-3). The decision tree method was adopted to establish the extraction models of soil salinization in the two key seasons (dry and wet seasons) of the study area, and the classification maps of soil salinization in the two seasons were drawn. The results showed that the decision tree method had a higher discrimination precision, being 87.2% in dry season and 85.3% in wet season, which was able to be used for effectively monitoring the dynamics of soil salinization and its spatial distribution, and to provide scientific basis for the comprehensive management of saline soils in arid area and the rational utilization of oasis land resources.
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
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.
This paper reports the preliminary testing of an infrared (IR) remote sensor (GASCOFIL) for the detection of carbon monoxide (CO) concentrations near the intersection of San Mateo Drive and Menaul Drive in Albuquerque, New Mexico on May 11, 1993. The goal of this test was to demonstrate the effectiveness of GASCOFIL as an in-situ monitor for studying the time dependent distribution of CO at intersections. In order to measure the concentration of CO, the sensor viewed a crossroad path seven feet above Menaul Drive three hundred and fifty feet from the center of San Mateo Drive. The sensor was positioned ten feet from a gas and aerosol-monitoring station equipped with an EPA approved point CO monitor. GASCOFIL produced real time data that showed variations in CO levels that correlated with traffic light cycles. Variations in the CO concentration due to individual vehicles were also recorded. A two hour average of the GASCOFIL CO concentration data taken through rush hour was six percent lower than CO data taken from an EPA point sensor adjacent to the intersection. The small percentage variance between the two averages might be due to the separation and size difference of the sample volumes. GASCOFIL measured variations and peaks in the CO concentration not seen by the EPA sensor because it had a faster time response and its sample volume was closer to the vehicular sources.
Carter, David J.
Reviews the content of 19 films on remote sensing published between 1973 and 1980. Concludes that they are overly simplistic, notably outdated, and generally too optimistic about the potential of remote sensing from space for resource exploration and environmental problem-solving. Provides names and addresses of more current 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.
Hamada, Yuki; Grippo, Mark A.; Smith, Karen P.
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.
Suggests using remote sensing technology to help students make sense of the natural world. Explains that satellite information allows observation of environmental changes over time. Identifies possible student projects based on remotely sensed data. Recommends obtaining the assistance of experts and seeking funding through effective project…
Satellite remote sensing, which is the monitoring, evaluation and prediction of the resources and features of the Earth's surface and its atmosphere from satellites, is an exciting, fast-growing technique used by environmental scientists to improve their knowledge of our planet. The non-military and non-communications satellites launched by the US, USSR, and the European Community produce digital images of the Earth's surface and its atmosphere. These images are used to search for undiscovered mineral resources, to conduct population, land use and resource censuses, to control pests and pollution, to illustrate weather movements on television and much more. This introductory book examines the physical basis of remote sensing-the sensors and satellites used to collect data, and the methods used to process these data as well as the application of satellite remote sensing in the study of vegetation, land use, geology, soils, the atmosphere and the hydrosphere. The last chapter looks at the future: space stations, international coordination, etc.
Through the Visiting Investigator Program (VIP) at Stennis Space Center, Community Coffee was able to use satellites to forecast coffee crops in Guatemala. Using satellite imagery, the company can produce detailed maps that separate coffee cropland from wild vegetation and show information on the health of specific crops. The data can control coffee prices and eventually may be used to optimize application of fertilizers, pesticides and irrigation. This would result in maximal crop yields, minimal pollution and lower production costs. VIP is a mechanism involving NASA funding designed to accelerate the growth of commercial remote sensing by promoting general awareness and basic training in the technology.
Whitmore, R. A., Jr. (Principal Investigator)
A syllabus and training materials prepared and used in a series of one-day workshops to introduce modern remote sensing technology to selected groups of professional personnel in Vermont are described. Success in using computer compatible tapes, LANDSAT imagery and aerial photographs is reported for the following applications: (1) mapping defoliation of hardwood forests by tent caterpillar and gypsy moth; (2) differentiating conifer species; (3) mapping ground cover of major lake and pond watersheds; (4) inventorying and locating artificially regenerated conifer forest stands; (5) mapping water quality; (6) ascertaining the boat population to quantify recreational activity on lakes and waterways; and (7) identifying potential aquaculture sites.
Malingreau, J. P.
The role played by remote sensors on-board the Landsat and NOAA-7 satellites in monitoring and management of three catastrophic events that took place in 1982 and 1983 in Indonesia (two major volcanic eruptions and a large-scale forest fire) is assessed. The modes of operation of the satellite platforms, the types of data derived, and data availability to the users are described, and the sources of failures and delays (such as the presence of clouds, technical and computer errors, red-tape, etc.) are examined. The major drawbacks of the Landsat-supplied information for monitoring short-lived and fast-changing events were the insufficient frequency of data acquisition, delayed delivery of data, and extended times needed for data distribution and processing. Indonesia's NOAA-7 and GMS sensors, although of low spatial resolution, offered higher frequency of data collection, and profited from the existence of a local receiving station. The present value of the space-based imagery is seen mainly in the baseline assessment of the disaster-prone areas, which can assist in preparing these areas for the impending catastrophic events.
Rochdi, Nadia; Eddy, Peter; Staenz, Karl; Zhang, Jinkai; Lutz, Christian
This paper investigates the abundance mapping of rangeland plant communities using hyperspectral remote sensing data. Spectral Mixture Analysis (SMA) was used to estimate the cover fraction of five rangeland components: green grass, yellow grass, litter, shrubs and soil. Two types of endmembers were assessed using canopy reflectance modeling and tested over real data. The first type is the leaf endmember based on the laboratory reflectance measurements of different samples of leaves. The second is the canopy endmember based on reflectance simulation using the canopy radiative transfer model SAIL. These two endmember types were first assessed in SMA using a number of homogenous canopy simulations with different Leaf Area Index (LAI). Subsequently, the leaf and the canopy endmembers were evaluated using ground spectra, and cover fractions were compared to actual data. Finally, both endmember types were applied in SMA to CHRIS/PROBA data to estimate the rangeland component cover fractions. Performances of leaf and canopy endmembers were evaluated based on the field knowledge of the area of interest. Results showed overall that the cover fraction estimates using the canopy endmembers tend to better agree with actual data.
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.
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.
Benedek, C; Descombes, X; Zerubia, J
In this paper, we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: 1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low-level change information between the time layers and object-level building description to recognize and separate changed and unaltered buildings. 2) To answer the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature-based modules. 3) To simultaneously ensure the convergence, optimality, and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel nonuniform stochastic object birth process which generates relevant objects with higher probability based on low-level image features.
Stute, Robert A. (Inventor); Galloway, F. Houston (Inventor); Medelius, Pedro J. (Inventor); Swindle, Robert W. (Inventor); Bierman, Tracy A. (Inventor)
A remote monitor alarm system monitors discrete alarm and analog power supply voltage conditions at remotely located communications terminal equipment. A central monitoring unit (CMU) is connected via serial data links to each of a plurality of remote terminal units (RTUS) that monitor the alarm and power supply conditions of the remote terminal equipment. Each RTU can monitor and store condition information of both discrete alarm points and analog power supply voltage points in its associated communications terminal equipment. The stored alarm information is periodically transmitted to the CMU in response to sequential polling of the RTUS. The number of monitored alarm inputs and permissible voltage ranges for the analog inputs can be remotely configured at the CMU and downloaded into programmable memory at each RTU. The CMU includes a video display, a hard disk memory, a line printer and an audio alarm for communicating and storing the alarm information received from each RTU.
Vaughan, A.; Cracknell, A.P.
This book, based on lectures from the Dundee Summer Schools in Remote Sensing in 1992, focuses on aspects of remote sensing related to climatic change. The organization of the book focuses on particular parts of the climate system and then discusses the different satellite systems relevant to their measurement. The following subject areas are included in the book: background information about the climate system and remote sensing; atmospheric applications in both lower and upper atmosphere; land surface including snow and ice, altimetry in Antarctica, land surface energy budget and albedo; marine science; ecological monitoring in St. Petersburg, Russia.
The physical principles describing the propagation of EM waves in the atmosphere and their interactions with matter are discussed as they apply to remote sensing, in an introductory text intended for graduate science students, environmental-science researchers, and remote-sensing practitioners. The emphasis is on basic effects rather than an specific remote-sensing techniques or observational results. Chapters are devoted to basic relations, the spectral lines of atmospheric gases, the spectral properties of condensed matter, and radiative transfer.
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.
The papers presented at the symposium focus on remote sensing, particularly on global monitoring of the earth with emphasis on the solution of environmental problems. Topics discussed include remote sensing of clouds and earth troposphere, sea ice remote sensing, optical remote sensing, land monitoring and thermal sensing, atmospheric sounding and monitoring, atmospheric correction, and satellite imaging data. Other subject areas are ecosystems and vegetation monitoring; ocean winds and surface scattering; ocean waves, currents and bathymetry; satellite oceanography; SAR for remote sensing; neural nets application to remote sensing; geographical information systems; and electromagnetic wave propagation. Also discussed environmental monitoring using ERS-1; Topex/Poseidon results; spaceborne instruments; image processing and classification algorithms; and future space missions.
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
Silvertooth, Maggie Lin
Scope and Method of Study. ASTER satellite data was collected and analyzed in order to quantify changes in temperature, vesicularity, and morphology of the dome and crater that support evidence of constructive and destructive phases of lava dome growth and destruction cycles. These cycles are characterized by sporadic growth of a lava dome that is subsequently destroyed by a Vulcanian or Pelean style eruption. Activity reports were compared with ASTER images and new deposits were mapped along the flanks of the volcano. There is no way to distinguish between pyroclastic material, rockfall deposits, lahar deposits or lava flows therefore all new flows were mapped. Findings and Conclusions. During a constructive phase, magma that is low in volatiles rises and forms a new dome. The low amount of volatiles leads to a decrease in vesicularity. Therefore during a destructive phase vesicularity is increased. Examining changes in temperature on the dome, it appears that temperatures are at a maximum before an eruptive event, such as incandescent material being extruded at the edge of the dome. Immediately after the lava dome is removed by an explosive event, a decrease in temperature is observed. Once activity resumes, increase in temperature is seen. Morphological changes on the dome can be due to explosive events, gravitational collapse, and factors affecting the endogenous and exogenous growth of the dome. Satellite data provides a synoptic view allowing for observation of new activity to be observed earlier than ground based data may allow. In the case of the Volcan de Colima, satellite remote sensing provided insight to the constructive and destructive phases of the lava dome and current activity.
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
Chong, G.; Steltzer, H.; Shory, R.; Petach, A.; Wallenstein, M. D.
Climate change models for the north¬ern Rocky Mountains predict changes in temperature and water availability that in turn may alter vegetation. Changes to vegetation may include timing of plant life-history events, or phenology, such as green-up, flower¬ing and senescence, and shifts in species composition. Moreover, climate changes may favor some species, such as non¬native, annual grasses over native species. Changes in vegetation could make forage for ungulates, sage-grouse, and livestock available earlier in the growing season, but could also result in earlier senescence (die-off or dormancy) and reduced overall production. The normalized difference vegetation index (NDVI) is regularly used to quantify greenness over large areas using remotely sensed reflectance data. The timing and scale of data collection, however, may be insufficient to capture fine-scale differences in phenology that are important indicators of habitat quality. We used data from near-surface light sensors to construct NDVI curves in native sagebrush vegetation with and without herbicide application for reducing non-native cheatgrass. We fit piecewise linear models to the data to compare characteristics of near-surface NDVI curves such as rate of green-up and duration of maximum greenness. Treated, inter-space areas had a later onset of peak season, but longer duration of greenness (greater productivity) than untreated inter-space. Sagebrush shrubs maintained relatively high greenness throughout the snow-free season. We compared our near-surface NDVI curves to curves constructed using remotely sensed data both locally (9 cell neighborhood) and regionally (southwest Wyoming) to identify the lag between actual green-up and green-up detected remotely and differences in the shapes of the NDVI curves. Understanding phenology and productivity at fine scales can help guide resource management decisions related to habitat quality, and monitoring changes in phenology and productivity over the
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
Nieland, Simon; Kleinschmit, Birgit; Förster, Michael
Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.
