Science.gov

Sample records for remote sensing monitoring

  1. Remotely sensed small reservoir monitoring

    NASA Astrophysics Data System (ADS)

    Eilander, Dirk; Annor, Frank; Iannini, Lorenzo; van de Giesen, Nick

    2013-04-01

    A new 'growing' maximum likelihood classification algorithm for small reservoir delineation has been developed and is tested with Radarsat-2 data for reservoirs in the semi-arid Upper East Region, Ghana. The delineation algorithm is able to find the land-water boundary from SAR imagery for different weather and environmental conditions. As such, the algorithm allows for remote sensed operational monitoring of small reservoirs. Multipurpose small reservoirs (1-100 ha) are important for many livelihoods in rural semi-arid West Africa. In order to manage and plan these reservoirs and to assess their hydrological impact at a river basin scale, it is important to monitor their water storage fluctuation. Several studies on remotely sensed reservoir mapping have recently been published, but no single method yields good results for all weather and environmental conditions. Detection of small reservoirs from optical satellite imagery using supervised maximum likelihood classification is a well proved method. The application of this method for the monitoring of small reservoirs is however limited because of its dependence on cloud-free day-acquisitions. Delineation from SAR images is promising, but because of difficulties with wind induced Bragg-scattering and low contrast between the water surface and the dried-out surroundings at the end of the dry season, only quasi manual methods have been applied successfully. A smart combination of optical satellite based detection combined with a delineation method for SAR imagery is proposed. From the optical satellite based small reservoir detection the reservoir window is determined in which the 'growing' maximum likelihood classification on SAR images is performed. A water-class seed and land-class seed are implemented and grown dependent on the likelihood of a pixel to belong to one class. The likelihood is calculated based on the probability distributions of the growing land and water populations. Combinations of single

  2. OPTICAL REMOTE SENSING FOR AIR QUALITY MONITORING

    EPA Science Inventory

    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...

  3. Satellite Remote Sensing for Monitoring and Assessment

    EPA Science Inventory

    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...

  4. Monitoring water quality by remote sensing

    NASA Technical Reports Server (NTRS)

    Brown, R. L. (Principal Investigator)

    1977-01-01

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

  5. Land border monitoring with remote sensing technologies

    NASA Astrophysics Data System (ADS)

    Malinowski, Radoslaw

    2010-09-01

    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.

  6. REMOTE SENSING FOR ENVIRONMENTAL COMPLIANCE MONITORING

    EPA Science Inventory

    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.
    1. Sp...

  7. Remote sensing monitoring of the global ozonosphere

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  8. Irrigated lands: Monitoring by remote sensing

    NASA Technical Reports Server (NTRS)

    Epiphanio, J. C. N.; Vitorelli, I.

    1983-01-01

    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.

  9. Remote Sensing Techniques for Monitoring Aquatic Vegetation

    NASA Astrophysics Data System (ADS)

    Blanco, Alfonso

    Hydrilla is an important submerged aquatic vegetation because it has a large capacity to absorb pollutants and it is an indicator of the eutrophic status of a waterbody. Monitoring and restoration of submerged aquatic vegetation is key for the preservation and restoration of the Chesapeake Bay. Remote sensing techniques have been used for assessing wetlands and non-invasive aquatic species, but there is limited studies of hydrilla monitoring combined with space-borne, airborne and in-situ remote sensing measurements for detecting and mapping hydrilla infestation. The first objective of this research was to establish a database of hydrilla spectral signatures from an experimental tank and from a field setting using a handheld spectrometer. The spectral signatures collected will be used to identify the optimal spectral and spatial characteristics that are required to identify and classify the distribution of hydrilla canopies in water bodies. The second objective is to process and analyze two hyperspectral images from a space-borne (Hyperion) and airborne (AISA) sensors with ENVI for detecting and mapping the infestation of hydrilla vertillicata in a coastal estuary in Chesapeake Bay. The third objective was to validate the satellite and airborne hyperspectral images with the spectral signatures collected with the in-situ field measurements. In addition, the Hyperion and AISA imaging results were compared with ground surveys and aerial photos collected by the Maryland Department of Natural Resources and the Virginia Institute of Marine Sciences for verifying the extent and the location of the hydrilla canopies. The hyperspectral analysis of both sensors provided for a dual results, one is the identification and classification of hydrilla from hyperspectral imaging sensors and secondly the identification of algae blooms in very productive waters. A hydrilla spectral signature database was established and housed in GMU's EastFIRE Lab of Environmental Science and

  10. Development of sea ice monitoring with aerial remote sensing technology

    NASA Astrophysics Data System (ADS)

    Jiang, Xuhui; Han, Lei; Dong, Liang; Cui, Lulu; Bie, Jun; Fan, Xuewei

    2014-11-01

    In the north China Sea district, sea ice disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the sea ice situation becomes too critical. The monitoring of sea ice is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor sea ice mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the sea ice in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of sea ice, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get sea ice charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor sea ice. Aerial remote sensing is an important means in sea ice monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the sea ice monitoring using aerial remote sensing technology are discussed.

  11. Groundwater inventory and monitoring technical guide: Remote sensing of groundwater

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  12. Monitoring Rangeland Health by Remote Sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  13. Multiple Scale Remote Sensing for Monitoring Rangelands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  14. [Monitoring gas concentration from carbon emissions by remote sensing].

    PubMed

    Wang, Li-Wen; Wei, Ya-Xing

    2012-06-01

    Global climate warming has become the focus question of international global climate change research, and is an important factor influencing world economy, political situation, and ecological environment. Produced carbon emission gases such as CO2, CH4, N2O, etc. caused by human activity are the main reason for global warming. In order to forecast future climate change and construct accurate carbon cycle model, monitoring accuracy of gas concentration from carbon emission must be improved. In the present paper, the newest progress in the international research results about monitoring gas concentration from carbon emissions by remote sensing was considered, monitoring method for carbon emissions was introduced, and remotely sensed monitoring technology about gas concentration from carbon emissions (including thermal infrared, sun spectrum, active remote sensing monitoring technology) was stated. In detail, several present and future satellite sensors were introduced (including TOVS, AIRS, IASI, SCIAMACHY, GOSAT, OCO, A-SCOPE and ASCENDS), and monitoring results achieved by these sensors were analyzed. PMID:22870656

  15. FLARE EFFICIENCY MONITORING BY REMOTE INFRARED SENSING: A FEASIBILITY DEMONSTRATION

    EPA Science Inventory

    The report gives results of an evaluation, involving field tests, of passive infrared methods for use in remotely monitoring the efficiency of industrial flares. The tests utilized a general infrared measurement device, the EPA ROSE (Remote Optical Sensing of Emissions), a Fourie...

  16. Energy and remote sensing. [satellite exploration, monitoring, siting

    NASA Technical Reports Server (NTRS)

    Summers, R. A.; Smith, W. L.; Short, N. M.

    1977-01-01

    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.

  17. Some applications of remote sensing in atmospheric monitoring programs

    NASA Technical Reports Server (NTRS)

    Heller, A. N.; Bryson, J. C.; Vasuki, N. C.

    1972-01-01

    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.

  18. Monitoring asphalt pavement damages using remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Mettas, Christodoulos; Themistocleous, Kyriacos; Neocleous, Kyriacos; Christofe, Andreas; Pilakoutas, Kypros; Hadjimitsis, Diofantos

    2015-06-01

    One of the main issues in the maintenance plans of road agencies or governmental organizations is the early detection of damaged asphalt pavements. The development of a smart and non-destructive systematic technique for monitoring damaged asphalt pavements is considered a main priority to fill this gap. During the 1970's, remote sensing was used to map road surface distress, while during the last decade, remote sensing became more advanced, thereby assisting in the evolution of the identification and mapping of roads. Various techniques were used in order to explore condition, age, weaknesses and imperfections of asphalted pavements. These methods were fairly successful in the classification of asphalted surfaces and in the detection of some of their characteristics. This paper explores the state of the art of using remote sensing techniques for monitoring damaged pavements and some typical spectral profiles of various asphalt pavements in Cyprus area acquired using the SVC1024 field spectroradiometer.

  19. Remote sensing hazard monitoring and assessment in Yushu earthquake disaster

    NASA Astrophysics Data System (ADS)

    Wen, Qi; Xu, Feng; Chen, Shirong

    2011-12-01

    Yushu Earthquake of magnitude 7.1 Richter in 2010 has brought a huge loss of personal lives and properties to China. National Disaster Reduction Center of China implemented the disaster assessment by using remote sensing images and field investigation. Preliminary judgment of disaster scope and damage extent was acquired by change detection. And the building region of hard-hit area Jiegu town was partitioned into 3-level grids in airborne remote sensing images by street, type of use, structure, and about 685 girds were numbered. Hazard assessment expert group were sent to implement field investigation according to each grid. The housing damage scope and extent of loss were defined again integrated field investigation data and local government reported information. Though remote sensing technology has played an important role in huge disaster monitoring and assessment, the automatic capability of disaster information extraction flow, three-dimensional disaster monitoring mode and bidirectional feedback mechanism of products and services should still be further improved.

  20. Environmental monitoring: civilian applications of remote sensing

    SciTech Connect

    Bolton, W.; Lapp, M.; Vitko, J. Jr.; Phipps, G.

    1996-11-01

    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.

  1. How Can Remote Sensing Be Used for Water Quality Monitoring?

    EPA Science Inventory

    “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...

  2. PLANT INCORPORATED PROTECTANT CROP MONITORING USING REMOTE SENSING

    EPA Science Inventory

    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...

  3. A NEW APPROACH TO PIP CROP MONITORING USING REMOTE SENSING

    EPA Science Inventory

    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...

  4. Natural Resource Monitoring of Rheum tanguticum by Multilevel Remote Sensing

    PubMed Central

    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

    2014-01-01

    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

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

    NASA Astrophysics Data System (ADS)

    Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

    2014-05-01

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

  6. Optimized Radar Remote Sensing for Levee Health Monitoring

    NASA Technical Reports Server (NTRS)

    Jones, Cathleen E.

    2013-01-01

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

  7. Drought monitoring using remote sensing of evapotranspiration

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. Water quality monitoring using remote sensing technique

    NASA Astrophysics Data System (ADS)

    Adsavakulchai, Suwannee; Panichayapichet, Paweena

    2003-03-01

    There has been a rapid growth of shrimp farm around Kung Krabaen Bay in the past decade. This has caused enormous rise in generation of domestic and industrial wastes. Most of these wastes are disposed in the Kung Krabaen Bay. There is a serious need to retain this glory by better water quality management of this river. Conventional methods of monitoring of water quality have limitations in collecting information about water quality parameters for a large region in detailed manner due to high cost and time. Satellite based technologies have offered an alternate approach for many environmental monitoring needs. In this study, the high-resolution satellite data (LANDSAT TM) was utilized to develop mathematical models for monitoring of chlorophyll-a. Comparison between empirical relationship of spectral reflectance with chl-a and band ratio between the near infrared (NIR) and red was suggested to detect chlorophyll in water. This concept has been successfully employed for marine zones and big lakes but not for narrow rivers due to constraints of spatial resolution of satellite data. This information will be very useful in locating point and non-point sources of pollution and will help in designing and implementing controlling structures.

  9. Remote sensing: Snow monitoring tool for today and tomorrow

    NASA Technical Reports Server (NTRS)

    Rango, A.

    1977-01-01

    Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

  10. Remote Sensing Techniques as a Tool for Environmental Monitoring

    NASA Astrophysics Data System (ADS)

    Faisal, K.; AlAhmad, M.; Shaker, A.

    2012-07-01

    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

  11. Tracking and Monitoring Oil Slicks Using remote Sensing

    NASA Astrophysics Data System (ADS)

    Klemas, V. V.

    2011-12-01

    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)

  12. Volcano monitoring by short wavelength infrared satellite remote sensing

    NASA Technical Reports Server (NTRS)

    Rothery, D. A.; Francis, P. W.; Wood, C. A.

    1988-01-01

    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.

  13. A remote sensing system for northern ecosystem monitoring

    SciTech Connect

    Li, Zhanqing; Cihlar, J.; Chen, Jing

    1997-11-01

    A suite of remote sensing techniques intended for northern terrestrial environment monitoring are described. Algorithms designed to derive land cover type, leaf area index, canopy absorbed photosynthetically active radiation, net primary productivity, active fires, and annual total burned area from remote sensing are also outlined. Prototype products of these parameters across Canada from single day and 10-day composite satellite measurements, some of which have been validated, are presented and discussed. The system used for data acquisition and processing includes three major components: data preprocessing, removal of artifacts, and inversion of surface parameters. The preprocessing includes satellite data calibration, registration, and clear sky compositing. Artifacts introduced by the presence of clouds, atmosphere, and angular dependence are eliminated or alleviated using various correction models. 69 refs., 1 fig.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  15. Monitoring crop biochemical concentrations by high spectral remote sensing

    NASA Astrophysics Data System (ADS)

    Wang, Wen; Yan, Jing; Chen, Yonghua; Niu, Zheng; Wang, Changyao

    1999-12-01

    High spectral remote sensing is a hopeful technology in diagnosing crop nutrition background. With surface spectral measurement and laboratory biochemical analysis, the relationship between crop properties and spectral remote sensing data has been established. Seven chemical components - total chlorophyll, water crude protein, soluble sugar, N, P, K - were analyzed by laboratory chemical analyzing instrument. Foliar spectral property was detected outdoors by surface spectrometer. Chemical concentrations have been related to foliar spectral properties through stepwise multiple regression. The statistical equations between the chemical concentrations and reflectance as well as its several transformations were established. They underscored good estimation performance for chlorophyll, water crude protein, N and K with high squared multiple correlation coefficients (R2) values and high believable level. Especially R2 value of the equation between crude protein concentration and the first derivative of reflectance is 0.9564, which is the best result in the study of the fresh leave biochemistry up to now. On the basis of field experiment, an airborne remote sensing for crop nutrition monitoring was conducted in Shunyi County, Beijing, PR China. The sensor, made by Chinese Academy of Sciences, is in visible and near IR band. By image processing, the crop biochemistry map is obtained.

  16. Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

    NASA Astrophysics Data System (ADS)

    Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

    2016-04-01

    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

  17. Integrating remote sensing data from multiple optical sensors for ecological and crop condition monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  18. Online change detection: Monitoring land cover from remotely sensed data

    SciTech Connect

    Fang, Yi; Ganguly, Auroop R; Singh, Nagendra; Vijayaraj, Veeraraghavan; Feierabend, Robert Neal; Potere, David T

    2006-01-01

    We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.

  19. Monitoring Mediterranean marine pollution using remote sensing and hydrodynamic modelling

    NASA Astrophysics Data System (ADS)

    La Loggia, Goffredo; Capodici, Fulvio; Ciraolo, Giuseppe; Drago, Aldo; Maltese, Antonino

    2011-11-01

    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.

  20. Monitoring desertification around Huolinguole using multitemporal remotely sensed imagery

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

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

  1. Using neural networks in remote sensing monitoring of exogenous processes

    NASA Astrophysics Data System (ADS)

    Sharapov, Ruslan; Varlamov, Alexey

    2015-03-01

    In paper considered the problem of using remote sensing monitoring of the exogenous processes. The satellite observations can used in tasks of detection of newly formed landslides, landslips and karst collapses. Practice shows that the satellite images of the same area, taken at different times, can have significant differences from each other. For this reason, it is necessary to perform the images correction to bring them into the same species, removing impact of changes in weather conditions, etc. In addition, it is needed to detect the clouds in the images. Clouds interfere with the analysis of images. The detection of exogenous processes manifestations can be make after these actions. For image correction and object detection can be used the neural networks. In paper are given the algorithm for image correction and the structure of a neural network.

  2. [Research on hyperspectral remote sensing in monitoring snow contamination concentration].

    PubMed

    Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan

    2011-05-01

    Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well. PMID:21800591

  3. Monitoring Tamarisk Defoliation and Scaling Evapotranspiration Using Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Dennison, P. E.; Hultine, K. R.; Nagler, P. L.; Miura, T.; Glenn, E. P.; Ehleringer, J. R.

    2008-12-01

    Non-native tamarisk (Tamarix spp.) has invaded riparian ecosystems throughout the Western United States. Another non-native species, the saltcedar leaf beetle (Diorhabda elongata), has been released in an attempt to control tamarisk infestations. Most efforts directed towards monitoring tamarisk defoliation by Diorhabda have focused on changes in leaf area or sap flux, but these measurements only give a local view of defoliation impacts. We are assessing the ability of remote sensing data for monitoring tamarisk defoliation and measuring resulting changes in evapotranspiration over space and time. Tamarisk defoliation by Diorhabda has taken place during the past two summers along the Colorado River and its tributaries near Moab, Utah. We are using 15 meter spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and 250 meter spatial resolution Moderate Resolution Imaging Spectrometer (MODIS) data to monitor tamarisk defoliation. An ASTER normalized difference vegetation index (NDVI) time series has revealed large drops in index values associated with loss of leaf area due to defoliation. MODIS data have superior temporal monitoring abilities, but at the sacrifice of much lower spatial resolution. A MODIS enhanced vegetation index time series has revealed that for pixels where the percentage of riparian cover is moderate or high, defoliation is detectable even at 250 meter spatial resolution. We are comparing MODIS vegetation index time series to site measurements of leaf area and sap flux. We are also using an evapotranspiration model to scale potential water savings resulting from the biocontrol of tamarisk.

  4. Remote Sensing to Support Monitoring of Soil Organic Carbon (Invited)

    NASA Astrophysics Data System (ADS)

    McNairn, H.; Pacheco, A.

    2009-12-01

    Soil organic carbon is fundamental to the sustainability of agricultural soils and soils play an important role in the global carbon balance. Estimating soil carbon levels and monitoring changes in these levels over time requires extensive data on climate, soil properties, land cover and land management. Remote sensing technologies are capable of providing some of the data needed in modeling soil organic carbon concentrations and in tracking changes in soil carbon. The characteristics of the vegetation cover influence the amount of organic matter in the soil and cultivation impacts the rate of organic matter decomposition. Consequently land management decisions, which include cropping and tillage practices, play a vital role in determining soil carbon levels. Agriculture and Agri-Food Canada (AAFC) has developed several methods to map land management practices from multispectral and Synthetic Aperture Radar (SAR) satellite sensors. These include identification of crops grown, estimation of crop residue cover left post-harvest and identification of tillage activities. Optical and SAR data are capable of identifying crop types to accuracies consistently above 85%. Knowledge of crop type also provides information needed to establish biomass levels and residue type, both of which influence the amounts and decomposition rates of organic matter. Scientists with AAFC have also extensively validated a method to estimate percent residue cover using spectral unmixing analysis applied to multispectral satellite data. Percentages for corn, soybean and small grain residues can be estimated to accuracies of 83%, 80% and 82%, respectively. Tillage activity influences residue decomposition and AAFC is investigating methods to identify tillage occurrence using advanced polarimetric SAR information. This presentation will provide an overview of methods and results from research ongoing at AAFC. The potential contribution of these remote sensing approaches to support wide area carbon

  5. Lidar Remote Sensing for Industry and Environment Monitoring

    NASA Technical Reports Server (NTRS)

    Singh, Upendra N. (Editor); Itabe, Toshikazu (Editor); Sugimoto, Nobuo (Editor)

    2000-01-01

    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

  6. Angkor site monitoring and evaluation by radar remote sensing

    NASA Astrophysics Data System (ADS)

    Chen, Fulong; Jiang, Aihui; Ishwaran, Natarajan

    2014-11-01

    Angkor, in the northern province of Siem Reap, Cambodia, is one of the most important world heritage sites of Southeast Asia. Seasonal flood and ground sinking are two representative hazards in Angkor site. Synthetic Aperture Radar (SAR) remote sensing has played an important role for the Angkor site monitoring and management. In this study, 46 scenes of TerraSAR data acquired in the span of February, 2011 to December, 2013 were used for the time series analysis and hazard evaluation; that is, two-fold classification for flood area extracting and Multi-Temporal SAR Interferometry (MT-InSAR) for ground subsidence monitoring. For the flood investigation, the original Single Look Complex (SLC) TerraSAR-X data were transferred into amplitude images. Water features in dry and flood seasons were firstly extracted using a proposed mixed-threshold approach based on the backscattering; and then for the correlation analysis between water features and the precipitation in seasonally and annually. Using the MT-InSAR method, the ground subsidence was derived with values ranging from -50 to +12 mm/yr in the observation period of February, 2011 to June, 2013. It is clear that the displacement on the Angkor site was evident, implying the necessity of continuous monitoring.

  7. Remote Sensing.

    ERIC Educational Resources Information Center

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

    1983-01-01

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

  8. Application of Remote Sensing Technologies for Forest Cover Monitoring

    NASA Astrophysics Data System (ADS)

    Agoltsov, Alexander; Sizov, Oleg; Rubtsova, Natalia

    2014-05-01

    Today we don't have full and reliable information about forests in Russia, so it is impossible to make any well-timed decision for forest management. Update of all this information by means of traditional methods (fieldwork) is a time-consuming and in fact impossible task. Also we do not think that using of the reports without objective information for cameral data actualization is an appropriate method in such situation. So our company uses remote sensing data and technologies to resolve this problem. Nowadays numerous satellites record numerous images every day. Remote sensing data are widespread and accessible, so we can use them as the source of actual and reliable information about current status of the Forest Fund. Furthermore regular monitoring allows extracting the information about the location and intensity of forests' changes like degradation and destruction. First of all we create a georeferenced data set to cover the area of interest with orthomosaic in targeting scale depending on the goals of the project (1:25 000 - 1:10 000). For example, we can do a mosaic from RapidEye (Germany) imagery with GSD = 6.5 m or from WorldView-2 (USA) imagery with GSD = 0.5 m. The next step is to create vector layers to describe the content of images. We use visual and contemporary automatic interpretation techniques. The benefit of such approach that we can extract not only information about forests (like boundary) but also the information about roads, hydrographic objects, power lines and so on. During vectorization except relevant orthomosaic we can use multi-temporal composites of images based on archive of satellite imagery. This helps us not only to detect general changes but detect illegal logging, areas affected by fires, windfalls. Then this information can be used for different products e.g. forest cover statistics, forest cover change statistics, maps of forest management and also we can analyze transport accessibility and economic assessment of forests.

  9. Monitoring leaking gases by OP-FTIR remote sensing.

    PubMed

    Li, Yan; Wang, Jun-De; Huang, Zhong-Hua; Xu, Hou-Qian; Zhou, Xue-Tie

    2002-09-01

    Measurement of leaking gases using Open Path Fourier Transform Infrared (OP-FTIR) spectroscopy was carried out in this study to acquire Path Integrated Concentration (PIC) data. Three hazardous Volatile Organic Compounds (VOCs) namely methylene chloride, chloroform and acetone were analyzed. For the two-component leaking source, the PIC data were easily obtained through ordinary calculation and compared to those obtained from Artificial Neural Network (ANN). When the leaking source was composed of three VOCs whose characteristic peaks interfere with each other, it was necessary to do spectral correction for multicomponent analysis with ANN. The Absorbance-Wavenumber-Time 3D spectra of the leaking sources and concentration variations with the leaking time were plotted. The results showed that OP-FTIR is a good quantitative analytical method for indoor or field air pollution. Further more, the remote sensing OP-FTIR system could be utilized to continuously monitor many more toxic gases and work as an alert system for the real time monitoring of hazardous gases beyond normal working conditions of various kinds of areas, such as living or industrial areas. PMID:12369638

  10. Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Bolten, J. D.

    2014-12-01

    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. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

  11. Dynamic Monitoring of Yin Xu Site by Remote Sensing

    NASA Astrophysics Data System (ADS)

    Yang, Ruixia; Peng, Yanyan

    2014-03-01

    Yin Xu, dates back more than 3,300 years, is the first relic of the capital of the Shang Dynasty literally recorded and confirmed by oracle bone scripts and the archaeological excavation in China. Located in Anyang City of Henan Province(northwestern suburbs of Huanhe banks) it covers an area of around 36 km2. According to the characteristics of Yin Xu, remote sensing has shown its great capabilities to solve many issues in different fields, e.g. visual interpretations of aerial photo were used to identify the feature of Yin Xu site in 1972, 1984, 1998, 2005 and 2010. Using the classification validated by field investigations,the change information such as the monitoring index of settlements, riverway, main roads, factory and green area can be extracted in heritage site. According to the monitoring results of land cover and the surrounding environment, we conclude that the protection planning system is effective, and the rapid expansion of neighboring building area has playing a negative role in Yin Xu protection.

  12. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status affecting evapotranspiration and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as...

  13. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status for estimating evapotranspiration and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g...

  14. Monitoring drought at continental scales using thermal remote sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 transpirat...

  15. REMOTE SENSING AND GEOSPATIAL MODELING FOR MONITORING INVASIVE PLANT SPECIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is used to show the actual distribution of distinctive invasive weeds such as leafy spurge (Euphorbia esula L.), whereas landscape modeling can show the potential distribution over an area. Geographic information system data and hyperspectral imagery [NASA JPL’s Airborne Visible Infra...

  16. Monitoring the Hazards of Silicic Volcanoes with Remote Sensing

    NASA Technical Reports Server (NTRS)

    Fink, Jonathan; Wessels, Rick; Eisinger, Chris; Ramsey, Michael; Hellman, Melanie; Kuhn, Sally

    2004-01-01

    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.

  17. Remote sensing for active volcano monitoring in Barren Island, India

    SciTech Connect

    Bhattacharya, A.; Reddy, C.S.S.; Srivastav, S.K. )

    1993-08-01

    The Barren Island Volcano, situated in the Andaman Sea of the Bay of Bengal, erupted recently (March, 1991) after a prolonged period of quiescence of about 188 years. This resumed activity coincides with similar outbreaks in the Philippines and Japan, which are located in an identical tectonic environment. This study addresses (1) remote sensing temporal monitoring of the volcanic activity, (2) detecting hot lava and measuring its pixel-integrated and subpixel temperatures, and (3) the importance of SWIR bands for high temperature volcanic feature detection. Seven sets of TM data acquired continuously from 3 March 1991 to 8 July 1991 have been analyzed. It is concluded that detectable pre-eruption warming took place around 25 March 1991 and volcanic activity started on 1 April 1991. It is observed that high temperature features, such as an erupting volcano, can register emitted thermal radiance in SWIR bands. Calculation of pixel-integrated and sub-pixel temperatures related to volcanic vents has been made, using the dual-band method. 6 refs.

  18. Remote Sensing Center

    NASA Technical Reports Server (NTRS)

    1973-01-01

    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.

  19. Trophic state monitoring of lakes and reservoirs using remote sensing

    NASA Astrophysics Data System (ADS)

    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

  20. Integration of remote sensing and geophysical techniques for coastal monitoring

    NASA Astrophysics Data System (ADS)

    Simoniello, T.; Carone, M. T.; Loperte, A.; Satriani, A.; Imbrenda, V.; D'Emilio, M.; Guariglia, A.

    2009-04-01

    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

  1. Agricultural biomass monitoring on watersheds based on remotely sensed data.

    PubMed

    Tamás, János; Nagy, Attila; Fehér, János

    2015-01-01

    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. PMID:26676009

  2. Monitoring Wetland Changes with Remote Sensing: An East African Example

    PubMed

    Haack

    1996-05-01

    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. PMID:8661611

  3. Active Ground Optical Remote Sensing for Improved Monitoring of Seedling Stress in Nurseries

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  4. Hyperspectral Geobotanical Remote Sensing for CO2 Storage Monitoring

    SciTech Connect

    Pickles, W; Cover, W

    2004-05-14

    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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  6. Advanced Remote Sensing Research

    USGS Publications Warehouse

    Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna

    2008-01-01

    '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).

  7. A remote sensing research agenda for mapping and monitoring biodiversity

    NASA Technical Reports Server (NTRS)

    Stoms, D. M.; Estes, J. E.

    1993-01-01

    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.

  8. Monitoring Coffee Yield Using Modis Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Bernardes, T.; Rosa, V. G.; Rudorf, B. F.; Adami, M.

    2011-12-01

    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

  9. An overview of crop growing condition monitoring in China agriculture remote sensing monitoring system

    NASA Astrophysics Data System (ADS)

    Huang, Qing; Zhou, Qing-bo; Zhang, Li

    2009-07-01

    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.

  10. Investigation of the application of remote sensing technology to environmental monitoring

    NASA Technical Reports Server (NTRS)

    Rader, M. L. (Principal Investigator)

    1980-01-01

    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.

  11. MONITORING WASTE HEAT REJECTION TO THE ENVIRONMENT VIA REMOTE SENSING

    SciTech Connect

    Garrett, A

    2009-01-13

    Nuclear power plants typically use waste heat rejection systems such as cooling lakes and natural draft cooling towers. These systems are designed to reduce cooling water temperatures sufficiently to allow full power operation even during adverse meteorological conditions. After the power plant is operational, the performance of the cooling system is assessed. These assessments usually rely on measured temperatures of the cooling water after it has lost heat to the environment and is being pumped back into the power plant (cooling water inlet temperature). If the cooling system performance is not perceived to be optimal, the utility will collect additional data to determine why. This paper discusses the use of thermal imagery collected from aircraft and satellites combined with numerical simulation to better understand the dynamics and thermodynamics of nuclear power plant waste heat dissipation systems. The ANS meeting presentation will discuss analyses of several power plant cooling systems based on a combination of remote sensing data and hydrodynamic modeling.

