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Sample records for adaptive remote-sensing techniques

  1. Adaptive Remote-Sensing Techniques Implementing Swarms of Mobile Agents

    Energy Technology Data Exchange (ETDEWEB)

    Asher, R.B.; Cameron, S.M.; Loubriel, G.M.; Robinett, R.D.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-11-25

    In many situations, stand-off remote-sensing and hazard-interdiction techniques over realistic operational areas are often impractical "and difficult to characterize. An alternative approach is to implement an adap- tively deployable array of sensitive agent-specific devices. Our group has been studying the collective be- havior of an autonomous, multi-agent system applied to chedbio detection and related emerging threat applications, The current physics-based models we are using coordinate a sensor array for mukivanate sig- nal optimization and coverage as re,alized by a swarm of robots or mobile vehicles. These intelligent control systems integrate'glob"ally operating decision-making systems and locally cooperative learning neural net- works to enhance re+-timp operational responses to dynarnical environments examples of which include obstacle avoidance, res~onding to prevailing wind patterns, and overcoming other natural obscurants or in- terferences. Collectively',tkensor nefirons with simple properties, interacting according to basic community rules, can accomplish complex interconnecting functions such as generalization, error correction, pattern recognition, sensor fusion, and localization. Neural nets provide a greater degree of robusmess and fault tolerance than conventional systems in that minor variations or imperfections do not impair performance. The robotic platforms would be equipped with sensor devices that perform opticaI detection of biologicais in combination with multivariate chemical analysis tools based on genetic and neural network algorithms, laser-diode LIDAR analysis, ultra-wideband short-pulsed transmitting and receiving antennas, thermal im- a:ing sensors, and optical Communication technology providing robust data throughput pathways. Mission scenarios under consideration include ground penetrating radar (GPR) for detection of underground struc- tures, airborne systems, and plume migration and mitigation. We will describe our

  2. Adaptive Remote-Sensing Techniques Implementing Swarms of Mobile Agents

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Loubriel, G.M.; Rbinett, R.D. III; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1999-04-01

    This paper focuses on our recent work at Sandia National Laboratories toward engineering a physics-based swarm of mobile vehicles for distributed sensing applications. Our goal is to coordinate a sensor array that optimizes sensor coverage and multivariate signal analysis by implementing artificial intelligence and evolutionary computational techniques. These intelligent control systems integrate both globally operating decision-making systems and locally cooperative information-sharing modes using genetically-trained neural networks. Once trained, neural networks have the ability to enhance real-time operational responses to dynamical environments, such as obstacle avoidance, responding to prevailing wind patterns, and overcoming other natural obscurants or interferences (jammers). The swarm realizes a collective set of sensor neurons with simple properties incorporating interactions based on basic community rules (potential fields) and complex interconnecting functions based on various neural network architectures, Therefore, the swarm is capable of redundant heterogeneous measurements which furnishes an additional degree of robustness and fault tolerance not afforded by conventional systems, while accomplishing such cognitive tasks as generalization, error correction, pattern recognition, and sensor fission. The robotic platforms could be equipped with specialized sensor devices including transmit/receive dipole antennas, chemical or biological sniffers in combination with recognition analysis tools, communication modulators, and laser diodes. Our group has been studying the collective behavior of an autonomous, multi-agent system applied to emerging threat applications. To accomplish such tasks, research in the fields of robotics, sensor technology, and swarms are being conducted within an integrated program. Mission scenarios under consideration include ground penetrating impulse radar (GPR) for detection of under-ground structures, airborne systems, and plume

  3. The Potential of AI Techniques for Remote Sensing

    Science.gov (United States)

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

    1984-01-01

    The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.

  4. Gully Features Extraction Using Remote Sensing Techniques ...

    African Journals Online (AJOL)

    Gullies are large and deep erosion depressions or channels normally occurring in drainage ways. They are spectrally heterogeneous, making them difficult to map using pixel based classification technique. The advancement of remote sensing in terms of Geographic Object Based Image Analysis (GEOBIA) provides new ...

  5. Noninvasive Remote Sensing Techniques for Infrastructures Diagnostics

    Directory of Open Access Journals (Sweden)

    Angelo Palombo

    2011-01-01

    Full Text Available The present paper aims at analyzing the potentialities of noninvasive remote sensing techniques used for detecting the conservation status of infrastructures. The applied remote sensing techniques are ground-based microwave radar interferometer and InfraRed Thermography (IRT to study a particular structure planned and made in the framework of the ISTIMES project (funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme. To exploit the effectiveness of the high-resolution remote sensing techniques applied we will use the high-frequency thermal camera to measure the structures oscillations by high-frequency analysis and ground-based microwave radar interferometer to measure the dynamic displacement of several points belonging to a large structure. The paper describes the preliminary research results and discusses on the future applicability and techniques developments for integrating high-frequency time series data of the thermal imagery and ground-based microwave radar interferometer data.

  6. A NDVI assisted remote sensing image adaptive scale segmentation method

    Science.gov (United States)

    Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

    2018-03-01

    Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

  7. Evaluation of reforestation using remote sensing techniques

    Science.gov (United States)

    Parada, N. D. J. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.

    1982-01-01

    The utilization of remotely sensed orbital data for forestry inventory. The study area (approximately 491,100 ha) encompasses the municipalities of Ribeirao Preto, Altinopolis, Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Sant Rita do Passa Quatro and Santa Rosa do Viterbo (Sao Paulo State). Materials used were LANDSAT data from channels 5 and 7 (scale 1:250,000) and CCT's. Visual interpretation of the imagery showed that for 1977 a total of 37,766.00 ha and for 1979 38,003.75 ha were reforested with Pinus and Eucalyptus within the area under study. The results obtained show that LANDSAT data can be used efficiently in forestry inventory studies.

  8. Offshore winds using remote sensing techniques

    International Nuclear Information System (INIS)

    Pena, Alfredo; Hasager, Charlotte Bay; Gryning, Sven-Erik; Courtney, Michael; Antoniou, Ioannis; Mikkelsen, Torben; Soerensen, Paul

    2007-01-01

    Ground-based remote sensing instruments can observe winds at different levels in the atmosphere where the wind characteristics change with height: the range of heights where modern turbine rotors are operating. A six-month wind assessment campaign has been made with a LiDAR (Light Detection And Ranging) and a SoDAR (Sound Detection and Ranging) on the transformer/platform of the world's largest offshore wind farm located at the West coast of Denmark to evaluate their ability to observe offshore winds. The high homogeneity and low turbulence levels registered allow the comparison of LiDAR and SoDAR with measurements from cups on masts surrounding the wind farm showing good agreement for both the mean wind speed and the longitudinal component of turbulence. An extension of mean wind speed profiles from cup measurements on masts with LiDAR observations results in a good match for the free sectors at different wind speeds. The log-linear profile is fitted to the extended profiles (averaged over all stabilities and roughness lengths) and the deviations are small. Extended profiles of turbulence intensity are also shown for different wind speeds up to 161 m. Friction velocities and roughness lengths calculated from the fitted log-linear profile are compared with the Charnock model which seems to overestimate the sea roughness for the free sectors

  9. Natural resource inventory for urban planning utilizing remote sensing techniques

    Science.gov (United States)

    Foster, K. E.; Mackey, P. F.; Bonham, C. D.

    1972-01-01

    Remote sensing techniques were applied to the lower Pantano Wash area to acquire data for planning an ecological balance between the expanding Tucson metropolitan area and its environment. The types and distribution of vegetation are discussed along with the hydrologic aspects of the Wash.

  10. Remote sensing and geochemistry techniques for the assessment of ...

    African Journals Online (AJOL)

    Chiedza

    4, No. 2, June 2015. 174. Remote sensing and geochemistry techniques for the assessment of coal mining pollution, Emalahleni (Witbank), Mpumalanga. ... Department of Environmental Affairs declared this air pollution hotspot as Highveld Priority ..... metal pollution in the urban stream sediments and its tributaries.

  11. Title: Gully Erosion Mapping Using Remote Sensing Techniques in ...

    African Journals Online (AJOL)

    NdifelaniM

    Abstract. Gullies are large and deep erosion depressions or channels normally occurring in drainage ways. They are spectrally heterogeneous, making them difficult to map using pixel based classification technique. The advancement of remote sensing in terms of Geographic Object Based Image Analysis. (GEOBIA) ...

  12. Assessing the accuracy of remote sensing techniques in vegetation ...

    African Journals Online (AJOL)

    This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil fractions in dune ecosystems along the Kenyan coast. The accurate measurements of field samples are required by Kenya Wildlife for environmental monitoring. The current methodology for ...

  13. a review of geothermal mapping techniques using remotely sensed ...

    African Journals Online (AJOL)

    Aliyu et al.

    Remote sensing offers a synoptic capability of covering large areas in real time and can cost effectively explore prospective geothermal sites not easily detectable using conventional survey methods, thus can aid in the prefeasibility stages of geothermal exploration. In this paper, we evaluate the techniques and approaches ...

  14. Application of remote sensing technique in biomass change detection

    African Journals Online (AJOL)

    Application of remote sensing technique in biomass change detection: a case study of Bromley and Chihota, Zimbabwe. ... There are various field methods used worldwide to determine density of forest resources but have several limitations because of the nature of factors influencing biomass change. These include ...

  15. Image processing techniques for remote sensing data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.

    interpretation and for processing of scene data for autonomous machine perception. The technique of digital image processing are used for' automatic character/pattern recognition, industrial robots for product assembly and inspection, military recognizance...-Type text/plain; charset=UTF-8 4. IMAGE PROCE:>SINGTOO~IQUE3FOR RmOTE SmSING DATA M. R. RAIirnH KUMAR National Institute of Oceanography, Dona PaUla, Goa-403004. Digital image processing is used for improvement of pictorial information for human...

  16. A practical CO2 flux remote sensing technique

    Science.gov (United States)

    Queisser, Manuel; Burton, Mike

    2017-04-01

    An accurate quantification of CO2 flux from both natural and anthropogenic sources is of great interest in various areas of the Earth, environmental and atmospheric sciences. As emitted excess CO2 quickly dilutes into the 400 ppm ambient CO2 concentration and degassing often occurs diffusively, measuring CO2 fluxes is challenging. Therefore, fluxes are usually derived from grids of in-situ measurements, which are labour intensive measurements. Other than a safe measurement distance, remote sensing offers quick, spatially integrated and thus a more thorough measurement of gas fluxes. Active remote sensing combines these merits with operation independent of sunlight or clear sky conditions. Due to their weight and size, active remote sensing platforms for CO2, such as LIDAR, cannot easily be applied in the field or transported overseas. Moreover, their complexity requires a rather lengthy setup procedure to be undertaken by skilled personal. To meet the need for a rugged, practical CO2 remote sensing technique to scan volcanic plumes, we have developed the CO2 LIDAR. It measures 1-D column densities of CO2 with sufficient sensitivity to reveal the contribution of magmatic CO2. The CO2 LIDAR has been mounted inside a small aircraft and used to measure atmospheric column CO2 concentrations between the aircraft and the ground. It was further employed on the ground, measuring CO2 emissions from mud volcanism. During the measurement campaign the CO2 LIDAR demonstrated reliability, portability, quick set-up time (10 to 15 min) and platform independence. This new technique opens the possibility of rapid, comprehensive surveys of point source, open-vent CO2 emissions, as well as emissions from more diffuse sources such as lakes and fumarole fields. Currently, within the proof-of-concept ERC project CarbSens, a further reduction in size, weight and operational complexity is underway with the goal to commercialize the platform. Areas of potential applications include fugitive

  17. Remote sensing techniques in monitoring areas affected by forest fire

    Science.gov (United States)

    Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

    2017-09-01

    Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

  18. ESTIMATION OF INSULATOR CONTAMINATIONS BY MEANS OF REMOTE SENSING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    G. Han

    2016-06-01

    Full Text Available The accurate estimation of deposits adhering on insulators is critical to prevent pollution flashovers which cause huge costs worldwide. The traditional evaluation method of insulator contaminations (IC is based sparse manual in-situ measurements, resulting in insufficient spatial representativeness and poor timeliness. Filling that gap, we proposed a novel evaluation framework of IC based on remote sensing and data mining. Varieties of products derived from satellite data, such as aerosol optical depth (AOD, digital elevation model (DEM, land use and land cover and normalized difference vegetation index were obtained to estimate the severity of IC along with the necessary field investigation inventory (pollution sources, ambient atmosphere and meteorological data. Rough set theory was utilized to minimize input sets under the prerequisite that the resultant set is equivalent to the full sets in terms of the decision ability to distinguish severity levels of IC. We found that AOD, the strength of pollution source and the precipitation are the top 3 decisive factors to estimate insulator contaminations. On that basis, different classification algorithm such as mahalanobis minimum distance, support vector machine (SVM and maximum likelihood method were utilized to estimate severity levels of IC. 10-fold cross-validation was carried out to evaluate the performances of different methods. SVM yielded the best overall accuracy among three algorithms. An overall accuracy of more than 70% was witnessed, suggesting a promising application of remote sensing in power maintenance. To our knowledge, this is the first trial to introduce remote sensing and relevant data analysis technique into the estimation of electrical insulator contaminations.