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.
Young, Steven D.; Harrah, Steven D.; deHaag, Maarten Uijt
Terrain Awareness and Warning Systems (TAWS) and Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data (e.g. terrain, obstacles, and/or features). As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. This lack of a quantifiable integrity level is one of the constraints that has limited certification and operational approval of TAWS/SVS to "advisory-only" systems for civil aviation. Previous work demonstrated the feasibility of using a real-time monitor to bound database integrity by using downward-looking remote sensing technology (i.e. radar altimeters). This paper describes an extension of the integrity monitor concept to include a forward-looking sensor to cover additional classes of terrain database faults and to reduce the exposure time associated with integrity threats. An operational concept is presented that combines established feature extraction techniques with a statistical assessment of similarity measures between the sensed and stored features using principles from classical detection theory. Finally, an implementation is presented that uses existing commercial-off-the-shelf weather radar sensor technology.
Lin, Yun-Bin; Lin, Yu-Pin; Deng, Dong-Po; Chen, Kuan-Wei
In Taiwan, earthquakes have long been recognized as a major cause oflandslides that are wide spread by floods brought by typhoons followed. Distinguishingbetween landslide spatial patterns in different disturbance regimes is fundamental fordisaster monitoring, management, and land-cover restoration. To circumscribe landslides,this study adopts the normalized difference vegetation index (NDVI), which can bedetermined by simply applying mathematical operations of near-infrared and visible-redspectral data immediately after remotely sensed data is acquired. In real-time disastermonitoring, the NDVI is more effective than using land-cover classifications generatedfrom remotely sensed data as land-cover classification tasks are extremely time consuming.Directional two-dimensional (2D) wavelet analysis has an advantage over traditionalspectrum analysis in that it determines localized variations along a specific direction whenidentifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series ofsolutions developed based on Open Geospatial Consortium specifications that can beapplied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2Dwavelet analysis of real-time NDVI images to effectively identify landslide patterns andshare resulting patterns via open geospatial techniques. As a case study, this study analyzedNDVI images derived from SPOT HRV images before and after the ChiChi earthquake(7.3 on the Richter scale) that hit the Chenyulan basin in Taiwan, as well as images aftertwo large typhoons (Xangsane and Toraji) to delineate the spatial patterns of landslidescaused by major disturbances. Disturbed spatial patterns of landslides that followed theseevents were successfully delineated using 2D wavelet analysis, and results of patternrecognitions of landslides were
Le, Xinghua; Fan, Zhewen; Fang, Yu; Yu, Yuping; Zhang, Yun
In order to monitor the wetland of the Poyang Lake national nature reserve zone, we selected three different seasons TM image data which were achieved individually in April 23th in 1988, Nov 2nd in 1994, and Jan 1st in 2000. Based on the band 5, band 4 and band 3of TM image, we divided the land coverage of Poyang Lake national nature reserve zone into three classes--water field, meadow field and the other land use by rule of maximum likelihood. Using the outcome data to make the statistical analysis, combining with the GIS overlay function operation, the land coverage changes of the Poyang Lake national nature reserve zone can be achieved. Clipped by the Poyang Lake national nature reserve zone boundary, the land coverage changes of Poyang Lake national nature reserve zone in three different years can be attained. Compared with the different wetland coverage data in year of 1988, 1994, 2000, the Poyang Lake national nature reserve zone eco-environment can be inferred from it. After analyzing the land coverage changes data, we draw the conclusion that the effort of Poyang Lake national nature reserve administration bureaucracy has worked well in certain sense.
McGill, Matthew J.; Starr, David OC. (Technical Monitor)
The laser radar, or lidar (for light detection and ranging) is an important tool for atmospheric studies. Lidar provides a unique and powerful method for unobtrusively profiling aerosols, wind, water vapor, temperature, and other atmospheric parameters. This brief overview of lidar remote sensing is focused on atmospheric applications involving pulsed lasers. The level of technical detail is aimed at the educated non-lidar expert and references are provided for further investigation of specific topics. The article is divided into three main sections. The first describes atmospheric scattering processes and the physics behind laser-atmosphere interactions. The second section highlights some of the primary lidar applications, with brief descriptions of each measurement capability. The third section describes the practical aspects of lidar operation, including the governing equation and operational considerations.
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…
This lecture is mainly based on the work of S.R. Cloude and presents examples for remote sensing applications Polarimetric SAR Interferometry...PolInSAR). PolInSAR has its origins in remote sensing and was first developed for applications in 1997 using SIRC L-Band data [1,2]. In its original form it
Application of remote sensing technologies in agriculture began with the use of aerial photography to identify cotton root rot in the late 1920s. From then on, agricultural remote sensing has developed gradually until the introduction of precision farming technologies in the late 1980s and biotechno...
The EPA Remote Sensing Data Gateway (RSDG) is a pilot project in the National Exposure Research Laboratory (NERL) to develop a comprehensive data search, acquisition, delivery and archive mechanism for internal, national and international sources of remote sensing data for the co...
Kong, Jin AU; Yueh, Herng-Aung; Shin, Robert T.
Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others.
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
Mulitsch, Melinda Jennifer
The spread of invasive species and climate change are among the most serious global environmental threats. The goal of this dissertation was to link inter-annual climate change and biological invasions at a landscape scale using novel remote sensing techniques applied to the San Francisco Bay/Sacramento- San Joaquin Delta Estuary. I evaluated the use of hyperspectral imagery for detecting invasive aquatic species in the Delta using 3 m HyMap hyperspectral imagery. The target invasive aquatics weeds were the emergent water hyacinth (Eichhornia crassipes) and the submerged Brazilian waterweed (Egeria densa). Data were analyzed using linear spectral mixture analysis (SMA). The results show the weeds were mapped with a classification accuracy of 90.6% compared to 2003 sample sites and 82.6% accuracy compared to 2004 sample sites. Brazilian waterweed locations were successfully mapped but the abundances were overestimated because we did not separate it from other submerged aquatic vegatation (SAV). I evaluated 3 m HyMap imagery, from 2004, for SAV species in the Delta, including: Brazilian waterweed ( Egeria densa), Eurasian watermilfoil (Myriophyllum spicatum ), curlyleaf pondweed (Potamogeton crispus), coontail (Ceratophyllum demersum), American pondweed (Potamogeton nodosus), fanwort (Cabomba caroliniana), and common elodea (Elodea canadensis). Data were analyzed using SMA with a classification accuracy of 84.4%. Spectral simulations of Brazilian waterweed and American pondweed show how spectral properties can change at different water depths and varying water quality. Finally I address the effect of inter-annual climate change on the estuary ecology in the San Francisco Bay by analyzing current (2002) and historical (1994-1996) Airborne Visible Infrared Imaging Spectrometer (AVIRIS) datasets to map salt marsh species distribution. The species in the estuary, Salicornia virginica, Spartinia foliosa, Scirpus robustus, and Distichlis spicata undergo dramatic changes in
The U. S. Geological Survey's (USGS) Commercial Remote Sensing Data Contracts (CRSDCs) provide government agencies with access to a broad range of commercially available remotely sensed airborne and satellite data. These contracts were established to support The National Map partners, other Federal Civilian agency programs, and Department of Defense programs that require data for the United States and its territories. Experience shows that centralized procurement of remotely sensed data leads to considerable cost savings to the Federal government through volume discounts, reduction of redundant contract administrative costs, and avoidance of duplicate purchases. These contracts directly support the President's Commercial Remote Sensing Space Policy, signed in 2003, by providing a centralized mechanism for civil agencies to acquire commercial remote sensing products to support their mission needs in an efficient and coordinated way. CRSDC administration is provided by the USGS Mid-Continent Mapping Center in Rolla, Missouri.
Gao, Maofang; Liu, Sanchao; Qin, Zhihao; Qiu, Jianjun; Xu, Bin; Li, Wenjuan; Yang, Xiuchun; Li, Jingjing
As an important pasture region, Tibet has about 82 million hectares of natural grassland, accounting for 68.11% of its total territory. Above 90% of Tibetan grassland belongs to the types of alpine meadow steppe and alpine steppe with highly nutritious forage plant. Animal husbandry constitutes a major part of agricultural economy in Tibet. It is believed that snow disaster become a significant threat to the development of animal husbandry in Tibet. The disaster often happens in winter and spring as a result of complicated mountainous features and mutable climatic conditions. Statistics indicates that, on average, there is a slight snow disaster for each 3-year, a medium disaster within 5 to 6 years, and a big disaster in 8-10 years. Large numbers of animals died of hungry and cold during the disaster period. Huge economic loss due to the disaster had brought giant difficulties to local herdsmen in Tibet. Accurate and timely monitoring of snow cover for snow disaster evaluating is very important to provide the required information for decision-making in anti-disaster campaigns. Remote sensing has many advantages in snow disaster monitoring hence been extensively applied as the main approach for snow cover monitoring. In this paper we present our study of snow cover monitoring and snow disaster evaluating in Tibet. An applicable approach has been developed in the study for the monitoring and evaluating. The approach is based on the normalize difference of snow index (NDSI) and DEM retrieved from MODIS and GIS data. Using the approach, we analyzed the snowstorm occurring in mid-March 2007 in southern Tibet. Results from our analysis indicated that the new approach is able to provide an accurate estimate of snow cover area and snow depth in southern Tibet. Thus we may conclude that the approach can be used as an efficient alternative for snow cover monitoring and snow disaster evaluating in Tibet.
Frodella, William; Ciampalini, Andrea; Gigli, Giovanni; Lombardi, Luca; Raspini, Federico; Nocentini, Massimiliano; Scardigli, Cosimo; Casagli, Nicola
The historic town of San Leo (Emilia Romagna Region, northern Italy) is located on top of an isolated rock massif above the Marecchia River valley hillside. On February 27th 2014, a northeastern sector of the massif collapsed; minor structural damages were reported in the town and a few buildings were evacuated as a precautionary measure. Although no fatalities occurred and the San Leo cultural heritage suffered no damage, minor rock fall events kept taking place on the newly formed rock wall, worsening this hazardous situation. In this framework, a monitoring system based on remote sensing techniques, such as radar interferometry (both spaceborne and ground-based) and terrestrial laser scanning, was planned in order to monitor the ground deformation of the investigated area and to evaluate the residual risk. In this paper the main outlines of a 1-year monitoring activity are described, including a pre-event analysis of possible landslide precursors and a post-event analysis of the displacements of both the collapse-affected rock wall sector and the rock fall deposits.
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.
Yuronen, Yu P.; Yuronen, E. A.; Ivanov, V. V.; Kovalev, I. V.; Zelenkov, P. V.
In this article the creation concept of the center of expeditious supervision and reaction for the solution of problems of environmental monitoring and support of adoption of administrative decisions is considered. The authors prove need of creation of the similar center in the territory of Krasnoyarsk region as the object consolidating existing and planned systems of land supervision and system of remote sensing.
Davis, Philip A.