  12. Remote Sensing and the Earth

    NASA Technical Reports Server (NTRS)

    Brosius, C. A.; Gervin, J. C.; Ragusa, J. M.

    1977-01-01

    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.

  13. Towards an unitary technical approach for monitoring urban growth in Romania using remote sensing data

    NASA Astrophysics Data System (ADS)

    Aldea, Mihaela; Petrescu, Florian; Sercaianu, Mihai; Gaman, Florian; Iacoboaea, Cristina

    2015-06-01

    Monitoring urban growth process and its patterns for the city of Bucharest was the starting point in our attempt to identify and propose a more general procedure for monitoring this type of process in Romania using remote sensing data. Several important technical aspects such as comparable data sources, comparable algorithms, interoperability issues as well as final presentation standards are discussed. The paper is meant to be considered as a basis for promoting a unitary technical approach concerning urban growth monitoring in Romania using remote sensing data.

  14. Monitoring drought for grassland and cropland using multi-sensor microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Zhang, A.; Jia, G.

    2012-12-01

    Remote sensing drought indices derived from optical and infrared bands have been successfully used in monitoring drought throughout the world; however the application of microwave remote sensing sensor in drought monitoring has not been thoroughly investigated. In this study, we propose a microwave remote sensing drought index, the Microwave Integrated Drought Index (MIDI), especially for short-term drought monitoring over northern China. The index combined three variables: the Tropical Rainfall Measuring Mission (TRMM) precipitation, land surface temperature (LST) and soil moisture (SM) obtained by the Vrije Universiteit Amsterdam and NASA Goddard Space Flight Center (VUA-NASA) from the Advanced Microwave Scanning Radiometer (AMSR-E) on-board Aqua satellite. The microwave remotely sensed variables were linearly scaled from 0 to 1 for each pixel based on absolute minimum and maximum values for each variable over time, in order to discriminate the weather-related component from the ecosystem component. The microwave indices were evaluated with the Standardized Precipitation Index (SPI), an in-situ meteorological data based drought index. Pearson correlation analyses were performed between the remotely sensed drought indices values and different time scale SPI values for the growing season from 2003 to 2010 to assess the capability of remotely sensed drought indices in monitoring drought over three different climate regions in northern China. There was significant spatial variability in the correlations between remote sensing drought indices and SPI, generally, the Precipitation Condition Index (PCI) showed the highest correlation with 1-month SPI (r around 0.70) whether compared to remote sensing drought indices or different time scale SPI; while correlations between Soil Moisture Condition Index (SMCI), Land Surface Temperature (TCI) and SPI exhibited different trends among three climate regions. The MIDI with proper weights of three components nearly possessed the

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  16. APPLIED REMOTE SENSING

    EPA Science Inventory

    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...

  17. Design and implementation for satellite remote sensing forest fire-points automatic monitoring system

    NASA Astrophysics Data System (ADS)

    Zou, Chunhui; Chen, Huailiang; Yin, Qing

    2009-08-01

    Satellite remote sensing monitoring of forest fire-points is a routine operation of weather service. By taking advantage of remote sensing information's characteristics such as relatively fixed resolution, little geometric distortion and quite stable data quality, the thesis establishes Henan Satellite Remote Sensing Forest Fire-points Automatic Monitoring System in the way of automatic geography registration based on gray correlation and control point database, which can realize automation of the whole process including automatic monitoring,automatic geography registration,automatic fire-points monitoring,automatic production releasing and cell phone short-message notice of fire-points warning information. The system could greatly improve service efficiency. Automatic registration of remote sensing information based on gray correlation and control point database features simpleness and quickness. Through automatic geography registration testing of sunny EOS/MODIS data (at daytime and nightime) during 18 periods from February 2008 to May 2008 in Henan Province with average error of registration is 0.637 pixels at daytime and 0.319 at nighttime, it can fully meet ordinary operation requirements. Fire-point identification and fire-point area estimate method in the system can be applied to monitoring different fires at daytime and at nighttime. Besides, it can automatically screen effective fire-points according to background geographic information, and thus it can improve monitoring accuracy.

  18. Development of a Cost-Effective Airborne Remote Sensing System for Coastal Monitoring.

    PubMed

    Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael

    2015-01-01

    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

  19. Development of a Cost-Effective Airborne Remote Sensing System for Coastal Monitoring

    PubMed Central

    Kim, Duk-jin; Jung, Jungkyo; Kang, Ki-mook; Kim, Seung Hee; Xu, Zhen; Hensley, Scott; Swan, Aaron; Duersch, Michael

    2015-01-01

    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

  20. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    NASA Astrophysics Data System (ADS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

    2014-03-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

  1. Remote sensing to monitor cover crop adoption in southeastern Pennsylvania

    USGS Publications Warehouse

    Hively, Wells; Sjoerd Duiker; Greg McCarty; Prabhakara, Kusuma

    2015-01-01

    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

  2. Monitoring winter wheat growth in North China by combining a crop model and remote sensing data

    NASA Astrophysics Data System (ADS)

    Yuping, Ma; Shili, Wang; Li, Zhang; Yingyu, Hou; Liwei, Zhuang; Yanbo, He; Futang, Wang

    2008-12-01

    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.

  3. Remote Sensing

    NASA Technical Reports Server (NTRS)

    Rickman, Douglas

    2008-01-01

    Remote sensing is measuring something without touching it. Most methods measure a portion of the electro-magnetic spectrum using energy reflected from or emitted by a material. Moving the instrument away makes it easier to see more at one time. Airplanes are good but satellites are much better. Many things can not be easily measured on the scale of an individual person. Example - measuring all the vegetation growing at one time in even the smallest country. A satellite can see things over large areas repeatedly and in a consistent way. Data from the detector is reported as digital values for a grid that covers some portion of the Earth. Because it is digital and consistent a computer can extract information or enhance the data for a specific purpose.

  4. Monitoring southwest drought of China using HJ-1A/B and Landsat remote sensing data

    NASA Astrophysics Data System (ADS)

    Huang, He; Zhou, Hongjian; Wang, Ping; Wu, Wei; Yang, Siquan

    2012-10-01

    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.

  5. A framework for developing an impact-oriented agricultural drought monitoring system from remote sensing

    NASA Astrophysics Data System (ADS)

    Zhang, Jie

    2016-04-01

    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.

  6. Connecting long-term monitoring data from vegetation plots and remote sensing in the Southwestern USA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Hydras+ Improving Drought Monitoring by Assimilating multi-source Remote Sensing Observations into Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Rains, Dominik; Lievens, Hans; Vernieuwe, Hilde; De Baets, Bernard; Hostache, Renaud; Chini, Marco; Pfister, Laurent; Matgen, Patrick; He, Guowei; Vereecken, Harry; Han, Xujun; Montzka, Carsten; Verhoest, Niko

    2015-04-01

    Given the expected increase in extreme events due to climate change, more drought events can be expected in the future. These events have often devastating impacts on society and the environment. Adequate monitoring of these events within disaster management is therefore of utmost importance. Remote sensing can provide important information, though does not allow for a complete assessment of droughts as (1) only measurements of the surface are obtained and (2) the spatial and temporal resolutions are often too coarse. Combining remote sensing with land surface models is generally opted for, and is already in place in many drought monitoring systems. However, prediction of drought events (occurrence, intensity, frequency) can be improved by improving modelling approaches via the assimilation of multiple sources of remote sensing data. If both remote sensing observation and model reliability and accuracy can be enhanced, a more precise monitoring and modelling is expected, and therefore improved drought forecast is possible. Within the recently initiated BELSPO/FNR funded HYDRAS+ project, research on these domains is carried out demonstrating the benefits of jointly assimilating several remote sensing sources (e.g. Sentinel 1, SMOS, SMAP) in land surface models for improved drought monitoring and prediction. It furthermore aims at assessing whether conceptual models (SUPERFLEX) can be used instead of complex and computation-expensive land surface models (CLM 4.5). If such models can be used, a faster computation of droughts at very large scale becomes possible. The findings will not be used to set up a standalone drought monitoring system but rather be used to potentially improve currently existing systems. Any improvement in the currently available systems will have important positive consequences with respect to disaster management as it will allow for an improved management of resources.

  8. The world mountain Damavand: documentation and monitoring of human activities using remote sensing data

    NASA Astrophysics Data System (ADS)

    Kostka, Robert

    The use of different remote sensing data is demonstrated by example of the world mountain, Mt. Damavand (5671 m) in the Alborz Mountains, Iran. Several types of satellite data were required to master the complex task of preparing a monograph of this mountain: SSEOP images of NASA, Russian KFA-1000 pictures, CORONA panoramic images of NASA and Russian KVR-1000 orthoimages. Examples of climatic studies, transportation routes, water resources, conservation areas and relicts of human land-use are presented in order to show the potential of remote sensing data. The right choice of image data is a top priority in applied remote sensing in order to obtain significant results in the documentation and monitoring of human activities.

  9. Application of remote sensing to monitoring and studying dispersion in ocean dumping

    NASA Technical Reports Server (NTRS)

    Johnson, R. W.; Ohlhorst, C. W.

    1981-01-01

    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.

  10. Use of remote sensing in monitoring and forecasting of harmful algal blooms

    NASA Astrophysics Data System (ADS)

    Stumpf, Richard P.; Tomlinson, Michelle C.

    2005-08-01

    Harmful algal blooms (HABs) have impacts on coastal economies, public health, and various endangered species. HABs are caused by a variety of organisms, most commonly dinoflagellates, diatoms, and cyanobacteria. In the late 1970's, optical remote sensing was found to have a potential for detecting the presence of blooms of Karenia brevis on the US Florida coast. Due to the nearly annual frequency of these blooms and the ability to note them with ocean color imagery, K. brevis blooms have strongly influenced the field of HAB remote sensing. However, with the variability between phytoplankton blooms, heir environment and their relatively narrow range of pigment types, particularly between toxic and non-toxic dinoflagellates and diatoms, techniques beyond optical detection are required for detecting and monitoring HABs. While satellite chlorophyll has some value, ecological or environmental characteristics are required to use chlorophyll. For example, identification of new blooms can be an effective means of identifying HABs that are quie intense, also blooms occurring after specific rainfall or wind events can be indicated as HABs. Several HAB species do not bloom in the traditional sense, in that they do not dominate the biomass. In these cases, remote sensing of SST or chlorophyll can be coupled with linkages to seasonal succession, changes in circulation or currents, and wind-induced transport--including upwelling and downwelling, to indicate the potential for a HAB to occur. An effective monitoring and forecasting system for HABs will require the coupling of remote sensing with an environmental and ecological understanding of the organism.

  11. Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

    NASA Astrophysics Data System (ADS)

    Ma, Yi; Zhang, Jie; Zhang, Jingyu

    2016-01-01

    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

  12. Remote monitoring of emissions using on-vehicle sensing and vehicle to roadside communications

    SciTech Connect

    Davis, D.T.

    1995-06-01

    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.

  13. Monitoring land at regional and national scales and the role of remote sensing

    NASA Astrophysics Data System (ADS)

    Dymond, John R.; Bégue, Agnes; Loseen, Danny

    There is a need world wide for monitoring land and its ecosystems to ensure their sustainable use. Despite the laudable intentions of Agenda 21 at the Rio Earth Summit, 1992, in which many countries agreed to monitor and report on the status of their land, systematic monitoring of land has yet to begin. The problem is truly difficult, as the earth's surface is vast and the funds available for monitoring are relatively small. This paper describes several methods for cost-effective monitoring of large land areas, including: strategic monitoring; statistical sampling; risk-based approaches; integration of land and water monitoring; and remote sensing. The role of remote sensing is given special attention, as it is the only method that can monitor land exhaustively and directly, at regional and national scales. It is concluded that strategic monitoring, whereby progress towards environmental goals is assessed, is a vital element in land monitoring as it provides a means for evaluating the utility of monitoring designs.

  14. Acoustic Remote Sensing

    NASA Astrophysics Data System (ADS)

    Dowling, David R.; Sabra, Karim G.

    2015-01-01

    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.

  15. Study of remote sensing monitoring of dynamic change of the Loess Plateau forest resources

    NASA Astrophysics Data System (ADS)

    Yuliang, Qiao; Ying, Wang; Junyou, Tang

    Taking for example Daning County, a key pilot area of ``the Three North Protection Forest Project'' in China's Loess Plateau, this article is to explore the method of using remote sensing technology to monitoring the dynamic change information of forest vegetation. It uses LANDSAT TM, CBERS-1 data and aerial remote sensing and ground investigation to monitoring the dynamic change of forest vegetation information of Daning County in three different periods - 1978, 1987 and 2000. The results of the research prove that, this method is worth widely popularized, by which the dynamic change information of the forest vegetation can be monitored simply and quickly so as to explore a scientific, rational and effective road for us to rectify the territory of China's Loess Plateau, change the poor physiognomy of this area, improve the ecological environment and promote the development of national economy.

  16. Landfill monitoring using remote sensing: a case study of Glina, Romania.

    PubMed

    Iacoboaea, Cristina; Petrescu, Florian

    2013-10-01

    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. PMID:23660748

  17. Research on the remote sensing methods of drought monitoring in Chongqing

    NASA Astrophysics Data System (ADS)

    Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

    2011-12-01

    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.

  18. Satellite remote sensing for land use and flooding duration monitoring

    NASA Astrophysics Data System (ADS)

    Sandoz, A.; Chauvelon, P.; Pichaud, M.

    2009-04-01

    We show limits and potential applications of satellite images linked with agricultural and natural habitats and flooded duration problematic. Satellite images could play a major role in the study and monitoring context. When we started our satellite images collection in 1975, it allowed us to map annual variations of habitats and flooded areas. Since the year 2004, we've acquired an important quantity of Spot 5 images through a special programming (ISIS program), which cover the area during all the hydrological year. Using them, the knowledge of spatiotemporal dynamics of habitats and flooded areas, could then, be formalised in a much better way. We present results of inventory and monitoring in the Rhone delta context, South of France, an area of high wetland biodiversity in a Mediterranean catchment area. Our objective is to propose an operational methodology for inventory and monitoring of wetland habitats and wetland flooded duration. The exceptional spatial and temporal resolution sharpness is demonstrated.

  19. Application of terrestrial microwave remote sensing to agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  20. A comparison between remote sensing approaches to water extent monitoring

    NASA Astrophysics Data System (ADS)

    elmi, omid; javad tourian, mohammad; sneeuw, nico

    2013-04-01

    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

  1. The potential for synthesizing multi-sensor remote sensing data for global volcano monitoring

    NASA Astrophysics Data System (ADS)

    Furtney, M.; Pritchard, M. E.; Carn, S. A.; McCormick, B.; Ebmeier, S. K.; Jay, J.

    2015-12-01

    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.

  2. [Thematic Issue: Remote Sensing.

    ERIC Educational Resources Information Center

    Howkins, John, Ed.

    1978-01-01

    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…

  3. Mechanism and look-alikes analysis of oil spill monitoring with optical remote sensing

    NASA Astrophysics Data System (ADS)

    Lan, Guoxin; Ma, Long; Li, Ying; Liu, Bingxin

    2011-12-01

    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.

  4. Remote sensing new model for monitoring the east Asian migratory locust infections based on its breeding circle

    NASA Astrophysics Data System (ADS)

    Han, Xiuzhen; Ma, Jianwen; Bao, Yuhai

    2006-12-01

    Currently the function of operational locust monitor system mainly focused on after-hazards monitoring and assessment, and to found the way effectively to perform early warning and prediction has more practical meaning. Through 2001, 2002 two years continuously field sample and statistics for locusts eggs hatching, nymph growth, adults 3 phases observation, sample statistics and calculation, spectral measurements as well as synchronically remote sensing data processing we raise the view point of Remote Sensing three stage monitor the locust hazards. Based on the point of view we designed remote sensing monitor in three stages: (1) during the egg hitching phase remote sensing can retrieve parameters of land surface temperature (LST) and soil moisture; (2) during nymph growth phase locust increases appetite greatly and remote sensing can calculate vegetation index, leaf area index, vegetation cover and analysis changes; (3) during adult phase the locust move and assembly towards ponds and water ditches as well as less than 75% vegetation cover areas and remote sensing combination with field data can monitor and predicts potential areas for adult locusts to assembly. In this way the priority of remote sensing technology is elaborated effectively and it also provides technique support for the locust monitor system. The idea and techniques used in the study can also be used as reference for other plant diseases and insect pests.

  5. Utilizing multisource remotely sensed data to dynamically monitor drought in China

    NASA Astrophysics Data System (ADS)

    Liu, Sanchao; Li, Wenbo

    2011-12-01

    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.

  6. Olympic main venue construction and urban growth model monitoring using remote sensing temporal data

    NASA Astrophysics Data System (ADS)

    Fang, Chengyin; Chen, Xue; Ma, Jianwen

    2007-11-01

    In order to follow up the concepts of "Green Olympics, High-tech Olympics and People's Olympics", Chinese Academy of Sciences set up a project to monitor the land cover and use change of Beijing city especially inner sixth ring road driven by the venues construction use remote sensing images after the successful bid for the 2008 Olympic Games. Landsat TM and airborne remote sensing temporal data were used in this paper to monitor the construction of Olympic main venues as well as the effluences on neighboring land use and urban growth. This research forms a complete set of urban growth model analysis, records the develop situation of Beijing driven by Olympic games and also provides decision and research reference of Olympic construction.

  7. Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

    NASA Technical Reports Server (NTRS)

    Tilton, James C.; Lawrence, William T.

    2005-01-01

    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.

  8. Construction of an unmanned aerial vehicle remote sensing system for crop monitoring

    NASA Astrophysics Data System (ADS)

    Jeong, Seungtaek; Ko, Jonghan; Kim, Mijeong; Kim, Jongkwon

    2016-04-01

    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.

  9. Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

    USGS Publications Warehouse

    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.

    2012-01-01

    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.

  10. Evaluating the feasibility of multitemporal hyperspectral remote sensing for monitoring bioremediation

    NASA Astrophysics Data System (ADS)

    Noomen, Marleen; Hakkarainen, Annika; van der Meijde, Mark; van der Werff, Harald

    2015-02-01

    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%.

  11. Remote sensing monitoring and driving force analysis to forest and greenbelt in Zhuhai

    NASA Astrophysics Data System (ADS)

    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

  12. Developing a flood monitoring system from remotely sensed data for the Limpopo basin

    USGS Publications Warehouse

    Asante, K.O.; Macuacua, R.D.; Artan, G.A.; Lietzow, R.W.; Verdin, J.P.

    2007-01-01

    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.

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

    PubMed Central

    Handcock, Rebecca N.; Swain, Dave L.; Bishop-Hurley, Greg J.; Patison, Kym P.; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J.

    2009-01-01

    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

  14. Land-atmosphere coupling metrics from satellite remote sensing as a global drought-monitoring tool

    NASA Astrophysics Data System (ADS)

    Roundy, Joshua K.; Santanello, Joseph A.

    2015-04-01

    Drought causes significant economic impact to society that can be reduced through preparations made possible by monitoring and prediction. Most drought monitoring systems utilize a variety of metrics to assess and understand drought. Feedbacks induced through land-atmosphere interactions are an important mechanism of drought intensification and persistence that is often not considered in current drought monitors due to a lack of spatially consistent observations. Recent work has developed a new classification of land-atmosphere interactions that summarizes the net impact of these interactions on drought intensification and recovery through the Coupling Drought Index (CDI). One thing that makes the CDI unique is that it can be calculated based on estimates from satellite remote sensing, which makes it particularly useful for global drought monitoring. Furthermore, the persistent nature of these coupling regimes provides a means of prediction through a Markov Chain Coupling Statistical Model (CSM). Previous work has shown that the CDI based on satellite remote sensing compares well with the U.S. Drought monitor in terms of drought intensification and recovery. On the other hand, the skill of the CSM forecasts over the U.S. is limited and still needs improvement. In this work the extent to which the CDI and CSM can be extended to other areas of the globe are explored. In particular, the ability of the satellite remote sensing based CDI to capture drought intensification and recovery over Africa and Europe are assessed. The benefits and limitations of using a metric of land-atmosphere interactions for global drought monitoring are also discussed.

  15. Remote sensing applied to crop disease control, urban planning, and monitoring aquatic plants, oil spills, rangelands, and soil moisture

    NASA Technical Reports Server (NTRS)

    1975-01-01

    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.

  16. Remote Sensing and the Kyoto Protocol: A Review of Available and Future Technology for Monitoring Treaty Compliance

    NASA Technical Reports Server (NTRS)

    Imhoff, Marc L.; Rosenquist, A.; Milne, A. K.; Dobson, M. C.; Qi, J.

    2000-01-01

    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.

  17. Recent Progress and Development on Multi-parameters Remote Sensing Application in Earthquake Monitoring in China

    NASA Astrophysics Data System (ADS)

    Shen, Xuhui; Zhang, Xuemin; Hong, Shunying; Jing, Feng; Zhao, Shufan

    2014-05-01

    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.

  18. Monitoring and Estimation of Reservoir Water Volume using Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Bhat, Nagaraj; Gouda, Krushna Chandra; Vh, Manumohan; Bhat, Reshma

    2015-04-01

    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.

  19. Research on Monitoring the Wetland Landcover Change Based on the Moderate Resolution Remote Sensing Image

    NASA Astrophysics Data System (ADS)

    Zhou, M.; Yuan, X.; Sun, L.

    2015-04-01

    Wetland is important natural resource. The main method to monitor the landcover change in wetland natural reserve is to extract and analyze information from remote sensing image. In this paper, the landcover information is extracted, summarized and analyzed by using multi-temporal HJ and Landsat satellite image in Zhalong natural reserve, Heilongjiang, China. The method can monitor the wetland landcover change accurately in real time and long term. This paper expounds the natural factors and human factors influence on wetland land use type, for scientific and effective support for the development of the rational use of wetlands in Zhalong natural wetland reserve.

  20. Winter wheat growth and grain protein uniformity monitoring through remotely sensed data

    NASA Astrophysics Data System (ADS)

    Song, Xiaoyu; Wang, Jihua; Huang, Wenjiang

    2010-10-01

    An uneven growing winter wheat will be slower to reach full ground cover and will be lead to uneven yield and quality for cropland. The traditional investigation of crop uniformity is mainly depends on manpower. Remote sensing technique is a potentially useful tool for monitoring the crop uniformity status for it can provide an area global view for entire field within the crop growth season with scathelessness. The objective of this study was to use remote sensing imagery to evaluate the crop growth uniformity, as well as the yield and grain quality variation for a winter wheat study area. One Quickbird image on winter wheat booting stage was collected and processed to monitoring the uniformity of wheat growth. The results indicated that the spectrum parameters of Quickbird image can reflect the spatial uniformity of winter wheat growth in the study areas. Meanwhile the spatial uniformity of wheat growth in early stage can reflect the uniformity of yield and grain quality. The wheat growth information at the booting stage has strong positive correlations with yield, and strong negative correlation with grain protein. The correlation coefficient between OSAVI (optimized soil adjusted vegetation index) and wheat yield was 0.536. It was -0.531 for GNDVI (Greeness-normalized difference vegetation index) and grain protein content. The study also indicated that diverse spectrum parameters had different sensitivity to the wheat growth spatial variance. So it is feasible to use remote sensing data to investigate the crop growth and quality spatial uniformity.

  1. Hyperspectral remote sensing application for monitoring and preservation of plant ecosystems

    NASA Astrophysics Data System (ADS)

    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

  2. [Stereoscopic remote sensing used in monitoring Enteromorpha Prolifra disaster in Chinese Yellow Sea].

    PubMed

    Gu, Xing-Fa; Chen, Xing-Feng; Yin, Qiu; Li, Zheng-Qiang; Xu, Hua; Shao, Yun; Li, Zi-Wei

    2011-06-01

    In the summer 2008, Enteromorpha Prolifra broke out in Yellow Sea and East Sea on a large scale for the first time, and became a marine disaster. The authors constructed a stereoscopic monitoring system which monitored the disaster continuously, dynamically and in real time. The present paper introduced the construction of the stereoscopic monitoring system; through analyzing the spectral characteristics of Enteromorpha Prolifra and ocean water which were acquired in a field experiment, confirmed Enteromorpha Prolifra retrieval models based on multi-platform multi-sensor and multi-spectral remote sensing data, contrasted the different scale monitoring results, and analyzed the evolvement rules with time-series analysis. This system was applied to the Enteromorpha Prolifra emergency monitoring in the 29th Olympic sailing area. It was proved feasible and valuable for the Olympic safeguard. PMID:21847947

  3. Applied Remote Sensing Program (ARSP)

    NASA Technical Reports Server (NTRS)

    Johnson, J. D.; Foster, K. E.; Mouat, D. A.; Miller, D. A.; Conn, J. S.

    1976-01-01

    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.

  4. MORFEO project: use of remote sensing technology for mapping, monitoring and forecasting landslides

    NASA Astrophysics Data System (ADS)

    Guzzetti, F.; Candela, L.; Carlà, R.; Fornaro, G.; Lanari, R.; Mondini, A.; Ober, G.; Fiorucci, F.; Zeni, G.

    2009-04-01

    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.

  5. Tropospheric Passive Remote Sensing

    NASA Technical Reports Server (NTRS)

    Keafer, L. S., Jr. (Editor)

    1982-01-01

    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.

  6. SUPERFUND REMOTE SENSING SUPPORT

    EPA Science Inventory

    This task provides remote sensing technical support to the Superfund program. Support includes the collection, processing, and analysis of remote sensing data to characterize hazardous waste disposal sites and their history. Image analysis reports, aerial photographs, and assoc...

  7. Optical Remote-sensing Monitoring and Forecasting of Atmospheric Pollution in Huaibei Area, China

    NASA Astrophysics Data System (ADS)

    Li, Su-wen; Xie, Pin-hua; Jiang, En-hua; Zhang, Yong; Dai, Hai-feng

    2012-12-01

    Huaibei is an energy city. Coal as the primary energy consumption brings a large number of regional pollution in Huaibei area. Differential optical absorption spectroscopy (DOAS) as optical remote sensing technology has been applied to monitor regional average concentrations and inventory of nitrogen dioxide, sulfur dioxide and ozone. DOAS system was set up and applied to monitor the main air pollutants in Huaibei area. Monitoring data were obtained from 7 to 28 August, 2011. Monitoring results show measurements in controlling pollution are effective, and emissions of pollutants are up to the national standard in Huaibei area. Prediction model was also created to track changing trend of pollutions. These will provide raw data support for effective evaluation of environmental quality in Huaibei area.

  8. [An improved method and its application for agricultural drought monitoring based on remote sensing].

    PubMed

    Zheng, You-Fei; Cheng, Jin-Xin; Wu, Rong-Jun; Guan, Fu-Lai; Yao, Shu-Ran

    2013-09-01

    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. PMID:24417121

  9. Experiment of monitoring thermal discharge drained from nuclear plant through airborne infrared remote sensing

    NASA Astrophysics Data System (ADS)

    Wang, Difeng; Pan, Delu; Li, Ning

    2009-07-01

    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.

  10. Framework design for remote sensing monitoring and data service system of regional river basins

    NASA Astrophysics Data System (ADS)

    Fu, Jun'e.; Lu, Jingxuan; Pang, Zhiguo

    2015-08-01

    Regional river basins, transboundary rivers in particular, are shared water resources among multiple users. The tempo-spatial distribution and utilization potentials of water resources in these river basins have a great influence on the economic layout and the social development of all the interested parties in these basins. However, due to the characteristics of cross borders and multi-users in these regions, especially across border regions, basic data is relatively scarce and inconsistent, which bring difficulties in basin water resources management. Facing the basic data requirements in regional river management, the overall technical framework for remote sensing monitoring and data service system in China's regional river basins was designed in the paper, with a remote sensing driven distributed basin hydrologic model developed and integrated within the frame. This prototype system is able to extract most of the model required land surface data by multi-sources and multi-temporal remote sensing images, to run a distributed basin hydrological simulation model, to carry out various scenario analysis, and to provide data services to decision makers.

  11. Remote sensing based water quality monitoring in Chivero and Manyame lakes of Zimbabwe

    NASA Astrophysics Data System (ADS)

    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.

  12. State-of-the-art remote sensing geospatial technologies in support of transportation monitoring and management

    NASA Astrophysics Data System (ADS)

    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

  13. Norwegian remote sensing spectrometry for mapping and monitoring of algal blooms and pollution - NORSMAP-89

    SciTech Connect

    Pettersson, L.H.; Johannessen, O.M.; Frette, O. )

    1990-01-09

    During the late spring of 1988 an extensive bloom of the toxic algae Chrysocromulina polylepis occurred in the Skagerrak region influencing most life in the upper 30 meter of the ocean. The algal front was advected northward with the Norwegian Coastal Current along the coast of southern Norway, where it became a severe threat to the Norwegian seafarming industry. An ad-hoc expert team was established to monitor and forecast the movement of the algae front. Remote sensing of sea surface temperature from the operational US NOAA satellites monitored the movement of the algal front, consistent with a warm ocean front. The lack of any optical remote sensing instrumentation was recognized as a major de-efficiency during this algal bloom. To prepare for similar events in the future Nansen Remote Sensing Center initiated a three week pilot study in the Oslofjord and Skagerrak region, during May 1989. The Canadian Compact Airborne Spectrographic Imager (CASI) was installed in the surveillance aircraft. Extensive in situ campaigns was also carried out by the Norwegian Institute for Water Research and Institute of Marine Research. A ship-borne non-imaging spectrometer was operated from the vessels participating in the field campaign. As a contribution from a joint campaign (EISAC '89) between the Joint Research Centre (JRC) of the European Community and the European Space Agency (ESA) both the Canadian Fluorescence Line Imager (FLI) and the US 64-channel GER scanner was operated simultaneously at the NORSMAP 89 test site. Regions of different biological and physical conditions were covered during the pilot study and preliminary analysis are obtained from oil slicks, suspended matter from river, as well as minor algal bloom. The joint analysis of the data collected during the NORSMAP 89 campaign and conclussions will be presented, as well as suggestions for future utilization of airborne spectroscopy systems for operational monitoring of algal bloom and water pollution.