  19. Glacier and climate changes in the Western Indian Himalayas (Ladakh and Lahul-Spiti): remote sensing, field techniques and adaptation techniques

    Science.gov (United States)

    Racoviteanu, Adina; Williams, Mark

    2010-05-01

    Anecdotal evidence from glacier termini observations in the Himalayas suggest that these glaciers have been in a state of general retreat since the last century, and point to "alarming" rates of retreat in the past decades. Concomitantly, local communities in the Western Himalayas have reported changes in glacier extents, snow cover and weather patterns. In response to "alarming" rates of glacial retreat, some indigenous cultures in the Himalayan area have begun a number of adaptive responses such as meltwater harvesting to construct "artificial" glaciers, which store the water during the dry season. There is urgency in: a) scientifically evaluating whether such practices of glacier regeneration can help provide water in a timely manner and 2) developing glacier datasets to assist such local efforts to ensure water supply in these data-scarce mountainous areas. Here we compare and contrast scientific and indigenous perspectives on spatial patterns of glacier changes in the dry areas of Ladakh (34.10°N and 77.34°E ) and Lahul-Spiti district (31.11°N and 77.15°E ) in the Western Indian Himalaya. A new glacier inventory of Lahul-Spiti was constructed using a combination of data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor with Shuttle Radar Topography Mission (SRTM), GPS field data and ground photography. Glacier changes were quantified by comparison with older ASTER inventory and topographic maps. We present changes reported by local communities and recorded in video, oral testimonies and ground photography. We focus on two indigenous practices of water harvesting for glacier regeneration: a) artificial glaciers and b) kul irrigation systems. Field data of artificial glaciers was acquired at Sabu, Stakmo and Phuktsey glaciers using a differential GPS system. Kul irrigation systems were documented in Spiti valley (Lara and Kibber villages). We will present the results of mapping these water harvesting systems with the goal

  20. Hyperspectral remote sensing techniques for early detection of plant diseases

    Science.gov (United States)

    Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas

    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications in Earth observation. Nowadays spectral remote sensing techniques allow presymptomatic monitoring of changes in the physiological state of plants with high spectral resolution. Hyperspectral leaf reflectance and chlorophyll fluorescence proved to be highly suitable for identification of growth anomalies of cultural plants that result from the environmental changes and different stress factors. Hyperspectral technologies can find place in many scientific areas, as well as for monitoring of plants status and functioning to help in making timely management decisions. This research aimed to detect a presence of viral infection in young pepper plants (Capsicum annuum L.) caused by Cucumber Mosaic Virus (CMV) by using hyperspectral reflectance and fluorescence data and to assess the effect of some growth regulators on the development of the disease. In Bulgaria CMV is one of the widest spread pathogens, causing the biggest economical losses in crop vegetable production. Leaf spectral reflectance and fluorescence data were collected by a portable fibre-optics spectrometer in the spectral ranges 450÷850 nm and 600-900 nm. Greenhouse experiment with pepper plants of two cultivars, Sivria (sensitive to CMV) and Ostrion (resistant to CMV) were used. The plants were divided into six groups. The first group consisted of healthy (control) plants. At growth stage 4-6 expanded leaf, the second group was inoculated with CMV. The other four groups were treated with growth regulators: Spermine, MEIA (beta-monomethyl ester of itaconic acid), BTH (benzo(1,2,3)thiadiazole-7-carbothioic acid-S-methyl ester) and Phytoxin. On the next day, the pepper plants of these four groups were inoculated with CMV. The viral concentrations in the plants were determined by the serological method DAS-ELISA. Statistical, first derivative and cluster analysis were applied and several vegetation indices were

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

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2010-03-01

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

  2. REMOTE SENSING TECHNIQUES AS A TOOL FOR ENVIRONMENTAL MONITORING

    Directory of Open Access Journals (Sweden)

    K. Faisal

    2012-07-01

    Full Text Available 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

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

    Science.gov (United States)

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

    2000-01-01

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

  4. The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales.

    Science.gov (United States)

    Strong, James Asa; Elliott, Michael

    2017-03-15

    The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review.

    Directory of Open Access Journals (Sweden)

    Satya Kalluri

    2007-10-01

    Full Text Available Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed.

  6. Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

    International Nuclear Information System (INIS)

    Cosentino, B.L.; Lillesand, T.M.

    1991-01-01

    Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

  7. Remote sensing techniques for conservation and management of natural vegetation ecosystems

    Science.gov (United States)

    Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

    1981-01-01

    The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

  8. Unsupervised Remote Sensing Domain Adaptation Method with Adversarial Network and Auxiliary Task

    Directory of Open Access Journals (Sweden)

    XU Suhui

    2017-12-01

    Full Text Available An important prerequisite when annotating the remote sensing images by machine learning is that there are enough training samples for training, but labeling the samples is very time-consuming. In this paper, we solve the problem of unsupervised learning with small sample size in remote sensing image scene classification by domain adaptation method. A new domain adaptation framework is proposed which combines adversarial network and auxiliary task. Firstly, a novel remote sensing scene classification framework is established based on deep convolution neural networks. Secondly, a domain classifier is added to the network, in order to learn the domain-invariant features. The gradient direction of the domain loss is opposite to the label loss during the back propagation, which makes the domain predictor failed to distinguish the sample's domain. Lastly, we introduce an auxiliary task for the network, which augments the training samples and improves the generalization ability of the network. The experiments demonstrate better results in unsupervised classification with small sample sizes of remote sensing images compared to the baseline unsupervised domain adaptation approaches.

  9. Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

    Science.gov (United States)

    Kiang, Richard K.

    1992-01-01

    Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

  10. Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

    Science.gov (United States)

    Pelletier, R. E.; Griffin, R. H.

    1985-01-01

    The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

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

    Science.gov (United States)

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

    1972-01-01

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

  12. Remote sensing of chlorophyll a fluorescence of vegetation canopies. 1. Near and far field measurement techniques

    International Nuclear Information System (INIS)

    Cecchi, G.; Mazzinghi, P.; Pantani, L.; Valentini, R.; Tirelli, D.; De Angelis, P.

    1994-01-01

    This article presents instruments and techniques, used in several vegetation monitoring experiments. Simultaneous monitoring was performed with different approaches, including fluorescence lidar and passive remote sensing, leaf level reflectance, and laser fluorimetry, and compared with physiological measurements. Most of the instrumentation described was designed and built for this application. Experiments were carried out in the laboratory and in the field, to investigate the relationship between chlorophyll fluorescence spectra and plant ecophysiology. Remote sensing, spectroscopy, and ecophysiology data were then collected by an intensive research team, joining different experiences and working in national and international projects

  13. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

    Science.gov (United States)

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-01-01

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

  14. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

    Science.gov (United States)

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-02-07

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

  15. The Use Of GIS And Remote Sensing Techniques To Analyse Water ...

    African Journals Online (AJOL)

    Analysis of water balance for Lake Bogoria in Kenya using GIS and remote sensing techniques is presented in this study. Due to limited meteorological and hydrological data, long term averages of mean annual rainfall, streamflow and potential evaporation were used. Land cover of the catchment was derived from Landsat ...

  16. A Remote Sensing Image Fusion Method based on adaptive dictionary learning

    Science.gov (United States)

    He, Tongdi; Che, Zongxi

    2018-01-01

    This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

  17. Remote Sensing

    Indian Academy of Sciences (India)

    netic radiation as a medium of interaction. Space borne remote sensing is fast emerging as a front running provider of information on natural resources in a spatial format. This article briefly discusses the physical basis of remote sensing, how information is extracted from images and various applications of remote sensing.

  18. A review of geothermal mapping techniques using remotely sensed ...

    African Journals Online (AJOL)

    However, the effectiveness of the techniques relies on the sophistication and innovative digital image processing methods employed to sieve out relevant spectral information. The use of algorithms to estimate land surface temperature and heat fluxes are also applied to aid thermal anomaly detection, nevertheless, remote ...

  19. Pattern recognition in remote-sensing imagery using data mining and statistical techniques

    Science.gov (United States)

    Singh, Rajesh Kumar

    The remote sensing image classification domain has been explored and examined by scientists in the past using classical statistical and machine-learning techniques. Statistical techniques like Bayesian classifiers are good when the data is noise-free or normalized, while implicit models, or machine learning algorithms, such as artificial neural networks (ANN) are more of a "black box", relying on iterative training to adjust parameters using transfer functions to improve their predictive ability relative to training data for which the outputs are known. The statistical approach performs better when a priori information about categories is available, but they have limitations in the case of objective classification and when the distribution of data points are not known, as is the case with remote sensing satellite data. Data mining algorithms, which have potential advantages over classical statistical classifiers in analyzing remote sensing imagery data, were examined for use in land use classification of remote sensing data. Spectral classifications of LANDSAT(TM) imagery from 1989 were conducted using data mining and statistical techniques. The site selected for this research was NASA's Kennedy Space Center (KSC) in Florida. The raw satellite data used in classification was obtained using feature-extraction image processing techniques. The classification effort can broadly be divided into two major categories: (a) Supervised classification with subjectively defined prior known classes, and (b) Unsupervised classification with objectively categorized natural groups of similar attributes. Several predictive models and segmentation classification schemes were developed. The techniques used for evaluation of spectral patterns were based on both statistical and data mining algorithms. The statistical technique involved k-nearest neighbor statistical method, while data mining algorithms included: (1) back-propagation artificial neural network technique for two

  20. Introduction. [usefulness of modern remote sensing techniques for studying components of California water resources

    Science.gov (United States)

    Colwell, R. N.

    1973-01-01

    Since May 1970, personnel on several campuses of the University of California have been conducting investigations which seek to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Emphasis has been given to California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan. This study is designed to consider in detail the supply, demand, and impact relationships. The specific geographic areas studied are the Feather River drainage in northern California, the Chino-Riverside Basin and Imperial Valley areas in southern California, and selected portions of the west side of San Joaquin Valley in central California. An analysis is also given on how an effective benefit-cost study of remote sensing in relation to California's water resources might best be made.

  1. Leds used as spectral selective light detectors in remote sensing techniques

    International Nuclear Information System (INIS)

    Weber, C; Tocho, J O; Rodriguez, E J; Acciaresi, H A

    2011-01-01

    Remote sensing has been commonly considered as an effective technique in developing precision agriculture tools. Ground based and satellite spectral sensors have wide uses to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies as well as vegetation ground cover. Usually in-field remote sensing technologies use either a combination of interferential filters and photodiodes or different compact spectrometers to separate the spectral regions of interest. In this paper we present a new development of a sensor with LEDs used as spectrally selective photodetectors. Its performance was compared with a photodiode-filter sensor used in agronomic applications. Subsequent measurements of weed cover degree were performed and compared with other methodologies. Results show that the new LEDs based sensor has similar features that conventional ones to determining the weed soil cover degree; while LEDs based sensor has comparative advantages related its very low manufacturing cost and its robustness compatible with agricultural field applications.

  2. Geographic techniques and recent applications of remote sensing to landscape-water quality studies

    Science.gov (United States)

    Griffith, J.A.

    2002-01-01

    This article overviews recent advances in studies of landscape-water quality relationships using remote sensing techniques. With the increasing feasibility of using remotely-sensed data, landscape-water quality studies can now be more easily performed on regional, multi-state scales. The traditional method of relating land use and land cover to water quality has been extended to include landscape pattern and other landscape information derived from satellite data. Three items are focused on in this article: 1) the increasing recognition of the importance of larger-scale studies of regional water quality that require a landscape perspective; 2) the increasing importance of remotely sensed data, such as the imagery-derived normalized difference vegetation index (NDVI) and vegetation phenological metrics derived from time-series NDVI data; and 3) landscape pattern. In some studies, using landscape pattern metrics explained some of the variation in water quality not explained by land use/cover. However, in some other studies, the NDVI metrics were even more highly correlated to certain water quality parameters than either landscape pattern metrics or land use/cover proportions. Although studies relating landscape pattern metrics to water quality have had mixed results, this recent body of work applying these landscape measures and satellite-derived metrics to water quality analysis has demonstrated their potential usefulness in monitoring watershed conditions across large regions.

  3. Supervised Classification of Agricultural Land Cover Using a Modified k-NN Technique (MNN and Landsat Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Karsten Schulz

    2009-11-01

    Full Text Available Nearest neighbor techniques are commonly used in remote sensing, pattern recognition and statistics to classify objects into a predefined number of categories based on a given set of predictors. These techniques are especially useful for highly nonlinear relationship between the variables. In most studies the distance measure is adopted a priori. In contrast we propose a general procedure to find an adaptive metric that combines a local variance reducing technique and a linear embedding of the observation space into an appropriate Euclidean space. To illustrate the application of this technique, two agricultural land cover classifications using mono-temporal and multi-temporal Landsat scenes are presented. The results of the study, compared with standard approaches used in remote sensing such as maximum likelihood (ML or k-Nearest Neighbor (k-NN indicate substantial improvement with regard to the overall accuracy and the cardinality of the calibration data set. Also, using MNN in a soft/fuzzy classification framework demonstrated to be a very useful tool in order to derive critical areas that need some further attention and investment concerning additional calibration data.

  4. Remote Sensing

    Indian Academy of Sciences (India)

    Rangnath R Navalgund, after working for more than two decades at the. Space Applications. Centre (ISRO),. Ahmedabad has moved over to the National. Remote Sensing Agency,. Department of Space,. Hyderabad, as its. Director since May 2001. Definition of Indian spacebome remote sensing missions and formulation of ...

  5. Estimating Crop Growth Stage by Combining Meteorological and Remote Sensing Based Techniques

    Science.gov (United States)

    Champagne, C.; Alavi-Shoushtari, N.; Davidson, A. M.; Chipanshi, A.; Zhang, Y.; Shang, J.

    2016-12-01

    Estimations of seeding, harvest and phenological growth stage of crops are important sources of information for monitoring crop progress and crop yield forecasting. Growth stage has been traditionally estimated at the regional level through surveys, which rely on field staff to collect the information. Automated techniques to estimate growth stage have included agrometeorological approaches that use temperature and day length information to estimate accumulated heat and photoperiod, with thresholds used to determine when these stages are most likely. These approaches however, are crop and hybrid dependent, and can give widely varying results depending on the method used, particularly if the seeding date is unknown. Methods to estimate growth stage from remote sensing have progressed greatly in the past decade, with time series information from the Normalized Difference Vegetation Index (NDVI) the most common approach. Time series NDVI provide information on growth stage through a variety of techniques, including fitting functions to a series of measured NDVI values or smoothing these values and using thresholds to detect changes in slope that are indicative of rapidly increasing or decreasing `greeness' in the vegetation cover. The key limitations of these techniques for agriculture are frequent cloud cover in optical data that lead to errors in estimating local features in the time series function, and the incongruity between changes in greenness and traditional agricultural growth stages. There is great potential to combine both meteorological approaches and remote sensing to overcome the limitations of each technique. This research will examine the accuracy of both meteorological and remote sensing approaches over several agricultural sites in Canada, and look at the potential to integrate these techniques to provide improved estimates of crop growth stage for common field crops.

  6. Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques

    OpenAIRE

    Magesh, N.S.; Chandrasekar, N.; Soundranayagam, John Prince

    2012-01-01

    Integration of remote sensing data and the geographical information system (GIS) for the exploration of groundwater resources has become a breakthrough in the field of groundwater research, which assists in assessing, monitoring, and conserving groundwater resources. In the present paper, various groundwater potential zones for the assessment of groundwater availability in Theni district have been delineated using remote sensing and GIS techniques. Survey of India toposheets and IRS-1C satell...

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

    Science.gov (United States)

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

    2017-05-01

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

  8. Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

    Directory of Open Access Journals (Sweden)

    M. Darvishi

    2013-09-01

    Full Text Available The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave. Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE, snow state (wet/dry and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR. Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH and differential reflectivity (ZDR in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

  9. Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

    Science.gov (United States)

    Darvishi, M.; Ahmadi, Gh. R.