In mid-2000, the Grand Canyon Monitoring and Research Center (GCMRC) began a remote-sensing initiative to evaluate all remote-sensing technologies and methods that had potential for providing improved data (capability) for its various programs that monitor the Colorado River ecosystem (CRE). The primary objective of the initiative was to determine the most cost-effective data collection protocols for GCMRC programs that (1) provide the accuracies required for currently measured parameters, (2) provide additional parameters for ecological monitoring, (3) reduce environmental impact by being less invasive than current methods, and (4) expand geographic extent of current ground approaches. The initial phase of the remote-sensing initiative determined the types of sampling parameters and their required accuracies for monitoring. This information was used to determine the most appropriate sensors for evaluation. The initiative evaluated 25 different data collections over a three-year period; many more remote-sensing instruments were considered, but were not evaluated because they could not meet the basic requirements on spatial resolution, wavelength, positional accuracy, or elevation accuracy. It was hoped that the evaluations would lead to a minimum set of technologies that would satisfy many program requirements. The results from all of our evaluations are reviewed in this report and are briefly summarized in this report.
Chen, Jianping; Tarolli, Paolo; Li, Ke; Yang, Xiaofei
Abundant mineral resource is the basis for high-speed social and economic development, and huge economic benefits promoted the rapid development of modern mining industry. However, mining leaves the most significant signature on the Earth, by strongly changing and influencing landscapes and eco-systems. Disasters like water/soil pollution, soil erosion, landslides and land subsidence are often induced by mining activities. Multi-temporal remote sensing surveys can offer a basis upon which develop methodologies for better understanding the influences of mining on landscapes and related Earth surface processes. The aim of the study is to monitor a mining area using multi-temporal remote sensing data, for discovering and evaluating the influence of the mining activities on the environment. Our research area is located in Yunnan Province, China, where open-pit mining activities have been going on for about 10 years. For the study area there is the availability of multi-temporal spatial adjusted remote sensing images (2001 TM with resolution of 30m/pix, 2009 TM with resolution of 30m/pix, 2011 WV-II with resolution of 0.5m/pix, 2012 WV-II with resolution of 0.5m/pix). Through photo interpretation, it was possible to collect the evolutions of mining area, and to recognize areas subject to erosion and landsliding. The results have been validated using field surveys carried out in 2011 and 2012. The multi-temporal image interpretation indicates that the mining activities started between 2001 and 2009, with a significant increasing of land degradation between 2009 and 2012. This study represents the first step of a long-term analysis of Yunnan Province mining area. The goal is to arrange a multi-sensor yearly survey using different platforms and technologies (e.g. ground GPS, Structure from Motion photogrammetric technique SfM, UAV, and airborne and terrestrial laser scanner), in order to better understand the landscape evolution of the area, and analyze in detail the Earth
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
Lagomasino, D.; Price, R. M.; Campbell, P. K.
analyzed for major ions (e.g, Cl-, SO42-, Na2+, Mg2+, K+, and Ca2+) and nutrients (e.g., total organic carbon, N and P). The spectral responses of each of the mangrove species were collected in-situ within a few days of the water sampling. Initial results illustrate good correlations (R2>0.65; P<0.05) between various spectra-derived biophysical indices (e.g., EVI, NDVI) and porewater chloride concentrations. Other correlations demonstrate complex relationships between total N and P concentrations and site-specific mangrove spectra, suggesting physiological differences of nutrient uptake induced by salinity-related stress. The findings suggest the potential for upscaling these relationships using airborne and satellite hyperspectral imagery (e.g., AVIRIS, Hyperion) in order to monitor salt-water intrusion remotely on a regional scale. Further investigations with this research could provide insight to water and carbon flux dynamics within the Everglades and similar coastal mangrove ecosystems throughout the world.
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
Monitoring of rangelands poses significant challenges to land managers due to broad extent and many uses of rangelands. The Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring (AIM) program seeks to efficiently collect standard, quantitative monitoring data which is collected onc...
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.
Cole, Beth; McMorrow, Julia; Evans, Martin
Recognising the importance of the timing of image acquisition on the spectral response in remote sensing of vegetated ecosystems is essential. This study used full wavelength, 350-2500 nm, field spectroscopy to establish a spectral library of phenological change for key moorland species, and to investigate suitable temporal windows for monitoring upland peatland systems. Spectral responses over two consecutive growing seasons were recorded at single species plots for key moorland species and species sown to restore eroding peat. This was related to phenological change using narrowband vegetation indices (Red Edge Position, Photochemical Reflectance Index, Plant Senescence Reflection Index and Cellulose Absorption Index); that capture green-up and senescence related changes in absorption features in the visible to near infrared and the shortwave infrared. The selection of indices was confirmed by identifying the regions of maximum variation in the captured reflectance across the full spectrum. The indices show change in the degree of variation between species occurring from April to September, measured for plant functional types. A discriminant function analysis between indices and plant functional types determines how well each index was able to differentiate between the plant functional groups for each month. It identifies April and July as the two months where the species are most separable. What is presented here is not one single recommendation for the optimal temporal window for operational monitoring, but a fuller understanding of how the spectral response changes with the phenological cycle, including recommendations for what indices are important throughout the year.
The goal of the project was to develop a wireless communications system, including communications, command, and control software, to remotely monitor the environmental state of a process or facility. Proof of performance would be tested and evaluated with a prototype demonstration in a functioning facility. AR Designs' participation provided access to software resources and products that enable network communications for real-time embedded systems to access remote workstation services such as Graphical User Interface (GUI), file I/O, Events, Video, Audio, etc. in a standardized manner. This industrial partner further provided knowledge and links with applications and current industry practices. FM and T's responsibility was primarily in hardware development in areas such as advanced sensors, wireless radios, communication interfaces, and monitoring and analysis of sensor data. This role included a capability to design, fabricate, and test prototypes and to provide a demonstration environment to test a proposed remote sensing system. A summary of technical accomplishments is given.
McDonald, K. C.; Njoku, E.; Kimball, J.; Running, S.; Thompson, C.; Lee, J. K.
The important role of the high latitudes in the functioning of global processes is becoming well established. The size and remoteness of arctic and boreal ecosystems, however, pose a challenge to quantification of both terrestrial ecosystem processes and their feedbacks to regional and global climate conditions. Boreal and arctic regions form a complex land cover mosaic where vegetation structure, condition and distribution are strongly regulated by environmental factors such as moisture availability, permafrost, growing season length, disturbance and soil nutrients.
Demetriades-Shah, Tanvir H.; Steven, Michael D.; Clark, Jeremy A.
The use of derivative spectra is an established technique in analytical chemistry for the elimination of background signals and for resolving overlapping spectral features. Application of this technique for tackling analogous problems such as interference from soil background reflectance in the remote sensing of vegetation or for resolving complex spectra of several target species within individual pixels in remote sensing is proposed. Methods for generating derivatives of high spectral resolution data are reviewed. Results of experiments to test the use of derivatives for monitoring chlorosis in vegetation show that derivative spectral indices are superior to conventional broad-band spectral indices such as the near-infrared/red reflectance ratio. Conventional broad-band indices are sensitive to both leaf cover as well as leaf color. New derivative spectral indices which were able to monitor chlorosis unambiguously were identified. Potential areas for the application of this technique in remote sensing are considered.
Jaworowski, C.; Heasler, H. P.; Rodriguez, J.; Hardy, C. C.; Seielstad, C.; Queen, L. P.
Protection of Yellowstone's unique geothermal resources is the main focus of Yellowstone National Park's effort to map and scientifically monitor heat emitted from selected hydrothermal areas and the entire 2.2 million acres of Yellowstone National Park. In 2005, Yellowstone National Park geologists began collaborations with researchers from the University of Montana's National Center For Landscape Fire Analysis(UM-NCLFA), Utah State University's Remote Sensing Services Laboratory, Montana State University and the USDA Fire Sciences Lab to accomplish this task. A goal of the remote sensing component of Yellowstone's Geothermal Monitoring Plan is the estimation of radiant heat flux for Norris Geyser Basin, the Upper Geyser Basin, Midway Geyser Basin, the Lower Geyser Basin, the Mud Volcano area, Mammoth Hot Springs, Hot Spring Basin, the Sour Creek resurgent dome and the entire Park. Norris Geyser Basin is an example of a fracture-controlled hydrothermal basin. The nine hydrothermal sub- basins that compose Norris Geyser Basin include: Porcelain Basin, Steamboat-Echinus, Gray Lakes-Porkchop, the Gap, the West Gap, Reservoir-Upper Tantalus Creek, Lower Tantalus Creek, One Hundred Spring Plain, and Sulfur Dust. Two orthogonal sets of fractures (northeast and northwest; north-south and east-west) direct the flow of heat and water through the otherwise impermeable Lava Creek B tuff within these sub-basins. Airborne mid- infrared (3-5 micron) imagery acquired at night clearly shows the flow of heat and water along these fracture trends. These major fracture sets also partition Norris Geyser Basin into numerous blocks, potentially allowing independent movements among blocks and hydrothermal sub-basins. We estimated radiant heat flux for the Norris Geyser Basin using airborne mid-infrared (3-5 micron) daytime imagery acquired by a thermal imagery contractor on 9 October 2002 and daytime imagery acquired with a different sensor but similar mid-infrared bandpass on 12
Lin, Wenpeng; Chen, Guangsheng; Guo, Pupu; ...
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. Inmore » this paper, 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 occupied by S
Lin, Wenpeng; Chen, Guangsheng; Guo, Pupu; Zhu, Wenquan; Zhang, Donghai
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 paper, 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 occupied by S
Yueh, Herng-Aung; Kong, Jin AU
the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.
Atwell, B. H.
The Mississippi Sound Remote Sensing Study was initiated as part of the research program of the NASA Earth Resources Laboratory. The objective of this study is development of remote sensing techniques to study near-shore marine waters. Included within this general objective are the following: (1) evaluate existing techniques and instruments used for remote measurement of parameters of interest within these waters; (2) develop methods for interpretation of state-of-the-art remote sensing data which are most meaningful to an understanding of processes taking place within near-shore waters; (3) define hardware development requirements and/or system specifications; (4) develop a system combining data from remote and surface measurements which will most efficiently assess conditions in near-shore waters; (5) conduct projects in coordination with appropriate operating agencies to demonstrate applicability of this research to environmental and economic problems.
The paper discusses remote sensing systems used at the Savannah River Plant. They include three ground-based systems: ground penetrating radar, sniffers, and lasers; and four airborne systems: multispectral photography, lasers, thermal imaging, and radar systems. (ACR)
Kong, J. A.
Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.
Summers, R. A.; Smith, W. L.; Short, N. M.
The nature of the U.S. energy problem is examined. Based upon the best available estimates, it appears that demand for OPEC oil will exceed OPEC productive capacity in the early to mid-eighties. The upward pressure on world oil prices resulting from this supply/demand gap could have serious international consequences, both financial and in terms of foreign policy implementation. National Energy Plan objectives in response to this situation are discussed. Major strategies for achieving these objectives include a conversion of industry and utilities from oil and gas to coal and other abundant fuels. Remote sensing from aircraft and spacecraft could make significant contributions to the solution of energy problems in a number of ways, related to exploration of energy-related resources, the efficiency and safety of exploitation procedures, power plant siting, environmental monitoring and assessment, and the transportation infrastructure.
Thomas, R. H.
Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.
Rees, W. G.
Substantially revised and expanded, this new edition includes a discussion of the radiative transfer equation, atmospheric sounding techniques and interferometric radar, an expanded list of problems (with solutions), and a discussion of the Global Positioning System (GPS). This book forms the basis of an introductory course in remote sensing. The main readership will be students and researchers in remote sensing, geography, cartography, surveying, meteorology, earth sciences and environmental sciences generally, as well as physicists, mathematicians and engineers.