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

    NASA Astrophysics Data System (ADS)

    Washington-Allen, R. A.

    2015-12-01

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

  15. Monitoring Global Food Security with New Remote Sensing Products and Tools

    NASA Astrophysics Data System (ADS)

    Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Husak, G. J.; Magadzire, T.; Verdin, J. P.

    2012-12-01

    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

  16. REMOTE SENSING TECHNOLOGIES APPLICATIONS RESEARCH

    EPA Science Inventory

    Remote sensing technologies applications research supports the ORD Landscape Sciences Program (LSP) in two separate areas: operational remote sensing, and remote sensing research and development. Operational remote sensing is provided to the LSP through the use of current and t...

  17. [Vegetation water content retrieval and application of drought monitoring using multi-spectral remote sensing].

    PubMed

    Wang, Li-Tao; Wang, Shi-Xin; Zhou, Yi; Liu, Wen-Liang; Wang, Fu-Tao

    2011-10-01

    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. PMID:22250560

  18. [High Resolution Remote Sensing Monitoring and Assessment of Secondary Geological Disasters Triggered by the Lushan Earthquake].

    PubMed

    Wang, Fu-tao; Wang, Shi-xin; Zhou, Yi; Wang, Li-tao; Yan, Fu-li; Li, Wen-jun; Liu, Xiong-fei

    2016-01-01

    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. PMID:27228764

  19. Active landslide monitoring using remote sensing data, GPS measurements and cameras on board UAV

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Kavoura, Katerina; Depountis, Nikolaos; Argyropoulos, Nikolaos; Koukouvelas, Ioannis; Sabatakakis, Nikolaos

    2015-10-01

    An active landslide can be monitored using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GPS and photogrammetric techniques using airphotos or high resolution satellite images. As the cost of the aerial photo campaign and the acquisition of very high resolution satellite data is quite expensive the use of cameras on board UAV could be an identical solution. Small UAVs (Unmanned Aerial Vehicles) have started their development as expensive toys but they currently became a very valuable tool in remote sensing monitoring of small areas. The purpose of this work is to demonstrate a cheap but effective solution for an active landslide monitoring. We present the first experimental results of the synergistic use of UAV, GPS measurements and remote sensing data. A six-rotor aircraft with a total weight of 6 kg carrying two small cameras has been used. Very accurate digital airphotos, high accuracy DSM, DGPS measurements and the data captured from the UAV are combined and the results are presented in the current study.

  20. Concept of an advanced hyperspectral remote sensing system for pipeline monitoring

    NASA Astrophysics Data System (ADS)

    Keskin, Göksu; Teutsch, Caroline D.; Lenz, Andreas; Middelmann, Wolfgang

    2015-10-01

    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.

  1. Remote sensing and monitor system for a large poultry farm based on Internet

    NASA Astrophysics Data System (ADS)

    Bai, Hongwu; Teng, Guanghui; Ma, Liang; Li, Zhizhong; Yuan, Zhengdong; Li, Minzan; Yang, Xiuslayerg

    2005-09-01

    A remote sensing and monitor system for a large poultry layer farm is developed based on distributed data acquisition and internet control. The supervising system applied patent techniques known as arc orbit movable vidicon, wireless video transmission and telecommunications. It features supervising at all orientations, and digital video telecommunicating through internet. All measured and control information is sent to a central computer, which is in charge of storing, displaying, analyzing and serving to internet, where managers can monitor real time production scene anywhere and customers can also see the healthy layers through internet. This paper primarily discusses how to design the remote sensing and monitor system (RSMS), and its usage in a large poultry farm, Deqingyuan Healthy Breeding Ecological Garden, Yanqing County, Beijing, China. The system applied web service technology and the middleware using XML language and Java language. It preponderated in data management, data exchange, expansibility, security, and compatibility. As a part of poultry sustainable development management system, it has been applied in a large farm with 1,200,000 layers. Tests revealed that there was distinct decline in the death ratio of chicken with 2. 2%, as the surroundings of layers had been ameliorated. At the same time, there was definite increase in the laying ratio with 3. 5%.

  2. Comparison of multispectral remote-sensing techniques for monitoring subsurface drain conditions. [Imperial Valley, California

    NASA Technical Reports Server (NTRS)

    Goettelman, R. C.; Grass, L. B.; Millard, J. P.; Nixon, P. R.

    1983-01-01

    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.

  3. Drought monitoring with remote sensing based land surface phenology applications and validation

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  5. The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

    NASA Technical Reports Server (NTRS)

    Savastano, K. J.; Leming, T. D.

    1975-01-01

    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.

  6. A Remote Sensing-based Global Agricultural Drought Monitoring and Forecasting System for Supporting GEOSS (Invited)

    NASA Astrophysics Data System (ADS)

    di, L.; Yu, G.; Han, W.; Deng, M.

    2010-12-01

    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

  7. POTENTIAL OF THERMAL INFRARED REMOTE SENSING FOR THE MONITORING OF LAND SURFACES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal infrared remote sensing over vegetated land surfaces is expected to provide valuable information for documenting soil-vegetation-atmosphere exchanges about heat, water and mass. On the one hand, the community benefits of various TIR remote sensing observations according to four dimensions: s...

  8. Monitoring the dynamics of an invasive emergent macrophyte community using operational remote sensing data

    USGS Publications Warehouse

    Albright, T.P.; Ode, D.J.

    2011-01-01

    Potamogeton crispus L. (curly pondweed) is a cosmopolitan aquatic macrophyte considered invasive in North America and elsewhere. Its range is expanding and, on individual water bodies, its coverage can be dynamic both within and among years. In this study, we evaluate the use of free and low-cost satellite remote sensing data to monitor a problematic emergent macrophyte community dominated by P. crispus. Between 2000 and 2006, we acquired eight satellite images of 24,000-ha Lake Sharpe, South Dakota (USA). During one of the dates for which satellite imagery was acquired, we sampled the lake for P. crispus and other emergent macrophytes using GPS and photography for documentation. We used cluster analysis to assist in classification of the satellite imagery and independently validated results using the field data. Resulting estimates of emergent macrophyte coverage ranged from less than 20 ha in 2002 to 245 ha in 2004. Accuracy assessment indicated 82% of image pixels were correctly classified, with errors being primarily due to failure to identify emergent macrophytes. These results emphasize the dynamic nature of P. crispus-dominated macrophyte communities and show how they can be effectively monitored over large areas using low-cost remote sensing imagery. While results may vary in other systems depending on water quality and local flora, such an approach could be applied elsewhere and for a variety of macrophyte communities. ?? Springer Science+Business Media B.V. 2010.

  9. Remote sensing based approach for monitoring urban growth in Mexico city, Mexico: A case study

    NASA Astrophysics Data System (ADS)

    Obade, Vincent

    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

  10. Water quality monitoring and assessment of an urban Mediterranean lake facilitated by remote sensing applications.

    PubMed

    Markogianni, V; Dimitriou, E; Karaouzas, I

    2014-08-01

    Degradation of water quality is a major problem worldwide and often leads to serious environmental impacts and concerns about public health. In this study, the water quality monitoring and assessment of the Koumoundourou Lake, a brackish urban shallow lake located in the northeastern part of Elefsis Bay (Greece), were evaluated. A number of water quality parameters (pH, temperature, dissolved oxygen concentration, electrical conductivity, turbidity, nutrients, and chlorophyll-a concentration) were analyzed in water samples collected bimonthly over a 1-year period from five stations throughout the lake. Moreover, biological quality elements were analysed seasonally over the 1-year period (benthic fauna). Statistical analysis was performed in order to evaluate the water quality of the lake and distinguish sources of variation measured in the samples. Furthermore, the chemical and trophic status of the lake was evaluated according to the most widely applicable classification schemes. Satellite images of Landsat 5 Thematic Mapper were used in order for algorithms to be developed and calculate the concentration of chlorophyll-a (Chl-a). The trophic status of the lake was characterized as oligotrophic based on phosphorus and as mesotrophic-eutrophic based on Chl-a concentrations. The results of the remote sensing application indicated a relatively high coefficient of determination (R (2)) among point sampling results and the remotely sensed data, which implies that the selected algorithm is reliable and could be used for the monitoring of Chl-a concentration in the particular water body when no field data are available. PMID:24705815

  11. Ground-based remote sensing scheme for monitoring aerosol-cloud interactions

    NASA Astrophysics Data System (ADS)

    Sarna, Karolina; Russchenberg, Herman W. J.

    2016-03-01

    A new method for continuous observation of aerosol-cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us 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 case studies were chosen from the Atmospheric Radiation Measurement (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius (re) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m-2 wide. For every LWP bin we present the correlation coefficient between ln re and ln ATB, as well as ACIr (defined as ACIr = -d ln re/d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACIr are in the range 0.01-0.1. We show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol-cloud interactions.

  12. Comparison of some very high resolution remote sensing techniques for the monitoring of a sandy beach

    NASA Astrophysics Data System (ADS)

    Jaud, M.; Delacourt, C.; Allemand, P.; Deschamps, A.; Cancouët, R.; Ammann, J.; Grandjean, P.; Suanez, S.; Fichaut, B.; Cuq, V.

    2011-12-01

    Because the anthropogenic pressure on the coastal fringe is continuously increasing, the comprehension of morphological coastal changes is a key problem. An efficient, practical and affordable monitoring strategy is essential to investigate the physical processes that are on the origin of these changes and to model the changes to come. This paper presents an assessment of several very high resolution remote sensing techniques (DGPS, stereo-photogrammetry by drone, Terrestrial Laser Scanning and shallow-water multi-beam echo-sounder) which have been jointly used to survey a beach in French Brittany. These techniques allow an integrated approach for Digital Elevation Model (DEM) differencing in order to quantify morphological changes and to monitor the beach evolution. Gathering topographic and bathymetric data enables to draw up the sediment budget of a complete sediment compartment.

  13. Monitoring of the mercury mining site Almadén implementing remote sensing technologies.

    PubMed

    Schmid, Thomas; Rico, Celia; Rodríguez-Rastrero, Manuel; José Sierra, María; Javier Díaz-Puente, Fco; Pelayo, Marta; Millán, Rocio

    2013-08-01

    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

  14. Remote sensing for monitoring of wildlife habitat: Lesser snow geese and sub-Arctic coastal marshes

    NASA Astrophysics Data System (ADS)

    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

  15. Remote sensing in support of high-resolution terrestrial carbon monitoring and modeling

    NASA Astrophysics Data System (ADS)

    Hurtt, G. C.; Zhao, M.; Dubayah, R.; Huang, C.; Swatantran, A.; ONeil-Dunne, J.; Johnson, K. D.; Birdsey, R.; Fisk, J.; Flanagan, S.; Sahajpal, R.; Huang, W.; Tang, H.; Armstrong, A. H.

    2014-12-01

    As part of its Phase 1 Carbon Monitoring System (CMS) activities, NASA initiated a Local-Scale Biomass Pilot study. The goals of the pilot study were to develop protocols for fusing high-resolution remotely sensed observations with field data, provide accurate validation test areas for the continental-scale biomass product, and demonstrate efficacy for prognostic terrestrial ecosystem modeling. In Phase 2, this effort was expanded to the state scale. Here, we present results of this activity focusing on the use of remote sensing in high-resolution ecosystem modeling. The Ecosystem Demography (ED) model was implemented at 90 m spatial resolution for the entire state of Maryland. We rasterized soil depth and soil texture data from SSURGO. For hourly meteorological data, we spatially interpolated 32-km 3-hourly NARR into 1-km hourly and further corrected them at monthly level using PRISM data. NLCD data were used to mask sand, seashore, and wetland. High-resolution 1 m forest/non-forest mapping was used to define forest fraction of 90 m cells. Three alternative strategies were evaluated for initialization of forest structure using high-resolution lidar, and the model was used to calculate statewide estimates of forest biomass, carbon sequestration potential, time to reach sequestration potential, and sensitivity to future forest growth and disturbance rates, all at 90 m resolution. To our knowledge, no dynamic ecosystem model has been run at such high spatial resolution over such large areas utilizing remote sensing and validated as extensively. There are over 3 million 90 m land cells in Maryland, greater than 43 times the ~73,000 half-degree cells in a state-of-the-art global land model.

  16. Monitoring grazing intensity: an experiment with canopy spectra applied to satellite remote sensing

    NASA Astrophysics Data System (ADS)

    Li, Fei; Zhao, Ying; Zheng, Jiajia; Luo, Juhua; Zhang, Xiaoqiang

    2016-04-01

    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.

  17. Monitoring land coverage change in mining area by remote sensing image classification

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Zhao, Li; Wu, Yanbin

    Based on remote sensing images, the panoramic views of land coverage distribution across a large geographic area can be accessed conveniently. In order to improve the accuracy of monitoring land use changes, the Chaos Genetic Algorithm was proposed. Chaos Immune Algorithm has capability of self-organizing, self-learning, self-recognition and self-memory, hence through the input samples the global optimization clustering center was found. And then the clustering center was employed to classify the view picture of remote sensing image. In this process, the ergodic property of chaos phenomenon was used to optimize the initial antibody population, so it could accelerate the convergence of Immune Algorithm. Through the clone selection operator, mutation operator and recruited antibody, local optimums were avoid. Chaos Immune Algorithm was applied to classify land use in Huainan -based on TM image. Based on confusion matrix, the classification of the Parallelepiped and Maximum likelihood methods were contrasted with Chaos Immune Algorithm. It is demonstrated that Chaos Immune Algorithm is superior to the two traditional algorithms, and its overall accuracy and Kappa coefficient reach 88.26% and 0.853respectively.

  18. An application of aerial remote sensing to monitor salinization at Xinding Basin

    NASA Astrophysics Data System (ADS)

    Qiao, Yu-Liang

    In this paper, a method to interpret the high, mid, low salinized ploughland and the salinized wasteland using comprehensive aerophoto interpretation principles will be described for Xinding Basin, Shanxi Province. The dynamic change of salinized soil during 7 years from 1980 to 1987 will be compared with the typical Dingxiang County. The map and data obtained, with an accuracy of more than 90%, are provided to the local government as the scientific grounds to instruct agricultural productivity. Soil salinization is a worldwide problem. With the sharp increase in world population and modern industrialisation development, the natural resource consumption is increasing day and day, and bringing about a lack of land resource worldwide. As a kind of back-up land resource, salinized land has not only attracted the concern and study of the agricultural scientists in all countries, but also by the whole society. Shanxi is such a province in China where more than 1/3 of its total area of irrigation land is salinized. The statistics used to monitor this salinized area lack objectivity and accuracy. In 1987, the government of Shanxi Province began to investigate the salinized area of the whole province, using remote sensing technology. We selected the Xinding Basin in central Shanxi as the test district to perform the aerial remote sensing investigation, and, at the same time, studied the salinization dynamic change on the Dingxiang County used as the typical district.

  19. Detection and monitoring of super sandstorm and its impacts on Arabian Sea-Remote sensing approach

    NASA Astrophysics Data System (ADS)

    Kunte, Pravin D.; M. A., Aswini

    2015-06-01

    The present study addresses an intense sandstorm event over the Persian Gulf and its transport over the Arabian Sea region and the Indian sub-continent using satellite observations and measurements. MODIS data are used to analyze the temporal variation of the dust events that occurred from 17 to 24 March 2012 with the strongest intensity on 20 March over the Arabian Sea. MODIS images are examined to provide an independent assessment of dust presence and plume location and its migration over the Arabian Sea to the Indian sub-continent. Dust enhancement and dust detection procedure is attempted to demarcate the dust event. Dust source, formation, transportation path, and dissipation is studied using source-back-tracking, surface wind, and surface pressure, wind speed and direction, geo-potential height for different pressure level, and remote sensing methods. Finally, an attempt is made to investigate the impact of super sandstorm on the Arabian Sea by studying sea surface temperature and chlorophyll a variability during the events. It is noted that sea surface temperature is decreased and chlorophyll a concentration increased during the post-event period. The present study demonstrates the use of remote sensing data and geospatial techniques in detecting and mapping of dust events and monitoring dust transport along specific regional transport pathways over land and ocean.

  20. Developing the remote sensing-based early warning system for monitoring TSS concentrations in Lake Mead.

    PubMed

    Imen, Sanaz; Chang, Ni-Bin; Yang, Y Jeffrey

    2015-09-01

    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. PMID:26093101

  1. Remote optical sensing network for gas monitoring based on laser spectroscopy over hybrid TDM/WDM-PONs

    NASA Astrophysics Data System (ADS)

    Huang, Ming-Fang; Plant, Genevieve; Tanaka, Akihiro; Cvijetic, Neda; Tian, Yue; Wysocki, Gerard; Wang, Ting

    2015-09-01

    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.

  2. Integration of wireless sensor network and remote sensing for monitoring and determining irrigation demand in Cyprus

    NASA Astrophysics Data System (ADS)

    Agapiou, Athos; Papadavid, George; Hadjimitsis, Diofantos G.

    2009-09-01

    This paper aims to highlight the benefits from the integration of wireless sensor network / meteorological data and remote sensing for monitoring and determine irrigation demand in Cyprus. Estimating evapotranspiration in Cyprus will help, in taking measures for an effective irrigation water management in the future in the island. For this purpose both multi-spectral satellite images (Landsat 7 ETM+ and ASTER) and hydro-meteorological data from wireless sensors and automatic meteorological stations have been used. The wireless sensor network, which consist approximately twenty wireless nodes, was placed in our case study. The wireless sensor network acts as a wide area distributed data collection system deployed to collect and reliably transmit soil and air environmental data to a remote base-station hosted at Cyprus University of Technology. Furthermore auxiliary meteorological field data, from an automatic meteorological station, nearby our case study, where used such as solar radiation, air temperature, air humidity and wind speed. These data were used in conjunction with remote sensing results. Satellite images where used in ERDAS Imagine Software after the necessary processing: geometric rectification, radiometric calibration and atmospheric corrections. The satellite images were atmospheric corrected and calibrated using spectro-radiometers and sun-photometers measurements taken in situ, in an agricultural area, south-west of the island of Cyprus. Evapotranspiration is difficult to determine since it combines various meteorological and field parameters while in literature quite many different models for estimating ET are indicated. For estimating evapotranspiration from satellite images and the hydro-meteorological data different methods have been evaluated such as FAO Penman-Monteith, Carlson-Buffum and Granger methods. These results have been compared with E-pan methods. Finally a water management irrigation schedule has been applied. The final results are

  3. Monitoring of Maize Damage Caused by Western Corn Rootworm by Remote Sensing

    NASA Astrophysics Data System (ADS)

    Nádor, G.; Fényes, D.; Vasas, L.; Surek, G.

    2009-04-01

    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.

  4. Agricultural drought risk monitoring and yield loss forecast with remote sensing data

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

    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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  6. Lidar Monitoring of Clouds and Aerosols at the Facility for Atmospheric Remote Sensing

    NASA Technical Reports Server (NTRS)

    Sassen, Kenneth

    2000-01-01

    We report on findings from ongoing polarization lidar research at the University of Utah Facility for Atmospheric Remote Sensing (FARS). This facility was established in 1987, and the current total of lidar and radiometric measurements is approx. 2,900-h. Research at FARS has been applied to the climatological investigation of cirrus cloud properties for basic research and satellite measurement validation (currently in its 13th year), and studies of contrails, mixed phase clouds, and volcanic and Asian dust aerosols. Among the techniques utilized for monitoring cloud and aerosol properties are triple-wave length linear depolarization measurements, and high (1.5-m by 10-Hz) resolution scanning observations. The usefulness of extended time lidar studies for atmospheric and climate research is illustrated.

  7. Application of pulsed GaAs diode lasers to spectral atmospheric monitoring and remote sensing

    NASA Astrophysics Data System (ADS)

    Pencheva, Vasilka H.; Penchev, S.; Naboko, Vassily N.; Naboko, Sergei V.

    1999-05-01

    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.

  8. Active Ground Optical Remote Sensing for Improved Monitoring of Seedling Stress in Nurseries

    PubMed Central

    Eitel, Jan U. H.; Keefe, Robert F.; Long, Dan S.; Davis, Anthony S.; Vierling, Lee A.

    2010-01-01

    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

  9. [Simplification of crop shortage water index and its application in drought remote sensing monitoring].

    PubMed

    Liu, Anlin; Li, Xingmin; He, Yanbo; Deng, Fengdong

    2004-02-01

    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. PMID:15146625

  10. Monitoring abandoned dreg fields of high-speed railway construction with UAV remote sensing technology

    NASA Astrophysics Data System (ADS)

    Lin, Jiayuan; Wang, Zhiliang; Wang, Yangchun; Lin, Yi; Du, Xiaolin

    2015-12-01

    High-speed railway construction will produce a large amount of abandoned dregs, so it is necessary to build enough dreg deposition fields along the railway. The task of the department of soil and water conservation is to monitor the construction and usage of abandoned dreg fields according to the design in the whole process of railway construction. As long linear construction projects, many high-speed railways go through regions of complex terrain, which poses great difficulties to monitoring current status of abandoned dreg fields. With the advantages of low cost, flexible launch and landing, safety, under-cloud-flying, hyperspatial image resolution, Unmanned Aerial Vehicles (UAVs) are very suitable for obtaining remote sensing imagery along the railway. One segment of the high-speed railway from Chongqing to Wanzhou and its neighborhood was chosen as the study area to demonstrate key technologies and specific procedures of monitoring abandoned dreg fields using the UAV system. The UAV system and its components are introduced along with the flight trajectories, acquired UAV imagery, and attitude data. Image preprocessing and generation of DEM and DOM are described in detail followed by image-based measurement accuracy assessment and abandoned dreg field status investigation on the resulting DOM and DEM. Results prove the feasibility and effectiveness of applying the fixed wing UAV system to rapidly monitoring the construction and usage of abandoned dreg fields

  11. [Research on remote sensing monitoring of soil salinization based on measured hyperspectral and EM38 data].

    PubMed

    Yao, Yuan; Ding, Jian-Li; Kelimul, Ardak; Zhang, Fang; Lei, Lei

    2013-07-01

    In the present study, the delta oasis between the Weigan River and the Kuqa River was selected as our study area. Firstly, the measured hyperspectral data related to different soil salinization extent was combined with electromagnetic induction instrument (EM38) in order to establish a soil salinization monitoring model; Secondly, by using the scaling transformation method, the model was adopted to calibrate the soil salinity index calculated from Landsat-TM images. Thirdly, the calibrated Landsat-TM images were used for the retrieval of regional soil salinity, and the retrieved data was verified based on the measured data. We found that at wavelengths of 456, 533, 686 and 1 373 nm, the interpretated data of EM38 were highly correlated with soil spectral reflectance (obtained via first order differentiation transformation of the spectra). Additionally, the soil salinity index model constructed from the combination of 456, 686 and 1 373 nm waveband was the best model among the different saliniza tion monitoring models. The authors' conclusion is that with R2 = 0.799 3 (p < 0.01), extracting the salinity information at regional scale by combining the electromagnetic and multispectral data performed better than those monitoring models with only salinity index extracted from multispectral remote sensing method (R2 = 0.587 4, p < 0 01). Our findings provides scientific bases for the future studies related to more accurate monitoring and prediction of soil salinization. PMID:24059201

  12. Enhancement of Capabilities in Hyperspectral and Radar Remote Sensing for Environmental Assessment and Monitoring

    NASA Technical Reports Server (NTRS)

    Hepner, George F.

    1999-01-01

    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.

  13. Monitoring Ephemeral Streams Using Airborne Very High Resolution Multispectral Remote Sensing in Arid Environments

    NASA Astrophysics Data System (ADS)

    Hamada, Y.; O'Connor, B. L.

    2012-12-01

    Development in arid environments often results in the loss and degradation of the ephemeral streams that provide habitat and critical ecosystem functions such as water delivery, sediment transport, and groundwater recharge. Quantification of these ecosystem functions is challenging because of the episodic nature of runoff events in desert landscapes and the large spatial scale of watersheds that potentially can be impacted by large-scale development. Low-impact development guidelines and regulatory protection of ephemeral streams are often lacking due to the difficulty of accurately mapping and quantifying the critical functions of ephemeral streams at scales larger than individual reaches. Renewable energy development in arid regions has the potential to disturb ephemeral streams at the watershed scale, and it is necessary to develop environmental monitoring applications for ephemeral streams to help inform land management and regulatory actions aimed at protecting and mitigating for impacts related to large-scale land disturbances. This study focuses on developing remote sensing methodologies to identify and monitor impacts on ephemeral streams resulting from the land disturbance associated with utility-scale solar energy development in the desert southwest of the United States. Airborne very high resolution (VHR) multispectral imagery is used to produce stereoscopic, three-dimensional landscape models that can be used to (1) identify and map ephemeral stream channel networks, and (2) support analyses and models of hydrologic and sediment transport processes that pertain to the critical functionality of ephemeral streams. Spectral and statistical analyses are being developed to extract information about ephemeral channel location and extent, micro-topography, riparian vegetation, and soil moisture characteristics. This presentation will demonstrate initial results and provide a framework for future work associated with this project, for developing the necessary

  14. Mapping and monitoring conifer mortality using remote sensing in the Lake Tahoe Basin

    SciTech Connect

    Macomber, S.A.; Woodcock, C.E. )

    1994-12-01

    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.

  15. Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

    DOE PAGESBeta

    Sarna, Karolina; Russchenberg, Herman W. J.

    2016-03-14

    A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us 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 case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius (re) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m–2 wide. For every LWP bin we present the correlation coefficient between ln re and ln ATB, as well as ACIr (defined as ACIr = –d ln re/d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACIr are in the range 0.01–0.1. Lastly, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

  16. Remote sensing techniques to monitor nitrogen-driven carbon dynamics in field corn

    NASA Astrophysics Data System (ADS)

    Corp, Lawrence A.; Middleton, Elizabeth M.; Campbell, Petya K. E.; Huemmrich, K. Fred; Cheng, Yen-Ben; Daughtry, Craig S. T.

    2009-08-01

    Patterns of change in vegetation growth and condition are one of the primary indicators of the present and future ecological status of the globe. Nitrogen (N) is involved in photochemical processes and is one of the primary resources regulating plant growth. As a result, biological carbon (C) sequestration is driven by N availability. Large scale monitoring of photosynthetic processes are currently possible only with remote sensing systems that rely heavily on passive reflectance (R) information. Unlike R, fluorescence (F) emitted from chlorophyll is directly related to photochemical reactions and has been extensively used for the elucidation of the photosynthetic pathways. Recent advances in passive fluorescence instrumentation have made the remote acquisition of solar-induced fluorescence possible. The goal of this effort is to evaluate existing reflectance and emerging fluorescence methodologies for determining vegetation parameters related to photosynthetic function and carbon sequestration dynamics in plants. Field corn N treatment levels of 280, 140, 70, and 0 kg N / ha were sampled from an intensive test site for a multi-disciplinary project, Optimizing Production Inputs for Economic and Environmental Enhancement (OPE). Aircraft, near-ground, and leaf-level measurements were used to compare and contrast treatment effects within this experiment site assessed with both reflectance and fluorescence approaches. A number of spectral indices including the R derivative index D730/D705, the normalized difference of R750 vs. R705, and simple ratio R800/R750 differentiated three of the four N fertilization rates and yielded high correlations to three important carbon parameters: C:N, light use efficiency, and grain yield. These results advocate the application of hyperspectral sensors for remotely monitoring carbon cycle dynamics in terrestrial ecosystems.

  17. Remote sensing for gas plume monitoring using state-of-the-art infrared hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Hinnrichs, Michele

    1999-02-01

    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.