    2013-09-01

    The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave). Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE), snow state (wet/dry) and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR). Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH) and differential reflectivity (ZDR) in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

  10. Using optical remote sensing techniques to track the development of ozone-induced stress

    Energy Technology Data Exchange (ETDEWEB)

    Meroni, Michele, E-mail: michele.meroni@unimib.i [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy); Panigada, Cinzia; Rossini, Micol [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy); Picchi, Valentina [CNR, Plant Virology Institute, Milan Unit, Milan (Italy); Department of Tree Science, Entomology and Plant Pathology ' G. Scaramuzzi' , University of Pisa, Pisa (Italy); Cogliati, Sergio; Colombo, Roberto [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy)

    2009-05-15

    In this paper, a literature review about optical remote sensing (RS) of O{sub 3} stress is presented. Studies on O{sub 3}-induced effects on vegetation reflectance have been conducted since late '70s based on the analysis of optical RS data. Literature review reveals that traditional RS techniques were able to detect changes in leaf and canopy reflectance related to O{sub 3}-induced stress when visible symptoms already occurred. Only recently, advanced RS techniques using hyperspectral sensors, demonstrated the feasibility of detecting the stress in its early phase by monitoring excess energy dissipation pathways such as chlorophyll fluorescence and non-photochemical quenching (NPQ). Steady-state fluorescence (Fs), measured by exploiting the Fraunhofer line depth principle and NPQ related xanthophyll-cycle, estimated through the photochemical reflectance index (PRI) responded to O{sub 3} fumigation before visible symptoms occurred. This opens up new possibilities for the early detection of vegetation O{sub 3} stress by means of hyperspectral RS. - Possibilities for the early detection of vegetation O{sub 3} stress by means of optical remote sensing are discussed.

  11. Differential Radiometers Using Fabry-Perot Interferometric Technique for Remote Sensing of Greenhouse Gases

    Science.gov (United States)

    Georgieva, Elena M.; Heaps,William S.; Wilson, Emily L.

    2007-01-01

    A new type of remote sensing radiometer based upon the Fabry-Perot interferometric technique has been developed at NASA's Goddard Space Flight Center and tested from both ground and aircraft platform. The sensor uses direct or reflected sunlight and has channels for measuring column concentration of carbon dioxide at 1570 nm, oxygen lines sensitive to pressure and temperature at 762 and 768 nm, and water vapor (940 nm). A solid Fabry-Perot etalon is used as a tunable narrow bandpass filter to restrict the measurement to the gas of interest's absorption bands. By adjusting the temperature of the etalon, which changes the index of refraction of its material, the transmission fringes can be brought into nearly exact correspondence with absorption lines of the particular species. With this alignment between absorption lines and fringes, changes in the amount of a species in the atmosphere strongly affect the amount of light transmitted by the etalon and can be related to gas concentration. The technique is applicable to different chemical species. We have performed simulations and instrument design studies for CH4, "Cot isotope, and CO detection. Index Terms- Absorbing media, Atmospheric measurements, Fabry-Perot interferometers, Optical interferometry, Remote sensing.

  12. A Study on Integrated Community Based Flood Mitigation with Remote Sensing Technique in Kota Bharu, Kelantan

    International Nuclear Information System (INIS)

    Ainullotfi, A A; Ibrahim, A L; Masron, T

    2014-01-01

    This study is conducted to establish a community based flood management system that is integrated with remote sensing technique. To understand local knowledge, the demographic of the local society is obtained by using the survey approach. The local authorities are approached first to obtain information regarding the society in the study areas such as the population, the gender and the tabulation of settlement. The information about age, religion, ethnic, occupation, years of experience facing flood in the area, are recorded to understand more on how the local knowledge emerges. Then geographic data is obtained such as rainfall data, land use, land elevation, river discharge data. This information is used to establish a hydrological model of flood in the study area. Analysis were made from the survey approach to understand the pattern of society and how they react to floods while the analysis of geographic data is used to analyse the water extent and damage done by the flood. The final result of this research is to produce a flood mitigation method with a community based framework in the state of Kelantan. With the flood mitigation that involves the community's understanding towards flood also the techniques to forecast heavy rainfall and flood occurrence using remote sensing, it is hope that it could reduce the casualties and damage that might cause to the society and infrastructures in the study area

  13. Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae habitat and population densities

    Directory of Open Access Journals (Sweden)

    Khalifa M. Al-Kindi

    2017-08-01

    Full Text Available In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

  14. The application of remote sensing technique to metallogenetic prognosis in the covered area

    International Nuclear Information System (INIS)

    Huang Xianfang; Tian Hua; Luo Fusheng; Feng Jie; Huang Shutao; Guo Hongyan; Zhang Shuiming

    1994-08-01

    The idea, method and procedure of remote sensing research in the covered area are discussed. Using satellite image processing method (including faint information processing) in combination with multiple information comprehensive interpretation to decipher information of geological bodies covered with unconsolidated overburden and to predict favourable districts is also introduced. Taking the Yili basin for example, how to interpret ore-controlling factors is described. The concealed productive uranium formations which dominate uranium distribution have been delineated. The uplift and subsidence which are related to sedimentary environment and mineralization concentration have been discriminated. The faults (including the buried faults) which control the formation and development of the basin have been discerned. The stable and active areas, which are connected with uranium concentration, and preservation, and regional discharge zone have been interpreted. The result shows the feasibility of using remote sensing technique to predict the mineralization in the covered area, and six target areas have been optimized for further uranium reconnaissance and exploration in the study area

  15. Hydrogeological activity of lineaments in Yaoundé Cameroon region using remote sensing and GIS techniques

    Directory of Open Access Journals (Sweden)

    William Teikeu Assatse

    2016-06-01

    Full Text Available Though Yaoundé zone is characterized by abundant rains, access to safe drinking water becomes a difficult activity, because of climate change and pollution caused by human activities. Lineament zones on the earth’s surface are important elements in understanding the dynamics of the subsurface fluid flow. However, good exposures of these features are always lacking in some areas around Yaoundé, characterized by thick alteration. During field surveys these conditions, in many cases, hinder the proper characterization of such features. Therefore, an approach that identifies the regional lineaments on remote-sensing images (Landsat Thematic Mapper and shaded digital terrain models, with its large scale synoptic coverage, could be promising. This paper aims to the structural organization of lineament network in the crystalline basement of Yaoundé from remote sensing data and characterize them by statistical and geostatistical techniques. The results were validated on the basis of the geological maps, the hydrogeological maps and the outcrop data. Statistical analysis of the lineaments network shows a distribution along the N0–10, N20–30, N40–60 and N140–150. The correlation between the productivity of high yield wells and the closest lineament confirms that these lineaments are surface traces of regional discontinuities and act as main groundwater flow paths.

  16. A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques.

    Science.gov (United States)

    Gholizadeh, Mohammad Haji; Melesse, Assefa M; Reddi, Lakshmi

    2016-08-16

    Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water's surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).

  17. Mapping Cropland in Smallholder-Dominated Savannas: Integrating Remote Sensing Techniques and Probabilistic Modeling

    Directory of Open Access Journals (Sweden)

    Sean Sweeney

    2015-11-01

    Full Text Available Traditional smallholder farming systems dominate the savanna range countries of sub-Saharan Africa and provide the foundation for the region’s food security. Despite continued expansion of smallholder farming into the surrounding savanna landscapes, food insecurity in the region persists. Central to the monitoring of food security in these countries, and to understanding the processes behind it, are reliable, high-quality datasets of cultivated land. Remote sensing has been frequently used for this purpose but distinguishing crops under certain stages of growth from savanna woodlands has remained a major challenge. Yet, crop production in dryland ecosystems is most vulnerable to seasonal climate variability, amplifying the need for high quality products showing the distribution and extent of cropland. The key objective in this analysis is the development of a classification protocol for African savanna landscapes, emphasizing the delineation of cropland. We integrate remote sensing techniques with probabilistic modeling into an innovative workflow. We present summary results for this methodology applied to a land cover classification of Zambia’s Southern Province. Five primary land cover categories are classified for the study area, producing an overall map accuracy of 88.18%. Omission error within the cropland class is 12.11% and commission error 9.76%.

  18. Modelling desertification risk in the north-west of Jordan using geospatial and remote sensing techniques

    Directory of Open Access Journals (Sweden)

    Jawad T. Al-Bakri

    2016-03-01

    Full Text Available Remote sensing, climate, and ground data were used within a geographic information system (GIS to map desertification risk in the north-west of Jordan. The approach was based on modelling wind and water erosion and incorporating the results with a map representing the severity of drought. Water erosion was modelled by the universal soil loss equation, while wind erosion was modelled by a dust emission model. The extent of drought was mapped using the evapotranspiration water stress index (EWSI which incorporated actual and potential evapotranspiration. Output maps were assessed within GIS in terms of spatial patterns and the degree of correlation with soil surficial properties. Results showed that both topography and soil explained 75% of the variation in water erosion, while soil explained 25% of the variation in wind erosion, which was mainly controlled by natural factors of topography and wind. Analysis of the EWSI map showed that drought risk was dominating most of the rainfed areas. The combined effects of soil erosion and drought were reflected on the desertification risk map. The adoption of these geospatial and remote sensing techniques is, therefore, recommended to map desertification risk in Jordan and in similar arid environments.

  19. A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

    Science.gov (United States)

    Gholizadeh, Mohammad Haji; Melesse, Assefa M.; Reddi, Lakshmi

    2016-01-01

    Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). PMID:27537896

  20. Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

    Directory of Open Access Journals (Sweden)

    PENG Gang

    2014-12-01

    Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

  1. Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

    International Nuclear Information System (INIS)

    Seinfeld, J.H.

    1982-01-01

    The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed

  2. Application of Remote Sensing Techniques for Appraising Changes in Wildlife Habitat

    Science.gov (United States)

    Nelson, H. K.; Klett, A. T.; Johnston, J. E.

    1971-01-01

    An attempt was made to investigate the potential of airborne, multispectral, line scanner data acquisition and computer-implemented automatic recognition techniques for providing useful information about waterfowl breeding habitat in North Dakota. The spectral characteristics of the components of a landscape containing waterfowl habitat can be detected with airborne scanners. By analyzing these spectral characteristics it is possible to identify and map the landscape components through analog and digital processing methods. At the present stage of development multispectral remote sensing techniques are not ready for operational application to surveys of migratory bird habitat and other such resources. Further developments are needed to: (1) increase accuracy; (2) decrease retrieval and processing time; and (3) reduce costs.

  3. Laboratory insights into the detection of surface biosignatures by remote-sensing techniques

    Science.gov (United States)

    Poch, O.; Pommerol, A.; Jost, B.; Roditi, I.; Frey, J.; Thomas, N.

    2014-03-01

    With the progress of direct imaging techniques, it will be possible in the short or long-term future to retrieve more efficiently the information on the physical properties of the light reflected by rocky exoplanets (Traub et al., 2010). The search for visible-infrared absorption bands of peculiar gases (O2, CH4 etc.) in this light could give clues for the presence of life (Kaltenegger and Selsis, 2007). Even more uplifting would be the direct detection of life itself, on the surface of an exoplanet. Considering this latter possibility, what is the potential of optical remote-sensing methods to detect surface biosignatures? Reflected light from the surface of the Earth exhibits a strong surface biosignature in the form of an abrupt change of reflectance between the visible and infrared range of the spectrum (Seager et al., 2005). This spectral feature called "vegetation red-edge" is possibly the consequence of biological evolution selecting the right chemical structures enabling the plants to absorb the visible energy, while preventing them from overheating by reflecting more efficiently the infrared. Such red-edge is also found in primitive photosynthetic bacteria, cyanobacteria, that colonized the surface of the Earth ocean and continents billions of years before multicellular plants (Knacke, 2003). If life ever arose on an Earth-like exoplanet, one could hypothesize that some form of its surface-life evolves into similar photo-active organisms, also exhibiting a red-edge. In this paper, we will present our plan and preliminary results of a laboratory study aiming at precising the potentiality of remote sensing techniques in detecting such surface biosignatures. Using equipment that has been developed in our team for surface photometry studies (Pommerol 2011, Jost 2013, Pommerol 2013), we will investigate the reflectance spectra and bidirectional reflectance function of soils containing bacteria such as cyanobacteria, in various environmental conditions. We will

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

    Science.gov (United States)

    Evangelista, Paul H.

    peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.

  5. AN ADAPTIVE MORPHOLOGICAL MEAN FILTER FOR VERY HIGH-RESOLUTION REMOTE SENSING IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lv

    2017-09-01

    Full Text Available Very high resolution (VHR remote sensing imagery can reveal the ground object in greater detail, depicting their color, shape, size and structure. However, VHR also leads much original noise in spectra, and this original noise may reduce the reliability of the classification’s result. This paper presents an Adaptive Morphological Mean Filter (AMMF for smoothing the original noise of VHR imagery and improving the classification’s performance. AMMF is a shape-adaptive filter which is constructed by detecting gradually the spectral similarity between a kernel-anchored pixel and its contextual pixels through an extension-detector with 8-neighbouring pixels, and the spectral value of the kernel-anchored pixel is instead by the mean of group pixels within the adaptive region. The classification maps based on the AMMF are compared with the classification of VHR images based on the homologous filter processing, such as Mean Filter (MF and Median Filter(MedF. The experimental results suggest the following: 1 VHR image processed using AMMF can not only preserve the detail information among inter-classes but also smooth the noise within intra-class; 2 The proposed AMMF processing can improve the classification’s performance of VHR image, and it obtains a better visual performance and accuracy while comparing with MF and MedF.

  6. MAPPING GLAUCONITE UNITES WITH USING REMOTE SENSING TECHNIQUES IN NORTH EAST OF IRAN

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    R. Ahmadirouhani

    2014-10-01

    Full Text Available Glauconite is a greenish ferric-iron silicate mineral with micaceous structure, characteristically formed in shallow marine environments. Glauconite has been used as a pigmentation agent for oil paint, contaminants remover in environmental studies and a source of potassium in plant fertilizers, and other industries. Koppeh-dagh basin is extended in Iran, Afghanistan and Turkmenistan countries and Glauconite units exist in this basin. In this research for enhancing and mapping glauconitic units in Koppeh-dagh structural zone in north east of Iran, remote sensing techniques such as Spectral Angle Mapper classification (SAM, band ratio and band composition methods on SPOT, ASTER and Landsat data in 3 steps were applied.

  7. Assessment of agricultural drought vulnerability in the Philippines using remote sensing and GIS-based techniques

    International Nuclear Information System (INIS)

    Macapagal, Marco D.; Olivares, Resi O.; Perez, Gay Jane P.

    2015-01-01

    Drought is a recurrent extreme climate event that can cause crop damage and yield loss, thereby inflicting negative socioeconomic impacts all over the world. According to several climate studies, drought events may be more frequent and more severe as global warming progresses. As an agricultural country, the Philippines is highly susceptible to adverse impacts of drought using remotely sensed information and geographic processing techniques. An agricultural drought vulnerability map identifying croplands that are least vulnerable, moderately vulnerable, and most vulnerable to crop water-related stress, was developed. Vulnerability factors, including land use system, irrigation support. Available soil-water holding capacity, as well as satellite-derived evapotranspiration and rainfall, were taken into consideration in classifying and mapping agricultural drought vulnerability at a national level. (author)

  8. Novel Technique and Technologies for Active Optical Remote Sensing of Greenhouse Gases

    Science.gov (United States)

    Singh, Upendra N.; Refaat, Tamer F.; Petros, Mulugeta

    2017-01-01

    The societal benefits of understanding climate change through identification of global carbon dioxide sources and sinks led to the desired NASA's active sensing of carbon dioxide emissions over nights, days, and seasons (ASCENDS) space-based missions of global carbon dioxide measurements. For more than 15 years, NASA Langley Research Center (LaRC) have developed several carbon dioxide active remote sensors using the differential absorption lidar (DIAL) technique operating at the two-micron wavelength. Currently, an airborne two-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development. This IPDA lidar measures carbon dioxide as well as water vapor, the dominant interfering molecule on carbon dioxide remote sensing. Advancement of this triple-pulse IPDA lidar development is presented.