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
Thompson Alves de Souza, Carlos Eduardo
Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR Carlos Eduardo Thompson Alves de Souza firstname.lastname@example.org Archaeologist Member of the European Association of Archaeologists B.A.Archaeology MA.Remote Sensing Abstract The Archaeological Research in Urban Environment with the Air Light Detection and Ranging is problematic for the Overlay Layers mixed with contexts concerning the Interpretation of Archaeological Data. However, in the Underwater Archaeology the results are excellent. This paper considers the application of Remote Sensing and Air Light Detection and Ranging (LIDAR) as separate things as well as Land Archaeology and the Underwater Archaeology. European Archaeologists know very little about Brazil and the article presents an Overview of Research in Brazil with Remote Sensing in Archaeology and Light Detection and Ranging in Land Archaeology and Underwater Archaeology, because Brazil has Continental Dimensions. Braziliańs Methodology for Location, Analysis and Monitoring of Archaeological Sites is necessarily more Complex and Innovative and therefore can serve as a New Paradigm for other archaeologists involved in the Advanced Management Heritage.
Komp, K. U.; Haub, C.
After four decades of space borne remote sensing, the unmapped white patches have mostly disappeared. Those basic information give the foundations to the observation of changes and even the introduction of monitoring programmes for a various number of features in the natural and human landscape of our planet. Recent indicators for climatic change together with worrisome alterations in regional food production versus the constantly increase of human population demand the design and implementation of reliable land management tools which will serve the food security as well as the sustainable use of resources of the ecosystem in its respective regional context. The positive responses and convincing results of ESA service elements in the efforts towards food security in several African countries have been the basis for the transfer of the methods into another region, the Western Siberian corn-belt. The large extends of cropping schemes in West Siberia demand advanced remote sensing methods to be applied in order to compare the impacts of climatic change not only on the agricultural production but also on risks for the ecosystem. A multi scale approach of remote sensing methods is introduced in analogy to the African activities. An adopted monitoring concept is developed using a nearly daily product of medium resolution for wide areas, high resolution sensors for stratified sample areas and in-situ observations. Beyond methodological research, the ability of remote sensing is contributing to operational solutions that can ensure the nutritional and ecological future of our planet.
Mouat, D. A.; Johnson, J. D.; Foster, K. E.
Descriptions of projects engaged by the Applied Remote Sensors Program in the state of Arizona are contained in an annual report for the fiscal year 1976-1977. Remote sensing techniques included thermal infrared imagery in analog and digital form and conversion of data into thermograms. Delineation of geologic areas, surveys of vegetation and inventory of resources were also presented.
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.
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.
Arp, C.D.; Jones, Benjamin M.; Whitman, Matthew; Larsen, A.; Urban, F.E.
Lake surface regimes are fundamental attributes of lake ecosystems and their interaction with the land and atmosphere. High latitudes may be particularly sensitive to climate change, however, adequate baselines for these lakes are often lacking. In this study, we couple monitoring, remote sensing, and modeling techniques to generate baseline datasets of lake surface temperature and ice cover in the Alaskan Subarctic and Arctic. No detectable trends were observed during this study period, but a number of interesting patterns were noted among lakes and between regions. The largest Arctic lake was relatively unresponsive to air temperature, while the largest Subarctic lake was very responsive likely because it is fed by glacial runoff. Mean late summer water temperatures were higher than air temperatures with differences ranging from 1.7 to 5.4°C in Subarctic lakes and from 2.4 to 3.2°C in Arctic lakes. The warmest mean summer water temperature in both regions was in 2004, with the exception of Subarctic glacially fed lake that was highest in 2005. Ice-out timing had high coherence within regions and years, typically occurring in late May in Subarctic and in early-July in Arctic lakes. Ice-on timing was more dependent on lake size and depth, often varying among lakes within a region. Such analyses provide an important baseline of lake surface regimes at a time when there is increasing interest in high-latitude water ecosystems and resources during an uncertain climate future.
Bishop, Peter C.
The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.
Classen, Hans George
Describes the joint effort of Canada and NASA in monitoring the Canadian environment using remote-sensing techniques. The project involves the Earth Resources Technology Satellite and has been used to observe seasonal changes, extent of snow cover, crop growth, sea ice, and land use patterns. (GS)
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.
Remote sensing is being used more and more for decision-making and policy development. Specific examples are: (1) Providing constraints on climate models used in IPCC assessments (2) Framing discussions about greenhouse gas monitoring (3) Providing support for hazard assessment and recovery.
Mouginis-Mark, Peter J.; Francis, Peter W.; Wilson, Lionel; Pieri, David C.; Self, Stephen; Rose, William I.; Wood, Charles A.
The possibility of using remote sensing to monitor potentially dangerous volcanoes is discussed. Thermal studies of active volcanoes are considered along with using weather satellites to track eruption plumes and radar measurements to study lava flow morphology and topography. The planned use of orbiting platforms to study emissions from volcanoes and the rate of change of volcanic landforms is considered.
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.
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.
Adjustment of the water treatment process to changes in the water quality has been an area of focus for engineers and managers of water treatment plants. This desired and preferred capability depends on timely and quantitative knowledge of water quality monitoring in terms of tot...
Pathak, N.; Loheide, S. P.
Intense agricultural practices and urbanization have negatively impacted wetlands globally; however, in the United States restoration initiatives have become popular in an attempt to reverse these trends. This study focuses on assessment of the hydroecology of a degraded wetland with historic aerial photograph analysis, field based monitoring, and saturated groundwater modeling. The study area is situated in an urbanized watershed of south central Wisconsin, USA and has been impacted by stormwater runoff. Analysis of aerial photographs from 1937 to 2007 show a shift from wetland and wet prairie vegetation to woody vegetation with more than a 20 fold increase in larger trees. GPS surveys and classification using high resolution NAIP imagery was utilized to estimate the distribution of various vegetation communities in the study area. Field based monitoring using 24 groundwater monitoring wells and 7 soil moisture stations was utilized to ascertain the hydrologic conditions supporting different vegetation types. A 2D saturated groundwater model was created to simulate changes in the hydroecologic condition of the site. An integrated approach utilizing historic data combined with field monitoring and numerical modeling has promise to act as a decision support system for land managers attempting to restore degraded wetlands such as the one studied here.
Bi, Siwen; Lin, Xuling; Yang, Song; Wu, Zhiqiang
According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.
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.
Giordan, Daniele; Allasia, Paolo; Dematteis, Niccolò; Dell’Anese, Federico; Vagliasindi, Marco; Motta, Elena
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. PMID:27775652
Giordan, Daniele; Allasia, Paolo; Dematteis, Niccolò; Dell'Anese, Federico; Vagliasindi, Marco; Motta, Elena
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
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
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
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.
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.
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.
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.
Dierssen, Heidi M.; Randolph, Kaylan
The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats
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.; 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.
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.
Estes, J. E.; Tinney, L. R. (Principal Investigator); Streich, T.
The use of digital LANDSAT techniques for monitoring agricultural land use conversions was studied. Two study areas were investigated: one in Ventura County and the other in Fresno County (California). Ventura test site investigations included the use of three dates of LANDSAT data to improve classification performance beyond that previously obtained using single data techniques. The 9% improvement is considered highly significant. Also developed and demonstrated using Ventura County data is an automated cluster labeling procedure, considered a useful example of vertical data integration. Fresno County results for a single data LANDSAT classification paralleled those found in Ventura, demonstrating that the urban/rural fringe zone of most interest is a difficult environment to classify using LANDSAT data. A general raster to vector conversion program was developed to allow LANDSAT classification products to be transferred to an operational county level geographic information system in Fresno.
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.
Barnes, Norman P.
NASA is developing active remote sensors to monitor the health of Planet Earth and for exploration of other planets. Development and deployment of these remote sensors can have a huge economic impact. Lasers for these active remote sensors span the spectral range from the ultraviolet to the mid infrared spectral regions. Development activities range from quantum mechanical modeling and prediction of new laser materials to the design, development, and demonstration be deployed in the field.
Peterson, D. A.; Solbrig, J. E.; Hyer, E. J.; Campbell, J. R.; Fromm, M. D.
Fire-triggered thunderstorms, known as pyrocumulonimbus (pyroCb), can alter fire behavior, influence smoke plume trajectory, and hinder fire suppression efforts. Intense pyroCb can also inject a significant quantity of aerosol mass into the lower stratosphere. Systematic detection and monitoring of these events is important for wildfire response and aviation applications, as well as understanding climate and air quality implications. The United States Naval Research Laboratory (NRL) recently developed a near-real-time pyroCb detection algorithm using geostationary satellite observations, currently focused on GOES-West. The algorithm is tuned to the microphysics of fire-perturbed thunderstorms over elevated terrain in western North America. By incorporating reanalysis data, NRL has also developed the first observationally-based conceptual model for pyroCb development. Results are focused on 41 large wildfires observed in the United States and Canada during 2013, which produced more than 50 intense pyroCb. The majority of these develop when a layer of increased moisture content and instability is advected over a dry, deep, and unstable mixed layer, typically along the leading edge of an approaching disturbance. The upper-tropospheric dynamics and synoptic pattern must also be conducive for vertical development of convection. Mid- and upper-tropospheric conditions similar to those that produce traditional dry thunderstorms are therefore paramount for development and maintenance of pyroCb. The amount of mid-level moisture and instability required is strongly dependent on the surface elevation of the contributing fire. Surface-based fire weather indices have limited capability for predicting pyroCb development. The intense radiant heat emitted by large wildfires can serve as a potential trigger, suggesting pyroCb may develop in the absence of traditional triggering mechanisms when an otherwise favorable meteorological environment is in place. This conceptual model
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.
Kuo, YaoCheng; Chen, ChiFarn
Change detection allows direct observation of land surface at repetitive intervals and provides important applications in environment monitoring, damage assessment and so on. And Detecting clouds in satellite imagery is becoming more important with increasing data availability, however many earth observation sensors are not designed for this task. Image radiometric normalization has caused problems in previous satellite image change and cloud detection methods is a precondition for deriving land change information of satellite imagery of different dates. To solve the ambiguity in using such resources, this paper proposes a complete change detection method based on iterative histogram and Fuzzy C-Mean which can cope with radiometric normalization, cloud and change detection. It firstly uses Fuzzy C-Mean clustering to dilute the small brightness area even with noise and outliers. And setting a different threshold at each band to find the cloud area. Then iterative algorithm applies the spectrum of invariant area for whole image with histogram matching. A threshold is then applied to difference images between the reference and the matched histogram subject images in order to detect the change areas. The image differentiation and threshold are again applied the updated histogram-matched image to further segment the change and the non-change areas. The creative parts of our approach lie in a three-step detection scheme is proved to be an efficient and effective way to differentiate the change area.
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.
Burton, E. A.; Pickles, W. L.; Gouveia, F. J.; Bogen, K. T.; Rau, G. H.; Friedmann, J.