  18. Monitoring plant cover on the Tibetan Plateau: A multi-scale remote sensing based approach

    NASA Astrophysics Data System (ADS)

    Lehnert, Lukas; Meyer, Hanna; Thies, Boris; Reudenbach, Christoph; Bendix, Jörg

    2014-05-01

    The degradation of the grasslands on the Tibetan Plateau (TP) is seen as ongoing process. This general assumption is based on small scale studies which are not comparable because field methods and indicators differ among the investigations. Thus, especially for remote areas, a remotely sensed monitoring system is critically needed to monitor degradation. Additionally, a single and comparable product for the entire TP is of urgent concern to evaluate the ecological consequences of the assumed ongoing degradation on ecosystem services provided by the grasslands on the TP. As indicator for degradation plant cover was used in this study because a close link between degradation and plant cover has been identified by several previous studies on the TP. Thus, we implemented a four-scale remote sensing approach to derive plant cover. As reference and validation data, field records were taken between 2011 and 2013 at 15 locations spanning the entire TP and covering all grazed grassland vegetation types. Plant cover was measured in situ at up to 210 plots per location using standardized taken digital photos. To classify green vegetated parts in the digital photos, simple threshold classifications were applied to the ratio of red and green color values. The geographical position of all plots was recorded using a differential GPS. Plant cover was derived from satellite data at three scales using spectral angle mapper (SAM), normalized difference band indices and linear spectral unmixing. The result of the first two approaches was transferred to plant cover using multiple linear regression techniques. Reference spectra and endmember spectra for SAM and linear spectral unmixing were recorded using a field spectrometer. The hyperspectral information was resampled to satellite bands using the spectral response functions of the sensors. To derive plant cover at local scale, we classified 35 high resolution WorldView-2, Quickbird and RapidEye satellite images using the in situ

  19. Land Remote Sensing Overview

    NASA Technical Reports Server (NTRS)

    Byrnes, Ray

    2007-01-01

    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.

  20. Remote sensing applications program

    NASA Technical Reports Server (NTRS)

    1984-01-01

    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.

  1. Evaluation of a Remotely Sensed Evaporative Stress Index for Monitoring Patterns of Anomalous Water Use

    NASA Astrophysics Data System (ADS)

    Anderson, M. C.; Hain, C.; Otkin, J.; Zhan, X.

    2012-12-01

    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 moisture storage. In contrast, evapotranspiration (ET) anomalies provide unique yet complementary information, reflecting variations in actual water use by crops and direct evaporation from the soil. For example, precipitation- and ET-based anomalies may differ significantly in regions of intensive irrigation, shallow water table, or deep rooting depth - areas where plants may be more resilient to soil moisture deficiencies inferred from rainfall patterns. In addition, an ET-based index can better capture impacts of hot, windy conditions leading to "flash droughts", where anomalously high water use precipitates rapid decay in soil moisture and crop condition. Here we describe a remotely sensed Evaporative Stress Index (ESI) based on anomalies in actual-to-reference ET ratio, and compare with patterns in precipitation-based drought indicators. Actual ET is derived from thermal remote sensing, using the morning land-surface temperature (LST) rise observed with geostationary satellites. In comparison with vegetation indices, LST is a fast-response variable, with the potential for providing early warning of crop stress reflected in increasing canopy temperatures. Spatiotemporal patterns in ESI reasonably match those in precipitation-based indices (such as SPI and modeled SM) and patterns in the U.S. Drought Monitor. However, because ESI does not use precipitation as an input, it provides an independent assessment of evolving drought conditions, and is more portable to data-sparse parts of the world lacking dense rain-gauge and Doppler radar networks. Integrating LST information from polar orbiting systems, the ESI has unique potential for sensing moisture stress at field scale

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  3. Monitoring road losses for Lushan 7.0 earthquake disaster utilization multisource remote sensing images

    NASA Astrophysics Data System (ADS)

    Huang, He; Yang, Siquan; Li, Suju; He, Haixia; Liu, Ming; Xu, Feng; Lin, Yueguan

    2015-12-01

    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.

  4. Soil water sensing methods-Usefulness for evapotranspiration monitoring and links to remote sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  5. Assessment of Superflux relative to fisheries research and monitoring. [airborne remote sensing of the Chesapeake bay plume and shelf regions

    NASA Technical Reports Server (NTRS)

    Thomas, J. P.

    1981-01-01

    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.

  6. Volcanic lava flow hot-spots monitoring from remote sensing data using neural networks

    NASA Astrophysics Data System (ADS)

    Piscini, Alessandro; Lombardo, Valerio

    2014-05-01

    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

  7. Remote sensing monitoring of bean crop cultivated in the Boi Branco watershed (Brazil)

    NASA Astrophysics Data System (ADS)

    Soares da Silva, Natália; Sánchez-Román, Rodrigo; Marchamalo Sacristán, Miguel; Rodriguez-Sinobas, Leonor

    2016-04-01

    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.

  8. Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS).

    PubMed

    Zhang, Yuanzhi; Chen, Zhengyi; Zhu, Boqin; Luo, Xiuyue; Guan, Yanning; Guo, Shan; Nie, Yueping

    2008-12-01

    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. PMID:18197462

  9. Remote sensing of wetlands

    NASA Technical Reports Server (NTRS)

    Roller, N. E. G.

    1977-01-01

    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.

  10. Product amount and quality monitoring in agricultural fields with remote sensing satellite and radio-control helicopter

    NASA Astrophysics Data System (ADS)

    Arai, Kohei

    Product amount and quality monitoring in agricultural fields with remote sensing satellite and radio-control helicopter is proposed. In particular, tealeaves and rice crop quality and amoujnt monitorings are peoposed as examples. Nitrogen rich tealeaves tasts good. Therefore, quality of tealeaves can be estimated with nitrogen content which is related with near infrared reflectance of the tealeves in concern. Also, rice crop quality depends on protein content in rice grain which is related to near infrared reflectance of rice leaves. Therefore, product quality can be estimated with observation of near infrared reflectance of the leaves in concern. Near infared reflectance is provided by near infrared radiometers onboard remote sensing satellites and by near infrared cameras onboard radio-control helicopter. This monitoring system is applicable to the other agricultural plant products. Through monitoring near ingfrared reflectance, it is possible to estimate quality as well as product amount.

  11. Monitoring the Philippine Forest Cover Change Using Ndvi Products of Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Torres, R. C.; Mouginis-Mark, P.; Wright, R.; Garbeil, H.; Craig, B.

    2004-12-01

    The Philippines has one of the world's fastest disappearing forest cover, which is being lost to natural processes and landscape-modifying human activities. Currently, forested landscape covers 24% (i.e., 7.2 million hectares) of the Philippines' total land area, of which only 800,000 hectares are considered as old-growth forests. Occasionally, volcanic activities and earthquakes cause large-scale impacts on the forest cover, but the systematic reduction of the country's forest has been sustained through unregulated logging operations and other human-induced landscape modification. Reforestation and watershed protection have become important public policy programs as forest denudation is linked to recent devastating landslides, debris flows and flashfloods. However, many watershed areas that are at risk to deforestation are hardly accessible to ground-based monitoring. A spaced-based monitoring system facilitates an efficient and timely response to changes in the quality and extent of the Philippine forest cover. This monitoring system relies in the generation of Normalized Difference Vegetation Index (NDVI) products from the red and infrared bands of remote sensing data, which correlates with the amount of chlorophyll in the vegetation. Given the existing forest classification maps, non-forested regions are masked in the data analysis, so that only forest-related changes in the vegetation are shown in the NDVI image difference products. A combination of two MODIS-bearing satellites, i.e., Terra and Aqua, acquire high temporal and moderate spatial resolution data, enabling the countrywide detection of vegetation changes within a certain observation period. MODIS data are calibrated for setting the pixel quality thresholds, which minimize the artifact of clouds and haze in the analysis. Areas showing dramatic changes are further investigated using higher resolution data, such as ASTER and Landsat 7 ETM. Sequential NDVI products of remote sensing data provide

  12. Applications of Remote Sensing

    NASA Astrophysics Data System (ADS)

    Jacha, Charlene

    2015-04-01

    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

  13. Global pollution aerosol monitoring (GPAM) in the atmospheric boundary layer using future earth observing satellite remote sensing

    NASA Astrophysics Data System (ADS)

    Qu, Jianhe; Kafatos, Menas; Yang, Ruixin; Chiu, Long S.; Riebau, Allen R.

    2003-04-01

    Global pollution aerosol monitoring is a very important climatic and environmental problem. It affects not only human health but also ecological systems. Because most pollution aerosols are concentrated in the atmospheric boundary layer where human, animal and vegetation live, global pollution aerosol stuides have been an important topic since about a decade ago. Recently, many new chemistry remote sensing satellite systems, such as NASA's Aura (EOS-CHEM), have been established. However, pollution aerosols in the atmospheric boundary layer cannot be detected using current remote sensing technologies. George Mason University (GMU) proposes to design scientific algorithms and technologies to monitor the atmospheric boundary layer pollution aerosols, using both satellite remote sensing measurements and ground measurements, collaborating with NASA and the United States Department of Agriculture (USDA)/Forest Services (FS). Boundary layer pollution aerosols result from industrial pollution, desert dust storms, smoke from wildfires and biomass burning, volcanic eruptions, and from other trace gases. The current and next generation satellite instruments, such as The Ozone Mapping and Profiler Suite (OMPS), Ozone Monitoring Instrument (OMI), Thermal Emission Spectrometer (TES), and High Resolution Dynamics Limb Sounder (HIRDLS) can be used for this study. Some surface measurements from USDA/FS and other agencies may also be used in this study. We will discuss critical issues for GPAM in the boundary layer using Earth observing satellite remote sensing in detail in this paper.

  14. Incorporating remote sensing data in crop model to monitor crop growth and predict yield in regional area

    NASA Astrophysics Data System (ADS)

    Guo, Jianmao; Lu, Weisong; Zhang, Guoping; Qian, Yonglan; Yu, Qiang; Zhang, Jiahua

    2006-12-01

    Accurate crop growth monitoring and yield predicting is very important to food security and agricultural sustainable development. Crop models can be forceful tools for monitoring crop growth status and predicting yield over homogeneous areas, however, their application to a larger spatial domains is hampered by lack of sufficient spatial information about model inputs, such as the value of some of their parameters and initial conditions, which may have great difference between regions even fields. The use of remote sensing data helps to overcome this problem. By incorporating remote sensing data into the WOFOST crop model (through LAI), it is possible to incorporate remote sensing variables (vegetation index) for each point of the spatial domain, and it is possible for this point to re-estimate new values of the parameters or initial conditions, to which the model is particularly sensitive. This paper describes the use of such a method on a local scale, for winter wheat, focusing on the parameters describing emergence and early crop growth. These processes vary greatly depending on the soil, climate and seedbed preparation, and affect yield significantly. The WOFOST crop model is calibrated under standard conditions and then evaluated under test conditions to which the emergence and early growth parameters of the WOFOST model are adjusted by incorporating remote sensing data. The inversion of the combined model allows us to accurately monitoring crop growth status and predicting yield on a regional scale.

  15. Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.

    2015-12-01

    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.

  16. Polarization In Remote Sensing

    NASA Astrophysics Data System (ADS)

    Egan, Walter G.

    1988-06-01

    Various aspects of polarization in remote sensing are presented including mathematical treatments and selected experimental observations. The observations are of the percent polarization from Haleakala volcanic ash, basalt powder, rhyolytic oumice. rose quartz, niccolite, ilmenite, black oak leaves. dried red pine needles, a New Haven red pine stand, moist soil, the sky above Mauna Loa Observatory, the sky above Long Island in summer and winter, and cirrus clouds. Also, space based shuttle photographic observations of polarization are described. Instrumental polarization from a Cassegrainian telescope is described as well as the design of an imaging soectropolarimeter for remote sensing. A list is presented of twelve polarimetric properties associated with remote sensing.

  17. Remote sensing program

    NASA Technical Reports Server (NTRS)

    Philipson, W. R. (Principal Investigator)

    1983-01-01

    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.

  18. InfoSequia: the first operational remote sensing-based Drought Monitoring System of Spain

    NASA Astrophysics Data System (ADS)

    Contreras, Sergio; Hunink, Johannes E.

    2016-04-01

    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.

  19. Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

    NASA Astrophysics Data System (ADS)

    Hashim, M.; Pour, A. B.; Onn, C. H.

    2014-02-01

    Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper+ (ETM+) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM+ dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate.

  20. Remote Sensing of Environmental Pollution

    NASA Technical Reports Server (NTRS)

    North, G. W.

    1971-01-01

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

  1. Monitoring displacements of an earthen dam using GNSS and remote sensing

    NASA Astrophysics Data System (ADS)

    Dardanelli, Gino; La Loggia, Goffredo; Perfetti, Nicola; Capodici, Fulvio; Puccio, Luigi; Maltese, Antonino

    2014-10-01

    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.

  2. Remote Sensing Methods

    NASA Technical Reports Server (NTRS)

    Sever, Thomas L.

    1998-01-01

    Remotely sensed data allows archeologists and historic preservationists the ability to non-destructively detect phenomena previously unobservable to them. Archeologists have successfully used aerial photography since the turn of the century and it continues to be an important research tool today. Multispectral scanners and computer-implemented analysis techniques extend the range of human vision and provides the investigator with innovative research designs at scales previously unimaginable. Pioneering efforts in the use of remote sensing technology have demonstrated its potential, but it is the recent technological developments in remote sensing instrumentation and computer capability that provide for unlimited, cost-effective applications in the future. The combination of remote sensing, Global Positioning System (GPS) technology, and Geographic Information Systems (GIS) are radically altering survey, inventory, and modelling approaches.

  3. Remote Sensing Information Classification

    NASA Technical Reports Server (NTRS)

    Rickman, Douglas L.

    2008-01-01

    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.

  4. A Protocol for Retrospective Remote-Sensing-based Ecological Monitoring of Rangelands

    NASA Astrophysics Data System (ADS)

    Washington-Allen, R. A.; West, N. E.; Ramsey, R. D.; Efroymson, R. A.

    2009-12-01

    Because the condition and trend of drylands in the United States at sub-regional to national scales is unknown, this paper presents a protocol for the monitoring and assessment of dryland degradation using historical remote sensing. Traditional field-based monitoring has proven inadequate for capturing the changes in spatial and temporal heterogeneity that may adversely affect drylands at sub-regional to national spatial scales. Continuous monitoring data of 14 to 25 years is required to detect and separate the effects of climatic processes from those induced by land management practices. However, few field-based datasets exist that have measured the trend of appropriate ecological indicators at regional to national scales. Landsat data has been collected and archived at least once-a month since 1972, and includes complete coverage of US drylands. Five assessment endpoints that relate to land degradation can be retrospectively measured for the last 33 years using surrogate indicators derived from Landsat imagery: change in vegetation physiognomy, decline in vegetation productivity, accelerated soil erosion, decline in soil quality, and change in landscape composition and configuration. Consequently, this protocol considers (1) how land degradation is characterized, i.e., what indicators are assessed, (2) which indicators are measured, (3) what reference conditions are appropriate, (4) which temporal and spatial scales are of concern, and finally, (5) which statistics and/or analyses are appropriate for determining the significance of a change? Aspects of two retrospective studies are presented as examples of application of the protocol to considerations of the land use impacts from military training and testing, and commercial grazing activities on drylands.

  5. Assessing the Remotely Sensed Drought Severity Index for Agricultural Drought Monitoring in North China

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Huang, J.; Mu, Q.

    2014-12-01

    With a warming climate, the world has experienced frequent droughts during the past few decades. A remotely sensed Drought Severity Index (DSI), which integrates both vegetation growth condition and evapotranspiration, has been recently proposed for drought monitoring at the global scale. However, there has been little research on its utility for regional application, especially on agricultural drought. As an important winter wheat producing region, the North China has suffered from frequent droughts in recent years. In this study, the capability of the DSI for drought monitoring and impact analysis in five wheat producing provinces of North China was investigated. First, the DSI was compared with precipitation and soil moisture to show its ability for characterizing moisture status. Then specifically for agricultural drought, the DSI was evaluated against agricultural drought severity and the impacts of drought on crop yield during the growing season were also explored using the 8-day DSI data. The main conclusions are: (1) The DSI shows generally good ability for characterizing moisture conditions at the province level with varying ability during winter wheat main growing season (March-June), and the best relationship was found in April. (2) Despite varying capability, the DSI is quite effective in characterizing agricultural drought severity at the province level. (3) Drought shows generally increasing agricultural impacts during winter wheat main growing season (March-June), with little impacts in March (green-up stage), emerging impacts in April (jointing and booting stages) and significant drought impacts in May (heading and filling stages). (4) Based on the spatial pattern of agricultural drought impacts, densely winter wheat planted areas such as South Hebei, Central/West Shandong and North/East Henan are identified as drought vulnerable regions and comprehensive monitoring in these hotspots is highly recommended.

  6. Evaluating the Potential Use of Remotely-Sensed and Model-Simulated Soil Moisture for Agricultural Drought Risk Monitoring

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    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.

  7. A Remote Sensing-Based Land Surface Phenology Application for Cropland Monitoring in the Volta River Basin of West Africa

    NASA Astrophysics Data System (ADS)

    Abd Salam El Vilaly, Mohamed; El Vilaly, Audra; Badiane, Ousmane

    2015-04-01

    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.

  8. A novel approach to co registering multi-temporal remotely sensed data in a vulnerability monitoring framework

    NASA Astrophysics Data System (ADS)

    Harb, Mostapha; De Vecchi, Daniele; Dell'Acqua, Fabio

    2014-05-01

    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

  9. Online Remote Sensing Interface

    NASA Technical Reports Server (NTRS)

    Lawhead, Joel

    2007-01-01

    BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

  10. Investigate the Capabilities of Remotely Sensed Crop Indicators for Agricultural Drought Monitoring in Kansas

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Becker-Reshef, I.; Justice, C. O.

    2013-12-01

    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

  11. Inferential monitoring of global change impact on biodiversity through remote sensing and species distribution modeling

    NASA Astrophysics Data System (ADS)

    Sangermano, Florencia

    2009-12-01

    The world is suffering from rapid changes in both climate and land cover which are the main factors affecting global biodiversity. These changes may affect ecosystems by altering species distributions, population sizes, and community compositions, which emphasizes the need for a rapid assessment of biodiversity status for conservation and management purposes. Current approaches on monitoring biodiversity rely mainly on long term observations of predetermined sites, which require large amounts of time, money and personnel to be executed. In order to overcome problems associated with current field monitoring methods, the main objective of this dissertation is the development of framework for inferential monitoring of the impact of global change on biodiversity based on remotely sensed data coupled with species distribution modeling techniques. Several research pieces were performed independently in order to fulfill this goal. First, species distribution modeling was used to identify the ranges of 6362 birds, mammals and amphibians in South America. Chapter 1 compares the power of different presence-only species distribution methods for modeling distributions of species with different response curves to environmental gradients and sample sizes. It was found that there is large variability in the power of the methods for modeling habitat suitability and species ranges, showing the importance of performing, when possible, a preliminary gradient analysis of the species distribution before selecting the method to be used. Chapter 2 presents a new methodology for the redefinition of species range polygons. Using a method capable of establishing the uncertainty in the definition of existing range polygons, the automated procedure identifies the relative importance of bioclimatic variables for the species, predicts their ranges and generates a quality assessment report to explore prediction errors. Analysis using independent validation data shows the power of this

  12. Wildfire monitoring via the integration of remote sensing with innovative information technologies

    NASA Astrophysics Data System (ADS)

    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.

    2012-04-01

    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

  13. River Sediment Monitoring Using Remote Sensing and GIS (case Study Karaj Watershed)

    NASA Astrophysics Data System (ADS)

    Shafaie, M.; Ghodosi, H.; Mostofi, K. H.

    2015-12-01

    Whereas the tank volume and dehydrating digits from kinds of tanks are depended on repository sludge, so calculating the sediments is so important in tank planning and hydraulic structures. We are worry a lot about soil erosion in the basin area leading to deposit in rivers and lakes. It holds two reasons: firstly, because the surface soil of drainage would lose its fertility and secondly, the capacity of the tank decreases also it causes the decrease of water quality in downstream. Several studies have shown that we can estimate the rate of suspension sediments through remote sensing techniques. Whereas using remote sensing methods in contrast to the traditional and current techniques is faster and more accurate then they can be used as the effective techniques. The intent of this study has already been to estimate the rate of sediments in Karaj watershed through remote sensing and satellite images then comparing the gained results to the sediments data to use them in gauge-hydraulic station. We mean to recognize the remote sensing methods in calculating sediment and use them to determine the rate of river sediments so that identifying their accuracies. According to the results gained of the shown relations at this article, the amount of annual suspended sedimentary in KARAJ watershed have been 320490 Tones and in hydrologic method is about 350764 Tones .

  14. Breaking the barriers to adopting satellite remote sensing for water quality management: ?monitoring cyanobacteria blooms

    EPA Science Inventory

    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...

  15. Hyperspectral remote sensing and geospatial modeling for monitoring invasive plant species

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is used to show the actual distribution of distinctive invasive weeds such as leafy spurge (Euphorbia esula L.), whereas landscape modeling can show the potential distribution over an area. Geographic information system data and hyperspectral imagery [NASA JPL’s Airborne Visible Infra...

  16. Use of remotely sensed evapotranspiration maps for monitoring drought impacts at field to continental scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  17. MONITORING GLOBAL CHANGE: COMPARISON OF FOREST COVER ESTIMATES USING REMOTE SENSING AND INVENTORY APPROACHES

    EPA Science Inventory

    Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. n this study, the authors compared forest cover estimates from a recently developed ...

  18. Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches.

    PubMed

    Turner, D P; Koerper, G; Gucinski, H; Peterson, C; Dixon, R K

    1993-07-01

    Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution ∼1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid. PMID:24220843

  19. Low resolution optical remote sensing applied to the monitoring of seasonal glacier mass balance.

    NASA Astrophysics Data System (ADS)

    Drolon, Vanessa; Maisongrande, Philippe; Berthier, Etienne; Swinnen, Else

    2015-04-01

    Mass balance is a key variable to describe the state of health of glaciers, their contribution to sea level rise and, in a few dry regions, their role in water resource. We explore here a new method to retrieve seasonal glacier mass balances from low resolution optical remote sensing. We derive winter and summer snow maps for each year during 1998-2014, using the Normalized Difference Snow Index (NDSI) computed from visible and SWIR channels available with SPOT/VEGETATION. The NDSI dynamic is directly linked to the area percentage of snow in the VGT kilometric pixel. The combination of 15 years of 10-daily NDSI maps with the SRTM DEM allows us to calculate the altitude of the transition between bare soil and snow. Then, we compare the interannual dynamic of this altitude with in situ measurements of mass balance available for 60 alpine glaciers (Huss et al., 2010; Zemp et al., 2009, 2013) and find promising relationships for winter mass balance. We also explore the possibility of a real-time monitoring of winter mass balance for a selection of alpine glaciers. Finally, we discuss the robustness and genericity of these relationships for their future application in regions where in situ glaciers mass balances are scarce or not available.

  20. Monitoring landscape response to climate change using remote sensing and GIS techniques

    SciTech Connect

    Yuhas, R.H.; Dolan, P.H.; Goetz, A.F.H. )

    1992-01-01

    Increasing concern over the threat of global warming has precipitated the need for study sites which can be scientifically monitored to detect and follow the effects of environmental landscape change. Extensive eolian dune deposits in northeastern Colorado provide an ideal study site. These dune complexes, found along the South Platte River, are currently stabilized by a thin cover of shortgrass prairie vegetation. However, stratigraphic evidence demonstrates that during at least four times in the past 10,000 years, the dunes were actively migrating across the landscape. In addition, climate models indicate that the High Plains could be one of the first areas to react to climate changes when they occur. The scaling relationships that contribute to the evolution of the landscape are nearly impossible to understand without the regional perspective that remote sensing and geographical information system (GIS) techniques provide. Imagery acquired with the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is processed to detect the amount of sand exposed, as well as the percent vegetation cover that is currently stabilizing the dunes. Excellent discrimination is found between areas of low and no vegetation, something not possible with traditional analysis methods. Seasonal changes are also emphasized. This information is incorporated into the GIS database the authors created, which also has information on parameters that influence the landscape: elevation, soil type, surface/subsurface hydrology, etc. With these data areas that are susceptible to climate change are highlighted, but more importantly, the reasons for the susceptibility are determined using the GIS's analytical capabilities.

  1. Mid Term Progress Report: Desertification Assessment and Monitoring in China Based on Remote Sensing

    NASA Astrophysics Data System (ADS)

    Gao, Zhihai; del Barrio, Gabriel; Li, Xiaosong; Wang, Bengyu; Puigdefabregas, Juan; Sanjuan, Maria E.; Bai, Lina; Wu, Junjun; Sun, Bin; Li, Changlong

    2014-11-01

    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.

  2. Using remote sensing to monitor surface freshwater storage in the Congo basin

    NASA Astrophysics Data System (ADS)

    Becker, M.; Bejannin, S.; Papa, F.; Frappart, F.; Calmant, S.; Santos Da Silva, J.

    2015-12-01

    Despite the global importance of the Congo Basin, which is the second largest river basin in the world, only a small number of studies to date have focused on its hydro-climatic variability. The limited understanding of climate dynamics in the Congo Basin is in part due to the lack of the in situ monitoring of climate variables in that area. Given the vast size of the Congo Basin, remote sensing observations provide the only viable approach to understanding the spatial and temporal variability of the basin's hydro-climatic patterns. To apprehend the water cycle of the Congo basin it is important to know how the freshwater is stored in this basin and its spatial and temporal dynamics. In this study, a multi-satellite approach is proposed to estimate the water stored in the floodplains of the Congo Basin at monthly time-scale using the surface water extent from the Global Inundation Extent Multi-Satellite (GIEMS) and the water level fluctuations derived from ENVISAT Radar Altimeter. The combination of these datasets for their overlapping period of record, from 2003 to 2007, enabled us to compute water level maps from which we estimated surface water storage in the Congo Basin.

  3. Urban ecological environment monitoring and evaluation based on remote sensing ecological index

    NASA Astrophysics Data System (ADS)

    Cheng, Peng-gen; Tong, Cheng-zhuo; Chen, Xiao-yong; Nie, Yun-ju

    2015-12-01

    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.

  4. Ground-based remote sensing scheme for monitoring aerosol-cloud interactions

    NASA Astrophysics Data System (ADS)

    Sarna, K.; Russchenberg, H. W. J.

    2015-11-01

    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.

  5. Monitoring land cover dynamics in the Aral Sea region by remote sensing

    NASA Astrophysics Data System (ADS)

    Kozhoridze, Giorgi; Orlovsky, Leah; Orlovsky, Nikolai

    2012-10-01

    The Aral Sea ecological crisis resulted from the USSR government decision in 1960s to deploy agricultural project for cotton production in Central Asia. Consequently water flow in the Aral Sea decreased drastically due to the regulation of Amydarya and Syrdarya Rivers for irrigation purposes from 55-60 km3 in 1950s to 43 km3 in 1970s, 4 km3 in 1980s and 9-10 km3 in 2000s. Expert land cover classification approach gives the opportunity to use the unlimited variable for classification purposes. The band algebra (band5/band4 and Band4/Band3) and remote sensing indices (Normalized differential Salinity Index (NDSI), Salt Pan Index (SPI), Salt Index (SI), Normalized difference Vegetation Index (NDVI), Albedo, Crust Index) utilized for the land cover classification has shown satisfactory result with classification overall accuracy 86.9 % and kappa coefficient 0.85. Developed research algorithm and obtained results can support monitoring system, contingency planning development, and improvement of natural resources rational management.

  6. Improving Rangeland Monitoring and Assessment: Integrating Remote Sensing, GIS, and Unmanned Aerial Vehicle Systems

    SciTech Connect

    Robert Paul Breckenridge

    2007-05-01

    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

  7. Vegetation water stress monitoring with remote sensing-based energy balance modelling

    NASA Astrophysics Data System (ADS)

    González-Dugo, Maria P.; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; José Polo, María

    2014-05-01

    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

  8. LOCAL AIR: Local Aerosol monitoring combining in-situ and Remote Sensing observations

    NASA Astrophysics Data System (ADS)

    Mona, Lucia; Caggiano, Rosa; Donvito, Angelo; Giannini, Vincenzo; Papagiannopoulos, Nikolaos; Sarli, Valentina; Trippetta, Serena

    2015-04-01

    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

  9. Application of HJ-1A/B and ZY-3 remote sensing data for drought monitoring in Hubei Province China

    NASA Astrophysics Data System (ADS)

    Huang, He; Fan, Yida; Yang, Siquan; Wen, Qi; Pan, Donghua; Fan, Chunbo; He, Haixia

    2013-10-01

    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.

  10. A potential to monitor nutrients as an indicator of rangeland quality using space borne remote sensing

    NASA Astrophysics Data System (ADS)

    Ramoelo, A.; Cho, M. A.; Madonsela, S.; Mathieu, R.; van der Korchove, R.; Kaszta, Z.; Wolf, E.

    2014-02-01

    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.

  11. Monitoring the coastline change of Hatiya Island in Bangladesh using remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Ghosh, Manoj Kumer; Kumar, Lalit; Roy, Chandan

    2015-03-01

    A large percentage of the world's population is concentrated along the coastal zones. These environmentally sensitive areas are under intense pressure from natural processes such as erosion, accretion and natural disasters as well as anthropogenic processes such as urban growth, resource development and pollution. These threats have made the coastal zone a priority for coastline monitoring programs and sustainable coastal management. This research utilizes integrated techniques of remote sensing and geographic information system (GIS) to monitor coastline changes from 1989 to 2010 at Hatiya Island, Bangladesh. In this study, satellite images from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) were used to quantify the spatio-temporal changes that took place in the coastal zone of Hatiya Island during the specified period. The modified normalized difference water index (MNDWI) algorithm was applied to TM (1989 and 2010) and ETM (2000) images to discriminate the land-water interface and the on-screen digitizing approach was used over the MNDWI images of 1989, 2000 and 2010 for coastline extraction. Afterwards, the extent of changes in the coastline was estimated through overlaying the digitized maps of Hatiya Island of all three years. Coastline positions were highlighted to infer the erosion/accretion sectors along the coast, and the coastline changes were calculated. The results showed that erosion was severe in the northern and western parts of the island, whereas the southern and eastern parts of the island gained land through sedimentation. Over the study period (1989-2010), this offshore island witnessed the erosion of 6476 hectares. In contrast it experienced an accretion of 9916 hectares. These erosion and accretion processes played an active role in the changes of coastline during the study period.