  9. USING REMOTE SENSING AND GIS-TECHNIQUES IN SOUTH EAST CASPIAN COASTAL CHANGES DETECTION

    Directory of Open Access Journals (Sweden)

    S. R. Mousavi

    2008-01-01

    Full Text Available Remote sensing and GIS techniques have been used to detect the shoreline changes along Miankaleh peninsula promontory of the Gorgan Bay entrance over the last three decades (1975-2002. For this purpose satellite data including LANDSAT ETM+, TM, SPOT, ASTER L1A and RADARSAT have been analyzed. SPOT-Pan data were georeferenced with respect to 1 : 50 000 topographic maps using a Universal Transverse Mercator (UTM projection, then all the needed data sets were registered to the SPOT-Pan image. The hydrological data showed a rapid rise of the Caspian Sea level by 2.6 m between “1975-1996”.

  10. Remote Sensing Analysis Techniques and Sensor Requirements to Support the Mapping of Illegal Domestic Waste Disposal Sites in Queensland, Australia

    Directory of Open Access Journals (Sweden)

    Katharine Glanville

    2015-10-01

    Full Text Available Illegal disposal of waste is a significant management issue for contemporary governments with waste posing an economic, social, and environmental risk. An improved understanding of the distribution of illegal waste disposal sites is critical to enhance the cost-effectiveness and efficiency of waste management efforts. Remotely sensed data has the potential to address this knowledge gap. However, the literature regarding the use of remote sensing to map illegal waste disposal sites is incomplete. This paper aims to analyze existing remote sensing methods and sensors used to monitor and map illegal waste disposal sites. The purpose of this paper is to support the evaluation of existing remote sensing methods for mapping illegal domestic waste sites in Queensland, Australia. Recent advances in technology and the acquisition of very high-resolution remote sensing imagery provide an important opportunity to (1 revisit established analysis techniques for identifying illegal waste disposal sites, (2 examine the applicability of different remote sensors for illegal waste disposal detection, and (3 identify opportunities for future research to increase the accuracy of any illegal waste disposal mapping products.

  11. Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status

    Science.gov (United States)

    Schmidt, Johannes; Fassnacht, Fabian Ewald; Neff, Christophe; Lausch, Angela; Kleinschmit, Birgit; Förster, Michael; Schmidtlein, Sebastian

    2017-08-01

    Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing

  12. Remote Sensing

    Indian Academy of Sciences (India)

    application area. RS data in conjunction with collateral data has greatly facilitated integrated development of land and water resources on watershed basis leading to sustainable develop- ment. Disaster monitoring, damage assessment and mitigation has been a main beneficiary of spaceborne remote sensing. Sequen-.

  13. Estimating biophysical properties of eucalyptus plantations using optical remote sensing techniques

    Science.gov (United States)

    Soares, Joao V.; Xavier, Alexandre C.; de Almeida, Auro C.; da Costa Freitas, Corina

    1998-12-01

    The feasibility of the inversion of optical remote sensing products to measure critical biophysical properties of Eucalyptus Forests at regional scales is investigated here. The biophysical variables used were leaf area Index, LAI, Diameter at Breast Height, DBH, Height and Age of Eucalyptus stands pertaining to a combination of different genetic materials (E. urophylla x E. grandis hybrids) and propagating systems (seeds or cuttings) and management system (planting and coppicing). The field sampling was done daily during 3 months, from April to June 1997, and covered 130 stands of minimum sizes of 9 hectares, within an Eucalyptus farming area of about 800 km2, centered at 19 degrees South, 42 degrees West, Brazil. The stands ranged from 12 to 84 months old. The measurements of LAI were done using two pairs of LAI-2000 (LICOR) under conditions of diffuse light. The Normalized Difference Vegetation Index, NDVI, and the Soil Adjusted Vegetation Index, SAVI, were derived from a LANDSAT-TM image acquired on June 5, 1997. Furthermore, a mixture model technique was applied to derive three new parameters: fraction of green vegetation, FGV, fraction of shadow, FSH, and fraction of soil, FS. Regression analysis were done between biophysical variables and remote sensing products. Linear correlation with coefficients of determination, R2, as high as 0.8 were found between LAI versus FGV and LAI versus SAVI, on all genetic materials. In general, SAVI was shown to give better estimates of LAI than NDVI, which is explained by the openings in the canopy as the Eucalyptus grow older. The correlation with the other biophysical variables (Height and DBH) were also shown to be significant, although the R2 ranged from 0.4 to 0.6. The correlation between FGV and SAVI was higher than 90% such that they can be used to estimate Eucalyptus biophysical parameters with the same statistical significance.

  14. PARALLEL AND ADAPTIVE UNIFORM-DISTRIBUTED REGISTRATION METHOD FOR CHANG’E-1 LUNAR REMOTE SENSED IMAGERY

    Directory of Open Access Journals (Sweden)

    X. Ning

    2012-08-01

    To resolve the above-mentioned registration difficulties, a parallel and adaptive uniform-distributed registration method for CE-1 lunar remote sensed imagery is proposed in this paper. Based on 6 pairs of randomly selected images, both the standard SIFT algorithm and the parallel and adaptive uniform-distributed registration method were executed, the versatility and effectiveness were assessed. The experimental results indicate that: by applying the parallel and adaptive uniform-distributed registration method, the efficiency of CE-1 lunar remote sensed imagery registration were increased dramatically. Therefore, the proposed method in the paper could acquire uniform-distributed registration results more effectively, the registration difficulties including difficult to obtain results, time-consuming, non-uniform distribution could be successfully solved.

  15. Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion techniques

    Science.gov (United States)

    Kimes, D. S.

    1983-01-01

    A physically based sensor response model of a row crop was used as the mathematical framework from which several inversion strategies were tested for extracting row structure information and component temperatures using a series of sensor view angles. The technique was evaluated on ground-based radiometric thermal infrared data of a cotton row crop that covered 48 percent of the ground in the vertical projection. The results showed that the accuracies of the predicted row heights and widths, vegetation temperatures, and soil temperatures of the cotton row crop were on the order of 5 cm, 1 deg, and 2 deg C, respectively. The inversion techniques can be applied to directional sensor data from aircraft platforms and even space platforms if the effects of atmospheric absorption and emission can be corrected. In theory, such inversion techniques can be applied to a wide variety of vegetation types and thus can have significant implications for remote sensing research and applications in disciplines that deal with incomplete vegetation canopies.

  16. Determination of Potential Fishing Grounds of Rastrelliger kanagurta Using Satellite Remote Sensing and GIS Technique

    International Nuclear Information System (INIS)

    Suhartono Nurdin; Muzzneena Ahmad Mustapha; Tukimat Lihan; Mazlan Abdul Ghaffar; Muzzneena Ahmad Mustapha; Nurdin, S.

    2015-01-01

    Analysis of relationship between sea surface temperature (SST) and Chlorophyll-a (chl-a) improves our understanding on the variability and productivity of the marine environment, which is important for exploring fishery resources. Monthly level 3 and daily level 1 images of Moderate Resolution Imaging Spectroradiometer Satellite (MODIS) derived SST and chl-a from July 2002 to June 2011 around the archipelagic waters of Spermonde Indonesia were used to investigate the relationship between SST and chl-a and to forecast the potential fishing ground of Rastrelliger kanagurta. The results indicated that there was positive correlation between SST and chl-a (R=0.3, p<0.05). Positive correlation was also found between SST and chl-a with the catch of R. kanagurta (R=0.7, p<0.05). The potential fishing grounds of R. kanagurta were found located along the coast (at accuracy of 76.9 %). This study indicated that, with the integration of remote sensing technology, statistical modeling and geographic information systems (GIS) technique were able to determine the relationship between SST and chl-a and also able to forecast aggregation of R. kanagurta. This may contribute in decision making and reducing search hunting time and cost in fishing activities. (author)

  17. The Study of Mining Activities and their Influences in the Almaden Region Applying Remote Sensing Techniques

    International Nuclear Information System (INIS)

    Rico, C.; Schmid, T.; Millan, R.; Gumuzzio, J.

    2010-01-01

    This scientific-technical report is a part of an ongoing research work carried out by Celia Rico Fraile in order to obtain the Diploma of Advanced Studies as part of her PhD studies. This work has been developed in collaboration with the Faculty of Science at The Universidad Autonoma de Madrid and the Department of Environment at CIEMAT. The main objective of this work was the characterization and classification of land use in Almaden (Ciudad Real) during cinnabar mineral exploitation and after mining activities ceased in 2002, developing a methodology focused on the integration of remote sensing techniques applying multispectral and hyper spectral satellite data. By means of preprocessing and processing of data from the satellite images as well as data obtained from field campaigns, a spectral library was compiled in order to obtain representative land surfaces within the study area. Monitoring results show that the distribution of areas affected by mining activities is rapidly diminishing in recent years. (Author) 130 refs

  18. Soil Erosion Estimation Using Remote Sensing Techniques in Wadi Yalamlam Basin, Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Jarbou A. Bahrawi

    2016-01-01

    Full Text Available Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing (RS and Geographic Information Systems (GIS techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating the K-factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk (37,740 ha. GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.

  19. Detecting Leakage from Carbon Capture and Storage Facilities Using Hyperspectral Remote Sensing Techniques

    Science.gov (United States)

    Yahaya, S.; Steven, M.; Foody, G.

    2012-12-01

    The study aims to detect the effects of leakage from carbon capture and storage (CCS) facilities using the spectral reflectance properties of vegetation. Carbon dioxide concentrations up to 80% in soil were applied to experimental plots as part of a study of the potential effects of CCS. Plant stress effects are detected by spectral scanning between 350 and 2500nm with an ASD Fieldspec FR spectroradiometer (ASD, Boulder, USA) fitted with a fibre optic probe having a 23 degrees field of view. The sampling interval over the 350-1050 nm range is 1.4 nm with a resolution of 3 nm. Over the 1050-2500 nm range the sampling interval is about 2 nm and the spectral resolution is between 10 and 12 nm. The results are then interpolated by the ASD software to produce readings at every 1 nm. Derivative analysis was used to locate the position and height of the inflection point of the red edge and other peaks that may indicate stress in plants. The study investigates the ability of hyperspectral remote sensing techniques to determine the severity of stress in crops.

  20. Applications of geographic information systems and remote sensing techniques to conservation of amphibians in northwestern Ecuador

    Directory of Open Access Journals (Sweden)

    Mariela Palacios González

    2015-01-01

    Full Text Available The biodiversity of the Andean Chocó in western Ecuador and Colombia is threatened by anthropogenic changes in land cover. The main goal of this study was to contribute to conservation of 12 threatened species of amphibians at a cloud forest site in northwestern Ecuador, by identifying and proposing protection of critical areas. We used Geographic Information Systems (GIS and remote sensing techniques to quantify land cover changes over 35 years and outline important areas for amphibian conservation. We performed a supervised classification of an IKONOS satellite image from 2011 and two aerial photographs from 1977 and 2000. The 2011 IKONOS satellite image classification was used to delineate areas important for conservation of threatened amphibians within a 200 m buffer around rivers and streams. The overall classification accuracy of the three images was ≥80%. Forest cover was reduced by 17% during the last 34 years. However, only 50% of the study area retained the initial (1977 forest cover, as land was cleared for farming and eventually reforested. Finally, using the 2011 IKONOS satellite image, we delineated areas of potential conservation interest that would benefit the long term survival of threatened amphibian species at the Ecuadorian cloud forest site studied.

  1. Impacts of soil sealing on potential agriculture in Egypt using remote sensing and GIS techniques

    Science.gov (United States)

    Mohamed, Elsayed Said; Belal, Abdelaziz; Shalaby, Adel

    2015-10-01

    This paper highlights the impacts of soil sealing on the agricultural soils in Nile Delta using remote sensing and GIS. The current work focuses on two aims. The first aim is to evaluate soil productivity lost to urban sprawl, which is a significant cause of soil sealing in Nile Delta. The second aim is to evaluate the Land Use and Land Cover Changes (LU LC) from 2001 to 2013 in El-Gharbia governorate as a case study. Three temporal data sets of images from two different sensors: Landsat 7 Enhanced Thematic Mapper (ETM+) with 30 m resolution acquired in 2001 and Landsat 8 acquired in 2013 with 30 m resolution, and Egypt sat acquired in 2010 with 7.8 m resolution, consequently were used. Four different supervised classification techniques (Maximum Likelihood (ML), Minimum Distance, Neural Networks (NN); and Support Vector Machine (SVM) were applied to monitor the changes of LULC in the investigated area. The results showed that the agricultural soils of the investigated area are characterized by high soil productivity depending on its chemical and physical properties. During 2010-2013, soil sealing took place on 1397 ha from the study area which characterized by soil productivity classes ranging between I and II. It is expected that the urban sprawl will be increased to 12.4% by 2020 from the study area, which means that additional 3400 ha of productive soils will be lost from agriculture. However, population growth is the most significant factor effecting urban sprawl in Nile Delta.

  2. Remote sensing techniques for determining landcover features: applications for a species at risk

    Directory of Open Access Journals (Sweden)

    Catherine Fauvelle

    2017-08-01

    Full Text Available Remote sensing techniques are becoming more advanced and commonplace in conservation biology, and are used to study spatial patterns of various taxa. The main objective of this study was to determine whether supervised classification of landcover types within Landsat imagery could be accurately used to find or locate islands on lakes that may have been overlooked during ground transects in central Saskatchewan. Additionally, we used telemetry data from collared female caribou to determine which islands were used and in which season(s, and to determine island char­acteristics that make caribou more likely to select them. We were able to successfully identify all islands within bodies of water relevant to collared caribou using a supervised classification method, which suggests that our methods were adequate. We also determined that none of the island characteristics significantly influenced caribou selection accord­ing to an occupancy model, however females tended to choose islands with a higher vegetation cover (NDVI during the summer months and a proportionally lower snow cover during the winter months, likely as forage and predator avoidance strategies respectively. Finally, we suggest directions for future studies as well as implications for both wildlife managers and land-use planners in Saskatchewan, Canada.

  3. The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills

    Science.gov (United States)

    Garron, J.; Trainor, S.

    2017-12-01

    Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill

  4. An Adaptive Web-Based Learning Environment for the Application of Remote Sensing in Schools

    Science.gov (United States)

    Wolf, N.; Fuchsgruber, V.; Riembauer, G.; Siegmund, A.