Correct assessment of the potential for CO2 leakage to the atmosphere or near surface is key to managing the risk associated with CO2 storage. Catastrophic, point-source leaks, diffuse seepage, and low leakage rates all merit assessment. Smaller leaks may be early warnings of catastrophic failures, and may be sufficient to damage natural vegetation or crops. Small leaks also may lead to cumulative build-up of lethal levels of CO2 in enclosed spaces, such as basements, groundwater-well head spaces, and caverns. Working with our ZERT partners, we are integrating a variety of monitoring and modeling approaches to understand how to assess potential health, property and environmental risks across this spectrum of leakage types. Remote sensing offers a rapid technique to monitor large areas for adverse environmental effects. If it can be deployed prior to the onset of storage operations, remote sensing also can document baseline conditions against which future claims of environmental damage can be compared. LLNL has been using hyperspectral imaging to detect plant stress associated with CO2 gas leakage, and has begun investigating use of NASA's new satellite or airborne instrumentation that directly measures gas compositions in the atmosphere. While remote sensing techniques have been criticized as lacking the necessary resolution to address environmental problems, new instruments and data processing techniques are demonstrated to resolve environmental changes at the scale associated with gas-leakage scenarios. During the shallow low-flow- CO2 release field experiments planned by ZERT, for the first time, we will have the opportunity to ground- truth hyperspectral data by simultaneous measurement of changes in hyperspectral readings, soil and root zone microbiology, ambient air, soil and aquifer CO2 concentrations. When monitoring data appear to indicate a CO2 leakage event, risk assessment and mitigation of that event requires a robust and nearly real-time method for
Oppelt, Natascha; Mauser, Wolfram
Biochemical components of vegetation canopies, such as chlorophyll and nitrogen, are among the parameters controlling physiological processes and therefore essential for the characterization of these processes and their integration in hydrological or vegetation modeling. AVIS (Airborne Visible/near Infrared imaging Spectrometer), built at the department for environmental sciences of the Ludwig-Maximilians-University Munich, is a cost-effective tool for environmental monitoring. Its spectral range lies between 550 and 1000nm and its multitemporal application enables observation of the development of chlorophyll and nitrogen content of plants throughout a vegetation period. Twelve and nine airborne data sets were gathered between April and September 1999 and 2000 respectively from three maize fields in a test site south-west of Munich in the Bavarian Alpine foothills, Germany (48° 6", 11° 17" E). Weekly ground-based measurements of plant parameters (plant height, phenology, biomass, nitrogen content, chlorophyll content) during the vegetation periods provided data validation. The chlorophyll and nitrogen content of the maize canopies were derived using the Chlorophyll Absorption Integral (CAI), which exhibited a high correlation with the chlorophyll content per area and the nitrogen content, both per area (g/m2) and in percentage of dry matter (nitrogen=%DM; chlorophyll=mg/g), during vegetative growth before emergence of the ear. The chlorophyll content per mass cannot be derived with the CAI, due to distinct variations of the chlorophyll per mass during plant growth caused by the low chilling tolerance of maize. The mean field values and the spatial distribution of parameter values within one of the fields will be presented, demonstrating the capabilities of AVIS.
Stelmaszczuk-Gorska, M. A.; Thiel, C. J.; Schmullius, C.
Aboveground biomass (AGB) plays an essential role in ecosystem research, global cycles, and is of vital importance in climate studies. AGB accumulated in the forests is of special monitoring interest as it contains the most of biomass comparing with other land biomes. The largest of the land biomes is boreal forest, which has a substantial carbon accumulation capability; carbon stock estimated to be 272 +/-23 Pg C (32%) . Russian's forests are of particular concern, due to the largest source of uncertainty in global carbon stock calculations , and old inventory data that have not been updated in the last 25 years . In this research new empirical models for AGB estimation are proposed. Using radar L-band data for AGB retrieval and optical data for an update of in situ data the processing scheme was developed. The approach was trained and validated in the Asian part of the boreal forest, in southern Russian Central Siberia; two Siberian Federal Districts: Krasnoyarsk Kray and Irkutsk Oblast. Together the training and testing forest territories cover an area of approximately 3,500 km2. ALOS PALSAR L-band single (HH - horizontal transmitted and received) and dual (HH and HV - horizontal transmitted, horizontal and vertical received) polarizations in Single Look Complex format (SLC) were used to calculate backscattering coefficient in gamma nought and coherence. In total more than 150 images acquired between 2006 and 2011 were available. The data were obtained through the ALOS Kyoto and Carbon Initiative Project (K&C). The data were used to calibrate a randomForest algorithm. Additionally, a simple linear and multiple-regression approach was used. The uncertainty of the AGB estimation at pixel and stand level were calculated approximately as 35% by validation against an independent dataset. The previous studies employing ALOS PALSAR data over boreal forests reported uncertainty of 39.4% using randomForest approach  or 42.8% using semi-empirical approach .
Tang, Qiang; Li, Shao-kun; Wang, Ke-ru; Xie, Rui-zhi; Chen, Bing; Wang, Fang-yong; Diao, Wan-ying; Xiao, Chun-hua
Biomass, leaf area index (LAI) and nitrogen status are important parameters for indicating crop growth potential and photosynthetic productivity in wheat. Nondestructive, quick assessment of leaf dry weight, LAI and nitrogen content is necessary for nitrogen nutrition diagnosis and cultural regulation in wheat production. In order to establish the monitoring model of nitrogen richness in winter wheat of growth anaphase, studying the relationship between the nitrogen richness (NR) containing nitrogen density, LAI and leaf dry weight and the difference of hyperspectral reflectance rates (deltaR), we conducted a comparable experiment with five winter wheat varieties under nitrogen application level of 0, 100, 200 and 400 kg x N x ha(-1). The results indicated the NRs of the different varieties of winter wheat leaves increased with increasing growth stage while in the different nitrogen levels it was sequenced as: NO>N3>N1>N2. Twelve vegetation indices were compared with corresponding NR. The NR had significantly negative correlation to TCARI and VD672 in those vegetation indices, and their correlations (r) arrived at 0.870 and 0.855, respectively. The coefficients of determination (R2) of two models were 0.757 and 0.731 by erecting model with the two indexes and NR Root mean square error (RMSE), relative error (RE) and determination coefficient between measured and estimated NR were employed to test the model reliability and predicting accuracy. Accuracy rates of the models based on TCARI and VD672 achieved 84.56% and 80.13%. The overall results suggested that leaf nitrogen status of growth anaphase in winter wheat has stable relationships with some vegetation indexes, especially index of TCARI and VD672.
Charpentier, M.A.; Groffman, P.M. )
This work is part of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), an international land-surface-atmosphere experiment aimed at improving the way climate models represent energy, water, heat, and carbon exchanges, and improving the utilization of satellite based remote sensing to monitor such parameters. This paper addresses the question of soil moisture variation within the field of view of a remote sensing pixel. Remote sensing is the only practical way to sense soil moisture over large areas, but it is known that there can be large variations of soil moisture within the field of view of a pixel. The difficulty with this is that many processes, such as gas exchange between surface and atmosphere can vary dramatically with moisture content, and a small wet spot, for example, can have a dramatic impact on such processes, and thereby bias remote sensing data results. Here the authors looked at the impact of surface topography on the level of soil moisture, and the interaction of both on the variability of soil moisture sensed by a push broom microwave radiometer (PBMR). In addition the authors looked at the question of whether variations of soil moisture within pixel size areas could be used to assign errors to PBMR generated soil moisture data.
Mialhe, François; Gunnell, Yanni; Ignacio, J. Andres F.; Delbart, Nicolas; Ogania, Jenifer L.; Henry, Sabine
This paper combines participatory activities (PA) with remote sensing analysis into an integrated methodology to describe and explain land-cover changes. A remote watershed on Mindanao (Philippines) is used to showcase the approach, which hypothesizes that the accuracy of expert knowledge gained from remote sensing techniques can be further enhanced by inputs from vernacular knowledge when attempting to understand complex land mosaics and past land-use changes. Six participatory sessions based on focus-group discussions were conducted. These were enhanced by community-based land-use mapping, resulting in a final total of 21 participatory land-use maps (PLUMs) co-produced by a sample of stakeholders with different sociocultural and ecological perspectives. In parallel, seven satellite images (Landsat MSS, Landsat TM, Landsat ETM+, and SPOT4) were classified following standard techniques and provided snapshots for the years 1976, 1996, and 2010. Local knowledge and collective memory contributed to define and qualify relevant land-use classes. This also provided information about what had caused the land-use changes in the past. Results show that combining PA with remote-sensing analysis provides a unique understanding of land-cover change because the two methods complement and validate one another. Substantive qualitative information regarding the chronology of land-cover change was obtained in a short amount of time across an area poorly covered by scientific literature. The remote sensing techniques contributed to test and to quantify verbal reports of land-use and land-cover change by stakeholders. We conclude that the method is particularly relevant to data-poor areas or conflict zones where rapid reconnaissance work is the only available option. It provides a preliminary but accurate baseline for capturing land changes and for reporting their causes and consequences. A discussion of the main challenges encountered (i.e. how to combine different systems of
Ong, K. G.; Wang, J.; Singh, R. S.; Bachas, L. G.; Grimes, C. A.; Daunert, S. (Principal Investigator)
A new technique is presented for in-vivo remote query measurement of the complex permittivity spectra of a biological culture solution. A sensor comprised of a printed inductor-capacitor resonant-circuit is placed within the culture solution of interest, with the impedance spectrum of the sensor measured using a remotely located loop antenna; the complex permittivity spectra of the culture is calculated from the measured impedance spectrum. The remote query nature of the sensor platform enables, for example, the in-vivo real-time monitoring of bacteria or yeast growth from within sealed opaque containers. The wireless monitoring technique does not require a specific alignment between sensor and antenna. Results are presented for studies conducted on laboratory strains of Bacillus subtilis, Escherichia coli JM109, Pseudomonas putida and Saccharomyces cerevisiae.
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
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.
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.
Bernstein, Adam; Dazeley, Steve; Dobie, Doug; Marleau, Peter; Brennan, Jim; Gerling, Mark; Sumner, Matthew; Sweany, Melinda
The overall goal of the WATCHMAN project is to experimentally demonstrate the potential of water Cerenkov antineutrino detectors as a tool for remote monitoring of nuclear reactors. In particular, the project seeks to field a large prototype gadolinium-doped, water-based antineutrino detector to demonstrate sensitivity to a power reactor at ~10 kilometer standoff using a kiloton scale detector. The technology under development, when fully realized at large scale, could provide remote near-real-time information about reactor existence and operational status for small operating nuclear reactors out to distances of many hundreds of kilometers.
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
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.
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
Mekaoussi, M.; Benmessaoud, H.
The functioning of Mediterranean ecosystems to daily or interannual scale presents an ecological and socio-economic interest. The intensive exploitation of natural resources of this ecosystem by the population has now reached a critical threshold. To this is added the effect of climate change leading to a drought that occurs mainly in the southern part. This leads to accelerated degradation of the ecosystem and requires the establishment of sustainable management rules. The objective of this study is to determine the contribution of multi-date satellite images in detecting global changes and monitoring of developments in the watershed of the Aurès Bouzina center. The approach is to use satellite images Landsat at different times (1986, 2001 and 2013) and sampling work for the confrontation with the ground truth, to conduct a thematic analysis of this environment, and view the global changes that have occurred in this area. The overall reading of the results of the tracking map changes, we notice a degradation of forest cover in ascending gradient from north to south and led to the reduction of vegetation cover drills. The area of irrigated crops registered an increase of grain. In favor of bare soils and wetlands, related to the influence of rivers, as well as the emergence of forage and vegetable crops. Bare soils dominated by a sandy texture are located primarily near areas of crops due to agricultural practices based on the intensification of agriculture as well as silting soil justified by an increase in bare soil. This work is a first step to track the degradation or restoration through ecological indicators field, related to remote sensing data.
Knepper, D. H., Jr.; Marrs, R. W.
Remote sensing techniques were applied to general geologic mapping along the Rio Grande rift zone in central Colorado. A geologic map of about 1,100 square miles was prepared utilizing (1) prior published and unpublished maps, (2) detailed and reconnaissance field maps made for this study, and (3) remote sensor data interpretations. The map is used for interpretation of the complex Cenozoic tectonic and geomorphic histories of the area.
A directory of over 140 firms and organizations which contains detailed information in the types of products, services and equipment which they offer is presented. Also included for each firm or organization are addresses, phone numbers, contact person(s), and experience in the remote sensing field.
Research projects concerning the development and application of remote sensors are discussed. Some of the research projects conducted are as follows: (1) aerial photographic inventory of natural resources, (2) detection of buried river channels, (3) delineation of interconnected waterways, (4) plant indicators of atmospheric pollution, and (5) techniques for data transfer from photographs to base maps. On-going projects involving earth resources analyses are described.