  12. Monitoring the Environment using High-Spatial Resolution Remote Sensing: Contribution to Health Information Systems

    NASA Astrophysics Data System (ADS)

    Tourre, Y. M.; Lacaux, J.

    2007-12-01

    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.

  13. Superflux I, II, and III experiment designs: Water sampling and analyses. [Chespeake Bay, environmental monitoring and remote sensing

    NASA Technical Reports Server (NTRS)

    Thomas, J. P.

    1981-01-01

    Both airborne remote sensors and seagoing research vessels were used to study the effects of man's continual use of the Chesapeake Bay offshore environments. The major focus of the study was to: (1) advance the development and transfer of improved remote sensing systems and techniques for monitoring environmental quality and effects on living marine resources; (2) increase understanding of the influence of estuarine outwellings (plumes) on contiguous shelf ecosystems; and (3) provide a synoptic, integrated and timely data base for application to problems of marine resources and environmental quality.

  14. Water quality monitoring by remote sensing in Hushan Tailings Reservoir of Huji, Hubei Province

    NASA Astrophysics Data System (ADS)

    Yang, Qiang; Zhang, Zhi; Chen, Wei-tao; Qian, Li-ping

    2008-11-01

    In this paper, the water quality of Hushan Tailings reservoir in Huji, Zhongxiang of Hubei province, was studied by remote sensing technology. Firstly, radioactive correction of ASTER data was processed by FLAASH Model, then the scatter was produced by SPSS, which was about reflectance or reflectance ratio of remote sensing(ASTER) and measured pollutant (Ag+, Ba2+, Hg2+, Ca2+, Mg2+, F-, Cl- , NO3-, H2PO4-, SO42-, et.)at sampling sites. After experimentation,conversion model was built with significance test, F=68.797(F0.05=11.821), R=0.793. Finally, the data of water reflectance was processed with our model, and the distribution of corresponding pollutant was obtained.

  15. The economic impact of remote sensing data as the source of nonpoint pollution monitoring and control

    NASA Technical Reports Server (NTRS)

    Miller, W. L.

    1974-01-01

    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.

  16. Synergies of the European Microwave Remote Sensing Missions SMOS and ASCAT for Monitoring Soil Moisture

    NASA Astrophysics Data System (ADS)

    Scipal, K.; Wagner, W.

    2003-04-01

    The lack of global soil moisture observations is one of the most glaring and pressing deficiencies in current research activities of related fields, from climate monitoring and ecological applications to the quantification of biogeophysical fluxes. This has implications for important issues of the international political agenda like managing global water resources, securing food production and studying climate change. Currently it is held that only microwave remote sensing offers the potential to produce reliable global scale soil moisture information economically. Recognising the urgent need for a soil moisture mission several international initiatives are planning satellite missions dedicated to monitor the global hydrological cycle among them two European microwave satellites. ESA is planning to launch the Soil Moisture and Ocean Salinity Mission SMOS, in 2006. SMOS will measure soil moisture over land and ocean salinity over the oceans. The mission rests on a passive microwave sensor (radiometer) operated in L-band which is currently believed to hold the largest potential for soil moisture retrieval. One year before (2005) EUMETSAT will launch the Meteorological Operational satellite METOP which carries the active microwave system Advanced Scatterometer ASCAT on board. ASCAT has been designed to retrieve winds over the oceans but recent research has established its capability to retrieve soil moisture. Although currently it is hold that, using active microwave techniques, the effect of surface roughness dominates that of soil moisture (while the converse is true for radiometers), the ERS scatterometer was successfully used to derive global soil moisture information at a spatial resolution of 50 km with weekly to decadal temporal resolution. The quality of the soil moisture products have been assessed by independent experts in several pilot projects funded by the European Space Agency. There is evidence to believe that both missions will provide a flow of

  17. Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine)

    NASA Technical Reports Server (NTRS)

    Trelogan, Jessica; Crawford, Melba; Carter, Joseph

    2002-01-01

    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.

  18. Monitoring of 2009 Krishna River Flood using Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Murthy, A.; Gouda, K. C.; Bhat, R.; Laxmikantha, B. P.; Prabhuraj, D. K.

    2012-12-01

    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.

  19. Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

    2010-01-01

    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.

  20. Agriculture In Uruguay: New Methods For Drought Monitoring and Crop Identification Using Remotely Sensed Data

    NASA Astrophysics Data System (ADS)

    Lessel, J.; Ceccato, P.

    2014-12-01

    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.

  1. The laser absorption spectrometer - A new remote sensing instrument for atmospheric pollution monitoring

    NASA Technical Reports Server (NTRS)

    Shumate, M. S.

    1974-01-01

    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.

  2. Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China

    PubMed Central

    Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

    2008-01-01

    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.

  3. Aerosol Remote Sensing

    NASA Technical Reports Server (NTRS)

    Lenoble, Jacqueline (Editor); Remer, Lorraine (Editor); Tanre, Didier (Editor)

    2012-01-01

    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.

  4. Applied remote sensing

    SciTech Connect

    Lo, C.P.

    1986-01-01

    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.

  5. Remote sensing and image interpretation

    NASA Technical Reports Server (NTRS)

    Lillesand, T. M.; Kiefer, R. W. (Principal Investigator)

    1979-01-01

    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.

  6. Engaging Remote Sensing and Citizen Science into Water Quality Monitoring: A Case Study in Nhue-Day River Basin, Vietnam

    NASA Astrophysics Data System (ADS)

    Thi Van Le, Khoa; Minkman, Ellen; Nguyen Thi Phuong, Thuy; Rutten, Martine; Bastiaanssen, Wim

    2016-04-01

    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.

  7. The Calibration and Characterization of Earth Remote Sensing and Environmental Monitoring Instruments. Chapter 10

    NASA Technical Reports Server (NTRS)

    Butler, James J.; Johnson, B. Carol; Barnes, Robert A.

    2005-01-01

    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) [1]. 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 [2] 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 [3]. An example of the study of a small-scale anthropogenic influence in climate variability is the Atlanta Land

  8. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation

    PubMed Central

    Kilpatrick, Adam D.; Lewis, Megan M.; Ostendorf, Bertram

    2015-01-01

    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

  9. Environmental monitoring based on automatic change detection from remotely sensed data: kernel-based approach

    NASA Astrophysics Data System (ADS)

    Shah-Hosseini, Reza; Homayouni, Saeid; Safari, Abdolreza

    2015-01-01

    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

  10. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

    PubMed

    Kilpatrick, Adam D; Lewis, Megan M; Ostendorf, Bertram

    2015-01-01

    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

  11. Dynamic change monitoring of forest resource by using Remote Sensing and Markov Process in Loess Plateau of China

    NASA Astrophysics Data System (ADS)

    Qiao Yuliang, Q.; Zhao Shangmin, Z.

    Forest resource is the main body of ecosystem on the earth land which is indispensable regenerated resource in improving the entironment and boosting the quality of habitation At present with rapid development of society and economy the grim challenge has to be faced with because of decrease of forest resource and gradually aggravation of entironment Application of earth observation technology to monitoring the dynamic change of forest resource in Loess Plateau with quite fragile zoology and badly erosive soil therefore has increasingly important significance in developing Chinese national economy reserving zoology and forecasting the change of world environment This study applies remote sensing technology combined with Markov process to monitor and forecast the dynamic change of forest resource in Chinese Loess Plateau At first according to the dynamic change maps of the forest resource from remote sensing data in three different periods--1978 cent1987 and 2000 the transitions among the forest resource types in the Daning County --- a key pilot area of the Three North Protection Forest Project in Chinese Loess Plateau are acquired by combining the different remote sensing information sources during those different periods Then the transition probability matrices at two primary states 1978 and 1987 are established easily Based on the transition probability matrices we can simulate and forecast the forest dynamic transformation pattern and the forest-transforming tendency in the future periods The results of the

  12. Applications of remote sensing to watershed management

    NASA Technical Reports Server (NTRS)

    Rango, A.

    1975-01-01

    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.

  13. Use of remote sensing in agriculture

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  14. What does remote sensing do for ecology?

    NASA Technical Reports Server (NTRS)

    Roughgarden, J.; Running, S. W.; Matson, P. A.

    1991-01-01

    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.

  15. Remote Sensing and Reflectance Profiling in Entomology.

    PubMed

    Nansen, Christian; Elliott, Norman

    2016-01-01

    Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering. PMID:26982438

  16. EPA REMOTE SENSING RESEARCH

    EPA Science Inventory

    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...

  17. Solar System Remote Sensing

    NASA Technical Reports Server (NTRS)

    2002-01-01

    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.

  18. Application of remote sensing

    NASA Technical Reports Server (NTRS)

    Graff, W. J. (Compiler)

    1973-01-01

    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.

  19. Literature relevant to remote sensing of water quality

    NASA Technical Reports Server (NTRS)

    Middleton, E. M.; Marcell, R. F.

    1983-01-01

    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.

  20. Feasibility of Using Remotely Sensed Data to Aid in Long-Term Monitoring of Biodiversity

    NASA Technical Reports Server (NTRS)

    Carroll, Mark L.; Brown, Molly E.; Elders, Akiko; Johnson, Kiersten

    2014-01-01

    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.

  1. Data-intensive multispectral remote sensing of the nighttime Earth for environmental monitoring and emergency response

    NASA Astrophysics Data System (ADS)

    Zhizhin, M.; Poyda, A.; Velikhov, V.; Novikov, A.; Polyakov, A.

    2016-02-01

    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

  2. Monitoring shoreline and topographic changes using remotely sensed data: Example from east coast of Korea

    NASA Astrophysics Data System (ADS)

    Eom, Jinah; Choi, Jong-Kuk; Ryu, Joo-Hyung; Park, Chanhong

    2014-05-01

    Sandy beaches are important habitats for coastal organisms and act as buffer zones during coastal disasters. Along the eastern coast of Korea, most of the coastal zone consists of sandy beaches. However, beach erosion has accelerated in recent years. In this study, we analyzed topographic and shoreline changes in Uljin County on the east coast of Korea. We used remotely sensed data collected from 1971 to 2009, airborne light detection and ranging (LiDAR) data for 2008 and 2010, and terrestrial LiDAR data for 2008 and 2009. Three coastal locations were studied: the area around a nuclear power plant, the area around a stream, and the area around the East Sea Research Institute (ESRI), a branch of the Korea Institute of Ocean Science & Technology (KIOST). Analysis of shoreline changes showed the occurrence of sand deposition, resulting in shoreline movement toward the nuclear power plant by a maximum of 120 m. Deposition also occurred near ESRI, causing shoreline movement of a maximum of 45 m from 1971 to 2003; however, a maximum of 44 m erosion was detected from 2003 to 2009. Topographic changes were determined using the airborne LiDAR data and indicated approximately 1 m of sand deposition in the area around the nuclear power plant. In the area around the stream, both deposition and erosion were found, whereas around the ESRI region, erosion of approximately 3 m was identified. The analysis of terrestrial LiDAR data showed trends in shoreline change that were similar to those obtained from airborne LiDAR. Changes in the shoreline near the stream included sedimentation of approximately 7 m between 2008 and 2009, which was identified by terrestrial LiDAR data. The shoreline around ESRI changed by approximately 15 m owing to erosion. Our results suggest that construction of the nuclear power plant caused topographic and shoreline changes in our study area. Such shoreline changes will influence coastal management and preservation policy, and thus continuous monitoring

  3. Monitoring Regional Vegetation Changes in Seward Peninsula, Alaska, Using Optical Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Baek, Jin; Ahn, Ji Young; Lee, Yoo Kyung; Yoon, Young Jun; Kim, Jeong Woo

    2013-04-01

    The vegetation at the Seward Peninsula, Alaska, has been studied and characterized by transitions from boreal forest to tundra resulting from the influences of climate change on disturbance and species composition. Most of the studies, however, focus on global scale responses, providing little information on regional vegetation changes more related to either local topography or climate patterns. Since the regional vegetation trend may change along with the variations in the gross productivity and range expansion of particular vegetation species during growing seasons, the vegetation index retrieved from optical remote sensing data is useful to monitor the vegetation transitions over long time span at the area of interest with fine spatial resolution. Landsat-5 TM and -7 ETM+ acquired during growing seasons from 1985 to 2010 over the townsite of Council in Alaska are analyzed for the temporal analysis of Normalized Difference Vegetation Index (NDVI) trends. The study area consists of three major vegetation groups of shrub, forest and tundra sites as researched by Arctic Transitions in the Land-Atmosphere System, but no detailed information on vegetation transitions are available to date. For improvements, the radiometric and atmospheric corrections are carried out converting 8-bit digital numbers to physical units, such as at-sensor radiance or exoatmospheric Top-Of-Atmosphere (TOA) reflectance at the time of each acquisition since the Landsat data need to be preprocessed yielding high-quality science data. In addition, Dark Object Subtraction (DOS) is applied to the TOA reflectance in order to minimize atmospheric effects which contaminate NDVI values where a common radiometric scale is not assumed among the multi-temporal datasets. NDVI ranging from +1 to -1 can then be simply retrieved using red and near infra-red bands of corrected Landsat data. The trend of NDVI is expected to represent the decadal variations in regional vegetation status and will be further

  4. Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

    NASA Technical Reports Server (NTRS)

    Price, Kevin P.; Nellis, M. Duane

    1996-01-01

    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

  5. Earth surface remote sensing 2

    SciTech Connect

    Cecchi, G.; Zilioli, E.

    1998-12-31

    This volume contains the proceedings of EOS/SPIE Remote Sensing Symposium which was held September 21--24, 1998 in Barcelona, Spain. Topics of discussion include the following: geological applications, cultural heritage, and geological hazards; land management; passive remote sensing of the ocean and sea ice; and active remote sensing of the ocean and sea ice.

  6. THE EPA REMOTE SENSING ARCHIVE

    EPA Science Inventory

    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...

  7. Remote sensing to monitor monotypic weed patches in semi-arid grasslands

    NASA Astrophysics Data System (ADS)

    Planck, Laura

    Remote sensing technology has great potential for mapping weed distributions. Fine-scale weed distribution maps can provide means to evaluate the success of weed control methods, to guide selection of future control methods, and to examine factors that influence the creation and persistence of monotypic weed patches. Here I examined the effectiveness of different classification approaches in detecting dense monotypic patches of the late-phenology weeds Taeniatherum caput-medusae (medusahead) and Aegilops triuncialis (barbed goatgrass), among cool-season forage grasses (Bromus spp. and Avena spp.) across multiple years in semi-arid rangelands in northern California (USA). I found that color infrared photographs acquired at two key phenological periods produced more accurate classifications than those based on one image alone, and that inclusion of training sites did not improve the overall accuracy of a classification. I also examined the association of remnant litter with transitions in species dominance in medusahead, goatgrass or forage patches. Persistence of goatgrass-dominated patches was correlated with the amount of remnant litter present, but surprisingly that of medusahead was not, suggesting a potential need for different strategies in control of these two noxious species. Overall, this study shows that remote sensing can be used to create weed distribution maps of phenologically distinct species, and help us further understand community response to invasion and evaluate the effectiveness of management treatments.

  8. Remote Sensing Methods for Monitoring the Climates of Venus, Earth and Mars

    NASA Astrophysics Data System (ADS)

    Crisp, D.

    2008-12-01

    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.

  9. Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation

    NASA Astrophysics Data System (ADS)

    Nguyen, Uyen

    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

  10. Monitoring and Management of Coastal Zones Which are Under Flooding Risk with Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Direk, S.; Seker, D. Z.; Musaoglu, N.; Gazioglu, C.

    2012-12-01

    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.

  11. Detection and Monitoring of E-Waste Contamination through Remote Sensing and Image Analysis

    NASA Astrophysics Data System (ADS)

    Garb, Yaakov; Friedlander, Lonia

    2015-04-01

    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

  12. A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

    NASA Astrophysics Data System (ADS)

    Shen, Xin; Zhang, Jing; Yao, Huang

    2015-12-01

    Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

  13. Digitise This! A Quick and Easy Remote Sensing Method to Monitor the Daily Extent of Dredge Plumes

    PubMed Central

    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

    2012-01-01

    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

  14. Evapotranspiration and remote sensing

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Gurney, R.

    1982-01-01

    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.

  15. Remote Sensing Laboratory - RSL

    ScienceCinema

    None

    2015-01-09

    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.

  16. Remote Sensing Laboratory - RSL

    SciTech Connect

    2014-11-06

    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.

  17. Joint use of soil moisture and vegetation growth condition by remote sensing on the agricultural drought monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Yang, Siquan; Huang, He; He, Haixia; Li, Suju; Cui, Yan

    2015-12-01

    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.

  18. Advanced laser remote sensing

    SciTech Connect

    Schultz, J.; Czuchlewski, S.; Karl, R.

    1996-11-01

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

  19. Superflux I, II, and III experiment design: Remote sensing aspects

    NASA Technical Reports Server (NTRS)

    Campbell, J. W.; Esaias, W. E.; Hypes, W. D.

    1981-01-01

    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.

  20. New and Improved Remotely Sensed Products and Tools for Agricultural Monitoring Applications in Support of Famine Early Warning

    NASA Astrophysics Data System (ADS)

    Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Pedreros, D.; Husak, G. J.; Bohms, S.

    2011-12-01

    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.

  1. Remote sensing of Earth terrain

    NASA Technical Reports Server (NTRS)

    Kong, J. A.

    1993-01-01

    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.

  2. Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets

    USGS Publications Warehouse

    Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark

    2009-01-01

    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.

  3. Potential for monitoring soil erosion features and soil erosion modeling components from remotely sensed data

    NASA Technical Reports Server (NTRS)

    Langran, K. J.

    1983-01-01

    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.

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

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Fukuoka, Hiroshi

    2012-01-01

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

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

    SciTech Connect

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

    2012-06-01

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

  6. Remotely Sensed Images for Flood Monitoring: Lessons Learned from the 2011 Midwestern US Floods

    NASA Astrophysics Data System (ADS)

    Sivanpillai, R.

    2014-12-01

    Remotely sensed images acquired by the member agencies of the International Charter on Space and Major Disasters (Charter Call ID# 362) in response to the 2011 Midwestern US Floods provided valuable information to first responders in several states along the Mississippi River. Economic damages were estimated to exceed 2 billion USD. Images collected by optical and RADAR sensors on satellites operated by seven countries, along with archived satellite imagery were rapidly processed and provided to first-responders in these states for planning relief efforts. This operation required collaboration among numerous international, national and local agencies, and data vendors. This presentation will share the experiences gained as the project manager of this activation and will highlight the Charter's role in requesting satellite imagery for disasters, identifying experts to process these data, and getting the information to first responders in a timely manner. Lessons learned in terms of addressing the needs of first responders from multi-state agencies will also be highlighted.

  7. Remote sensing as characterizing and monitoring tool for Asiatic Lion habitat

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.; Raval, P. P.; Bhatt, K.; Raval, V.

    The Gir Wild Life Sanctuary and National Park (200 57^'-210 20^' N ; 700 28^'-710 13^' E), last home of Asiatic Lions, is spread over 1153.41 sq km and supports 709 carnivores (and 37512 herbivores) including 304 lions and 268 leopards (1995 census). Increasing lion and leopard population demands periodic precision monitoring of the habitat at close intervals using space based remote sensing data sets. Dry deciduous nature of forest leads to very different vegetation scenarios in October (post-rain), January / February (leaf shedding) and May (summer) months. Spectral separability in 23.5 m resolution IRS-1C LISS-III data for 13 October 1997 was poor among dense, riverine and open forests; and was marginal between mixed and scrub forests. These spectral mix-ups were getting resolved in LISS-III data of 22 January, 1997. Training areas at sub-class levels were identified with the joint use of January and October data sets and classification for these two individual dates and the combined October & January data set was carried out at sub-class levels. Sub-classes were later merged into corresponding main class. The achieved classification accuracy for October, January and combined October & January data set was 60%, 48.4% and 87.2%, respectively. The probable corridors for natural dispersion of lions, to cope with increasing population pressure, were identified in 188 m spatial resolution WiFS (in conjunction with LISS-III) data of 25 February, 1997 based on predominant grassland pathways in N and NE directions (less human activity zones); along river streams or broad grassland pathways towards coastal forest in the south; and grassland pathway in the west for movement to lower reach of Girnar hill forest shelter zone. Temperature computed from February, May and October 1997 NOAA AVHRR data were used to compute relative thermal stress index (RTSI) images given by [(Tp --Tr) / (Tmax-Tr)] wherein Tr, Tmax and Tp refer to lower boundary reference temperature for the

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  9. Winter wheat growth spatial variation monitoring through hyperspectral remote sensing image

    NASA Astrophysics Data System (ADS)

    Song, Xiaoyu; Li, Ting; Wang, Jihua; Gu, Xiaohe; Xu, Xingang

    2015-10-01

    This work aims at quantifying the winter wheat growth spatial heterogeneity captured by hyperspectral airborne images. The field experiment was conducted in 2001 and 2002 and airborne hyperspectral remote-sensing data was acquired at noon on 11 April 2001 using an operational modular imaging spectrometer (OMIS). Totally 12 winter fields which covered by both dense and sparse winter wheat canopies were selected to analysis the winter wheat growth heterogeneity. The experimental semi-variograms for bands covered from invisible to mid-infrared were computed for each field then the theoretical models were be fitted with least squares algorithm for spherical model, exponential model. The optimization model was selected after evaluated by R-square. Three key terms in each model, the sill, the range, and nugget variance were then calculated from the models. The study results show that the sill, range and nugget for same field wheat were varied with the wavelength from blue to mid infrared bands. Although wheat growth in different fields showed different spatial heterogeneity, they all showed an obvious sill pattern. The minimum of mean range value was 7.52 m for mid-infrared bands while the maximum value was 91.71 m for visible bands. The minimum of mean sill value ranged from 1.46 for visible bands to 39.76 for NIR bands, the minimum of mean nugget value ranged from 0.06 for visible bands to5.45 for mid-infrared bands. This study indicate that remote sensing image is important for crop growth spatial heterogeneity study. But it is necessary to explore the effect of different wavelength of image data on crop growth semi-variogram estimation and find out which band data could be used to estimate crop semi-variogram reliably.

  10. Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts

    NASA Astrophysics Data System (ADS)

    Szczypta, C.; Calvet, J.-C.; Maignan, F.; Dorigo, W.; Baret, F.; Ciais, P.

    2014-05-01

    Two new remotely sensed leaf area index (LAI) and surface soil moisture (SSM) satellite-derived products are compared with two sets of simulations of the ORganizing Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) land surface models. We analyse the interannual variability over the period 1991-2008. The leaf onset and the length of the vegetation growing period (LGP) are derived from both the satellite-derived LAI and modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI and LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. In order to investigate how recent droughts affected vegetation over the Euro-Mediterranean area, a case study addressing the summer 2003 drought is presented. It shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite-derived product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of the Ukraine and southern Russia.

  11. Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring

    USGS Publications Warehouse

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

    2012-01-01

    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.

  12. Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: Laying a foundation for monitoring

    NASA Astrophysics Data System (ADS)

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

    2012-02-01

    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.

  13. Sub-bandage sensing system for remote monitoring of chronic wounds in healthcare

    NASA Astrophysics Data System (ADS)

    Hariz, Alex; Mehmood, Nasir; Voelcker, Nico

    2015-12-01

    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.

  14. Measuring and Monitoring Long Term Disaster Recovery Using Remote Sensing: A Case Study of Post Katrina New Orleans

    NASA Astrophysics Data System (ADS)

    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

  15. Remote Monitoring Transparency Program

    SciTech Connect

    Sukhoruchkin, V.K.; Shmelev, V.M.; Roumiantsev, A.N.

    1996-08-01

    The objective of the Remote Monitoring Transparency Program is to evaluate and demonstrate the use of remote monitoring technologies to advance nonproliferation and transparency efforts that are currently being developed by Russia and the United States without compromising the national security to the participating parties. Under a lab-to-lab transparency contract between Sandia National Laboratories (SNL) and the Kurchatov Institute (KI RRC), the Kurchatov Institute will analyze technical and procedural aspects of the application of remote monitoring as a transparency measure to monitor inventories of direct- use HEU and plutonium (e.g., material recovered from dismantled nuclear weapons). A goal of this program is to assist a broad range of political and technical experts in learning more about remote monitoring technologies that could be used to implement nonproliferation, arms control, and other security and confidence building measures. Specifically, this program will: (1) begin integrating Russian technologies into remote monitoring systems; (2) develop remote monitoring procedures that will assist in the application of remote monitoring techniques to monitor inventories of HEU and Pu from dismantled nuclear weapons; and (3) conduct a workshop to review remote monitoring fundamentals, demonstrate an integrated US/Russian remote monitoring system, and discuss the impacts that remote monitoring will have on the national security of participating countries.

  16. Detection and Monitoring of Vegetation Patterns and Borderlines in High Mountain Environments by using combined Terrestrial and Remote Sensing Methods

    NASA Astrophysics Data System (ADS)

    Nutz, M.; Klipp, M.; Schardt, M.; Pauli, H.

    2009-04-01

    The GLORIA network collects ground-based, multi-site, long-term monitoring data since 1999 to document how changes in biodiversity and vegetation patterns correlate with climate change in the world's high mountain ecosystems (www.gloria.ac.at). To broaden GLORIA's basic multi-summit approach, more terrestrial and remote sensing methods will be applied combined in order to use the synergetic effects of detailed information at a large scale as well as area-wide information at a smaller scale. The proposed target region is located in the Hohe Tauern Nationalpark, Austria, which will serve as the first study site to realize this conception. A second study site will be chosen to validate the novel monitoring-concept. The retrospective development of both sites will be studied by means of orthophotographs. The current situation of vegetation patterns and borderlines will be recorded by terrestrial vegetation mapping as well as by semi-automated classifications of QuickBird data (very high spatial resolution). The results will be used as ground truth for a sub-pixel classification of RapidEye data (very high temporal resolution). Phenological time series will be defined. Consequently, change detection will be used to test the aptitude of the data for a monitoring system. To investigate critical borderlines, transects with permanent plots perpendicular to the borderlines in question will be implemented. Satellite data and aerial photographs (20 cm geometric resolution) will be used for remote sensing investigations. Thus, the changes in community distribution and altitudinal determined borderlines beyond the GLORIA summit area, will be monitored. Summarized, in this project, a monitoring concept will be developed by observing two target regions at three spatial and two temporal scales to provide information about changes in vegetation cover due to climate change.

  17. [Monitoring of soil salinization in Northern Tarim Basin, Xinjiang of China in dry and wet seasons based on remote sensing].

    PubMed

    Yao, Yuan; Ding, Jian-Li; Zhang, Fang; Wang, Gang; Jiang, Hong-Nan

    2013-11-01

    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. PMID:24564152

  18. Remote Sensing and the Earth.

    ERIC Educational Resources Information Center

    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.…

  19. Remote Sensing: A Film Review.

    ERIC Educational Resources Information Center

    Carter, David J.

    1986-01-01

    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…

  20. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring.

    PubMed

    Allison, Robert S; Johnston, Joshua M; Craig, Gregory; Jennings, Sion

    2016-01-01

    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

  1. Remote Sensing and the Environment.

    ERIC Educational Resources Information Center

    Osmers, Karl

    1991-01-01

    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…

  2. Accelerating Commercial Remote Sensing

    NASA Technical Reports Server (NTRS)

    1995-01-01

    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.

  3. Remote sensing program

    NASA Technical Reports Server (NTRS)

    Whitmore, R. A., Jr. (Principal Investigator)

    1980-01-01

    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.

  4. Remote sensing of wetlands

    NASA Technical Reports Server (NTRS)

    Butera, M. K.

    1983-01-01

    Results are given for three separate investigations of remote sensing over wetlands, including the delineations of roseau cane and mangrove from both Landsat and aircraft MSS data, and the delineation of wetland communities for potential waste assimilation in a coastal river floodplain from Landsat MSS data only. Attention is also given to data processing and analysis techniques of varying levels of sophistication, which must increase with surface cover diversity. All computer processing in these studies was performed on a minicomputer configured with the adequate memory, image display capability, and associated peripherals, using state-of-the-art digital MSS data analysis software.

  5. Satellite remote sensing. An introduction

    SciTech Connect

    Harris, R.

    1987-01-01

    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.