    2016-06-01

    Satellite images have great educational potential for teaching on environmental issues and can promote the motivation of young people to enter careers in natural science and technology. Due to the importance and ubiquity of remote sensing in science, industry and the public, the use of satellite imagery has been included into many school curricular in Germany. However, its implementation into school practice is still hesitant, mainly due to lack of teachers' know-how and education materials that align with the curricula. In the project "Space4Geography" a web-based learning platform is developed with the aim to facilitate the application of satellite imagery in secondary school teaching and to foster effective student learning experiences in geography and other related subjects in an interdisciplinary way. The platform features ten learning modules demonstrating the exemplary application of original high spatial resolution remote sensing data (RapidEye and TerraSAR-X) to examine current environmental issues such as droughts, deforestation and urban sprawl. In this way, students will be introduced into the versatile applications of spaceborne earth observation and geospatial technologies. The integrated web-based remote sensing software "BLIF" equips the students with a toolset to explore, process and analyze the satellite images, thereby fostering the competence of students to work on geographical and environmental questions without requiring prior knowledge of remote sensing. This contribution presents the educational concept of the learning environment and its realization by the example of the learning module "Deforestation of the rainforest in Brasil".

  5. Synchronization of Well Log Data and Geophysical Data with Remote Sensing Technique to Develop the Hydrocarbon System of Bengal Basin

    Science.gov (United States)

    Kesh, S.; Samadder, P. K.

    2012-12-01

    Remote sensing along with more conventional exploration techniques such as geophysics and reconnaissance field mapping can help to establish regional geologic relationships, to extract major structural features and to pinpoint anomalous patterns. Many well have been drilled in Bengal basin still no commercially viable reserves have been discovered. Geophysical well logging is used in virtually every oil well. It is the primary means by which we characterize the subsurface in search of hydrocarbons. Oil and gas exploration activities for large areas require ground gravity surveys to facilitate detailed geological interpretations for subsurface features integrating geological cross-sections with the sub-surface structural trends leads to the identification of prospect areas. Remote sensing, geological and geophysical data integration provide accurate geometric shapes of the basins. Bengal basin has a sedimentary fill of 10-15 km, is the northernmost of the east coast basins of India In the first phase Remote sensing satellite sensors help in identifying surface anomaly which indicates the presence of hydrocarbon reservoirs providing regional geological settings of petroleferous basins. It provides accurate and visual data for directly determining geometric shapes of basin. It assists in the selection of exploration regions by defining the existence of sedimentary basin. Remote sensing methods can generate a wealth of information useful in determining the value of exploratory prospecting. In the second phase Well Log data provide relative subsurface information for oil and gas exploration. Remote sensing data are merged with other available information such as Aeromagnetic, gravity, geochemical surveys and 2D seismic surveys. The result of this phase is to estimate the outcome of oil discovery probabilities for locating oil prospects

  6. Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa

    Directory of Open Access Journals (Sweden)

    Dambach Peter

    2012-03-01

    Full Text Available Abstract Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM, precipitation (Tropical Rainfall Measurement Mission = TRMM, land surface temperatures (LST. Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines

  7. A fast combinatorial enhancement technique for earthquake damage identification based on remote sensing image

    Science.gov (United States)

    Dou, Aixia; Wang, Xiaoqing; Ding, Xiang; Du, Zecheng

    2010-11-01

    On the basis of the study on the enhancement methods of remote sensing images obtained after several earthquakes, the paper designed a new and optimized image enhancement model which was implemented by combining different single methods. The patterns of elementary model units and combined types of model were defined. Based on the enhancement model database, the algorithm of combinatorial model was brought out via C++ programming. The combined model was tested by processing the aerial remote sensing images obtained after 1976 Tangshan earthquake. It was proved that the definition and implementation of combined enhancement model can efficiently improve the ability and flexibility of image enhancement algorithm.

  8. Environmental modelling of Omerli catchment area in Istanbul, Turkey using remote sensing and GIS techniques.

    Science.gov (United States)

    Coskun, H Gonca; Alparslan, Erhan

    2009-06-01

    Omerli Reservoir is one of the major drinking water reservoirs of Greater Metropolis Istanbul, providing 40% of the overall water demand. Istanbul where is one of the greatest metropolitan areas of the world with a population over 10 million and a rate of population increase about twice that of Turkey. As a result of population growth and industrial development, Omerli watershed is highly affected by the wastewater discharges from the residential areas and industrial plants. The main objective of this study is to investigate the temporal assessment of the land-use/cover of the Omerli Watershed and the water quality changes in the Reservoir. It is not possible to adequately control urbanization and other pollution sources affecting the water quality. Responses of these detrimental effects are due to rapidly increasing population, unplanned and illegal housing, and irrelevant industries at the protection zones of the watershed, together with insufficient infrastructure. The study is focused on the assessment of urbanization in relation to land use and water quality using Remote Sensing (RS) and Geographic Information Systems (GIS) techniques for all the four protection zones of the Reservoir and a time variant analyzing model is obtained. IRS-1C LISS and IRS-1C PAN, LANDSAT-5 TM satellite data of 1997, 1998, 2000, 2001 and 2006 are analyzed by confirmation through the ground truth data. RS data have been transferred into UTM coordinate system and image enhancement and classification techniques were used. Raster data were converted to vector data that belongs to study area to analyze in GIS for the purpose of planning and decision-making on protected watersheds.

  9. Detecting Subsurface Agricultural Tile Drainage using GIS and Remote Sensing Technique

    Science.gov (United States)

    Budhathoki, M.; Gokkaya, K.; Tank, J. L.; Christopher, S. F.; Hanrahan, B.

    2015-12-01

    Subsurface tile drainage is a common practice in many of the row crop dominated agricultural lands in the Upper Midwest, which increases yield by making the soil more productive. It is reported that nearly half of all cropland in Indiana benefits from some sort of artificial drainage. However, subsurface tile has a significant negative impact on surface water quality by providing a fast means of transport for nutrients from fertilizers. Therefore, generating spatial data of tile drainage in the field is important and useful for agricultural landscape and hydrological studies. Subsurface tile drains in Indiana's croplands are not widely mapped. In this study, we will delineate subsurface tile drainage in agricultural land in Shatto Ditch watershed, located in Kosciusko County, Indiana. We will use geo-spatial methodology, which was purposed by earlier researchers to detect tile drainage. We will use aerial color-infrared and satellite imagery along with Light Detection and Ranging (LiDAR) data. In order to map tile lines with possible accuracy, we will use GIS-based analysis in combination with remotely sensed data. This research will be comprised of three stages: 1) masking out the potential drainage area using a decision tree rule based on land cover information, soil drainage category, surface slope, and satellite image differencing technique, 2) delineate tile lines using image processing techniques, and 3) check the accuracy of mapped tile lines with ground control points. To our knowledge, this study will be the first to check the accuracy of mapping with ground truth data. Based on the accuracy of results, we will extend the methodology to greater spatial scales. The results are expected to contribute to better characterizing and controlling water pollution sources in Indiana, which is a major environmental problem.

  10. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

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

  11. Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

    Science.gov (United States)

    S. Panda; D.M. Amatya; G. Hoogenboom

    2014-01-01

    Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

  12. Remote sensing techniques to assess active fire characteristics and post-fire effects

    Science.gov (United States)

    Leigh B. Lentile; Zachary A. Holden; Alistair M. S. Smith; Michael J. Falkowski; Andrew T. Hudak; Penelope Morgan; Sarah A. Lewis; Paul E. Gessler; Nate C. Benson

    2006-01-01

    Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous...

  13. Estimation the Amount of Oil Palm Trees Production Using Remote Sensing Technique

    Science.gov (United States)

    Fitrianto, A. C.; Tokimatsu, K.; Sufwandika, M.

    2017-12-01

    Currently, fossil fuels were used as the main source of power supply to generate energy including electricity. Depletion in the amount of fossil fuels has been causing the increasing price of crude petroleum and the demand for alternative energy which is renewable and environment-friendly and it is defined from vegetable oils such palm oil, rapeseed and soybean. Indonesia known as the big palm oil producer which is the largest agricultural industry with total harvested oil palm area which is estimated grew until 8.9 million ha in 2015. On the other hand, lack of information about the age of oil palm trees and changes also their spatial distribution is mainly problem for energy planning. This research conducted to estimate fresh fruit bunch (FFB) of oil palm and their distribution using remote sensing technique. Cimulang oil palm plantation was choose as study area. First step, estimated the age of oil palm trees based on their canopy density as the result from Landsat 8 OLI analysis and classified into five class. From this result, we correlated oil palm age with their average FFB production per six months and classified into seed (0-3 years, 0kg), young (4-8 years, 68.77kg), teen (9-14 years, 109.08kg), and mature (14-25 years, 73.91kg). The result from satellite image analysis shows if Cimulang plantation area consist of teen old oil palm trees that it is covers around 81.5% of that area, followed by mature oil palm trees with 18.5% or corresponding to 100 hectares and have total production of FFB every six months around 7,974,787.24 kg.

  14. Monitoring deforestation and urbanization growth in rawal watershed area using remote sensing and gis techniques

    International Nuclear Information System (INIS)

    Saeed, M.A.; Ashraf, A.

    2011-01-01

    The Rawal watershed in Pothwar region of Pakistan has undergone significant changes in its environmental conditions and landuse activities due to numerous socio-economic and natural factors. These ultimately influence the livelihood of the inhabitants of the area. The connected environmental changes are resulting in accelerated land degradation, deforestation, and landslides. In the present study, spatio-temporal behaviour of landuse/landcover in the Rawal watershed area was investigated using Remote Sensing (RS) and Geographical Information System (GIS) techniques. Satellite image data of LANDSAT ETM+ of 1992, 2000 and 2010 periods were processed and analyzed for detecting land use change and identifying risk prone locations in the watershed area. The study results revealed significant changes in the coverage of conifer forest (34 % decrease), scrub forest (29 % decrease) and settlement (231 % increase) during the decade 1992-2010. The rate of decline in conifer class is about 19 ha/annum while that of scrub class is 223 ha/annum. In both the cases, the rates of decrease were higher during the period 1992-2000 than the period 2000-2010. The Agriculture land has shown an increase of about 1.8% while built-up land had increased almost four folds, i.e. from 2.6 % in 1992 to 8.7 % in 2010. The growth in urbanization may result in further loss of forest cover in the watershed area. The findings of the study could help in developing effective strategies for future resource management and conservation, as well as for controlling land degradation in the watershed area. (author)

  15. Morphotectonics of the Jamini River basin, Bundelkhand Craton, Central India; using remote sensing and GIS technique

    Science.gov (United States)

    Prakash, K.; Mohanty, T.; Pati, J. K.; Singh, S.; Chaubey, K.

    2017-11-01

    Morphological and morphotectonic analyses have been used to obtain information that influence hydrographic basins, predominantly these are modifications of tectonic elements and the quantitative description of landforms. Discrimination of morphotectonic indices of active tectonics of the Jamini river basin consists the analyses of asymmetry factor, ruggedness number, basin relief, gradient, basin elongation ratio, drainage density analysis, and drainage pattern analysis, which have been completed for each drainage basin using remote sensing and GIS techniques. The Jamini river is one of the major tributaries of the Betwa river in central India. The Jamini river basin is divided into five subwatersheds viz. Jamrar, Onri, Sainam, Shahzad and Baragl subwatershed. The quantitative approach of watershed development of the Jamini river basin, and its four sixth (SW1-SW4) and one fifth (SW5) order subwatersheds, was carried out using Survey of India toposheets (parts of 54I, 54K, 54L, 54O, and 54P), Landsat 7 ETM+, ASTER (GDEM) data, and field data. The Jamini river has low bifurcation index which is a positive marker of tectonic imprint on the hydrographic network. The analyses show that the geomorphological progression of the study area was robustly influenced by tectonics. The analysis demonstrates to extensional tectonics system with the following alignments: NE-SW, NW-SE, NNE-SSW, ENE-WSW, E-W, and N-S. Three major trends are followed by lower order streams viz. NE-SW, NW-SE, and E-W directions which advocate that these tectonic trends were active at least up to the Late Pleistocene. The assessment of morphotectonic indices may be used to evaluate the control of active faults on the hydrographic system. The analysis points out westward tilting of the drainage basins with strong asymmetry in some reaches, marked elongation ratio of subwatersheds, and lower order streams having close alignment with lineaments (active faults). The study facilitated to considerate the

  16. Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection

    Science.gov (United States)

    Rueda-Velasquez, Carlos Alberto

    Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources. Although various approaches formulated to model multidimensional data can in principle be applied to the inherent complexity of remotely sensed geospatial data, there are still challenging peculiarities that demand a precise characterization in the context of change detection, particularly in scenarios of fast changes. In the same vein, geospatial image streams do not fit appropriately in the standard Data Stream Management System (DSMS) approach because these systems mainly deal with tuple-based streams. Recognizing the necessity for a systematic effort to address the above issues, the work presented in this thesis is a concrete step toward the foundation and construction of an integrated Geospatial Image Stream Processing framework, GISP. First, we present a data and metadata model for remotely sensed image streams. We introduce a precise characterization of images and image streams in the context of remotely sensed geospatial data. On this foundation, we define spatially-aware temporal operators with a consistent semantics for change analysis tasks. We address the change detection problem in settings where multiple image stream sources are available, and thus we introduce an architectural design for the processing of geospatial image streams from multiple sources. With the aim of targeting collaborative scientific environments, we construct a realization of our architecture based on Kepler, a robust and widely used scientific workflow management system, as the underlying computational support; and open data and Web interface standards, as a means to facilitate the interoperability of GISP instances with other processing infrastructures and client applications. We demonstrate our

  17. Application of remote sensing techniques for monitoring the thermal pollution of cooling-water discharge from nuclear power plant.

    Science.gov (United States)

    Chen, Chuqun; Shi, Ping; Mao, Qingwen

    2003-08-01

    This article introduces a practical method to investigate thermal pollution in coastal water from satellite data. The intensity and distribution areas of thermal pollution by the heated effluent discharge from the nuclear power plant on Daya Bay, southern China were investigated by using Landsat-5 Thematic Mapper (TM) thermal band data from 1994 to 2001. A local algorithm was developed, based on sea-truth data of water surface temperature measured when the satellite passed over the study area. The local algorithm was then applied to estimate water temperature from TM data. It shows that the remote sensing technique provides an effective means to quantitatively monitor the intensity of thermal pollution and to retrieve a very detailed distribution pattern of thermal pollution in coastal waters. The remotely-sensed results of the thermal pollution can be used for environmental management of coastal waters.

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

    Science.gov (United States)

    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

  19. A technique of the structural-tectonic elevations prediction using Earth remote sensing data

    Science.gov (United States)

    Tishaev, I. V.; Zatserkovnyi, V. I.; Yagorlytska, K. P.