Manual leak detection and repair (LDAR) programs are currently implemented on a regular basis at refinery sites to limit fugitive emissions of volatile organic compounds (VOC). However, LDAR surveys can be time-consuming and are not always cost-effective. Fence line monitoring of...
Koster, R.; Houser, P.; Engman, E.; Kustas, W.
, field experiments must be designed that combine relevant satellite measurements with traditional in situ measurements in regions that are al- ready well understood hydrologically. Such field experiments can lead to the development of hydrological models that are driven with remotely sensed data. Once the performance of these models is deemed acceptable in the heavily monitored basins, they can be "transported" for use in regions having little or no in situ measurement system. Author,5: Randal D. Koster, Paul R. Houser and Edwin T. Engman, Hydrological Sciences Branch, Laboratory for Hydrospheric Process, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; William P. Kustas, Hydrology Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland, USA.
Kahn, Ralph A.
Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.
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.
Latham, J. P.
Color, color infrared, and minus-blue films obtained by RB-57 remote sensing aircraft at an altitude of 60,000 feet over Boca Raton and Southeast Florida Earth Resources Test Site were analyzed for nine different types of photographic images of the geographic patterns of the surface. Results of these analyses are briefly described.
Kuehn, Friedrich; King, Trude V.; Hoerig, Bernhard; Peters, Douglas C.; Kuehn, Friedrich; King, Trude V.; Hoerig, Bernhard; Peters, Douglas C.
This volume, Remote Sensing for Site Characterization, describes the feasibility of aircraft- and satellite-based methods of revealing environmental-geological problems. A balanced ratio between explanations of the methodological/technical side and presentations of case studies is maintained. The comparison of case studies from North America and Germany show how the respective territorial conditions lead to distinct methodological approaches.
Bianchi, R.; Casacchia, R.; Coradini, A.; Duncan, A. M.; Guest, J. E.; Kahle, A.; Lanciano, P.; Pieri, D. C.; Poscolieri, M.
The results of a July 1986 remote sensing campaign of Italian volcanoes are reviewed. The equipment and techniques used to acquire the data are described and the results obtained for Campi Flegrei and Mount Etna are reviewed and evaluated for their usefulness for the study of active and recently active volcanoes.
Various imaging techniques are outlined for use in mapping, land use, and land management in Mexico. Among the techniques discussed are pattern recognition and photographic processing. The utilization of information from remote sensing devices on satellites are studied. Multispectral band scanners are examined and software, hardware, and other program requirements are surveyed.
Huber, Thomas P.
Describes general concepts of remote sensing and provides three examples of how its techniques have been used in the context of environmental issues. Examples focus on the use of this data gathering technique in the visible (aerial photography), near infrared, and thermal infrared ranges. (JN)
With the increasing need for global food production in the presence of dwindling productive acres, the business of modern agriculture needs to use all possible information available to maximize production. One tool that is being used to obtain this information is remote sensing. Any crop disease o...
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.
Atwell, B. H.; Thomann, G. C.
Remote sensing techniques are being developed to study near shore marine waters in the Mississippi Sound. Specific elements of the investigation include: (1) evaluation of existing techniques and instrument capabilities for remote measurement of parameters which characterize near shore water; (2) integration of these parameters into a system which will make possible the definition of circulation characteristics; (3) conduct of applications experiments; and (4) definition of hardware development requirements and/or system specifications. Efforts have emphasized: (1) development of a satisfactory system of gathering ground truth over the entire area of Mississippi Sound to aid in evaluating remotely sensed data; (2) conduct of two data acquisition experiments; (3) analysis of individual sensor data from completed flights; and (4) pursuit of methods which will allow interrelations between data from individual sensors in order to add another dimension to the study.
Barrios, J. M.
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 contagium. 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 climatological 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
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
Bethel, Glenn R.
A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.
Rango, A. (Editor)
Topic concerning remote sensing capabilities for providing reliable snow cover data and measurement of snow water equivalents are discussed. Specific remote sensing technqiues discussed include those in the microwave region of the electromagnetic spectrum.
A digest of information on remote sensor data systems is given. It includes characteristics of spaceborne sensors and the supportive systems immediately associated therewith. It also includes end-to-end systems information that will assist the user in appraising total data system impact produced by a sensor. The objective is to provide a tool for anticipating the complexity of systems and potential data system problems as new user needs are generated. Materials in this handbook span sensor systems from the present to those planned for use in the 1990's. Sensor systems on all planned missions are presented in digest form, condensed from data as available at the time of compilation. Projections are made of anticipated systems.
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
The 2008 Sichuan earthquake, occurred on 12 May 2008 with a magnitude of 8.0 and the center at Wenchuan (31.021°N, 103.367°E), has not only caused a large number of human casualties and property loss, but also severely damaged the ecological system in its surrounding 10 counties, threatening the local ecological safety. As part of the post-disaster reconstruction services, a systematic monitoring of the ecological restoration at the central quake-hit areas has been made based on RS & GIS remote sensing. In this paper we selected the Dujiangyan area for analysis. The reason to select this region is because that Dujiangyan area is about 40 km from the epicenter, and as a region in the subtropical monsoon climate zone, it has a well developed forest ecosystem in the northern part before the earth quake. The coverage of grassland in this region is relatively less. Since the ecological restoration after the earthquake is a long term process, the restoration for different vegetation types has different characteristics. From the analysis of the spatiotemporal change of land-use and vegetation cover in Dujiangyan area from the post-earthquake in 2008 to 2013, we found: (1) During the earthquake, the major vegetation type destroyed is the woodland, which accounts for 99.34% of the destroyed area, and the next are arable land and grassland. (2) The ecological restoration started from the grassland and gradually transited to shrub. In two years after the earthquake, the most significant increase in both area of coverage and magnitude is the grassland, and by 2013, the area of grassland decreased slightly, and instead the area of shrub increased, demonstrating a transition trend from the grassland to the shrub. (3) From the map of vegetation cover, we can see these change occurs mainly in the northern mountain area, while the change of land use mainly occurred in the southern part of the city. These changes can be linked clearly with the earthquake disaster and the post
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.
Six essential processes that must be accomplished if use of a remote - sensing system is to result in useful information are defined as problem...to be useful in remote - sensing projects are described. An overview of the current state-of-the-art of remote sensing is presented.
Yang, Bangjie; Qian, Yonglan; Pei, Zhiyuan; Jiao, Xianfeng
China is one of the main soybean production countries in the world and soybean is of great importance in agricultural industry, domestic consumption and international trade. In recent years, however, China has become the largest soybean importer in the world. Therefore timely credible information about soybean planting area and production is essential for government decision making and agricultural management on domestic consumption and international trade. Moreover, information on soybean planting and continuous planting location is critical for distributing farmer subsidies and production management. In this paper, an operational system based on multi-resolution remotely sensed data was developed for the soybean area inventory and continuous cropping area monitoring. A stratified sampling method is employed to extract and locate major soybean-planting regions, which are later surveyed using remote sensing data. At the same time, sub regions are constructed based on cropping systems in which remotely sensed data of different resolutions are applied for the soybean area estimation and replanting area location assessment.
Seppke, Benjamin; Dreschler-Fischer, Leonie; Wilms, Christian
The extraction of road signatures from remote sensing images as a promising indicator for urbanization is a classical segmentation problem. However, some segmentation algorithms often lead to non-sufficient results. One way to overcome this problem is the usage of superpixels, that represent a locally coherent cluster of connected pixels. Superpixels allow flexible, highly adaptive segmentation approaches due to the possibility of merging as well as splitting and form new basic image entities. On the other hand, superpixels require an appropriate representation containing all relevant information about topology and geometry to maximize their advantages.In this work, we present a combined geometric and topological representation based on a special graph representation, the so-called RS-graph. Moreover, we present the use of the RS-graph by means of a case study: the extraction of partially occluded road networks in rural areas from open source (spectral) remote sensing images by tracking. In addition, multiprocessing and GPU-based parallelization is used to speed up the construction of the representation and the application.
These eleven papers were given at a conference on remote sensing of geographical data. Subjects include fingerprinting of oil spills using fluorescence spectroscopy, satellites, air pollution monitoring, uranium exploration, geomorphology, water pollution, forest diseases and ecology, plumes, and optical techniques.
Bouchillon, C. W.; Miller, W. F.; Landphair, H.; Zitta, V. L.
The use of remote sensing techniques to help the state of Mississippi recognize and solve its environmental, resource, and socio-economic problems through inventory, analysis, and monitoring is suggested.
remote sensing methods for identification and assessment of expanses of aquatic plants. Both materials and techniques are examined for cost effectiveness and capability to sense aquatic plants on both the local and regional scales. Computer simulation of photographic responses was employed; Landsat, high-altitude photography, side-looking airborne radar, and low-altitude photography were examined to determine the capabilities of each for identifying and assessing aquatic plants. Results of the study revealed Landsat to be the most cost effective for regional surveys,
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.
Knyazikhin, Yuri; Schull, Mitchell A; Stenberg, Pauline; Mõttus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Latorre Carmona, Pedro; Kaufmann, Robert K; Lewis, Philip; Disney, Mathias I; Vanderbilt, Vern; Davis, Anthony B; Baret, Frédéric; Jacquemoud, Stéphane; 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.
Results obtained through the NASA Earth Resources Aircraft Program at Mill Creek, Oklahoma, provide a case history example of the application of remote sensing to the identification of geologic rock units. Thermal infrared images are interpreted by means of a sequence of models of increasing complexity. The roles of various parameters are examined: rock properties (thermal inertia, albedo, emissivity), site location (latitude), season (sun's declination), atmospheric effects (cloud cover, transmission, air temperature), and topographic orientation (slope, azimuth). The results obtained at this site also illustrate the development of an important application of remote sensing in geologic identification. Relatively pure limestones and dolomites of the Mill Creek test area can be differentiated in nighttime infrared images, and facies changes between them can be detected along and across strike. The predominance on the earth's surface of sedimentary rocks, of which limestone and dolomite are major members, indicates the importance of this discrimination.
Curran, Paul J.
Remotely sensed data are being used to estimate foliar chemical content. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content.
Isaacson, Sivan; Blumberg, Dan G.; Ginat, Hanan; Shalmon, Benny
Vegetation in hyper arid zones is very sparse as is. Monitoring vegetation changes in hyper arid zones is important because any reduction in the vegetation cover in these areas can lead to a considerable reduction in the carrying capacity of the ecological system. This study focuses on the impact of climate fluctuations on the acacia population in the southern Arava valley, Israel. The period of this survey includes a sequence of dry years with no flashfloods in most of the plots that ended in two years with vast floods. Arid zone acacia trees play a significant role in the desert ecosystem by moderating the extreme environmental conditions including radiation, temperature, humidity and precipitation. The trees also provide nutrients for the desert dwellers. Therefore, acacia trees in arid zones are considered to be `keystone species', because they have major influence over both plants and animal species, i.e., biodiversity. Long term monitoring of the acacia tree population in this area can provide insights into long term impacts of climate fluctuations on ecosystems in arid zones. Since 2000, a continuous yearly based survey on the three species of acacia population in seven different plots is conducted in the southern Arava (established by Shalmon, ecologist of the Israel nature and parks authority). The seven plots representing different ecosystems and hydrological regimes. A yearly based population monitoring enabled us to determine the mortality and recruitment rate of the acacia populations as well as growing rates of individual trees. This survey provides a unique database of the acacia population dynamics during a sequence of dry years that ended in a vast flood event during the winter of 2010. A lack of quantitative, nondestructive methods to estimate and monitor stress status of the acacia trees, led us to integrate remote sensing tools (ground and air-based) along with conventional field measurements in order to develop a long term monitoring of acacia
Wegener, Steve; Hipskind, R. Stephen (Technical Monitor)
The science and application of remote sensing is flourishing in the digital age. Geographical information systems can provide a broad range of information tailored to the specific needs of disaster managers. Recent advances in airborne platforms, sensors and information technologies have come together provide the ability to put geo-registered, multispectral imagery on the web in near real-time. Highlights of a demonstration of NASA's First Response Experiment (FiRE) will be presented.