  6. Monitoring Freeze-Thaw States in the Pan-Arctic: Application of Microwave Remote Sensing to Monitoring Hydrologic and Ecological Processes

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

    The transition of the landscape between predominantly frozen and non-frozen conditions in seasonally frozen environments impacts climate, hydrological, ecological and biogeochemical processes profoundly. Satellite microwave remote sensing is uniquely capable of detecting and monitoring a range of related biophysical processes associated with the measurement of landscape freeze/thaw status. We present the development, physical basis, current techniques and selected hydrological applications of satellite-borne microwave remote sensing of landscape freeze/thaw states for the terrestrial cryosphere. Major landscape hydrological processes embracing the remotely-sensed freeze/thaw signal include timing and spatial dynamics of seasonal snowmelt and associated soil thaw, runoff generation and flooding, ice breakup in large rivers and lakes, and timing and length of vegetation growing seasons and associated productivity and trace gas exchange. Employing both active and passive microwave sensors, we apply a selection of temporal change classification algorithms to examine a variety of hydrologic processes. We investigate contemporaneous and retrospective applications of the QuikSCAT scatterometer, and the SSM/I and SMMR radiometers to this end. Results illustrate the strong correspondence between regional thawing, seasonal ice break up for rivers, and the springtime pulse in river flow. We present the physical principles of microwave sensitivity to landscape freeze/thaw state, recent progress in applying these principles toward satellite remote sensing of freeze/thaw processes over broad regions, and potential for future global monitoring of this significant phenomenon of the global cryosphere. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and at the University of Montana, Missoula, under contract to the National Aeronautics and Space Administration.

  7. Remote Monitoring Transparency Program

    SciTech Connect

    Sukhoruchkin, V.K.; Shmelev, V.M.; Roumiantsev, A.N.; Croessmann, C.D.; Horton, R.D.; Matter, J.C.; Czajkowski, A.F.; Sheely, K.B.; Bieniawski, A.J.

    1996-12-31

    The objective of the Remote Monitoring Transparency Program is to evaluate and demonstrate the use of remote monitoring technologies to advance nonproliferation and transparency efforts that are currently being developed by Russia and the US without compromising the national security of the participating parties. Under a lab-to-lab transparency contract between Sandia National Laboratories (SNL) and the Kurchatov Institute (KI RRC), the Kurchatov Institute will analyze technical and procedural aspects of the application of remote monitoring as a transparency measure to monitor inventories of direct-use HEU and plutonium (e.g., material recovered from dismantled nuclear weapons). A goal of this program is to assist a broad range of political and technical experts in learning more about remote monitoring technologies that could be used to implement nonproliferation, arms control, and other security and confidence building measures. Specifically, this program will: (1) begin integrating Russian technologies into remote monitoring systems; (2) develop remote monitoring procedures that will assist in the application of remote monitoring techniques to monitor inventories of HEU and Pu from dismantled nuclear weapons; and (3) conduct a workshop to review remote monitoring fundamentals, demonstrate an integrated US/Russian remote monitoring will have on the national security of participating countries.

  8. Remote sensing and disaster monitoring - A review of applications in Indonesia

    NASA Technical Reports Server (NTRS)

    Malingreau, J. P.

    1985-01-01

    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.

  9. A Neural Network Approach For Volcanic Monitoring Of Sulpher Dioxide Using Hyperspectral Remote Sensed Data

    NASA Astrophysics Data System (ADS)

    Piscini, Alessandro; Carboni, Elisa; Don Granger, Roy; Del Frate, Fabio

    2013-12-01

    This paper describes an application of ANN for the simultaneous estimation of the columnar content and height of the SO2 plume from volcanic eruptions using hyperspectral remotely sensing data. ANN have been trained using all IASI channels between 1000-1200 and 1300-1410 cm-1, as inputs, and the corresponding values of SO2 amount and plume's height obtained using the Oxford retrieval scheme as outputs. As a case study we have chosen the Eyjafjallajökull volcano (Iceland), in particular the eruption took place during the months of April and May 2010, which had an enormous impact on the world economy. ANNs have been validated on some independent data sets belonging to the same eruption and also on IASI images of Grímsvötn eruption, occurred on May 2011. The results have provided values of RMSE between ANN outputs and targets always less than 20 DU for SO2 and 200 mb for height, so demonstrating the good performance in retrieval achieved by the ANN technique.

  10. Development of a Remote Sensing Program to Monitor for Resistance Development in Transgenic Crops

    NASA Astrophysics Data System (ADS)

    Copenhaver, K.; Glaser, J. A.; Fridgen, J.; Carroll, M.

    2006-12-01

    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.

  11. Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.

    PubMed

    Benedek, C; Descombes, X; Zerubia, J

    2012-01-01

    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. PMID:21576749

  12. Monitoring the urban expansion of Sparta and Nafplio cities using remote sensing and GIS techniques

    NASA Astrophysics Data System (ADS)

    Zervakou, Alexandra D.; Nikolakopoulos, Konstantinos G.; Tsombos, Panagiotis I.; Papanikolaou, George P.

    2008-10-01

    During the last four decades, Greece has suffered from an enormous internal immigration. The majority of small villages were abandoned and the population has been gathered into urban areas, usually into the prefectural capital cities. Because of the significant increase of population, the urban expansion was excessive and in some cases catastrophic. A lot of changes have been occurred to the landforms, drainage networks and landuse. The Institute of geology and Mineral Exploration of Greece (I.G.M.E.), in the frame of CSF 2000 - 2006 (Community Support Framework 2000-2006), has been implementing the pilot project titled "Collection, Codification and Documentation of geothematic information for urban and suburban areas in Greece - pilot applications". Four different cities (Drama - North Greece, Nafplio & Sparta -Peloponnesus and Thrakomakedones - Attica) were selected as pilot areas.For these cities we have tried to detect and map the urban extent and expansion and estimate their growth rate, using GIS and remote sensing techniques. Multitemporal and multiresolution satellite data covering the period 1975-2007 and topographic maps at a scale of 1:5.000 were used for the urban growth mapping and observation.The qualitative and quantitative results for the cities of Nafplio & Sparta are presented in this study.

  13. Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform

    NASA Astrophysics Data System (ADS)

    Samseemoung, Grianggai; Jayasuriya, Hemantha P. W.; Soni, Peeyush

    2011-01-01

    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.

  14. Smart monitoring of water quality in Asprokremmos Dam in Paphos, Cyprus using satellite remote sensing and wireless sensor platform

    NASA Astrophysics Data System (ADS)

    Papoutsa, Christiana; Hadjimitsis, Diofantos G.; Themistocleous, Kyriacos; Perdikou, Skevi; Retalis, Adrianos; Toulios, Leonidas

    2010-10-01

    The use of satellite remote sensing for water quality monitoring in inland waters has substantial advantages over the insitu sampling method since it provides the ability for overall area coverage and also for study and supervision of isolated locations. The development of algorithms for water quality monitoring using satellite data and surface measurements can be widely found in literature. Such algorithms require validation and one of the major problems faced during these attempts was the need for continuous surface measurements requiring numerous in-situ samplings that imply also very high costs due to the need of increased human labour. The development of an automatic and autonomous sensor system able to be remotely controlled, will cover this gap and will allow the real time combined analysis of satellite and surface data for the continuous monitoring of water quality in dams as well as the overall water resources management. Wireless Sensor Networks (WSN) can provide continuous measurements of parameters taken from the field by deploying a lot of wireless sensors to cover a specific geographical area. An innovative, energy-autonomous floating sensor platform (buoy) transferring data via wireless network to a remote central database has been developed for this study which can be applied on all dams in Cyprus. Indeed this project describes the results obtained by an existing running campaign in which in-situ spectroradiometric (GER1500 field spectroradiometer) measurements, water sampling measurements (turbidity), sensor measurements (turbidity) and Landsat TM/ETM+ data have been acquired at the Asprokremmos Dam in Paphos, Cyprus). By applying several regression analyses between reflectance against turbidity for all the spectral bands that correspond to Landsat TM/ETM+ 1-2-3-4, the highest correlation was found for TM band 3 (R2=0.83).

  15. The 1994 International Geoscience and Remote Sensing Symposium (IGARSS 1994)

    NASA Technical Reports Server (NTRS)

    1994-01-01

    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.

  16. [Monitoring the thermal plume from coastal nuclear power plant using satellite remote sensing data: modeling, and validation].

    PubMed

    Zhu, Li; Zhao, Li-Min; Wang, Qiao; Zhang, Ai-Ling; Wu, Chuan-Qing; Li, Jia-Guo; Shi, Ji-Xiang

    2014-11-01

    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

  17. Utilizing Operational and Improved Remote Sensing Measurements to Assess Air Quality Monitoring Model Forecasts

    NASA Astrophysics Data System (ADS)

    Gan, Chuen-Meei

    Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.

  18. Integration of Remote Sensing Techniques With Statistical Methods For Landslide Monitoring and Risk Assessment

    NASA Astrophysics Data System (ADS)

    van Westen, Cees; Wunderle, Stefan; Pasquali, Paolo

    In the frame of the Date User Program 2 (DUP) of the European Space Agency (ESA) a new method will be presented to derive landslide hazards, which was developed in close co-operation with the end users in Honduras and Switzerland, respectively. The objective of thi s project is to define a sustainable service using the novel approach based on the fusion of two independent methods, namely combining differential SAR Interferometry techniques (DInSAR) with a statistical approach. The bivariate statistical analysis is based on parameter maps (slope, geomorphology, land use) derived from remote sensing data and field checks as well as on historical aerial photos. The hybrid method is based on SAR data of the last years and new ENVISAT-ASAR data as well as historical data (i.e. former landslides detected in aerial photos), respectively. The historical occurrence of landslides will be combined with actual land sliding and creeping obtained from DInSAR. The landslide occurrence map in high quality forms the input for the statistical landslide hazard analysis. The method intends to derive information on landslide hazards, preferably in the form of probabilities, which will be combined with information on building stock, infrastructure and population density. The vulnerability of population and infrastructure will be taken into account by a weighting factor. The resulting risk maps will be of great value for local authorities, Comisión Permanente de Contingencias (COPECO) of Honduras, local GIS specialists, policy makers and reinsurance companies. We will show the results of the Service Definition Project with some examples of the new method especially for Tegucigalpa the capital of Honduras with approximately 1 million inhabitants.

  19. Monitoring drought impact on Mediterranean oak savanna vegetation using remote sensing

    NASA Astrophysics Data System (ADS)

    González-Dugo, Maria P.; Carpintero, Elisabet; Andreu, Ana

    2015-04-01

    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

  20. Monitoring soil moisture patterns in alpine meadows using ground sensor networks and remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike

    2015-04-01

    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

  1. Timing is everything: using near-surface and remote sensing to monitor vegetation phenology in sagebrush steppe

    NASA Astrophysics Data System (ADS)

    Chong, G.; Steltzer, H.; Shory, R.; Petach, A.; Wallenstein, M. D.

    2012-12-01

    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

  2. Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

    NASA Astrophysics Data System (ADS)

    Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

    2015-05-01

    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.

  3. Remote sensing monitoring of thermal discharge in Daya Bay Nuclear Power Station based on HJ-1 infrared camera

    NASA Astrophysics Data System (ADS)

    Zhu, Li; Yin, Shoujing; Wu, Chuanqing; Ma, Wandong; Hou, Haiqian; Xu, Jing

    2014-11-01

    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.

  4. Lidar Remote Sensing

    NASA Technical Reports Server (NTRS)

    McGill, Matthew J.; Starr, David OC. (Technical Monitor)

    2002-01-01

    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.

  5. Real-Time Integrity Monitoring of Stored Geo-Spatial Data Using Forward-Looking Remote Sensing Technology

    NASA Technical Reports Server (NTRS)

    Young, Steven D.; Harrah, Steven D.; deHaag, Maarten Uijt

    2002-01-01

    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.

  6. Use of thermal infrared remote sensing data for fisheries, environmental monitoring, oil and gas exploration, and ship routing.

    NASA Astrophysics Data System (ADS)

    Roffer, M. A.; Gawlikowski, G.; Muller-Karger, F.; Schaudt, K.; Upton, M.; Wall, C.; Westhaver, D.

    2006-12-01

    Thermal infrared (TIR) and ocean color remote sensing data (1.1 - 4.0 km) are being used as the primary data source in decision making systems for fisheries management, commercial and recreational fishing advisory services, fisheries research, environmental monitoring, oil and gas operations, and ship routing. Experience over the last 30 years suggests that while ocean color and other remote sensing data (e.g. altimetry) are important data sources, TIR presently yields the most useful data for studying ocean surface circulation synoptically on a daily basis. This is due primarily to the greater temporal resolution, but also due to one's better understanding of the dynamics of sea surface temperature compared with variations in ocean color and the spatial limitations of altimeter data. Information derived from commercial operations and research is being used to improve the operational efficiency of fishing vessels (e.g. reduce search time and increase catch rate) and to improve our understanding of the variations in catch distribution and rate needed to properly manage fisheries. This information is also being used by the oil and gas industry to minimize transit time and thus, save costs (e.g., tug charter, insurance), to increase production and revenue up to 500K dollars a day. The data are also be used to reduce the risk of equipment loss, loss of time and revenue to sudden and unexpected currents such as eddies. Sequential image analysis integrating TIR and ocean color provided near-real time, synoptic visualization of the rapid and wide dispersal of coastal waters from the northern Gulf of Mexico following Hurricanes Katrina and Rita in September 2005. The satellite data and analysis techniques have also been used to monitor the effects and movement of other potential environmentally damaging substances, such as dispersing nutrient enriched waste water offshore. A review of our experience in several commercial applications and research efforts will reinforce the

  7. Improved drought monitoring in the Greater Horn of Africa by combining meteorological and remote sensing based indicators

    NASA Astrophysics Data System (ADS)

    Horion, Stephanie; Kurnik, Blaz; Barbosa, Paulo; Vogt, Jürgen

    2010-05-01

    Drought is a complex and insidious natural hazard. It is hence difficult to detect in its early stages and to monitor its spatial evolution. Defining drought is already a challenge and can be done differently by meteorologists, hydrologists or socio-economists. In each one of these research areas, various indicators were already set up to depict the development of drought. However they are usually considering only one aspect of the phenomenon. The development of integrated indicators could help to detect faster/better the onset of drought, to monitor more efficiently its evolution in time and space, and therefore to better trigger timely and appropriate actions on the field. In this study, meteorological and remote sensing based drought indicators were compared over the Greater Horn of Africa in order to better understand: (i) how they depict historical drought events ; (ii) if they could be combined into an integrated drought indicator. The meteorological indicator selected for our study is the well known Standardized Precipitation Index, SPI. This statistical indicator is evaluating the lack or surplus of precipitation during a given period of time as a function of the long-term average precipitation and its distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different regions in the Greater Horn of Africa. The time window for the statistical analysis was set to the rainy season, as it is the most critical period for

  8. A Remote-Sensing Mission

    ERIC Educational Resources Information Center

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

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

  9. Remote sensing for cotton farming

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  10. THE REMOTE SENSING DATA GATEWAY

    EPA Science Inventory

    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...

  11. Commerical Remote Sensing Data Contract

    USGS Publications Warehouse

    U.S. Geological Survey

    2005-01-01

    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.

  12. Hyperspectral remote sensing for monitoring species-specific drought impacts in southern California

    NASA Astrophysics Data System (ADS)

    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

  13. Remote sensing of California estuaries: Monitoring climate change and invasive species

    NASA Astrophysics Data System (ADS)

    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

  14. Contextual classification of hyperspectral remote sensing images Application in vegetation monitoring

    NASA Astrophysics Data System (ADS)

    Thoonen, Guy

    The goal of this thesis is the study of strategies for including contextual information in the classification of hyperspectral remote sensing images. The objectives are twofold. The first objective is the development of new techniques for including contextual information. To this end, an important category of techniques, i.e. modelling the relationships between local pixel neighbourhoods as Markov Random Fields, is first considered. A strategy to extend the flexibility of this technique, by describing the classification problem at hand by an extended hierarchical tree, is introduced. The second technique under study, i.e. the state-of-the-art approach to extract contextual information in the form of attribute profiles, is extended to colour images. As a practical application, two images from the same scene, including a hyperspectral and a high spatial resolution colour image, are jointly classified by first extracting colour attribute profiles from the latter. In addition, a hybrid decision fusion approach is proposed to perform the classification. The third technique, developed in this work, is an approach for assessing the accuracy of contextual classification results, by introducing a new reference, and considering a new measure, based on the complexity of edges, i.e. transitions between classes. The second objective of this thesis is the application of contextual classification techniques to the essential problem of assessing the conservation status of Natura 2000 habitats. The main challenge is in the structural complexity of most of the habitats under study, since these habitats display a high degree of heterogeneity and, in addition, cannot be simply identified by the presence of a single or a few dominant species. In order to handle this complexity, a contextual framework has been developed to reduce the problem to a number of more manageable sub-problems. First, the list of habitats is translated to a hierarchical scheme that includes the most important

  15. Using remote sensing to monitor herbicide injury and biomass of waterhyacinth [Eichhornia crassipes (Mart.) Solms

    NASA Astrophysics Data System (ADS)

    Robles, Wilfredo

    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

  16. Synergic use of satellite and ground based remote sensing methods for monitoring the San Leo rock cliff (Northern Italy)

    NASA Astrophysics Data System (ADS)

    Frodella, William; Ciampalini, Andrea; Gigli, Giovanni; Lombardi, Luca; Raspini, Federico; Nocentini, Massimiliano; Scardigli, Cosimo; Casagli, Nicola

    2016-07-01

    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.

  17. Assessment of the capability of remote sensing and GIS techniques for monitoring reclamation success in coal mine degraded lands.

    PubMed

    Karan, Shivesh Kishore; Samadder, Sukha Ranjan; Maiti, Subodh Kumar

    2016-11-01

    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. PMID:27491028

  18. Dynamic monitoring of grassland degradation with remote sensing and the strategy of ecological restoration in Shandan County of Heihe Basin

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Jiao, Yuanmei; Wang, Lihong; Xiao, Honglang

    2003-07-01

    Remote sensing(RS) technology, which has made great progress in many applied fields, can provide an efficient means for active identification of grassland degradation. In this paper, we used the Landsat TM images in 1980"s and 2000 to monitor the dynamics of grassland degradation in Shandan County where was famous with its army horse feeding and the important self-restraint regions of soil and water in the upper Heihe basin in Northwest China. By integrating RS and Geographic Information System(GIS), we calculated the amounts and the changes of grassland types during the past 15 years. Using satellite monitoring and retrieval means to get the productivity of grassland, analyzed the carrying capacity of livestock, and classified the grassland into 4 degradation levels and created the grassland degradation maps. Then, we use the landscape ecology principles to design the recovering planning of the corresponding degraded regions. At last, we promoted the corresponding strategies to restore the different degraded grasslands in Shandan County. This approach to dynamic monitoring of grassland degradation and the retrieval of grassland productivity is a fully digital operation, so it makes best use of computer and GIS to manage, display, query and map the grassland degradation data.

  19. The concept of creation of information system for environmental monitoring based on modern GIS-technologies and earth remote sensing data

    NASA Astrophysics Data System (ADS)

    Yuronen, Yu P.; Yuronen, E. A.; Ivanov, V. V.; Kovalev, I. V.; Zelenkov, P. V.

    2015-10-01

    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.

  20. Using multi-temporal remote sensing for mining area monitoring and management: the Yunnan Province case study (China)

    NASA Astrophysics Data System (ADS)

    Chen, Jianping; Tarolli, Paolo; Li, Ke; Yang, Xiaofei

    2014-05-01

    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

  1. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

    PubMed

    Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

    2013-02-01

    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

  2. Remote sensing-based Information for crop monitoring: contribution of SAR and Moderate resolution optical data on Asian rice production

    NASA Astrophysics Data System (ADS)

    Boschetti, Mirco; Holectz, Francesco; Manfron, Giacinto; Collivignarelli, Francesco; Nelson, Andrew

    2013-04-01

    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

  3. Monitoring hydrogeochemical interactions in coastal mangroves in Everglades National Park using field spectroscopy and remote sensing

    NASA Astrophysics Data System (ADS)

    Lagomasino, D.; Price, R. M.; Campbell, P. K.

    2011-12-01

    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.

  4. Remote sensing in hydrology

    NASA Astrophysics Data System (ADS)

    Schultz, Gert A.

    1988-07-01

    The "Electronic Age" offers new and attractive opportunities to hydrologists for remote sensing (RS) of hydrological data. A discussion of hydrologically relevant platforms and sensors and the type of electromagnetic signals used by such sensors is followed by an analysis of the structure of mathematical hydrologic models which use RS information either as input or to provide a basis for model parameter estimation. Three examples of RS application in hydrological modeling are given: (1) model parameter estimation with the aid of multispectral Landsat satellite data; (2) computation of historic monthly runoff for design purposes with the aid of a lumped system model using NOAA infrared satellite data as input; and (3) real-time flood forecasting applying a distributed system model using radar rainfall measurements as input. Further applications of RS information in hydrology are discussed in the field of evapotranspiration, soil moisture, rainfall, surface water, snow and ice, sediments and water quality. A brief discussion of RS data availability and the hardware and software required is followed by an assessment of future opportunities. The potential of passive and active microwave sensors for hydrological applications is emphasized.

  5. Using remote sensing and grid-based meteorological datasets for regional soybean crop yield prediction and crop monitoring

    NASA Astrophysics Data System (ADS)

    Mali, Preeti

    Regional crop yield estimations using crop models is a national priority due to its contributions to crop security assessment and food pricing policies. Many of these crop yield assessments are performed using time-consuming, intensive field surveys. This research was initiated to test the applicability of remote sensing and grid-based meteorological model data for providing improved and efficient predictive capabilities for crop bio-productivity. The soybean prediction model (Sinclair model) used in this research, requires daily data inputs to simulate yield which are temperature, precipitation, solar radiation, day length initialization of certain soil moisture parameters for each model run. The traditional meteorological datasets were compared with simulated South American Land Data Assimilation System (SALDAS) meteorological datasets for Sinclair model runs and for initializing soil moisture inputs. Considering the fact that grid-based meteorological data has the resolution of 1/8th of a degree, the estimations demonstrated a reasonable accuracy level and showed promise for increase in efficiency for regional level yield predictions. The research tested daily composited Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (both AQUA and TERRA platform) and simulated Visible/Infrared Imager Radiometer Suite (VIIRS) sensor product (a new sensor planned to be launched in the near future) for crop growth and development based on phenological events. The AQUA and TERRA fusion based daily MODIS NDVI was utilized to develop a planting date estimation method. The results have shown that daily MODIS composited NDVI values have the capability for enhanced monitoring of soybean crop growth and development. The method was able to predict planting date within +/-3.4 days. A geoprocessing framework for extracting data from the grid data sources was developed. Overall, this study was able to demonstrate the utility of

  6. Using remote sensing and spatial analysis of trees characteristics for long-term monitoring in arid environments

    NASA Astrophysics Data System (ADS)

    Isaacson, Sivan; Blumberg, Dan G.; Rachmilevitch, Shimon; Ephrath, Jhonathan E.; Maman, Shimrit

    2016-04-01

    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

  7. Using the best available data: integrating field data and remote sensing imagery to monitor rangelands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. Center of Excellence in Remote Sensing at SDSM&T

    NASA Technical Reports Server (NTRS)

    Price Maribeth H.

    1999-01-01

    The College of Earth Systems at the South Dakota School of Mines and Technology established a Center for Remote Sensing to consolidate and coordinate the educational and research thrusts from different parts of campus into unified center with a focus on applications of remote sensing data in integrated environmental assessments. The threefold mission objectives of the Center are: 1) To educate students and the community in the principles and applications of remote sensing 2) To facilitate use of remote sensing in research coupling earth modeling, monitoring, and GIS 3) To distribute remote sensing data and expertise to regional federal, state, tribal, and local agencies.

  9. [Establishment of snow disaster remote sensing monitoring and damage estimation systems in Altai pastoral region of Xinjiang].

    PubMed

    Liu, Xingyuan; Chen, Quangong; Liang, Tiangang; Guo, Zhenggang; Chai, Qi

    2006-02-01

    It is of significance to establish an integrated evaluation system of snow disaster in northern pastoral areas. Based on the NOAA satellite digital images, field observation data, and maps of grassland type and seasonal pastureland, this paper selected the winter and spring pasturelands in Aletai region of Xinjiang as the main area of snow disaster-remote sensing monitoring. With affecting factors of economy and the characteristics of natural resource distribution comprehensively analyzed, and using 3S techniques and field survey information, a fundamental information processing model for integrated evaluation of snow disaster was built up, and snow disaster-spatial evaluation indices and damage level systems were constructed. Natural and social systems and 20 indices were selected in snow disaster evaluation indicator system. Four principal factors, i.e., snow cover area, snow depth on grassland, persistence days of low temperature, and livestock death rate, were used as the grading indices of snow disaster damage level, and the models of snow disaster identification and loss estimatation were set up to quantitatively analyze snow disaster. The results indicated that the system could accurately reflect the details of snow hazard grade and the situation of a disaster in temporal and spatial scales, which would help to carry out the dynamic monitoring and scientific estimatation of big area's snow disaster in pastoral region. PMID:16706041

  10. Spectral monitoring of moorland plant phenology to identify a temporal window for hyperspectral remote sensing of peatland

    NASA Astrophysics Data System (ADS)

    Cole, Beth; McMorrow, Julia; Evans, Martin

    2014-04-01

    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.

  11. Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

    NASA Technical Reports Server (NTRS)

    Lam, N.; Qiu, H.-I.; Quattrochi, Dale A.; Zhao, Wei

    1997-01-01

    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.

  12. Potential of the Thermal Infrared Wavelength Region to predict semi-arid Soil Surface Properties for Remote Sensing Monitoring

    NASA Astrophysics Data System (ADS)

    Eisele, Andreas; Chabrillat, Sabine; Lau, Ian; Hecker, Christoph; Hewson, Robert; Carter, Dan; Wheaton, Buddy; Ong, Cindy; Cudahy, Thomas John; Kaufmann, Hermann

    2014-05-01

    Digital soil mapping with the means of passive remote sensing basically relies on the soils' spectral characteristics and an appropriate atmospheric window, where electromagnetic radiation transmits without significant attenuation. Traditionally the atmospheric window in the solar-reflective wavelength region (visible, VIS: 0.4 - 0.7 μm; near infrared, NIR: 0.7 - 1.1 μm; shortwave infrared, SWIR: 1.1 - 2.5 μm) has been used to quantify soil surface properties. However, spectral characteristics of semi-arid soils, typically have a coarse quartz rich texture and iron coatings that can limit the prediction of soil surface properties. In this study we investigated the potential of the atmospheric window in the thermal wavelength region (long wave infrared, LWIR: 8 - 14 μm) to predict soil surface properties such as the grain size distribution (texture) and the organic carbon content (SOC) for coarse-textured soils from the Australian wheat belt region. This region suffers soil loss due to wind erosion processes and large scale monitoring techniques, such as remote sensing, is urgently required to observe the dynamic changes of such soil properties. The coarse textured sandy soils of the investigated area require methods, which can measure the special spectral response of the quartz dominated mineralogy with iron oxide enriched grain coatings. By comparison, the spectroscopy using the solar-reflective region has limitations to discriminate such arid soil mineralogy and associated coatings. Such monitoring is important for observing potential desertification trends associated with coarsening of topsoil texture and reduction in SOC. In this laboratory study we identified the relevant LWIR wavelengths to predict these soil surface properties. The results showed the ability of multivariate analyses methods (PLSR) to predict these soil properties from the soil's spectral signature, where the texture parameters (clay and sand content) could be predicted well in the models

  13. Remote sensing of earth terrain

    NASA Technical Reports Server (NTRS)

    Yueh, Herng-Aung; Kong, Jin AU

    1991-01-01

    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.

  14. Mississippi Sound Remote Sensing Study

    NASA Technical Reports Server (NTRS)

    Atwell, B. H.

    1973-01-01

    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.

  15. Remote sensing at Savannah River

    SciTech Connect

    Corey, J.C.

    1986-01-01

    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)

  16. Remote sensing of Earth terrain

    NASA Technical Reports Server (NTRS)

    Kong, J. A.

    1992-01-01

    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.

  17. Energy and remote sensing applications

    NASA Technical Reports Server (NTRS)

    Summers, R. A.; Smith, W. L.; Short, N. M.

    1978-01-01

    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.

  18. Monitoring boreal ecosystem phenology with integrated active/passive microwave remote sensing

    NASA Technical Reports Server (NTRS)

    McDonald, K. C.; Njoku, E.; Kimball, J.; Running, S.; Thompson, C.; Lee, J. K.

    2002-01-01

    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.

  19. Remote sensing for vineyard management

    NASA Technical Reports Server (NTRS)

    Philipson, W. R.; Erb, T. L.; Fernandez, D.; Mcleester, J. N.

    1980-01-01

    Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.

  20. Remote-Sensed Monitoring of Dominant Plant Species Distribution and Dynamics at Jiuduansha Wetland in Shanghai, China

    SciTech Connect

    Lin, Wenpeng; Chen, Guangsheng; Guo, Pupu; Zhu, Wenquan; Zhang, Donghai

    2015-08-11

    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

  1. Remote-Sensed Monitoring of Dominant Plant Species Distribution and Dynamics at Jiuduansha Wetland in Shanghai, China

    DOE PAGESBeta

    Lin, Wenpeng; Chen, Guangsheng; Guo, Pupu; Zhu, Wenquan; Zhang, Donghai

    2015-08-11

    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

  2. Applied Remote Sensing Program (ARSP)

    NASA Technical Reports Server (NTRS)

    Mouat, D. A.; Johnson, J. D.; Foster, K. E.