    2016-12-01

    We consider an approach of using methods of Earth remote sensing data (RSD) classification for solving tasks of exploration geology and geophysics. Information obtained from the remote sensing data gives a possibility to clarify the structure of investigated areas and to determine neotectonic elevations, which act as certain indicators of promising areas with hydra-carbons contents. Reasonability of using such methods of RSD classification is based on connection between deep structure of surface resources (structural-tectonic setting) with current landscape, character of hydrologic network, geo-morphological, geo-botanical and other features. The advantage of Bayes classificator is not only in determination of object belonging to certain class, but also in calculation of probability of such belonging. For the formulated task this lets to forecast a presence of structural-tectonic elevations, which are potentially promising areas for hydra-carbons contents, using a formali! zed quantitative criterion. contents.

  20. Using multi-scale remote sensing techniques to quantify hillslope channel coupling in bedrock landscapes

    Science.gov (United States)

    Neely, A. B.; DiBiase, R.

    2016-12-01

    Quantifying the role of rock material properties in controlling landscape-scale erosion rates is a long-standing problem in geomorphology, yet is necessary for accurate interpretation of spatial and temporal patterns of climate and tectonics encoded in Earth's topography. In bedrock landscapes, rockfall from cliffs commonly provides the largest and strongest clasts to stream networks and, until these clasts are eroded or mobilized, can inhibit channel incision into bedrock. Hillslope and channel morphology are thought to be coupled through a connection between bedrock fracture spacing and the resulting grain size distribution of stream sediment, but field quantification of this effect in bedrock landscapes is difficult due to the inaccessibility of steep terrain and challenges characterizing heterogeneity at a range of scales. Here, we use a suite of nested field and remote sensing techniques to characterize bedrock landscape morphology in the San Jacinto and San Gabriel mountain ranges of Southern California. These ranges have similar climate, granitic bedrock, and topographic relief, but exhibit a 5-fold difference in erosion rate that we hypothesize to be a result of a contrast in bedrock fracture spacing and grain size of channel-bed material. Using airborne lidar-derived elevation point clouds, we show that bedrock cliffs in the San Jacinto Mountains are systematically steeper and taller across all spatial scales compared with those in the San Gabriel Mountains. From georeferenced high-resolution photographs taken from along exposed ridgelines, we constructed cm-scale topographic models of 100-m scale cliffs and debris chutes using Structure-from-Motion (SfM) techniques, in order to quantify (1) the extent of bedrock on hillslopes, (2) the spacing and orientation of bedrock fractures on cliffs, and (3) the grain size of rockfall deposits at the base of cliffs and in headwater channels. Our results highlight the utility of nesting SfM surveys with airborne

  1. Use hyperspectral remote sensing technique to monitoring pine wood nomatode disease preliminary

    Science.gov (United States)

    Qin, Lin; Wang, Xianghong; Jiang, Jing; Yang, Xianchang; Ke, Daiyan; Li, Hongqun; Wang, Dingyi

    2016-10-01

    The pine wilt disease is a devastating disease of pine trees. In China, the first discoveries of the pine wilt disease on 1982 at Dr. Sun Yat-sen's Mausoleum in Nanjing. It occurred an area of 77000 hm2 in 2005, More than 1540000 pine trees deaths in the year. Many districts of Chongqing in Three Gorges Reservoir have different degrees of pine wilt disease occurrence. It is a serious threat to the ecological environment of the reservoir area. Use unmanned airship to carry high spectrum remote sensing monitoring technology to develop the study on pine wood nematode disease early diagnosis and early warning and forecasting in this study. The hyper spectral data and the digital orthophoto map data of Fuling District Yongsheng Forestry had been achieved In September 2015. Using digital image processing technology to deal with the digital orthophoto map, the number of disease tree and its distribution is automatic identified. Hyper spectral remote sensing data is processed by the spectrum comparison algorithm, and the number and distribution of disease pine trees are also obtained. Two results are compared, the distribution area of disease pine trees are basically the same, indicating that using low air remote sensing technology to monitor the pine wood nematode distribution is successful. From the results we can see that the hyper spectral data analysis results more accurate and less affected by environmental factors than digital orthophoto map analysis results, and more environment variable can be extracted, so the hyper spectral data study is future development direction.

  2. Long-term monitoring on environmental disasters using multi-source remote sensing technique

    Science.gov (United States)

    Kuo, Y. C.; Chen, C. F.

    2017-12-01

    Environmental disasters are extreme events within the earth's system that cause deaths and injuries to humans, as well as causing damages and losses of valuable assets, such as buildings, communication systems, farmlands, forest and etc. In disaster management, a large amount of multi-temporal spatial data is required. Multi-source remote sensing data with different spatial, spectral and temporal resolutions is widely applied on environmental disaster monitoring. With multi-source and multi-temporal high resolution images, we conduct rapid, systematic and seriate observations regarding to economic damages and environmental disasters on earth. It is based on three monitoring platforms: remote sensing, UAS (Unmanned Aircraft Systems) and ground investigation. The advantages of using UAS technology include great mobility and availability in real-time rapid and more flexible weather conditions. The system can produce long-term spatial distribution information from environmental disasters, obtaining high-resolution remote sensing data and field verification data in key monitoring areas. It also supports the prevention and control on ocean pollutions, illegally disposed wastes and pine pests in different scales. Meanwhile, digital photogrammetry can be applied on the camera inside and outside the position parameters to produce Digital Surface Model (DSM) data. The latest terrain environment information is simulated by using DSM data, and can be used as references in disaster recovery in the future.

  3. Soil loss estimation using GIS and Remote sensing techniques: A case of Koga watershed, Northwestern Ethiopia

    Directory of Open Access Journals (Sweden)

    Habtamu Sewnet Gelagay

    2016-06-01

    Full Text Available Soil loss by runoff is a severe and continuous ecological problem in Koga watershed. Deforestation, improper cultivation and uncontrolled grazing have resulted in accelerated soil erosion. Information on soil loss is essential to support agricultural productivity and natural resource management. Thus, this study was aimed to estimate and map the mean annual soil loss by using GIS and Remote sensing techniques. The soil loss was estimated by using Revised Universal Soil Equation (RUSLE model. Topographic map of 1:50,000 scale, Aster Digital Elevation Model (DEM of 20 m spatial resolution, digital soil map of 1:250,000 scale, thirteen years rainfall records of four stations, and land sat imagery (TM with spatial resolution of 30 m was used to derive RUSLE's soil loss variables. The RUSLE parameters were analyzed and integrated using raster calculator in the geo-processing tools in ArcGIS 10.1 environment to estimate and map the annual soil loss of the study area. The result revealed that the annual soil loss of the watershed extends from none in the lower and middle part of the watershed to 265 t ha−1 year−1 in the steeper slope part of the watershed with a mean annual soil loss of 47 t ha−1 year−1. The total annual soil loss in the watershed was 255283 t, of these, 181801 (71% tones cover about 6691 (24% hectare of land. Most of these soil erosion affected areas are spatially situated in the upper steepest slope part (inlet of the watershed. These are areas where Nitosols and Alisols with higher soil erodibility character (0.25 values are dominant. Hence, Slope gradient and length followed by soil erodibility factors were found to be the main factors of soil erosion. Thus, sustainable soil and water conservation practices should be adopted in steepest upper part of the study area by respecting and recognizing watershed logic, people and watershed potentials.

  4. Monitoring changes in riverine forests of Sindh-Pakistan using remote sensing and GIS techniques

    Science.gov (United States)

    Siddiqui, M. N.; Jamil, Z.; Afsar, J.

    Depletion in the forest area threatens the sustainability of agricultural production systems and en-dangers the economy of the country. Every year extensive areas of arable agricultural and forestlands are degraded and turned into wastelands over time, due to natural causes or human interventions. Depletion in forest cover, therefore, has an important impact on socio-economic development and ecological balance. High population growth rate in Pakistan is one of the main causes for rapid deterioration of the physical environment and natural resource base. In view of this, it was felt necessary to carryout landuse studies focusing on mapping the past and present conditions and the extent of forests and rangelands using satellite remote sensing (SRS) and Geographic Information System (GIS) technologies. The SRS and GIS technologies provide a possible means of monitoring and mapping the changes occurring in natural resources and the environment on a continuous basis. The riverine forests of Sindh mostly growing along the river Indus in the flood plains are spread over an area of 241,000 ha but are disappearing very rapidly. Construction of dams/barrages on the upper reaches of the river Indus for hydroelectric power and irrigation works have significantly reduced the discharge of fresh water into the lower Indus basin and as a result 100,000 acres of forests have disappeared. Furthermore, heavy floods that occurred in 1978, 1988, 1992 and 1997, altered the course of the River Indus in many places, especially in the lower reaches, this has also damaged the riverine forests of Sindh. An integrated approach involving analysis of SRS data from 1977 to 1998 and GIS technique have been used to evaluate the geographic extent and distribution of the riverine forests of Sindh and to monitor temporal changes in the forest cover between 1977 and 1990; 1990 and 1998; and 1977 and 1998. The integrated landuse forest cover maps have shown not only the temporal changes that occur in

  5. Application of remote sensing techniques to study aerosol water vapour uptake in a real atmosphere

    Science.gov (United States)

    Fernández, A. J.; Molero, F.; Becerril-Valle, M.; Coz, E.; Salvador, P.; Artíñano, B.; Pujadas, M.

    2018-04-01

    In this work, a study of several observations of aerosol water uptake in a real (non-controlled) atmosphere, registered by remote sensing techniques, are presented. In particular, three events were identified within the Atmospheric Boundary Layer (ABL) and other two events were detected in the free troposphere (beyond the top of the ABL). Then, aerosol optical properties were measured at different relative humidity (RH) conditions by means of a multi-wavelength (MW) Raman lidar located at CIEMAT (Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Research Centre for Energy, Environment and Technology) facilities in Madrid (Spain). Additionally, aerosol optical and microphysical properties provided by automatic sun and sky scanning spectral radiometers (CIMEL CE-318) and a meteorological analysis complement the study. However, a detailed analysis only could be carried out for the cases observed within the ABL since well-mixed atmospheric layers are required to properly characterize these processes. This characterization of aerosol water uptake is based on the curve described by the backscatter coefficient at 532 nm as a function of RH which allows deriving the enhancement factor. Thus, the Hänel parameterization is utilized, and the results obtained are in the range of values reported in previous studies, which shows the suitability of this approach to study such hygroscopic processes. Furthermore, the anti-correlated pattern observed on backscatter-related Ångström exponent (532/355 nm) and RH indicates plausible signs of aerosol hygroscopic growth. According to the meteorological analysis performed, we attribute such hygroscopic behaviour to marine aerosols which are advected from the Atlantic Ocean to the low troposphere in Madrid. We have also observed an interesting response of aerosols to RH at certain levels which it is suggested to be due to a hysteresis process. The events registered in the free troposphere, which deal with volcano

  6. Realizing parameterless automatic classification of remote sensing imagery using ontology engineering and cyberinfrastructure techniques

    Science.gov (United States)

    Sun, Ziheng; Fang, Hui; Di, Liping; Yue, Peng

    2016-09-01

    It was an untouchable dream for remote sensing experts to realize total automatic image classification without inputting any parameter values. Experts usually spend hours and hours on tuning the input parameters of classification algorithms in order to obtain the best results. With the rapid development of knowledge engineering and cyberinfrastructure, a lot of data processing and knowledge reasoning capabilities become online accessible, shareable and interoperable. Based on these recent improvements, this paper presents an idea of parameterless automatic classification which only requires an image and automatically outputs a labeled vector. No parameters and operations are needed from endpoint consumers. An approach is proposed to realize the idea. It adopts an ontology database to store the experiences of tuning values for classifiers. A sample database is used to record training samples of image segments. Geoprocessing Web services are used as functionality blocks to finish basic classification steps. Workflow technology is involved to turn the overall image classification into a total automatic process. A Web-based prototypical system named PACS (Parameterless Automatic Classification System) is implemented. A number of images are fed into the system for evaluation purposes. The results show that the approach could automatically classify remote sensing images and have a fairly good average accuracy. It is indicated that the classified results will be more accurate if the two databases have higher quality. Once the experiences and samples in the databases are accumulated as many as an expert has, the approach should be able to get the results with similar quality to that a human expert can get. Since the approach is total automatic and parameterless, it can not only relieve remote sensing workers from the heavy and time-consuming parameter tuning work, but also significantly shorten the waiting time for consumers and facilitate them to engage in image

  7. Estimation of Actual Evapotranspiration Using an Agro-Hydrological Model and Remote Sensing Techniques

    Directory of Open Access Journals (Sweden)

    mostafa yaghoobzadeh

    2017-02-01

    Full Text Available Introduction: Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing land use on water yields. Different methods are available for ET estimation including Bowen ratio energy balance systems, eddy correlation systems, weighing lysimeters.Water balance techniques offer powerful alternatives for measuring ET and other surface energy fluxes. In spite of the elegance, high accuracy and theoretical attractions of these techniques for measuring ET, their practical use over large areas might be limited. They can be very expensive for practical applications at regional scales under heterogeneous terrains composed of different agro-ecosystems. To overcome aforementioned limitations by use of satellite measurements are appropriate approach. The feasibility of using remotely sensed crop parameters in combination of agro-hydrological models has been investigated in recent studies. The aim of the present study was to determine evapotranspiration by two methods, remote sensing and soil, water, atmosphere, and plant (SWAP model for wheat fields located in Neishabour plain. The output of SWAP has been validated by means of soil water content measurements. Furthermore, the actual evapotranspiration estimated by SWAP has been considered as the “reference” in the comparison between SEBAL energy balance models. Materials and Methods: Surface Energy Balance Algorithm for Land (SEBAL was used to estimate actual ET fluxes from Modis satellite images. SEBAL is a one-layer energy balance model that estimates latent heat flux and other energy balance components without information on soil, crop, and management practices. The near surface energy balance equation can be approximated as: Rn = G + H + λET Where Rn: net radiation (Wm2; G

  8. A regression technique for evaluation and quantification for water quality parameters from remote sensing data

    Science.gov (United States)

    Whitlock, C. H.; Kuo, C. Y.

    1979-01-01

    The objective of this paper is to define optical physics and/or environmental conditions under which the linear multiple-regression should be applicable. An investigation of the signal-response equations is conducted and the concept is tested by application to actual remote sensing data from a laboratory experiment performed under controlled conditions. Investigation of the signal-response equations shows that the exact solution for a number of optical physics conditions is of the same form as a linearized multiple-regression equation, even if nonlinear contributions from surface reflections, atmospheric constituents, or other water pollutants are included. Limitations on achieving this type of solution are defined.

  9. An adaptive weighted Lp metric with application to optical remote sensing classification problems

    Science.gov (United States)

    Pratiher, Sawon; Krishnamoorthy, Vigneshram; Bhattacharya, Paritosh

    2017-06-01

    In this contribution, a novel metric learning framework by jointly optimizing the feature space structural coherence manifested by the Cosine similarity measure and the error contribution induced by the Minkowski metric is presented with a loss function involving Mahalanobis distance measure governing the outlier robustness for maximal inter-sample and minimal intra-sample separation of the feature space vectors. The outlier's robustness and scale variation sensitivity of the proposed measure by exploiting the prior statistical entropy of the correlated feature components in weighing the different feature dimensions according to their degree of cohesion within the data clusters and the conceptual architecture for the optimality criterion in terms of the optimal Minkowski exponent, `poptimal' through semi-definite convex optimization with its lower and upper bounds of the proposed distance function have been discussed. Classification results involving special cases of the proposed distance measure on publicly available datasets validates the adequacy of the proposed methodology in remote sensing problems.