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.
Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.
Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.
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
Rose, William I.
A second international workshop on the remote sensing of volcanic clouds was recently held to improve and expand the use of satellite-based remote sensing data for hazard mitigation and other research purposes, such as volcano-atmosphere interactions and chemical and meteorological effects on the troposphere and stratosphere. Forty-six researchers attended, representing 11 countries, 10 universities, and several government meteorological and volcanological organizations. Also represented were the Volcanic Ash Aviation Centers in Washington, D.C.; Anchorage; Montreal; Darwin; London; and Tokyo, which monitor volcanic ash plumes and predict their displacement within their areas of responsibility The nine VAACs were established by the International Civil Aviation Organization (ICAO) to address various aviation concerns related to volcanic ash.
Rose, William I.
An international workshop on the Remote Sensing of Volcanic Clouds was held July 29-August 3, 2001, at Michigan Technological University The workshop's goal was to improve and expand the use of satellite-based remote sensing data for hazard mitigation and other research purposes, such as volcano-atmosphere interactions and chemical and meteorological effects on the troposphere and stratosphere. Forty-six researchers attended, representing 11 countries, 9 universities, and several government meteorological and volcanological organizations, as well as the Volcanic Ash Aviation Centers in Washington, D.C., Anchorage, Montreal, Darwin, London, and Toulouse. (The Volcanic Ash Aviation Centers monitor volcanic ash plumes within their assigned airspace. There are 9 in all and they were created at the request of the International Civil Aviation Organization (ICAO) and other aviation concerns.)
Hirschfeld, T.; Haugen, G.; Milanovich, F. P.
The sensing and analytical abilities of the laser-fluorescence spectrometer was extended beyond the physical confines of the laboratory by means of communications-grade optical fibers. These fiber probes are extremely rugged, compared with sensitive laboratory equipment, and also extremely inexpensive. Sensitive chemical analyses may be performed in hostile environments without risking damage to the laser and the spectrometer. Special-purpose optrodes that are sensitive to selected chemicals were produced. With multiplexing, a number of fibers whose terminals are at widely scattered locations, gathering information in one central instrument without the expense and delay involved in manual sample gathering are scanned. A remote analyzer for monitoring rare earth ion migration in a nuclear-waste repository, an environment too hostile for any previous remote sensing device is being developed. Optrodes sensitive to a wide variety of non-chemical stimuli are being developed.
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.
Hlavka, Christine A.; Sheffner, Edwin J.
The USDA, the California Department of Water Resources (CDWR), the Remote Sensing Research Program of the University of California (UCB) and NASA have completed a 4-yr cooperative project on the use of remote sensing in monitoring California agriculture. This report is a summary of the project and the final report of NASA's contribution to it. The cooperators developed procedures that combined the use of LANDSAT Multispectral Scanner imagery and digital data with good ground survey data for area estimation and mapping of the major crops in California. An inventory of the Central Valley was conducted as an operational test of the procedures. The satellite and survey data were acquired by USDA and UCB and processed by CDWR and NASA. The inventory was completed on schedule, thus demonstrating the plausibility of the approach, although further development of the data processing system is necessary before it can be used efficiently in an operational environment.
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.
Diaz, J. A.; Pieri, D. C.; Bland, G.; Fladeland, M. M.
The development of small unmanned aerial systems (sUAS) with a variety of sensor packages, enables in situ and proximal remote sensing measurements of volcanic plumes. Using Costa Rican volcanoes as a Natural Laboratory, the University of Costa Rica as host institution, in collaboration with four NASA centers, have started an initiative to develop low-cost, field-deployable airborne platforms to perform volcanic gas & ash plume research, and in-situ volcanic monitoring in general, in conjunction with orbital assets and state-of-the-art models of plume transport and composition. Several gas sensors have been deployed into the active plume of Turrialba Volcano including a miniature mass spectrometer, and an electrochemical SO2 sensor system with temperature, pressure, relative humidity, and GPS sensors. Several different airborne platforms such as manned research aircraft, unmanned aerial vehicles, tethered balloons, as well as man-portable in-situ ground truth systems are being used for this research. Remote sensing data is also collected from the ASTER and OMI spaceborne instruments and compared with in situ data. The CARTA-UAV 2013 Mission deployment and follow up measurements successfully demonstrated a path to study and visualize gaseous volcanic emissions using mass spectrometer and gas sensor based instrumentation in harsh environment conditions to correlate in situ ground/airborne data with remote sensing satellite data for calibration and validation purposes. The deployment of such technology improves on our current capabilities to detect, analyze, monitor, model, and predict hazards presented to aircraft by volcanogenic ash clouds from active and impending volcanic eruptions.
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
Lin, Yun-Bin; Lin, Yu-Pin; Deng, Dong-Po; Chen, Kuan-Wei
In Taiwan, earthquakes have long been recognized as a major cause of landslides that are wide spread by floods brought by typhoons followed. Distinguishing between landslide spatial patterns in different disturbance regimes is fundamental for disaster monitoring, management, and land-cover restoration. To circumscribe landslides, this study adopts the normalized difference vegetation index (NDVI), which can be determined by simply applying mathematical operations of near-infrared and visible-red spectral data immediately after remotely sensed data is acquired. In real-time disaster monitoring, the NDVI is more effective than using land-cover classifications generated from remotely sensed data as land-cover classification tasks are extremely time consuming. Directional two-dimensional (2D) wavelet analysis has an advantage over traditional spectrum analysis in that it determines localized variations along a specific direction when identifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series of solutions developed based on Open Geospatial Consortium specifications that can be applied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2D wavelet analysis of real-time NDVI images to effectively identify landslide patterns and share resulting patterns via open geospatial techniques. As a case study, this study analyzed NDVI images derived from SPOT HRV images before and after the ChiChi earthquake (7.3 on the Richter scale) that hit the Chenyulan basin in Taiwan, as well as images after two large typhoons (xangsane and Toraji) to delineate the spatial patterns of landslides caused by major disturbances. Disturbed spatial patterns of landslides that followed these events were successfully delineated using 2D wavelet analysis, and results of pattern recognitions
The increasing device implantations to treat cardiovascular diseases such as arrhytmias and heart failures, aging of the population, and the growing number of patients with access to new therapies as well as the wider access to health systems are the reasons why the number of new implantations carried out each year is rising. Hence, we should have an equipment that can control these patients at a distance, making the follow-up closer. The answer to this enormous challenge is the remote monitoring of these devices. Biotronik is a pioneer in this task and since 2001 it has been comercializing pacemakers and portable wireless monitors (CardioMessenger). Currently, there are more than 100,000 installed systems. Thanks to the continuous and completely automatized follow-up, as well as the wireless net, the system integrity can be confirmed, and then proceed to adjust the therapies in an optimized manner according to each patient's needs; also take action to prevent the development of some arrhytmias, or even the evolution of a heart failure. Likewise, the system can improve the clynical efficiency of the treatment and help to economize to the Ministry of Healthcare.
With increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.
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.
Application of active and passive microwave remote sensing to the study of ocean pollution is discussed. Previous research efforts, both in the field and in the laboratory were surveyed to derive guidance for the design of a laboratory program of research. The essential issues include: choice of radar or radiometry as the observational technique; choice of laboratory or field as the research site; choice of operating frequency; tank sizes and material; techniques for wave generation and appropriate wavelength spectrum; methods for controlling and disposing of pollutants used in the research; and pollutants other than oil which could or should be studied.
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.
Topics covered include: Passive Remote Sensing Methods, Imaging Spectroscopy Approach, Remote Measurement via Spectral Fitting, Imaging Spectroscopy Mapping Wetland Dominants 2010 LA (AVIRIS), Deepwater Horizon Response I, Deepwater Horizon Response II, AVIRIS Ocean Color Studies.
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
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
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
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
illustrated in relation toIother oceanographic parameters. > reevavy programs which have supported the Remote Sensing Branch’s developments in water ...optics are described. The Navy relevance of water optics to these programs is indicated.’ "I 1 ’ ( ;j "IJl: ,t n ! /H i.i OCEAN OPTICAL REMOTE SENSING...Development Activity (NORDA) Remote Sensing Branch (Code 321) has been conducting investigative programs in water optics since 1977. The major thrust of
Guiness, E. A.; Sultan, M.; Arvidson, R. E.
A brief assessment of remote sensing applied to geological studies is given. An analysis of thematic mapping data on oak-hickory forests in southern Missouri is discussed. It was found that there is a control on the infrared reflectance (bands 4, 5, and 7 of the Thematic Mapper (TM) of the forests that correlates with rock and soil types. During the growing season, soils with low water retention capacities correlate with high infrared (band 4, lesser with band 5 and 7) signatures. A metamorphic core complex called the Meatiq located in the Eastern Desert of Egypt was studied. The dome provides exposure of most of the rock units of the Arabian-Nubian Precambrian Shield. The dome bears many resemblances to Cordilleran metamorphic complexes. LANDSAT TM data was used to improve on reconnaissance maps of the dome. The remote sensing data was interpreted in the context of field observations, petrographic, and chemical analysis of rock units in the dome, in order to map similar domes in the Eastern Desert from TM data. Mapping projects such as the one just described will help constrain the geologic evolution of the Arabian-Nubian Shield. Two particular hypotheses that researchers hope to test for the development of the shield are: (1) closure of a proto-Red Sea; and (2) accretion of a primitive island arc system onto the shield.
The surface emissivity and reflectivity of soil are strong functions of its moisture content. Changes in emissivity, observed by passive microwave techniques (radiometry), and changes in reflectivity, observed by active microwave techniques (radar), can provide information on the moisture content of the 0 to 5 cm surface layer. In addition, the thermal inertia of the surface layer, which can be remotely sensed by observing the diurnal range of surface temperature, is an indicator of soil moisture content. The thermal infrared approach to remote sensing of soil moisture has little utility in the presence of cloud cover, but provides soil moisture data at high spatial resolutions and thermal data which are a potentially useful indicator of crop status. Microwave techniques can penetrate cloud covers. The passive technique has been demonstrated by both aircraft and spacecraft instruments, but spatial resolution is limited by the size of the antenna which can be flown. Active microwave systems offer the possibility of better spatial resolution, but have yet to be demonstrated from aircraft or spacecraft platforms.
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.
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.
Carmichael, J. J.; Eldridge, R. G.; Frey, E. J.; Friedman, E. J.; Ghovanlou, A. H.
The capabilities of specific NASA remote sensing systems to provide appropriate measurements of stratospheric parameters for potential user needs were assessed. This was used to evaluate the capabilities of the remote sensing systems to perform global monitoring of the stratosphere. The following conclusions were reached: (1) The performance of current remote stratospheric sensors, in some cases, compares quite well with identified measurement requirements. Their ability to measure other species has not been demonstrated. (2) None of the current, in-situ methods have the capability to satisfy the requirements for global monitoring and the temporal constraints derived from the users needs portion of the study. (3) Existing, non-remote techniques will continue to play an important role in stratospheric investigations for both corroboration of remotely collected data and in the evolutionary development of future remote sensors.
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...
Raupp, M. A.; Pereiradacunha, R.; Novaes, R. A.