    1977-01-01

    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.

  3. Operational fog monitoring using FY-1D remotely sensed data in China

    NASA Astrophysics Data System (ADS)

    Qian, Yonglan; Zhang, Guoping; Wang, Maoxin

    2006-12-01

    Fog is a disaster that troubles the people life especially the traffic safety and air quality. NOAA and EOS/MOSDIS data can both be used to monitor the fog disaster, but FY-1D data is the best in China for its timely acquirement that covers the local region. So fog monitoring using FY-1D in China can offer timely fog disaster information for traffic safety forecast and further weather trend analyses. Fog monitoring mainly uses visible and infrared bands which are not very good for fog mapping, however. The paper analyzed the image spectral properties of fog and low stratus to choose the best band combination for optimal fog mapping. The paper proposed the method of using FY-1D data to monitor daytime fog disaster in China.

  4. Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

    NASA Astrophysics Data System (ADS)

    El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

    2012-12-01

    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

  5. Global Monitoring for Food Security and Sustainable Land Management - Recent Advances of Remote Sensing Applications to African and Siberian Show Cases

    NASA Astrophysics Data System (ADS)

    Komp, K. U.; Haub, C.

    2012-07-01

    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.

  6. Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR

    NASA Astrophysics Data System (ADS)

    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 cethompsoniii@hotmail.com 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.

  7. Earth view: A business guide to orbital remote sensing

    NASA Technical Reports Server (NTRS)

    Bishop, Peter C.

    1990-01-01

    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.

  8. Remote Sensing Via Satellite: The Canadian Experience

    ERIC Educational Resources Information Center

    Classen, Hans George

    1974-01-01

    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)

  9. Remote sensing of volcanos and volcanic terrains

    NASA Technical Reports Server (NTRS)

    Mouginis-Mark, Peter J.; Francis, Peter W.; Wilson, Lionel; Pieri, David C.; Self, Stephen; Rose, William I.; Wood, Charles A.

    1989-01-01

    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.

  10. Application of remote sensing in forestry

    NASA Technical Reports Server (NTRS)

    Lauer, D. T.

    1973-01-01

    The use of remote sensing techniques in forestry studies is investigated. In particular, inventory, monitoring, detection, and management are discussed. Data show that infrared imagery appears to be the best technique for forestry studies. Data also show that color photographs are more easily interpreted than black and white ones.

  11. Remote sensing and today's forestry issues

    NASA Technical Reports Server (NTRS)

    Sayn-Wittgenstein, L.

    1977-01-01

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

  12. Remote Sensing for Climate and Environmental Change

    NASA Technical Reports Server (NTRS)

    Evans, Diane

    2011-01-01

    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.

  13. Remote sensing analysis of forest disturbances

    NASA Technical Reports Server (NTRS)

    Asner, Gregory P. (Inventor)

    2012-01-01

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

  14. Remote Sensing Analysis of Forest Disturbances

    NASA Technical Reports Server (NTRS)

    Asner, Gregory P. (Inventor)

    2015-01-01

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

  15. Remote Environmental Monitoring System CRADA

    SciTech Connect

    Hensley, R.D.

    2000-03-30

    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.

  16. Water Extent Monitoring Exploiting MR and HR Remote Sensing Data: Synergy, Constraints and Limits

    NASA Astrophysics Data System (ADS)

    Huber, C.; Uribe, C.; Lai, X.; Huang, S.; Yesou, H.

    2013-01-01

    EO MR and HR imagery, particularly SAR data, are powerful tools to monitor water extent that allow to understand the mechanism of complex key ecosystems such as Poyang Lake, considered as a key element for flood natural control and reduction as well as major resources within the Yangtze middle basin. To assess and validate a such long monitoring (2000 to 2011 with an image every 10 days), a particular attention was paid on data quality : the assessment of water extent synergy derived from multi-resolution dataset, and the impact of meteorological conditions, wind (inducing an increasing of surface roughness) and rain, on the SAR signal quality with bands C and X.

  17. Use of remote sensing to monitor nutrient uptake by winter cover crops in the Choptank River Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Winter cover crops are recognized as an important agricultural conservation practice for reducing nitrogen (N) losses to groundwater, and state cost-share programs have been established to promote winter cover crops on farms throughout the Chesapeake Bay watershed. Remote sensing provides a tool for...

  18. Monitoring urban impervious surface area change using China-Brazil Earth Resources Satellites and HJ-1 remote sensing images

    NASA Astrophysics Data System (ADS)

    Du, Peijun; Xia, Junshi; Feng, Li

    2015-01-01

    Impervious surface area (ISA) plays an important role in monitoring urbanization and related environmental changes, and has become a hotspot in urban and environmental studies. Xuzhou City, located in northwest Jiangsu Province, China, is chosen as the study area, and two scenes of China-Brazil Earth Resources Satellites images and one scene of HJ-1 image are employed to estimate ISA percentage and analyze the change trend from 2001 to 2009. Using a linear spectral mixture model (LSMM) and nonlinear backpropagation neural network (BPNN) method, all pixels are decomposed to derive four fraction images representing the abundance of four endmembers: vegetation, high-albedo objects, low-albedo objects, and soil. The ISA percentage is then derived by the combination of high- and low-albedo fraction images after removing the influence of water. Some high spatial resolution images are selected to validate the ISA estimation results, and the experimental results indicate that the accuracy of BPNN is higher than LSMM. By comparing the urban ISA abundances derived by BPNN from three dates, it is found that the ISA of Xuzhou City has increased rapidly from 2001 to 2009, especially in the northeast and southeast regions, corresponding to the urban planning scheme and fast urbanization. Compared to other medium remote sensing images, the revisit cycle of HJ-1 multispectral image is only two days, demonstrating the potential of such data for ISA extraction in urbanization, disaster, and other related applications.

  19. Monitoring the urban expansion of Athens using remote sensing and GIS techniques in the last 35 years

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos; Pavlopoulos, Kosmas; Chalkias, Christos; Manou, Dora

    2005-10-01

    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.

  20. Lake temperature and ice cover regimes in the Alaskan Subarctic and Arctic: Integrated monitoring, remote sensing, and modeling

    USGS Publications Warehouse

    Arp, C.D.; Jones, Benjamin M.; Whitman, Matthew; Larsen, A.; Urban, F.E.

    2010-01-01

    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.

  1. Some aspects of remote sensing for consideration in planning for environmental monitoring of the Alyeska Pipeline, Alaska

    USGS Publications Warehouse

    Skibitzke, Herbert E.

    1974-01-01

    Remote sensing data were taken along a line surveyed for the building of the Alyeska Pipeline, Alaska, in the winter of 1973-74. The portion considered in this report is the area from the Yukon River south to Isabel Pass in the Alaska Range. The occurrences of aufeis gave the appearance of four rather distinct modes of formation. In the area south of Big Delta, the icings occurred as seepage at the toes of the terraces and along the bottoms of the stream channels cutting into the terraces. In the Yukon-Tanana uplands, the icings occurred generally as seepage at the lowest points in the U-shaped valleys and along the surfaces of the streams in the tributary valleys incised into the rolling hills. The icings formed in the stream channels in both regions have similar hydraulic considerations as do the icings formed in the lower part of the valleys at the toes of the terraces. Aerial techniques of collecting data by photography and thermal imagery were tested in this setting as a basis for consideration in planning for potential environmental monitoring of the pipeline.

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

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

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

  3. Remote Sensing of Rain

    NASA Technical Reports Server (NTRS)

    Haddad, Ziad S.

    1999-01-01

    The first problem addressed concerns passive-microwave rain retrievals. Most current approaches start by building off-line a cloud-model-derived database. Given data, the retrieval algorithms search the database for the microwave temperatures "closest" to the observed data, then after some fine-tuning (performed in different ways by different implementations) the rain is estimated to be that which corresponds to the selected (and fine-tuned) set of database temperatures. These approaches have three drawbacks: they cannot properly take into account the ambiguities which arise from the fact that several rain scenarios can produce the same observed temperatures; they are quite inefficient since they require manipulating a large database along with often complex "fine-tuning" procedures; and they cannot refine their estimates if additional data is available. This past year we have derived closed formulae relating observed microwave brightness temperatures, T(sub b), and the underlying rain rates, R: average T(sub b) =f (rain) and average rain = g (T(sub b)), along with the corresponding covariance matrices. These results are sufficient to describe the conditional probabilities p(R/T(sub b)) and p(T(sub b)/R) to second order. Progress has also been made towards deriving a robust description of the rain drop size distribution (DSD). The widespread approach consisting in parameterizing the DSD as a gamma-distribution in terms of the drop diameter D suffers from the facts that, in reality, the DSD is not a smooth function of D and that the largely arbitrary Gamma model imposes unintended behavior, which has implications on any quantities derived from the DSD model. We have therefore developed a non-parametric yet practical description of the DSD, which is particularly well-suited for use in remote-sensing applications. The diagram on the left shows a comparison between an actual DSD sample and the truncated non-parametric representation. One figure shows the relation

  4. Remote sensing aids geologic mapping.

    NASA Technical Reports Server (NTRS)

    Knepper, D. H., Jr.; Marrs, R. W.

    1973-01-01

    Remote sensing techniques have been 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 to be used for interpretation of the complex Cenozoic tectonic and geomorphic histories of the area. Regional and local geologic mapping can be aided by the proper application of remote sensing techniques. Conventional color and color infrared photos contain a large amount of easily-extractable general geologic information and are easily used by geologists untrained in the field of remote sensing. Other kinds of sensor data used in this study, with the exception of SLAR imagery, were generally found to be impractical or unappropriate for broad-scale general geologic mapping.

  5. Quantifying Hydroecologic Change in a Degraded Wetland with Remote Sensing, Field Based Monitoring, and Modeling Approaches

    NASA Astrophysics Data System (ADS)

    Pathak, N.; Loheide, S. P.

    2009-12-01

    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.

  6. A REMOTE SENSING TECHNIQUE TO MONITOR 'CLADOPHORA' IN THE GREAT LAKES

    EPA Science Inventory

    The feasibility of using an airborne multispectral scanner to monitor shoreline algae problems has been demonstrated. Multispectral data were collected at two sites on the U.S. Lake Ontario shoreline. Computer generated color maps were produced to show spatial distribution of Cla...

  7. Evaluation of a remotely sensed evaporative stress index for monitoring patterns of anomalous water-use

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. Developing the Remote Sensing-based Early Warning System for Monitoring TSS Concentrations in Lake Mead

    EPA Science Inventory

    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...

  9. Application of Satellite Remote Sensing on Mountain Glacier and Coastal Zone Classification And Monitoring in South Asia

    NASA Astrophysics Data System (ADS)

    Zhu, Kefeng

    Observations from Earth's remote sensing satellites have been a promising tool for studies on land cover and its changes, and related environmental phenomena. In this study, we demonstrate two environmental related land cover classification applications using integrated methods that involve multiple passive and active remote sensing sensors onboard different satellites, including Landsat Thematic Mapper (TM) and other optical/infrared imageries, synthetic aperture radar (SAR) system such as the Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard of the Advanced Land Observing Satellite (ALOS), and radar altimeters such as the Environmental Satellite (ENVISAT), etc. Firstly, we did a case study in Geladandong glacier of classifying and obtaining the rock/glacier boundary using Landsat data as well as integrated SAR methods, including polarimetric SAR classification and repeat pass SAR correlation coefficients technique. Over 40 years, the shrinkage of the glacier was observed from the results of analyzing and classifying Landsat series data. The estimated retreating rates are 0.148 km2/year and 0.134 km2/year in region B and C of Geladandong glacier during 1973˜2014. The Randolph Glacier Inventory (RGI) 4.0 does not provide this dynamic changing of the glacier extent. Moreover, considerable biases have also been observed in several regions. To further strengthen the finding, we employed SAR and polarimetric SAR data by applying correlation coefficient calculation and polarimetric SAR decomposition and segmentation. The results were consistent with those from Landsat classification in every particular small glacier region. Secondly, data from multiple satellite sensors, including Landsat series, ALOS-1 PALSAR Synthetic Aperture Radar and ENVISAT altimeter are employed for the purpose of analyzing the water extent in polder regions and its changing trend in last 40 years and of surveying the impact on polder embankments caused by erosion and

  10. Remote sensing monitoring study for water area change of Fuxian Lake in last 40 years

    NASA Astrophysics Data System (ADS)

    Li, Jia; Wang, Jinliang; Duan, Ping

    2015-12-01

    Fuxian Lake located in the middle of Yunnan Province is second deepest lake in china. The water level of Fuxian Lake descends and its water area reduces in recent years owing to the climate changing. Therefore, it is crucial for rational utilization of lake resources to study the change trend of Fuxian Lake's area. Landsat images from 1974 to 2014 were used to monitor Fuxian Lake's area change. Monitoring results show that there are four apparent features of Fuxian Lake's area: (1) Years in which Fuxian Lake's area are larger are concentrated in 2006 to 2009. (2) From 1974 to 1990, Fuxian Lake's area change has a trend of decrease. (3) From 1990 to 2005, Fuxian Lake's area change shows a rise trend on the whole. (4) From 2005 to 2014, there is an obvious decrease trend of Fuxian Lake's area change.

  11. Using remote sensing imagery to monitoring sea surface pollution cause by abandoned gold-copper mine

    NASA Astrophysics Data System (ADS)

    Kao, H. M.; Ren, H.; Lee, Y. T.

    2010-08-01

    The Chinkuashih Benshen mine was the largest gold-copper mine in Taiwan before the owner had abandoned the mine in 1987. However, even the mine had been closed, the mineral still interacts with rain and underground water and flowed into the sea. The polluted sea surface had appeared yellow, green and even white color, and the pollutants had carried by the coast current. In this study, we used the optical satellite images to monitoring the sea surface. Several image processing algorithms are employed especial the subpixel technique and linear mixture model to estimate the concentration of pollutants. The change detection approach is also applied to track them. We also conduct the chemical analysis of the polluted water to provide the ground truth validation. By the correlation analysis between the satellite observation and the ground truth chemical analysis, an effective approach to monitoring water pollution could be established.

  12. On-Orbit MTF Measurement and Product Quality Monitoring for Commercial Remote Sensing Systems

    NASA Technical Reports Server (NTRS)

    Person, Steven

    2007-01-01

    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.

  13. Using in-field and remote sensing techniques for the monitoring of small-scale permafrost decline in Northern Quebec

    NASA Astrophysics Data System (ADS)

    May, Inga; Kim, Jun Su; Spannraft, Kati; Ludwig, Ralf; Hajnsek, Irena; Bernier, Monique; Allard, Michel

    2010-05-01

    Permafrost-affected soils represent about 45% of Canadian arctic and subarctic regions. Under the recently recorded changed climate conditions, the areas located in the discontinuous permafrost zones are likely to belong to the most impacted environments. Degradations of Palsas and lithalsas as being the most distinct permafrost landforms as well as an extension of wetlands have been observe during the past decades by several research teams all over the northern Arctic. These alterations, caused by longer an warmer thawing periods, are expected to become more and more frequent in the future. The effects on human beings and on the surrounding sensitive ecosystems are presumed to be momentous and of high relevance. Hence, there is a high demand for new techniques that are able to detect, and possibly even predict, the behavior of the permafrost within a changing environment. The presented study is part of an international research collaboration between LMU, INRS and UL within the framework of ArcticNet. The project intends to develop a monitoring system strongly based on remote sensing imagery and GIS-based data analysis, using a test site located in northern Quebec (Umiujaq, 56°33' N, 76°33' W). It shall be investigated to which extent the interpretation of satellite imagery is feasible to partially substitute costly and difficult geophysical point measurements, and to provide spatial knowledge about the major factors that control permafrost dynamics and ecosystem change. In a first step, these factors, mainly expected to be determined from changes in topography, vegetation cover and snow cover, are identified and validated by means of several consecutive ground truthing initiatives supporting the analysis of multi-sensoral time series of remotely sensed information. Both sources are used to generate and feed different concepts for modeling permafrost dynamics by ways of parameter retrieval and data assimilation. On this poster, the outcomes of the first project

  14. Remote sensing of drought: progress, challenges and opportunities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This review 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 relative humidity data from the Atmos...

  15. Remote Sensing of Ocean Color

    NASA Astrophysics Data System (ADS)

    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

  16. Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

    NASA Astrophysics Data System (ADS)

    Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

    2015-12-01

    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

  17. Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

    NASA Astrophysics Data System (ADS)

    Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

    2014-12-01

    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

  18. Support for global science - Remote sensing's challenge

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Star, J. L.

    1986-01-01

    Advances in remote sensing techniques are discussed. The benefits possible to remote sensing with the new Earth Observing System, which is composed of the Space Station and coorbiting and polar satellite platforms, are examined. Current changes in the remote sensing field, which involve a change from an industrial society to an informational society, force technology to high technology with high touch, short term to long term, centralized to decentralized, hierarchies to networks, and either/or to multiple option systems are studied. The explanatory and objective types of analyses for investigating biophysical, geochemical, and socioeconomic processes are described; the procedures include: morphometric, cause and effect, temporal and functional and ecological system analyses, inventory, mapping, monitoring, and modeling.

  19. Monitoring and Simulation Changes of Typical Lake Basin in Tibetan Plateau Using Remote Sensing Data (1980-2010)

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Zheng, H.; Zhang, B.; Lei, L.

    2013-12-01

    The environmental factors including snow cover, vegetation and hydrologic regime of lake are all sensitive factors and can reflect ecosystem responses to changing climate. A series of satellite-based environmental data archives including variation of snow cover, vegetation phenology and lake level, together with the in situ observation data were used to monitor and simulate the variation of typical lake basins in Tibetan Plateau for the period 1980-2010. Nam Co Lake is the highest lake in the central Tibetan Plateau and there was no any meteorological observation station or hydrological station in the basin before 2005. We chose Nam Co Lake as a typical study region. We chose Nam Co Lake as a typical study region and our results are including: (1) We provides a method for estimating the lake water storage based on historical meteorological records from 1976 to 2009, remote sensing images scattered in this period, in situ bathymetric survey, and GIS techniques, and presents a comprehensive 34-year analysis of intra-annual and inter-annual variations of Nam Co Lake water storage. (2) A series of satellite imagery-based environmental data archives including variation of snow cover, vegetation phenology and lake level in Nam Co Lake Basin, were mapped. (3) Simulation of lake level variation (1980-2010) has been conducted through modeling at a monthly time step for the first time and the contemporaneous water storage series was acquired, based on the satellite altimetric data, meterological data and the in-situ bathymetric survey data. (4) The scenario analysis method was used for further lake level simulation in the future ten years. We suppose the future climate status as 1971-1980, 1981-1990, 1991-2000, 2001-2010 and the average value during 1971-2010 respectively, totally five scenarios for lake level forecasting. (5) A mathematically defined sensitivity coefficient is used to evaluate the sensitivity of lake level related to climate variables. And the result shows

  20. Use of hyperspectral remote sensing for detection and monitoring of chemical and biological agents: a survey

    NASA Astrophysics Data System (ADS)

    Gomez, Richard B.; Dasgupta, Swarvanu

    2004-12-01

    This paper surveys the potential use of hyperspectral imaging technology for standoff detection of chemical and biological agents in terrorism defense applications. In particular it focuses on the uses of hyperspectral imaging technology to detect and monitor chemical and biological attacks. In so doing it examines current technologies, their advantages and disadvantages, and investigates the possible role of hyperspectral imaging for homeland security applications. The study also addresses and provides applicable solutions for several of the potential challenges that currently create barriers to the full use of hyperspectral technology in the standoff detection of likely available chemical and biological agents.

  1. Developments in Monitoring Rangelands Using Remotely-Sensed Cross-Fence Comparisons

    NASA Astrophysics Data System (ADS)

    Kilpatrick, A. D.; Warren-Smith, S. C.; Read, J. L.; Lewis, M. M.; Ostendorf, B.

    2012-07-01

    This paper presents a new method for the use of earth-observation images to assess relative land condition over broad regions, using a cross-fence comparison methodology. It controls for natural spatial and temporal variables (e.g. rainfall, temperature soils, ecosystem) so that we can objectively monitor rangelands and other areas for the effects of management. The method has been tested with small and large scale theoretical models, as well as a case study in South Australian rangelands. This method can also be applied in other systems and experiments such as field trials of crop varieties as a robust spatial statistic.

  2. Agriculture and food availability -- remote sensing of agriculture for food security monitoring in the developing world

    USGS Publications Warehouse

    Budde, Michael E.; Rowland, James; Funk, Christopher C.

    2010-01-01

    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.

  3. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

    NASA Astrophysics Data System (ADS)

    Hao, Cui; Zhang, Jiahua; Yao, Fengmei

    2015-03-01

    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

  4. Using Remote Sensing and Rpas for Archaeology and Monitoring in Western Greenland

    NASA Astrophysics Data System (ADS)

    Pavelka, K.; Šedina, J.; Matoušková, E.; Faltýnová, M.; Hlaváčová, I.

    2016-06-01

    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.

  5. Ambient vibration monitoring of slender structures by microwave interferometer remote sensing

    NASA Astrophysics Data System (ADS)

    Gikas, Vassilis

    2012-11-01

    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.

  6. Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing

    USGS Publications Warehouse

    Wylie, Bruce K.; Boyte, Stephen P.; Major, Donald J.

    2012-01-01

    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.

  7. Photogrammetry - Remote Sensing and Geoinformation

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  8. Remote Sensing of Earth Terrain

    NASA Technical Reports Server (NTRS)

    Kong, J. A.

    1984-01-01

    Theoretical models that are useful and practical in relating remote sensing data to the important physical parameters characterizing Earth terrain are developed. The development of models that are useful in data analysis and interpretation, scene simulation, and developing new remote sensing approaches and techniques is discussed. Numerous theoretical models that are applicable to the active and passive remote sensing of plowed fields, atmospheric precipitation, vegetation, and snow fields were developed. The radiative transfer theory is used to interpret the active and passive data as a function of rain rate. Both the random medium model and the discrete scatterer model is used to study the remote sensing of vegetation fields. Due to the non-spherical geometry of the scatterers there is strong azimuthal dependence in the observed data. Thus, the anisotropic random medium model and the discrete scatterer model with nonspherical particles was developed. In order to relate the remote sensing data to the actual physical parameters, the scattering of electromagnetic waves from randomly distributed dielectric scatterers was studied. Both the rigorous random discrete scatterer theory and the strong fluctuation theory are used to derive the backscattering cross section in terms of the actual physical parameters and the results agree well with the data obtained from the snow fields.

  9. Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

    NASA Technical Reports Server (NTRS)

    Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.

    1996-01-01

    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.

  10. UAV-based remote sensing of landslides as complement to geophysical subsurface monitoring

    NASA Astrophysics Data System (ADS)

    Rothmund, S.; Niethammer, U.; Joswig, M.

    2012-04-01

    It's just some years that UAVs (unmanned aerial vehicles) can acquire high-resolution aerial photos to produce digital elevation models, orthophotos of cm resolution, and short-term dislocation maps by repetitive flight campaigns. We have developed such UAV quadrocopter system at our institute, and successfully applied in high Alpine terrain to observe creeping landslides simultaneously to geophysical measuring campaigns. At Super-Sauze (France) and Heumös (Austria), we observed slide quakes by nanoseismic monitoring, subsurface topography by 2D/3D seismic, and soil moisture by geoelectric tomography. Aerial photos were processed by means of a multi-view-stereo approach for DTM and orthophotos, and multi-spectral decomposition for soil moisture changes. The joint interpretation unveiled surface manifestations of subsurface slide quakes as fissure structures of strike slip, normal and reverse faulting, and vegetation contrasts along water pathway changes.

  11. Prime agricultural land monitoring and assessment component of the California Integrated Remote Sensing System

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Tinney, L. R. (Principal Investigator); Streich, T.

    1981-01-01

    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.

  12. Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

    SciTech Connect

    Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.

    1996-12-31

    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.

  13. Laser Remote Sensing at NASA

    NASA Technical Reports Server (NTRS)

    Barnes, Norman P.

    2005-01-01

    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.

  14. Soil moisture variability within remote sensing pixels

    SciTech Connect

    Charpentier, M.A.; Groffman, P.M. )

    1992-11-30

    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.

  15. Detection and Monitoring of Intense Pyroconvection in Western North America using Remote Sensing and Meteorological Data

    NASA Astrophysics Data System (ADS)

    Peterson, D. A.; Solbrig, J. E.; Hyer, E. J.; Campbell, J. R.; Fromm, M. D.

    2015-12-01

    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

  16. Optical remote sensing for monitoring evolution of ablation season mountain snow cover

    NASA Astrophysics Data System (ADS)

    Lampkin, Derrick J.

    The investigations contained in this body of work detail a viable proof-of-concept model for monitoring seasonal snow pack propensity for melt release based on time-variant snow surface optical and thermal properties. The model has been called the Near Surface Moisture Index-(Snow) (NSMI). The NSMI was developed based on time-variant snow surface optical and thermal properties. This research achieved three primary objectives: (1) development of theoretical foundation and surface moisture sensitive algorithm used to track both surface melt and pack discharge potential; (2) time-dependent phases of coupling and decoupling between snow surface properties and melt discharge were characterized through analysis of long-term surface and sub-surface state variables; and (3) sensitivity of optical satellite systems specifically, EOS TERRA-MODIS, to melting were was examined through radiative transfer simulations. Simulated at-sensor radiance was produced for various grain size changes to determine MODIS capacity to track melt onset. MODIS wavelengths greater than 667nm were sensitive to large changes in grain sizes, particularly bands with coarse spatial resolution (1000m). Longer wavelengths showed greater sensitivity to small changes in smaller grains than to small changes in larger grains. Shorter wavelengths at 500m spatial resolution appeared less effective overall for monitoring changes in grain size. NMSI feature space using Normalized Difference Snow Index (NDSI) on the abscissa and brightness temperature (Tb) on the ordinate was simulated. Simulated NDSI as a function of grain radius saturated approximately around 400--450mum. ASTER derived NSMI demonstrated behavior consistent with simulations with deviations due to topography, vegetation, and regional heterogeneity. We examined NSMI performance during an entire melt season through tracking phases of coupling between snow surface properties and propensity for melt using two ground-base approaches; one with higher

  17. Monitored landscape change of Lake Baiyangdian wetland with dynamic reed area based on remote sensing

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; He, Lei; Zhang, Shengwei; Lei, Yuping

    2009-09-01

    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.

  18. National Land Use Monitoring Program in Multi-Temporal Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Kuo, YaoCheng; Chen, ChiFarn

    2016-04-01

    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.

  19. Remote sensing for urban planning

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  20. Aboveground Biomass Monitoring over Siberian Boreal Forest Using Radar Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Stelmaszczuk-Gorska, M. A.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    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%) [1]. Russian's forests are of particular concern, due to the largest source of uncertainty in global carbon stock calculations [1], and old inventory data that have not been updated in the last 25 years [2]. 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 [2] or 42.8% using semi-empirical approach [3].

  1. Integrated Monitoring and Modeling of Carbon Dioxide Leakage Risk Using Remote Sensing, Ground-Based Monitoring, Atmospheric Models and Risk-Indexing Tools

    NASA Astrophysics Data System (ADS)

    Burton, E. A.; Pickles, W. L.; Gouveia, F. J.; Bogen, K. T.; Rau, G. H.; Friedmann, J.

    2006-12-01

    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

  2. Remote sensing aids geologic mapping

    NASA Technical Reports Server (NTRS)

    Knepper, D. H., Jr.; Marrs, R. W.

    1972-01-01

    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.

  3. iPot: Improved potato monitoring in Belgium using remote sensing and crop growth modelling

    NASA Astrophysics Data System (ADS)

    Piccard, Isabelle; Gobin, Anne; Curnel, Yannick; Goffart, Jean-Pierre; Planchon, Viviane; Wellens, Joost; Tychon, Bernard; Cattoor, Nele; Cools, Romain

    2016-04-01

    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

  4. River Ice monitoring over the Susquehanna River Basin using remote sensing data

    NASA Astrophysics Data System (ADS)

    Chaouch, N.; Temimi, M.; Khanbilvardi, R.; Cabrera, R.; McKillop, G.

    2010-12-01

    The main goal of this study is to implement an automated multi-satellite based technique for the detection and monitoring of ice in the Susquehanna River. The timely detection of ice jams and ice breakups along the river is crucial because of the rapidity of these processes. Satellite images in the visible and infrared wavelengths are sensitive to ice and offer a frequent revisiting time and large spatial coverage. They are therefore very useful in achieving the goal of this study. Their main limitation, however, is that they cannot penetrate clouds. The simultaneous use of multi-satellite data and the development of daily and weekly composited images mitigate the cloud impact and permit for a better detection of ice. For this purpose, data from MODIS Terra, MODIS Aqua and AVHRR satellites are used. MODIS Terra and MODIS Aqua data are available since 1999 and 2002, respectively. They provide observations in the visible, near infrared and infrared at spatial resolution of 250 m, 500 m and 1 km. A comprehensive archive of almost 30 years of AVHRR and MODIS images covering the study area has been created. The proposed approach to detect and delineate river ice is based on an image fusion concept. This technique assigns red, green and blue colors to two different co-registered images which coincide in space but not in time. One of the two images corresponds to the visible data and the second image corresponds to the near infrared data. MODIS cloud mask product MOD35/MOD09 at the spatial resolution of 1 km is used. Recall that MODIS cloud mask was developed and tuned to perform reasonably well on a global scale. As an alternative, another local cloud detection technique will be tested and implemented. A threshold based technique will be utilized to automatically detect and map river ice. Developed ice maps will be verified using aerial photographs provided by the NOAA National Weather Service. Observed river discharge and water level at various cross-sections of the

  5. Monitoring particulate matters in urban areas in Malaysia using remote sensing and ground-based measurements

    NASA Astrophysics Data System (ADS)

    Kanniah, K. D.; Kamarul Zaman, Nurul Amalin Fatihah; Lim, H. Q.; Reba, Mohd Nadzri Md.