  10. A Novel Technique to Compute the Revisit Time of Satellites and Its Application in Remote Sensing Satellite Optimization Design

    Directory of Open Access Journals (Sweden)

    Xin Luo

    2017-01-01

    Full Text Available This paper proposes a novel technique to compute the revisit time of satellites within repeat ground tracks. Different from the repeat cycle which only depends on the orbit, the revisit time is relevant to the payload of the satellite as well, such as the tilt angle and swath width. The technique is discussed using the Bezout equation and takes the gravitational second zonal harmonic into consideration. The concept of subcycles is defined in a general way and the general concept of “small” offset is replaced by a multiple of the minimum interval on equator when analyzing the revisit time of remote sensing satellites. This technique requires simple calculations with high efficiency. At last, this technique is used to design remote sensing satellites with desired revisit time and minimum tilt angle. When the side-lap, the range of altitude, and desired revisit time are determined, a lot of orbit solutions which meet the mission requirements will be obtained fast. Among all solutions, designers can quickly find out the optimal orbits. Through various case studies, the calculation technique is successfully demonstrated.

  11. Remote sensing of key grassland nutrients using hyperspectral techniques in KwaZulu-Natal, South Africa

    Science.gov (United States)

    Singh, Leeth; Mutanga, Onisimo; Mafongoya, Paramu; Peerbhay, Kabir

    2017-07-01

    The concentration of forage fiber content is critical in explaining the palatability of forage quality for livestock grazers in tropical grasslands. Traditional methods of determining forage fiber content are usually time consuming, costly, and require specialized laboratory analysis. With the potential of remote sensing technologies, determination of key fiber attributes can be made more accurately. This study aims to determine the effectiveness of known absorption wavelengths for detecting forage fiber biochemicals, neutral detergent fiber, acid detergent fiber, and lignin using hyperspectral data. Hyperspectral reflectance spectral measurements (350 to 2500 nm) of grass were collected and implemented within the random forest (RF) ensemble. Results show successful correlations between the known absorption features and the biochemicals with coefficients of determination (R2) ranging from 0.57 to 0.81 and root mean square errors ranging from 6.97 to 3.03 g/kg. In comparison, using the entire dataset, the study identified additional wavelengths for detecting fiber biochemicals, which contributes to the accurate determination of forage quality in a grassland environment. Overall, the results showed that hyperspectral remote sensing in conjunction with the competent RF ensemble could discriminate each key biochemical evaluated. This study shows the potential to upscale the methodology to a space-borne multispectral platform with similar spectral configurations for an accurate and cost effective mapping analysis of forage quality.

  12. Use of Geophysical and Remote Sensing Techniques During the Comprehensive Test Ban Treaty Organization's Integrated Field Exercise 2014

    Science.gov (United States)

    Labak, Peter; Sussman, Aviva; Rowlands, Aled; Chiappini, Massimo; Malich, Gregor; MacLeod, Gordon; Sankey, Peter; Sweeney, Jerry; Tuckwell, George

    2016-04-01

    The Integrated Field Exercise of 2014 (IFE14) was a field event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of a Comprehensive Test Ban Treaty's (CTBT) on-site inspection (OSI). During an OSI, up to 40 inspectors search a 1000km2 inspection area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of an OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams to execute the scenario in which the exercise was played, to those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, a number of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force Group (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, as well as other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection by other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.

  13. Tools and Techniques to Collaborate and Connect with At-Risk Climate Communities UsingSensors, Remote Sensing Data, and Media

    Science.gov (United States)

    Drapkin, J. K.; Ramamurthy, P.; Vant-Hull, B.; Yuen, K.; Glenn, A.; Jusino, C.; Corbin, C.; Schuerman, M.; Keefe, J.; Brooke, H.

    2016-12-01

    Those most at risk during heat waves and floods are often the socio-economically vulnerable. Yet very few studies exist of indoor temperatures during heat waves or of standing water events at the neighborhood level during extreme events. ISeeChange, a community weather and climate journal, is developing tools and testing techniques in a series of community pilots in Harlem and New Orleans to assess if a combination of citizen science, remote sensing, and journalism can bridge the gap. Our consortium of media (WNYC,Adapt NYC, ISeeChange), scientists (CUNY, CoCoRaHS, NASAJPL), and community partners (WE ACT for Environmental Justice, tenant, and neighborhood associations) are collaborating to engage with residents, report radio stories, as well as develop scientifically valuableinformation for decision-making. Community volunteers place temperature and humidity sensors inside residences (Harlem) or photograph standing water using specific methodologies (New Orleans). Sensordata, photographs, and text documenting the impacts of extreme weather on residents are posted on the ISeeChange platform via mobile app or community ambassadors and compared to other remote sensing data products (surface temperature, precipitation, subsidence) Preliminary results of the Harlem pilot show that indoor temperatures are far more stable than outdoor temperatures, so can be both cooler during the day but warmer at night; preliminary work on the New Orleans pilot is set to begin in fall 2016. A full analysis of the Harlem pilot will be presented along with preliminary results of the New Orleans pilot.

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

    Directory of Open Access Journals (Sweden)

    P. Ranade

    2007-01-01

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

  15. Identification of glacial flood hazards in karakorum range using remote sensing technique and risk analysis

    International Nuclear Information System (INIS)

    Ashraf, A.; Roohi, R.; Naz, R.

    2011-01-01

    Glacial Lake Outburst Floods (GLOFs) are great hazard for the downstream communities in context of changing climatic conditions in the glaciated region of Pakistan. The remote sensing data of Landsat ETM+ was utilized for the identification of glacial lakes susceptible to posing GLOF hazard in Karakoram Range. Overall, 887 glacial lakes are identified in different river-basins of Karakoram Range, out of which 16 lakes are characterized as potentially dangerous in terms of GLOF. The analysis of community's response to GLOF events of 2008 in the central Karakoram Range indicated gaps in coordination and capacity of the local communities to cope with such natural hazards. A regular monitoring of hot spots and potential GLOF lakes along with capacity- of local communities and institutions in coping future disaster situation is necessary, especially in the context of changing climatic conditions in Himalayan region. (author)

  16. Integrated Evaluation of Urban Development Suitability Based on Remote Sensing and GIS Techniques - A Case Study in Jingjinji Area, China.

    Science.gov (United States)

    Dong, Jiang; Zhuang, Dafang; Xu, Xinliang; Ying, Lei

    2008-09-25

    Jingjinji area (namely Beijing, Tianjin and He Bei Province) is one of the three largest regional economic communities in China. Urban expansion has sped up in the past 20 years in this area due to the rapid economic and population growth. Evaluating the landuse suitability for urban growth on a regional scale is an urgent need, because the most suitable areas and the most suitable scale of urban growth can thus be determined accordingly. In order to meet this requirement, remote sensing and geographic information system (GIS) techniques were adopted, and an integrated evaluating model was developed supported by AHP method. The integrated urban development suitability index (UDSI) was calculated using this model. According to the UDSI result, the spatial distribution of urban development suitability and its driving forces were analyzed. Urban boundaries in 1995, 2000 and 2005, which were derived from Landsat TM/ETM+ satellite data, were overlaid on the UDSI map, and the suitable urban develop tendency in this area were discussed. The result of this study indicated that integrated evaluation of urban development could be conducted in an operational way using remote sensing data, GIS spatial analysis technique and AHP modeling method.

  17. Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

    Science.gov (United States)

    Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

    2017-04-01

    Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

  18. Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques

    Directory of Open Access Journals (Sweden)

    N.S. Magesh

    2012-03-01

    Full Text Available Integration of remote sensing data and the geographical information system (GIS for the exploration of groundwater resources has become a breakthrough in the field of groundwater research, which assists in assessing, monitoring, and conserving groundwater resources. In the present paper, various groundwater potential zones for the assessment of groundwater availability in Theni district have been delineated using remote sensing and GIS techniques. Survey of India toposheets and IRS-1C satellite imageries are used to prepare various thematic layers viz. lithology, slope, land-use, lineament, drainage, soil, and rainfall were transformed to raster data using feature to raster converter tool in ArcGIS. The raster maps of these factors are allocated a fixed score and weight computed from multi influencing factor (MIF technique. Moreover, each weighted thematic layer is statistically computed to get the groundwater potential zones. The groundwater potential zones thus obtained were divided into four categories, viz., very poor, poor, good, and very good zones. The result depicts the groundwater potential zones in the study area and found to be helpful in better planning and management of groundwater resources.

  19. Scale issues in remote sensing

    CERN Document Server

    Weng, Qihao

    2014-01-01

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

  20. Study on the techniques of valuation of ecosystem services based on remote sensing in Anxin County

    Science.gov (United States)

    Wang, Hongyan; Li, Zengyuan; Gao, Zhihai; Wang, Bengyu; Bai, Lina; Wu, Junjun; Sun, Bin; Wang, Zhibo

    2014-05-01

    The farmland ecosystem is an important component of terrestrial ecosystems and has a fundamental role in the human life. The wetland is an unique and versatile ecological system. It is important for rational development and sustainable utilization of farmland and wetland resources to study on the measurement of valuation of farmland and wetland ecosystem services. It also has important significance for improving productivity. With the rapid development of remote sensing technology, it has become a powerful tool for evaluation of the value of ecosystem services. The land cover types in Anxin County mainly was farmland and wetland, the indicator system for ecosystem services valuation was brought up based on the remote sensing data of high spatial resolution ratio(Landsat-5 TM data and SPOT-5 data), the technology system for measurement of ecosystem services value was established. The study results show that the total ecosystem services value in 2009 in Anxin was 4.216 billion yuan, and the unit area value was between 8489 yuan/hm2 and 329535 yuan/hm2. The value of natural resources, water conservation value in farmland ecosystem and eco-tourism value in wetland ecosystem were higher than the other, total of the three values reached 2.858 billion yuan, and the percentage of the total ecosystem services values in Anxin was 67.79%. Through the statistics in the nine towns and three villages of Anxin County, the juantou town has the highest services value, reached 0.736 billion yuan. Scientific and comprehensive evaluation of the ecosystem services can conducive to promoting the understanding of the importance of the ecosystem. The research results had significance to ensure the sustainable use of wetland resources and the guidance of ecological construction in Anxin County.

  1. Monitoring of petroleum hydrocarbon pollution in surface waters by a direct comparison of fluorescence spectroscopy and remote sensing techniques

    Energy Technology Data Exchange (ETDEWEB)

    De Domenico, L.; Crisafi, E. (Consiglio Nazionale delle Ricerche, Messina (Italy). Thalassografic Inst.); Magazzu, G. (Lecce Univ. (Italy). Dept. of Biology); Puglisi, A. (Mediterranean Oceanological Centre (CEOM), Palermo (Italy)); La Rosa, A. (Air-Survey, Italy s.r.l., Catania (Italy))

    1994-10-01

    Oil pollution levels were estimated using simultaneous acquisition of data from remote sensing by helicopter and fluorescence spectroscopy on surface samples. Laboratory quantitative analysis of hydrocarbons was used to calibrate remotely sensed data. The data were treated using a computer to generate a colour-coded map not attainable with conventional methods representing seawater pollution. Results were in good agreement and indicated that remotely sensed data together with those achieved by fluorescence spectroscopy are applicable for monitoring hydrocarbon pollution. (author)

  2. Prioritization of Watersheds across Mali Using Remote Sensing Data and GIS Techniques for Agricultural Development Planning

    Directory of Open Access Journals (Sweden)

    Murali Krishna Gumma

    2016-06-01

    Full Text Available Implementing agricultural water management programs over appropriate spatial extents can have positive effects on water access and erosion management. Lack of access to water for domestic and agricultural uses represents a major constraint on agricultural productivity and perpetuates poverty and hunger in sub-Saharan Africa (SSA. This lack of access is the result of erratic precipitation, poor water management, limited knowledge of hydrological systems, and inadequate investment in water infrastructure. Water management programs should be made by multi-disciplinary teams that consider the interrelationship between hydraulic and anthropogenic factors. This paper proposes a method to prioritize watersheds for water management and agricultural development across Mali (Western Africa using remote sensing data and GIS tools. The method involves deriving a set of relevant thematic layers from satellite imagery. Satellite images from Landsat ETM+ were used to generate thematic layers such as land use/land cover. Slope and drainage density maps were derived from Shuttle RADAR Topography Mission (SRTM Digital Elevation Model (DEM at 90 m spatial resolution. Population grids were available from the Global rural-urban mapping project (GRUMP database for the year 2000 and mean rainfall maps were extracted from Tropical rainfall measuring mission (TRMM grids for each year between 1988 and 2014. Each thematic layer was divided into classes that were assigned a rank for agriculture and livelihoods development provided by experts in the relevant field (e.g., Soil scientist ranking the soil classes and published literature on those themes. Zones of priority were delineated based on the combination of high scoring ranks from each thematic layer. Five categories of priority zones ranging from “very high” to “very low” were determined based on total score percentages. Field verification was then undertaken in selected categories to check the priority

  3. ANALYSIS OF URBAN SPRAWL PHENOMENON IN BATNA CITY (ALGERIA BY REMOTE SENSING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    DRIDI Hadda

    2015-12-01

    Full Text Available Define Batna city, define its outlines and follow the spatio-temporal evolution is one of the complex problems. Urban sprawl, that rapid urbanization is the occupancy factor of soil changes, generally irreversible. His study in a medium-sized city is an important issue that requires monitoring and detailed analysis. Our approach includes the use of remotely sensed images to evaluate and qualify urban sprawl in Batna. For this purpose, we used a series of images in digital format for the years 1972, 1987, 2001 and 2013, acquired by multispectral sensors mounted on Landsat satellite platforms, for area which is the subject of experimentation, then supervised classification by Support Vector Machine (Radio Basis Function classifier RBFC was utilized. The selection of the images available from Landsat archives was made so that their acquisition date is spread enough to better distinguish changes within the urban fabric. The results obtained confirm that urban area increased 173.32% between 1972 -1987, 55.62% between 1987 -2001 and 38.71% between 2001 -2013. Furthermore, Shannon’s entropy index shows that the city has a high level of sprawl along its urban expansion history.

  4. Introduction to remote sensing

    CERN Document Server

    Cracknell, Arthur P

    2007-01-01

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

  5. On the detection of adobe buried archaeological structures using multiscale remote sensing techniques : Piramide Naranja in Cahuachi (Peru)

    Science.gov (United States)

    Masini, N.; Rizzo, E.; Lasaponara, R.; Orefici, G.