Most of the remote sensing activities in Brazil have been conducted by the Institute for Space Research (INPE). This report describes briefly INPE's activities in remote sensing in the last years. INPE has been engaged in research (e.g., radiance studies), development (e.g., CCD-scanners, image processing devices) and applications (e.g., crop survey, land use, mineral resources, etc.) of remote sensing. INPE is also responsible for the operation (data reception and processing) of the LANDSATs and meteorological satellites. Data acquisition activities include the development of CCD-Camera to be deployed on board the space shuttle and the construction of a remote sensing satellite.
Catoe, C. E.; Mclean, J. T.
Study of the possibility of developing an effective remote sensing system for oil pollution monitoring which would be capable of detecting oil films on water, mapping the areal extent of oil slicks, measuring slick thickness, and identifying the oil types. In the spectral regions considered (ultraviolet, visible, infrared, microwave, and radar), the signatures were sufficiently unique when compared to the background so that it was possible to detect and map oil slicks. Both microwave and radar techniques are capable of operating in adverse weather. Fluorescence techniques show promise in identifying oil types. A multispectral system will be required to detect oil, map its distribution, estimate film thickness, and characterize the oil pollutant.
Aubé, Martin; Kocifaj, Miroslav
This special issue contains papers related to the measurement, prediction, consequences and control of light pollution. The main underlying question of the special issue is: How remote sensing and field experiments can help us to understand and monitor light pollution? Through the papers published herein, you will find answers related to the use of remote sensing techniques as diverse as hyperspectral measurements, broadband photometry, along with DSLR color cameras image analysis.
Miller, W. F.; Carter, B. D.; Solomon, J. L.; Williams, S. G.; Powers, J. S.; Clark, J. R. (Principal Investigator)
Progress is reported in the following areas: remote sensing applications to land use planning Lowndes County, applications of LANDSAT data to strip mine inventory and reclamation, white tailed deer habitat evaluation using LANDSAT data, remote sensing data analysis support system, and discrimination of unique forest habitats in potential lignite areas of Mississippi. Other projects discussed include LANDSAT change discrimination in gravel operations, environmental impact modeling for highway corridors, and discrimination of fresh water wetlands for inventory and monitoring.
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.
Romero Sanchez, Martin Enrique
In this thesis, a methodological framework for the assessment and monitoring of forest degradation based on remote sensing techniques and field data, as part of the REDD+ programme, is presented. The framework intends to support the implementation of a national Monitoring, Verification and Report (MRV) system in developing countries. The framework proposed an operational definition of forest degradation and a set of indicators, namely Canopy Cover (CC), Aboveground Biomass (AGB) and Net Primary Productivity (NPP), derived from remote sensing data. The applicability of the framework is tested in a sub-deciduous tropical forest in the Southeast of Mexico. The results from the application of the methodological framework showed that the higher rates of forest degradation, 1596-2865 ha˙year-1, occur in areas with high population density. Estimations of aboveground biomass in these degraded areas span from 1 to 24 Mg˙ha-1, with a rate of carbon fixation ranging from 130 to 246 gC˙m2˙year. The results also showed that 43 % of the forests of the study area remain with no evident signs of degradation, as detected by the indicators selected, during the period evaluated. The integration of the different elements conforming the methodological framework for the assessment and monitoring of forest degradation enabled the identification of areas that maintain a stable condition and areas that change over the period evaluated. The methodology outlined in this thesis also allows for the identification of the temporal and spatial distributions of forest degradation based on the indicators selected, and it is expected to serve as the basis for operations of the REDD+ programme with the appropriate adaptations to the area in turn.
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…
The concepts of radar remote sensing and microwave radiometry are discussed and their utility in earth resource sensing is examined. The direct relationship between the character of the remotely sensed data and the level of decision making for which the data are appropriate is considered. Applications of active and a passive microwave sensing covered include hydrology, land use, mapping, vegetation classification, environmental monitoring, coastal features and processes, geology, and ice and snow. Approved and proposed microwave sensors are described and the use of space shuttle as a development platform is evaluated.
Nghiem, S. V.; Yueh, S. H.; Kwok, R.
Relationships among polarimetric backscattering coefficients are derived from the viewpoint of symmetry groups. For both reciprocal and non-reciprocal media, symmetry encountered in remote sensing due to reflection, rotation, azimuthal, and centrical symmetry groups is considered. The derived properties are general and valid to all scattering mechanisms, including volume and surface scatterings and their interactions, in a given symmetrical configuration. The scattering coefficients calculated from theoretical models for layer random media and rough surfaces are shown to obey the symmetry relations. Use of symmetry properties in remote sensing of structural and environmental responses of scattering media is also discussed. Orientations of spheroidal scatterers described by spherical, uniform, planophile, plagiothile, erectophile, and extremophile distributions are considered to derive their polarimetric backscattering characteristics. These distributions can be identified from the observed scattering coefficients by comparison with theoretical symmetry calculations. A new parameter is then defined to study scattering structures in geophysical media. Observations from polarimetric data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar over forests, sea ice, and sea surface are presented. Experimental evidences of the symmetry relationships are shown and their use in polarimetric remote sensing is illustrated. For forests, the coniferous forest in Mt. Shasta area (California) and mixed forest near Presque Isle (Maine) exhibit characteristics of the centrical symmetry at C-band. For sea ice in the Beaufort Sea, multi-year sea ice has a cross-polarized ratio e close to e(sub 0), calculated from symmetry, due to the randomness in the scattering structure. First-year sea ice has e much smaller than e(sub 0) due to the preferential alignment of the columnar structure of the ice. From polarimetric data of a sea surface in the Bering Sea, it is
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
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.
Akay, Abdullah Emin; Inac, Selcuk; Yildirim, Ismet Ceyhun
Striped hyenas (Hyaena hyaena L.) are one of the large carnivores whose numbers have rapidly decreased in Turkey. To monitor and assess the distribution of striped hyenas in Mediterranean region of Turkey, geographical information systems (GIS) and remote sensing technologies were implemented. For this purpose, the GIS database was generated and digital maps were produced in ArcGIS 9.2 program, considering some of the main factors including signs of striped hyenas, elevation, slope, land use types, feeding sources, and road network. The land use types in the distribution area of striped hyenas were classified by using ERDAS Imagine program. The results from the land use classification indicated that the signs of striped hyenas mostly distributed over the agricultural areas especially with olive groves, and followed by maquis. It was found that there was a spatial relationship between the signs of striped hyenas and feeding sources such as organic waste centers and a chicken farm in the region.
Thorne, J. F.
State agencies need rapid, synoptic and inexpensive methods for lake assessment to comply with the 1972 Amendments to the Federal Water Pollution Control Act. Low altitude aerial photography may be useful in providing information on algal type and quantity. Photography must be calibrated properly to remove sources of error including airlight, surface reflectance and scene-to-scene illumination differences. A 550-nm narrow wavelength band black and white photographic exposure provided a better correlation to algal biomass than either red or infrared photographic exposure. Of all the biomass parameters tested, depth-integrated chlorophyll a concentration correlated best to remote sensing data. Laboratory-measured reflectance of selected algae indicate that different taxonomic classes of algae may be discriminated on the basis of their reflectance spectra.
Raney, W. P.
In the Earth remote sensing area, NASA's three functions are to understand the basic mechanics and behavior of the Earth, evaluate what resources are available (in the way of minerals, and hydrocarbons on a general scale), and to arrange a scheme for managing our national assets. The capabilities offered by LANDSAT D and technology improvements needed are discussed. The French SPOT system, its orbits, possibilities for stereo imagery, and levels of preprocessing and processing with several degrees of radiometric and geometric corrections are examined. Progress in the AgRISTARS project is mentioned as well as future R & D programs in the use of fluorescence, microwave measurements, and synthetic aperture radar. Other areas of endeaver include studying man environment interactions and Earth radiation budgets, and the establishment of data systems programs.
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.
Arvidson, Raymond E.; Petroy, S. B.; Plaut, J. J.; Shepard, Michael K.; Evans, D.; Farr, T.; Greeley, Ronald; Gaddis, L.; Lancaster, N.
The Mojave Remote Sensing Field Experiment (MFE), conducted in June 1988, involved acquisition of Thermal Infrared Multispectral Scanner (TIMS); C, L, and P-band polarimetric radar (AIRSAR) data; and simultaneous field observations at the Pisgah and Cima volcanic fields, and Lavic and Silver Lake Playas, Mojave Desert, California. A LANDSAT Thematic Mapper (TM) scene is also included in the MFE archive. TM-based reflectance and TIMS-based emissivity surface spectra were extracted for selected surfaces. Radiative transfer procedures were used to model the atmosphere and surface simultaneously, with the constraint that the spectra must be consistent with field-based spectral observations. AIRSAR data were calibrated to backscatter cross sections using corner reflectors deployed at target sites. Analyses of MFE data focus on extraction of reflectance, emissivity, and cross section for lava flows of various ages and degradation states. Results have relevance for the evolution of volcanic plains on Venus and Mars.
Hardisky, M. A.; Klemas, V.; Gross, M. F.
Various aircraft and satellite sensors for detecting and mapping wetlands properties are examined. The uses of color IR photography to map coastal vegetation, and of Landsat MSS and TM and SPOT data to quantify biomass and productivity for large wetland areas are discussed. For spectral estimation of biomass and productivity, the relation between radiance and biomass needs to be studied; the quantity and orientation of dead biomass and the amount of soil reflectance in comparison with vegetation reflectance in a given target area affect the spectral estimation of biomass. The radiometric evaluation of brackish wetland, and remote sensing in mangroves are described. The collection of images in narrow, contiguous spectral band using imaging spectrometry is considered.
Low altitude black and white aerial photography is the prinicipal remote sensing tool for geologic investigations in West Virginia, although side looking radar and color infrared photography are also used. The first land use/cover map for the state was produced in color infrared and is being digitized. Linear features in Cabell and Wayne Counties, as revealed by LANDSAT, were evaluated to test the possible correlations with rock fractures and gas production from shales. A LANDSAT linear features map (1:250,000) was prepared for the entire state, also. Presently investigations are being made to understand karst and to predict areas that should not be used for development. Aerial photography and field mapping is being conducted to detect the location and causes of landslides.
The current state of understanding of the biosphere is reviewed, the major scientific issues to be addressed are discussed, and techniques, existing and in need of development, for the science are evaluated. It is primarily concerned with developing the scientific capabilities of remote sensing for advancing the subject. The global nature of the scientific objectives requires the use of space-based techniques. The capability to look at the Earth as a whole was developed only recently. The space program has provided the technology to study the entire Earth from artificial satellites, and thus is a primary force in approaches to planetary biology. Space technology has also permitted comparative studies of planetary atmospheres and surfaces. These studies coupled with the growing awareness of the effects that life has on the entire Earth, are opening new lines of inquiry in science.
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
Data from the first earth resources technology satellite (ERTS) as well as from NASA and other aircraft, contain much of the information indicative of the distribution of groundwater and the extent of its utilization. Thermal infrared imagery from aircraft is particularly valuable in studying groundwater discharge to the sea and other surface water bodies. Color infrared photography from aircraft and space is also used to locate areas of potential groundwater development. Anomalies in vegetation, soils, moisture, and their pattern of distribution may be indicative of underlying groundwater conditions. Remote sensing may be used directly or indirectly to identify stream reaches for test holes or production wells. Similarly, location of submarine springs increase effectiveness of groundwater exploration in the coastal zone.
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.
Diverse applications of LANDSAT data, problem solutions, and operational goals are described by remote sensing users from 14 western states. The proposed FY82 federal budget reductions for technology transfer activities and the planned transition of the operational remote sensing system to NOAA's supervision are also considered.
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...
Post, Brian Nelson; Smith, Jody Lynn; Geib, Peter L.; Nandy, Prabal; Wang, Nancy Nairong
This remote sensing science and exploitation work focused on exploitation algorithms and methods targeted at the analyst. SMART is a 'plug-in' to commercial remote sensing