    2014-10-01

    Monitoring particulate matter less than 10 μm (PM10) near the ground routinely is critical for Malaysia for emergency management because Malaysia receives considerable amount of pollutants from both local and trans-boundary sources. Nevertheless, aerosol data covering major cities over a large spatial extent and on a continuous manner are limited. Thus, in the present study we aimed to estimate PM10 at 5 km spatial scale using AOD derived from MERIS sensor at 3 metropolitan cities in Malaysia. MERIS level 2 AOD data covering 5 years (2007-2011) were used to develop an empirical model to estimate PM10 at 11 locations covering Klang valley, Penang and Johor Bahru metropolitan cities. This study is different from previous studies conducted in Malaysia because in the current study we estimated PM10 by considering meteorological parameters that affect aerosol properties, including atmospheric stability, surface temperature and relative humidity derived from MODIS data and our product will be at ~5 km spatial scale. Results of this study show that the direct correlation between monthly averaged AOD and PM10 yielded a low and insignificant relationship (R2= 0.04 and RMSE = 7.06μg m-3). However, when AOD, relative humidity, land surface temperature and k index (atmospheric stability) were combined in a multiple linear regression analysis the correlation coefficient increased to 0.34 and the RMSE decreased to 8.91μg m-3. Among the variables k- index showed highest correlation with PM 10 (R2=0.35) compared to other variables. We further improved the relationship among PM10 and the independent variables using Artificial Neural Network. Results show that the correlation coefficient of the calibration dataset increased to 0.65 with low RMSE of 6.72μg m-3. The results may change when we consider more data points covering 10 years (2002- 2011) and enable the construction of a local model to estimate PM10 in urban areas in Malaysia.

  6. Improved ground-based remote-sensing systems help monitor plant response to climate and other changes

    USGS Publications Warehouse

    Dye, Dennis G.; Bogle, Rian C.

    2016-01-01

    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.

  7. Remote sensing procurement package: Remote Sensing Industry Directory

    NASA Technical Reports Server (NTRS)

    1981-01-01

    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.

  8. Monitoring of bacteria growth using a wireless, remote query resonant-circuit sensor: application to environmental sensing

    NASA Technical Reports Server (NTRS)

    Ong, K. G.; Wang, J.; Singh, R. S.; Bachas, L. G.; Grimes, C. A.; Daunert, S. (Principal Investigator)

    2001-01-01

    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.

  9. Monitoring of bacteria growth using a wireless, remote query resonant-circuit sensor: application to environmental sensing.

    PubMed

    Ong, K G; Wang, J; Singh, R S; Bachas, L G; Grimes, C A

    2001-06-01

    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. PMID:11390218

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  11. Application of remote sensing data to monitoring of oil pollution as part of the environmental expert system

    NASA Astrophysics Data System (ADS)

    Shagarova, Lyudmila; Muratova, Mira; Abuova, Sholpan

    2016-07-01

    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

  12. Detection and Monitoring of Global Changes and the Evolution in the Region of Bouzina (aures) Using Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Mekaoussi, M.; Benmessaoud, H.

    2015-10-01

    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.

  13. Remote sensing program

    NASA Technical Reports Server (NTRS)

    Liang, T.

    1973-01-01

    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.

  14. Remote Sensing May Provide Unprecedented Hydrological Data

    NASA Technical Reports Server (NTRS)

    Koster, R.; Houser, P.; Engman, E.; Kustas, W.

    1999-01-01

    , 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.

  15. Application of remote sensing to water resources problems

    NASA Technical Reports Server (NTRS)

    Clapp, J. L.

    1972-01-01

    The following conclusions were reached concerning the applications of remote sensing to water resources problems: (1) Remote sensing methods provide the most practical method of obtaining data for many water resources problems; (2) the multi-disciplinary approach is essential to the effective application of remote sensing to water resource problems; (3) there is a correlation between the amount of suspended solids in an effluent discharged into a water body and reflected energy; (4) remote sensing provides for more effective and accurate monitoring, discovery and characterization of the mixing zone of effluent discharged into a receiving water body; and (5) it is possible to differentiate between blue and blue-green algae.

  16. Remote sensing estimates of actual evapotranspiration in an irrigation district

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate estimates of the spatial distribution of actual evapotranspiration (AET) are useful in hydrology, but can be difficult to obtain. Remote sensing provides a potential capability for routinely monitoring AET by combining remotely sensed surface temperature and vegetation cover observations w...

  17. Remote sensing for site characterization

    USGS Publications Warehouse

    Kuehn, Friedrich, (Edited By); King, Trude V.; Hoerig, Bernhard; Peters, Douglas C.

    2000-01-01

    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.

  18. Satellite Remote Sensing: Aerosol Measurements

    NASA Technical Reports Server (NTRS)

    Kahn, Ralph A.

    2013-01-01

    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.

  19. Remote sensing of Italian volcanos

    NASA Technical Reports Server (NTRS)

    Bianchi, R.; Casacchia, R.; Coradini, A.; Duncan, A. M.; Guest, J. E.; Kahle, A.; Lanciano, P.; Pieri, D. C.; Poscolieri, M.

    1990-01-01

    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.

  20. Remote sensing. [land use mapping

    NASA Technical Reports Server (NTRS)

    Jinich, A.

    1979-01-01

    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.

  1. Remote sensing and aerial application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  2. Remote Sensing in Environmental Education.

    ERIC Educational Resources Information Center

    Huber, Thomas P.

    1983-01-01

    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)

  3. Remote Sensing of Water Pollution

    NASA Technical Reports Server (NTRS)

    White, P. G.

    1971-01-01

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

  4. Remote sensing of environmental disturbance

    NASA Technical Reports Server (NTRS)

    Latham, J. P.

    1972-01-01

    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.

  5. Development of a novel optical remote sensing monitor for fenceline monitoring and enhancement of existing leak detection and repair programs

    EPA Science Inventory

    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...

  6. Mississippi Sound remote sensing study

    NASA Technical Reports Server (NTRS)

    Atwell, B. H.; Thomann, G. C.

    1972-01-01

    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.

  7. Monitoring and analyses of volcanic activity using remote sensing data at the Alaska Volcano Observatory: Case study for Kamchatka, Russia, December 1997

    NASA Astrophysics Data System (ADS)

    Schneider, D. J.; Dean, K., G.; Dehn, J.; Miller, T., P.; Kirianov, V. Yu.

    There are about 100 potentially active volcanoes in the North Pacific Ocean region that includes Alaska, the Kamchatka Peninsula, and the Kurile Islands, but fewer than 25% are monitored seismically. The region averages about five volcanic eruptions per year, and more than 20,000 passengers and millions of dollars of cargo fly the air routes in this region each day. One of the primary public safety objectives of the Alaska Volcano Observatory (AVO) is to mitigate the hazard posed by volcanic ash clouds drifting into these busy air traffic routes. The AVO uses real-time remote sensing data (AVHRR, GOES, and GMS) in conjunction with other methods (primarily seismic) to monitor and analyze volcanic activity in the region. Remote sensing data can be used to detect volcanic thermal anomalies and to provide unique information on the location, movement, and composition of volcanic eruption clouds. Satellite images are routinely analyzed twice each day at AVO and many times per day during crisis situations. As part of its formal working relationship with the Kamchatka Volcanic Eruption Response Team (KVERT), the AVO provides satellite observations of volcanic activity in Kamchatka and distributes notices of volcanic eruptions from KVERT to non-Russian users in the international aviation community. This paper outlines the current remote sensing capabilities and operations of the AVO and describes the responsibilities and procedures of federal agencies and international aviation organizations for volcanic eruptions in the North Pacific region. A case study of the December 4, 1997, eruption of Bezymianny volcano, Russia, is used to illustrate how real-time remote sensing and hazard communication are used to mitigate the threat of volcanic ash to aircraft.

  8. Remote sensing data handbook

    NASA Technical Reports Server (NTRS)

    1978-01-01

    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.

  9. Microwave remote sensing of snowpack properties

    NASA Technical Reports Server (NTRS)

    Rango, A. (Editor)

    1980-01-01

    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.

  10. Operational Use of Remote Sensing within USDA

    NASA Technical Reports Server (NTRS)

    Bethel, Glenn R.

    2007-01-01

    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.

  11. Remote water monitoring system

    NASA Technical Reports Server (NTRS)

    Grana, D. C.; Haynes, D. P. (Inventor)

    1978-01-01

    A remote water monitoring system is described that integrates the functions of sampling, sample preservation, sample analysis, data transmission and remote operation. The system employs a floating buoy carrying an antenna connected by lines to one or more sampling units containing several sample chambers. Receipt of a command signal actuates a solenoid to open an intake valve outward from the sampling unit and communicates the water sample to an identifiable sample chamber. Such response to each signal receipt is repeated until all sample chambers are filled in a sample unit. Each sample taken is analyzed by an electrochemical sensor for a specific property and the data obtained is transmitted to a remote sending and receiving station. Thereafter, the samples remain isolated in the sample chambers until the sampling unit is recovered and the samples removed for further laboratory analysis.

  12. A remote sensing tool to monitor and predict epidemiologic outbreaks of Hanta virus infections and Lyme disease

    NASA Astrophysics Data System (ADS)

    Barrios, J. M.

    2009-04-01

    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

  13. A remote sensing tool to monitor and predict epidemiologic outbreaks of Hanta virus infections and Lyme disease

    NASA Astrophysics Data System (ADS)

    Barrios, M.; Verstraeten, W. W.; Amipour, S.; Wambacq, J.; Aerts, J.-M.; Maes, P.; Berckmans, D.; Lagrou, K.; van Ranst, M.; Coppin, P.

    2009-04-01

    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

  14. Remote sensing on Indian and public lands

    NASA Technical Reports Server (NTRS)

    Torbert, G. B.; Woll, A. M.

    1972-01-01

    The use of remote sensing techniques by the Bureaus of Indian Affairs and Land Management in planning resource problems, making decisions, writing environmental impact statements, and monitoring their respective programs is investigated. For Indian affairs, data cover the Papago, Fort Apache, San Carlos, and South Dakota Reservations. For the Land Management Office, data cover cadastral surveys, California desert study, range watersheds, and efforts to establish a natural resources information system.

  15. Monitoring Phenological Variability across a Tropical Savanna Aridity Gradient with Remote Sensing across Seasonal to Annualand Extreme Events

    NASA Astrophysics Data System (ADS)

    Huete, A.; Eamus, D.; Ma, X.; Restrepo-Coupe, N.; Boulain, N.; Hutley, L.

    2011-08-01

    Tropical savannas are key components of the global carbon and water cycles and understanding their functioning is critical to understanding ecosystem feedbacks to global climate. By observing broad scale vegetation responses to climatic variability, remote sensing offers powerful insights into the patterns and processes underlying savanna behaviour. However, savannas are highly complex, multi-layer and heterogenous ecosystems composed of C3 (herbaceous) and C4 (woodland) components with asynchronous phenological responses to environmental controls. There are concerns about optimizing the detection of savanna functioning as well as in understanding their environmental controls with remote-sensing data due to their coarse resolution. Furthermore, seasonalphenologic variations in satellite observations need to be sufficiently accurate to ensure confidence in interpreting vegetation responses to interannual climatic variation and to aid in constraining models of carbon and water fluxes. In this study, we analysed several years of high temporal frequency MODIS and TRMM satellite data sets of vegetation dynamics and rainfall, respectively, to seasonal and interannual responses of savanna multifunctional components to climate variability across a tropical savanna aridity gradient (1760 to 580 mm annual rainfall) in northern Australia. We compared our results with a series of eddy covariance (EC) tower flux data of gross primary production and analyzed a wide set of ecosystem processes including photosynthesis, net primary productivity, phenological metrics in timing of the growing season, and rain use efficiencies. We found MODIS satellite measurements to yield highly accurate spatial and temporal variability in ecosystem functioning and able to replicate interannual patterns and responses to rainfall observed with the EC tower data. Although these results appear promising for regional extensions of satelliteflux tower relationships at the landscape level, we also

  16. Application of Coastal Remote Sensing to Rhincodon Typus Habitat Monitoring Northeast of the Yucatán Peninsula

    NASA Astrophysics Data System (ADS)

    Leben, R. R.; Shannon, M. R.

    2013-05-01

    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.

  17. Combining Remote Sensing and Landscape Metrics to monitor Urban Spatial Variation - Examples from Growing and Shrinking Regions

    NASA Astrophysics Data System (ADS)

    Netzband, M.

    2011-12-01

    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

  18. Monitoring and forecasting of hazardous hydrometeorological phenomena on the basis of conjuctive use of remote sensing data and the results of numerical modeling

    NASA Astrophysics Data System (ADS)

    Voronov, Nikolai; Dikinis, Alexandr

    2015-04-01

    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.

  19. Guidelines for the selection of appropriate remote sensing technologies for landslide detection, monitoring and rapid mapping: the experience of the SafeLand European Project.

    NASA Astrophysics Data System (ADS)

    Stumpf, A.; Malet, J.-P.; Kerle, N.; Tofani, V.; Segoni, S.; Casagli, N.; Michoud, C.; Jaboyedoff, M.; Fornaro, G.; Peduto, D.; Cascini, L.; Baron, I.; Supper, R.; Oppikofer, T.; L'Heureux, J.-S.; Van Den Eeckhaut, M.; Hervás, J.; Moya, J.; Raucoules, D.; Carman, M.

    2012-04-01

    New earth observation satellites, innovative airborne platforms and sensors, high precision laser scanners, and enhanced ground-based geophysical investigation tools are a few examples of the increasing diversity of remote sensing technologies used in landslide analysis. The use of advanced sensors and analysis methods can help to significantly increase our understanding of potentially hazardous areas and helps to reduce associated risk. However, the choice of the optimal technology, analysis method and observation strategy requires careful considerations of the landslide process in the local and regional context, and the advantages and limitations of each technique. Guidelines for the selection of the most suitable remote sensing technologies according to different landslide types, displacement velocities, observational scales and risk management strategies have been proposed. The guidelines are meant to aid operational decision making, and include information such as spatial resolution and coverage, data and processing costs, and maturity of the method. The guidelines target scientists and end-users in charge of risk management, from the detection to the monitoring and the rapid mapping of landslides. They are illustrated by recent innovative methodologies developed for the creation and updating of landslide inventory maps, for the construction of landslide deformation maps and for the quantification of hazard. The guidelines were compiled with contributions from experts on landslide remote sensing from 13 European institutions coming from 8 different countries. This work is presented within the framework of the SafeLand project funded by the European Commission's FP7 Programme.

  20. Application of remote sensing to state and regional problems

    NASA Technical Reports Server (NTRS)

    Bouchillon, C. W.; Miller, W. F.; Landphair, H.; Zitta, V. L.

    1974-01-01

    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.

  1. 1984 World Conference on remote sensing technical papers

    SciTech Connect

    Morgan, K.M.

    1984-01-01

    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.

  2. Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

    NASA Astrophysics Data System (ADS)

    Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

    2015-04-01

    Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

  3. Remote sensing of foliar chemistry

    NASA Technical Reports Server (NTRS)

    Curran, Paul J.

    1989-01-01

    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.

  4. Geophysical aspects of remote sensing

    NASA Technical Reports Server (NTRS)

    Watson, K.

    1971-01-01

    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.

  5. Hyperspectral Remote Sensing of Foliar Nitrogen Content

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  6. Hyperspectral remote sensing of foliar nitrogen content.

    PubMed

    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

    2013-01-15

    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. PMID:23213258

  7. Remote sensing in biological oceanography

    NASA Technical Reports Server (NTRS)

    Esaias, W. E.

    1981-01-01

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

  8. Remote Sensing Information Science Research

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  9. Remote maintenance monitoring system

    NASA Technical Reports Server (NTRS)

    Simpkins, Lorenz G. (Inventor); Owens, Richard C. (Inventor); Rochette, Donn A. (Inventor)

    1992-01-01

    A remote maintenance monitoring system retrofits to a given hardware device with a sensor implant which gathers and captures failure data from the hardware device, without interfering with its operation. Failure data is continuously obtained from predetermined critical points within the hardware device, and is analyzed with a diagnostic expert system, which isolates failure origin to a particular component within the hardware device. For example, monitoring of a computer-based device may include monitoring of parity error data therefrom, as well as monitoring power supply fluctuations therein, so that parity error and power supply anomaly data may be used to trace the failure origin to a particular plane or power supply within the computer-based device. A plurality of sensor implants may be rerofit to corresponding plural devices comprising a distributed large-scale system. Transparent interface of the sensors to the devices precludes operative interference with the distributed network. Retrofit capability of the sensors permits monitoring of even older devices having no built-in testing technology. Continuous real time monitoring of a distributed network of such devices, coupled with diagnostic expert system analysis thereof, permits capture and analysis of even intermittent failures, thereby facilitating maintenance of the monitored large-scale system.

  10. Remote sensing of Earth terrain

    NASA Technical Reports Server (NTRS)

    Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.

    1990-01-01

    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.

  11. The application of remote sensing in the environmental risk monitoring of tailings pond: a case study in Zhangjiakou area of China

    NASA Astrophysics Data System (ADS)

    Xiao, Rulin; Shen, Wenming; Fu, Zhuo; Shi, Yuanli; Xiong, Wencheng; Cao, Fei

    2012-10-01

    As a kind of huge environmental risk source, tailings pond could cause a huge environmental disaster to the downstream area once an accident happened on it. Therefore it has become one key target of the environmental regulation in china. Especially, recently environmental emergencies caused by tailings pond are growing rapidly in China, the environmental emergency management of the tailings pond has been confronting with a severe situation. However, the regulatory agency is badly weak in the environmental regulation of tailings pond, due to the using of ground surveys and statistics which is costly, laborious and time consuming, and the lacking of strong technical and information support. Therefore, in this paper, according to the actual needs of the environmental emergency management of tailings pond, we firstly make a brief analysis of the characteristics of the tailings pond and the advantages and capability of remote sensing technology, and then proposed a comprehensive and systematic indexes system and the method of environmental risk monitoring of tailings pond based on remote sensing and GIS. The indexes system not only considers factors from the upstream area, the pond area and the downstream area in a perspective of the risk space theory, but also considers factors from risk source, risk receptor and risk control mechanism in a perspective of risk systems theory. Given that Zhangjiakou city has up to 580 tailings pond and is nearly located upstream of the water source of Beijing, so finally we apply the proposed indexes system and method in Zhangjiakou area in China to help collect environmental risk data of tailings pond in that area and find out it works well. Through the use case in Zhajiakou, the technique of using remote sensing to monitor environmental risk of tailings pond is feasible and effective, and would contribute to the establishment of `Space-Ground' monitoring network of tailings pond in future.

  12. An overview of GNSS remote sensing

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  13. Individual based, long term monitoring of acacia trees in hyper arid zone: Integration of a field survey and a remote sensing approach

    NASA Astrophysics Data System (ADS)

    Isaacson, Sivan; Blumberg, Dan G.; Ginat, Hanan; Shalmon, Benny

    2013-04-01

    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

  14. Ten ways remote sensing can contribute to conservation.

    PubMed

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

    2015-04-01

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

  15. The California Cooperative Remote Sensing Project

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Sheffner, Edwin J.

    1988-01-01

    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.

  16. Review of oil spill remote sensing.

    PubMed

    Fingas, Merv; Brown, Carl

    2014-06-15

    Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing. PMID:24759508

  17. Combining Remote Sensing imagery of both fine and coarse spatial resolution to Estimate Crop Evapotranspiration and quantifying its Influence on Crop Growth Monitoring.

    NASA Astrophysics Data System (ADS)

    Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio; Duveiller, Gregory; Piccard, Isabelle; de Wit, Allard; Tychon, Bernard; Bakary, Djaby; Defourny, Pierre

    2010-05-01

    This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. Evapotranspiration (ET) is a valuable parameter in the crop monitoring context since it provides information on the plant water stress status, which strongly influences crop development and, by extension, crop yield. To assess crop evapotranspiration over the GLOBAM study areas (300x300 km sites in Northern Europe and Central Ethiopia), a Soil-Vegetation-Atmosphere Transfer (SVAT) model forced with remote sensing and numerical weather prediction data has been used. This model runs at pre-operational level in the framework of the EUMETSAT LSA-SAF (Land Surface Analysis Satellite Application Facility) using SEVIRI and ECMWF data, as well as the ECOCLIMAP database to characterize the vegetation. The model generates ET images at the Meteosat Second Generation (MSG) spatial resolution (3 km at subsatellite point),with a temporal resolution of 30 min and monitors the entire MSG disk which covers Europe, Africa and part of Sud America . The SVAT model was run for 2007 using two approaches. The first approach is at the standard pre-operational mode. The second incorporates remote sensing information at various spatial resolutions going from LANDSAT (30m) to SEVIRI (3-5 km) passing by AWIFS (56m) and MODIS (250m). Fine spatial resolution data consists of crop type classification which enable to identify areas where pure crop specific MODIS time series can be compiled and used to derive Leaf Area Index estimations for the most important crops (wheat and maize). The use of this information allowed to characterize

  18. Developing Remote Sensing Methodology to Characterize Savanna Vegetation Structure and Composition for Rangeland Monitoring and Conservation Applications

    NASA Astrophysics Data System (ADS)

    Tsalyuk, M.; Kelly, M.; Getz, W.

    2012-12-01

    Rangeland ecosystems cover more than fifty percent of earth's land surface, host considerable biodiversity and provide vital ecosystem services. However, rangelands around the world face degradation due to climate change, land use change and overgrazing. Human-driven changes to fire and grazing regimes enhance degradation processes. The purpose of this research is to develop a remote sensing methodology to characterize the structure and composition of savanna vegetation, in order to improve the ability of conservation managers to monitor and address such degradation processes. Our study site, Etosha National Park, is a 22,270 km^2 semi-arid savanna located in north-central Namibia. Fencing and provision of artificial water sources for wildlife have changed the natural grazing patterns, which has caused bush encroachment and vegetation degradation across the park. We used MODIS and Landsat ETM+ 7 satellite imagery to map the vegetation type, dominant species, density, cover and biomass of herbaceous and woody vegetation in Etosha. We used imagery for 2007-2012 together with extensive field sampling, both in the wet and the dry seasons. At each sampling point, we identified the dominant species and measured the density, canopy size, height and diameter of the trees and shrubs. At only 31% of the sampling points, the identified vegetation type matched the class assigned at the 1996 classification. This may indicate significant habitat modifications in Etosha. We used two parallel analytical approaches to correlate between radiometric and field data. First, we show that traditional supervised classification identifies well five classes: bare soil, grassland, steppe, shrub savanna and tree savanna. We then refined this classification to enable us to identify the species composition in an area utilizing the phenological differences in timing and duration of greenness of the dominant tree and shrub species in Etosha. Specifically, using multi-date images we were able to

  19. High rate and high spatial resolution surface deformation monitoring of the Argentiere glacier from complementary remote sensing and geodetic data

    NASA Astrophysics Data System (ADS)

    Benoit, Lionel; Pham, Ha-Thai; Trouvé, Emmanuel; Vernier, Flavien; Moreau, Luc; Martin, Olivier; Thom, Christian; Briole, Pierre

    2014-05-01

    The Argentière glacier in the French Alps (Mont-Blanc massif) is a 10 km long glacier covering 19 km². Its flow on a large scale has been studied for over a hundred years by glaciologists, but the time and space fluctuations of its flow are still poorly documented. We selected a small area of the glacier, about 1 km upstream of the Lognan serac fall to measure the glacier flow with in-situ GPS measurements combined with time series of ground based pictures and time series of synthetic aperture radar images from the TerreSAR-X satellite. The experiment took place during two months between September and November 2013 with a network of thirteen single-frequency GPS receivers (eleven set up on the glacier and two on the nearby bedrock) deployed in the field with a sampling rate of 30s. Our data processing allows us to estimate epoch by epoch coordinates of each GPS site with a centimetric precision. The main interest of this approach is twofold : the monitoring of the temporal evolution of the flow and the providing of ground control points for the local and satellite remote sensing imagery. The average velocities of the stations is around 15 cm/day with peaks reaching 25cm/day lasting a few hours to one day after rainfalls or cooling periods. We explain these accelerations as the consequence of an increased basal water pressure. The strain tensor analysis shows a good consistency between the main strain axis and the orientation of the cracks on both sides of the glacier. However, available only at eleven points, the GPS data can not in any case give a picture of the overall deformation of the glacier. In order to map the glacier flow as a whole, including crevasse areas or serac falls, two automatic digital cameras were installed during the experiment on the bedrock on the shore of the glacier with acquisitions every three hours during day time. The processing of the stereo pairs produces maps in which the pixels coordinates (and their changes) are estimated with a

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  1. In situ Volcanic Plume Monitoring with small Unmanned Aerial Systems for Cal/Val of Satellite Remote Sensing Data: CARTA-UAV 2013 Mission (Invited)

    NASA Astrophysics Data System (ADS)

    Diaz, J. A.; Pieri, D. C.; Bland, G.; Fladeland, M. M.

    2013-12-01

    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.

  2. UAS remote sensing missions for rangeland applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rangelands cover about 50% of the earth’s land surface, are in remote areas and have low population densities, all of which provide an ideal opportunity for remote sensing applications from unmanned aircraft systems (UAS). In this paper, we describe a proven workflow for UAS-based remote sensing, an...

  3. Cardiac remote monitoring in France.

    PubMed

    Maillard, Nicolas; Perrotton, Fanny; Delage, Emilie; Gourraud, Jean-Baptiste; Lande, Gilles; Solnon, Aude; Probst, Vincent; Grimandi, Gael; Clouet, Johann

    2014-04-01

    The increase in number of implanted cardiac medical devices and the announced decrease in number of cardiologists have led to remote monitoring being considered as a pivotal tool for patient follow-up. For 10 years, remote monitoring has been the subject of multiple clinical studies. In these studies, reliability and clinical efficacy have been demonstrated, but the use of remote monitoring remains quite limited in France compared with other countries. To explain this delay in uptake, some organizational difficulties and the lack of reimbursement of remote monitoring are often mentioned. The results of medico-economic studies might provide answers about the value of remote monitoring and enable the supervisory authorities to define how its use will be financed. This review provides a global view of remote monitoring in France, and covers the principle, clinical efficacy, organizational and regulatory aspects, and medico-economic data. PMID:24709285

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

    PubMed

    Geymen, Abdurrahman; Baz, Ibrahim

    2008-05-01

    The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation. PMID:17624804

  5. Biogeochemical cycling and remote sensing

    NASA Technical Reports Server (NTRS)

    Peterson, D. L.

    1985-01-01

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

  6. Microwave remote sensing laboratory design

    NASA Technical Reports Server (NTRS)

    Friedman, E.

    1979-01-01

    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.

  7. Application of Remote Sensing in Agriculture

    NASA Astrophysics Data System (ADS)

    Piekarczyk, Jan

    2014-12-01

    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.

  8. Airborne Remote Sensing for Earth Science Applications

    NASA Technical Reports Server (NTRS)

    Aubrey, Andrew

    2013-01-01

    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.

  9. POTENTIAL FOR REMOTE SENSING FROM AGRICULTURAL AIRCRAFT USING DIGITAL VIDEO

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An imaging system for remote sensing was developed for agricultural aircraft. The system uses a digital video camera, GPS, and a video mapping system (VMS) as the GPS interface to video. Remote control and monitoring was implemented to allow the pilot to image only field areas of interest, facilitat...

  10. Proceedings of the twenty-third international symposium on remote sensing of environment

    SciTech Connect

    Not Available

    1990-01-01

    Presentations given in Plenary Sessions included the following topics: 30 Years of Operational Environmental Satellites: A Retrospective and Future View; Global Change Programs: A Status Report; Global Change Programs: The Role of Donors in Developing Countries; The technology Transfer Problem: Are There Solutions ; Commercialization of Remote Sensing: A Status Report. Poster Session topics included: National Remote Sensing Programs; Remote Sensing for Monitoring Environmental Change; Remote Sensing for Resource Development and Preservation; Remote Sensing for Economic and Policy Planning; New Remote Sensing Technology, Methodology and Training Programs.

  11. Nuclear Power Plant environment`s surveillance by satellite remote sensing and in-situ monitoring data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria

    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

  12. Analysis of remote sensing data

    NASA Astrophysics Data System (ADS)

    Guiness, E. A.; Sultan, M.; Arvidson, R. E.

    1985-08-01

    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.

  13. Analysis of Remote Sensing Data

    NASA Technical Reports Server (NTRS)

    Guiness, E. A.; Sultan, M.; Arvidson, R. E.

    1985-01-01

    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