    2009-04-01

    The detection of buried adobe structures is a crucial issue for the remote sensing (ground, aerial and satellite) applied to archaeology for the widespread of sun-dried earth as building material in several ancient civilizations in Central and Southern America, Middle East and North Africa. Moreover it is complex, due to the subtle contrast existing between the archaeological features and the surrounding, especially in arid setting, as in the case of the well know Nazca Ceremonial Centre of Cahuachi, located in the desert of Nazca (Southern Peru) . During the last two decades of excavations adobe monuments dating back from the 6th century B.C. to the 4th century A.D have been highlighted by the Centro de Estudios Arqueológicos Precolombinos (CEAP), an italian-peruvian mission directed by Giuseppe Orefici. Actually, the archaeologists are excavating and restoring the core of the Ceremonial centre where is located a great pyramid (kown as Gran Piramide). Beginning from 2007 the two institutes of CNR, IMAA and IBAM, have been involved by CEAP, in order to provide a scientific and technological support for the archaeological research. Therefore, a multi-scale approach based on the integration of aerial and satellite remote sensing with geophysical techniques was employed in order to provide data useful for archaeological excavations. The abstract refers to the last investigations performed on a mound, known as "Piramide Naranja", during the 2008. The processing of an aerial imagery time series and two QuickBird satellite images acquired in 2002 and 2005, allowed for identifying some features related to shallow and buried structures. Such features were verified by means of geophysical prospections, performed by using the magnetometric method which observed changes in the magnetic field within the first few metres beneath the subsurface detecting buried walls and anomalies linked to ceramic deposits referable to possible tombs. Finally, the integration of all data

  6. Techniques of the environmental observer: India's earth remote sensing program in the age of global information

    Science.gov (United States)

    Denicola, Lane A.

    This research examines the emergence in India of earth remote sensing (ERS), a principal medium for environmental analysis, communication, and policy-making. ERS---the science and "craft" of analyzing images of terrestrial phenomena collected by aircraft or satellite---constitutes an information technology whose predominance in environmental discourse has grown continuously since first proposed for such applications by American researchers in 1962. Raising many thorny issues in information access and control, the use and popularization of ERS has intensified dramatically since the mid-1980s. In Westernized discourse (both popular and expert), space research and industry are often depicted at a double-remove from the so-called "developing world," where exotic technologies and esoteric goals are overshadowed by patent human needs and a lack of basic infrastructure. Yet advocates hail the utility of ERS in socially relevant applications, and India has amassed upwards of five decades of experience in space, with systems and products rivaled today only by those of the United States and China. A multi-sited ethnography of a nascent visual medium, the dissertation triangulates on its topic by tracing three analytical threads: (1) a diachronic analysis of Indian ERS satellites as an allegory of statehood and participation in the global present, (2) a synchronic analysis of ERS imagery as a discursive artifact and global information commodity, and (3) an analysis of interpretive practice as observed through a single class of Indian and foreign students at the Indian Institute of Remote Sensing (IIRS), considered here as an "interpretive community" of environmental experts. The dissertation is the result of four years of research with ERS students, faculty, researchers, users and administrators in the U.S., the U.K., Turkey and India. In particular, I conducted nine months of ethnographic fieldwork in India in 2002 and 2005, the latter half of which was spent in participant

  7. Integrated remote sensing techniques for the detection of buried archaeological adobe structures: preliminary results in Cahuachi (Peru

    Directory of Open Access Journals (Sweden)

    N. Masini

    2008-11-01

    Full Text Available This paper is focused on the jointly use of satellite Quickbird (QB images and Ground Probing Radar (GPR for assessing their capability in the detection of archaeological adobe structures (sun-dried earth material. Such detection is particularly complex. due to the low contrast generally existing between the archaeological features and the background. Two significant test areas were investigated in the Ceremonial Centre of Cahuachi (in the Nasca territory, Southern Peru dating back to 6th century BC to 4th century AD.

    Our results showed that both satellite and GPR data provided valuable indications for unearthing precious ancient remains. Our preliminary analyses pointed out that the integrated use of non destructive remote sensing techniques has high potentiality for its important scientific implications and for its significant contributions to cultural resource management.

  8. Use of Remote Sensing Techniques For Geomorphological Study of Some Sites For Eroticism In Farafra Area, Western Desert, Egypt

    International Nuclear Information System (INIS)

    EI Gammal, E.A.; Salem, S.M.

    2008-01-01

    The present study deals with investigating some significant geomorphic features in the Farafra Oasis area such as natural caves and white desert which display remarkable landscapes of high esthetic value and very important sites for ecotourism. The study aims to produce a GIS ready database for registration of the natural caves with stalactites and stalagmites and a set of printed thematic maps for the above mentioned features with an explanatory notes for the features considered. To achieve these goals remote sensing and GIS techniques have been used, verified by field trip and GPS instrument for correct locations. The used thematic maps are: topographic maps for roads and tracks and main cities, and geologic maps. The study will be illustrated by numerous field photos. The description of the considered features and including significant photographs will be presented on a CD

  9. Integrated remote sensing techniques for the detection of buried archaeological adobe structures: preliminary results in Cahuachi (Peru)

    Science.gov (United States)

    Masini, N.; Rizzo, E.; Lasaponara, R.; Orefici, G.

    2008-11-01

    This paper is focused on the jointly use of satellite Quickbird (QB) images and Ground Probing Radar (GPR) for assessing their capability in the detection of archaeological adobe structures (sun-dried earth material). Such detection is particularly complex. due to the low contrast generally existing between the archaeological features and the background. Two significant test areas were investigated in the Ceremonial Centre of Cahuachi (in the Nasca territory, Southern Peru) dating back to 6th century BC to 4th century AD. Our results showed that both satellite and GPR data provided valuable indications for unearthing precious ancient remains. Our preliminary analyses pointed out that the integrated use of non destructive remote sensing techniques has high potentiality for its important scientific implications and for its significant contributions to cultural resource management.

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

    Science.gov (United States)

    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.

  11. Extraction of shoreline changes in Selangor coastal area using GIS and remote sensing techniques

    Science.gov (United States)

    Selamat, S. N.; Maulud, K. N. Abdul; Jaafar, O.; Ahmad, H.

    2017-05-01

    Nowadays, coastal zones are facing shoreline changes that stemming from natural and anthropogenic effect. The process of erosion and accretion will affect the physical environment of the shoreline. Therefore, the study of shoreline changes is important to identify the patterns of changes over time. The rapid growth of technology nowadays has facilitated the study of shoreline changes. Geographical Information System (GIS) alongside Remote Sensing (RS) technology is a useful tool to study these changes due to its ability to generate information, monitoring, analysis and prediction of the shoreline changes. Hence, the future projection of the trend for a specific coastal area can be done effectively. This study investigates the impact of shoreline changes to the community in Selangor area which mainly focus on the physical aspects. This study presents preliminary result using satellite image from SPOT 5 to identify the shoreline changes from the year 1984 to 2013 at Selangor coastal area. Extraction of shoreline from satellite image is vital to analyze the erosion and accretion along the shoreline area. This study shows that a shoreline change for the whole area is a categorized as a medium case. The total eroded and accretion of Selangor area from 1984 to 2013 is 2558 hectares and 2583 hectares respectively. As a result, Kapar, Jugra, Telok Panglima Garang and Kelanang are categorized as high risk erosion area. Shoreline changes analysis provides essential information to determine on the shoreline changes trends. Therefore, the results of this study can be used as essential information for conservation and preservation of coastal zone management.

  12. Estimating primary productivity of tropical oil palm in Malaysia using remote sensing technique and ancillary data

    Science.gov (United States)

    Kanniah, K. D.; Tan, K. P.; Cracknell, A. P.

    2014-10-01

    The amount of carbon sequestration by vegetation can be estimated using vegetation productivity. At present, there is a knowledge gap in oil palm net primary productivity (NPP) at a regional scale. Therefore, in this study NPP of oil palm trees in Peninsular Malaysia was estimated using remote sensing based light use efficiency (LUE) model with inputs from local meteorological data, upscaled leaf area index/fractional photosynthetically active radiation (LAI/fPAR) derived using UK-DMC 2 satellite data and a constant maximum LUE value from the literature. NPP values estimated from the model was then compared and validated with NPP estimated using allometric equations developed by Corley and Tinker (2003), Henson (2003) and Syahrinudin (2005) with diameter at breast height, age and the height of the oil palm trees collected from three estates in Peninsular Malaysia. Results of this study show that oil palm NPP derived using a light use efficiency model increases with respect to the age of oil palm trees, and it stabilises after ten years old. The mean value of oil palm NPP at 118 plots as derived using the LUE model is 968.72 g C m-2 year-1 and this is 188% - 273% higher than the NPP derived from the allometric equations. The estimated oil palm NPP of young oil palm trees is lower compared to mature oil palm trees (age of oil palm trees as estimated using the allomeric equations. It was found in this study that LUE models could not capture NPP variation of oil palm trees if LAI/fPAR is used. On the other hand, tree height and DBH are found to be important variables that can capture changes in oil palm NPP as a function of age.

  13. Application of multispectral remote sensing techniques for dismissed mine sites monitoring and rehabilitation

    Science.gov (United States)

    Bonifazi, Giuseppe; Serranti, Silvia

    2007-09-01

    Mining activities, expecially those operated in open air (open pit), present a deep impact on the sourrondings. Such an impact, and the related problems, are directly related to the correct operation of the activities, and usually strongly interact with the environment. Impact can be mainly related to the following issues: high volumes of handled material, ii) generation of dust, noise and vibrations, water pollution, visual impact and, finally, mining area recovery at the end of exploitation activities. All these aspects can be considered very important, and must be properly evaluated and monitored. Environmental impact control is usually carried out during and after the end of the mining activities, adopting methods related to the detection, collection, analysis of specific environmental indicators and with their further comparison with reference thresholding values stated by official regulations. Aim of the study was to investigate, and critically evaluate, the problems related to development of an integrated set of procedures based on the collection and the analysis of remote sensed data in order to evaluate the effect of rehabilitation of land contaminated by extractive industry activities. Starting from the results of these analyses, a monitoring and registration of the environmental impact of such operations was performed by the application and the integration of modern information technologies, as the previous mentioned Earth Observation (EO), with Geographic Information Systems (GIS). The study was developed with reference to different dismissed mine sites in India, Thailand and China. The results of the study have been utilized as input for the construction of a knowledge based decision support system finalized to help in the identification of the appropriate rehabilitation technologies for all those dismissed area previously interested by extractive industry activities. The work was financially supported within the framework of the Project ASIA IT&C - CN

  14. Deforestation Analysis of Riverine Forest of Sindh Using Remote Sensing Techniques

    Directory of Open Access Journals (Sweden)

    Habibullah Abbasi

    2011-07-01

    Full Text Available During recent decades the large scale deterioration of forests and natural resources is an eye opener. The degradation of forests and other natural resources has affected the ecology, environment, health and economy. The ecological problems with living organisms such as animals and plants and environmental problems such as increase in temperature and carbon dioxide, these factors have contributed to change in regional climate, health problems such as skin, eye diseases and sunstroke and economic problems such as loss of income to rural population and resources which depend on forests such as livestock. Therefore, it was necessary to carry out land cover/use research focusing on the monitoring and management of the present and past state of forests cover and other related objects using RS (Remote Sensing technologies. The RS is a way of mapping and monitoring the changes taking place in forests cover and other objects on a continuing basis. Sukkur and Shikarpur riverine forests are vanishing quickly due to the construction of barrages /dams on upper streams to produce hydroelectricity and irrigation installations which reduce the discharge of fresh water into the downstream Indus basin. Moreover, anthropogenic activities, livestock population, increased grazing, load and illegal tree cutting have contributed to this. The riverine forests are turning into barren land and most of the land is used for agriculture. These uncontrolled changes contribute to climate change and global warming. These changes are difficult to monitor and control without using RS technology. Assessment of deforestation of the Sukkur and Shikarpur to find temporal changes in the forests cover from April, 1979 to April, 2009 is presented in this paper. The integrated classes such as water body, grass/agriculture land, dry/barren land and forest cover maps show the temporal changes taking place in the forests cover for the last 30 years period. RS has been employed in the

  15. Remote sensing for urban planning

    Science.gov (United States)

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

    1994-01-01

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

  16. Study of Influence of Effluent on Ground Water Using Remote Sensing, GIS and Modeling Techniques

    Science.gov (United States)

    Pathak, S.; Bhadra, B. K.; Sharma, J. R.

    2012-07-01

    The area lies in arid zone of western Rajasthan having very scanty rains and very low ground water reserves. Some of the other problems that are faced by the area are disposal of industrial effluent posing threat to its sustainability of water resource. Textiles, dyeing and printing industries, various mechanical process and chemical/synthetic dyes are used and considerable wastewater discharged from these textile units contains about high amount of the dyes into the adjoining drainages. This has caused degradation of water quality in this water scarce semi-arid region of the country. Pali city is located South-West, 70 Kms from Jodhpur in western Rajasthan (India). There are four Common Effluent Treatment Plant (CETP) treating wastewater to meet the pollutant level permissible to river discharge, a huge amount of effluent water of these factories directly meets the into the river Bandi - a tributary of river Luni. In order to monitor the impact of industrial effluents on the environment, identifying the extent of the degradation and evolving possible means of minimizing the impacts studies on quality of effluents, polluted river water and water of adjoining wells, the contamination migration of the pollutants from the river to ground water were studied. Remote sensing analysis has been carried out using Resourcesat -1 multispectral satellite data along with DEM derived from IRS P5 stereo pair. GIS database generated of various thematic layers viz. base layer - inventorying all waterbodies in the vicinity, transport network and village layer, drainage, geomorphology, structure, land use. Analysis of spatial distribution of the features and change detection in land use/cover carried out. GIS maps have been used to help factor in spatial location of source and hydro-geomorphological settings. DEM & elevation contour helped in delineation of watershed and identifying flow modelling boundaries. Litholog data analysis carried out for aquifer boundaries using specialized

  17. Utilization of Remote Sensing Techniques for Monitoring and Evaluation of Solo Watershed Management

    Directory of Open Access Journals (Sweden)

    Totok Gunawan

    2004-01-01

    Full Text Available This research is an application of remote sensing technology for monitoring and evaluation of watershed management, which was conducted is Solo Watershed, Central and East Java. The research objectives were 1 to investigate the capability of photomorphic analysis of Landsat Thematic Mapper (TM and Enhanced Themmatic Mapper (ETM + imagery as the basic for analyzes of landforms, landuse, and morphometry of the land surface; 2 to calculate the overland flow – peak discharge and erosion – sediment yield as indicators of land degradation of the area; 3 to use the indicators as set of instrument for monitoring and evaluation of watershed management. In this study, visual interpretation by means of on-screen digilization of the digital imagery was carried out in order to identify and to delineate land parameters using photomorphic approach. Based on the photomorphic analysis, several image – based parameters such as relief topography, physical soil characteristic, litho – stratigraphy, and vegetation cover were integrated with other themati maps in a geographic information system (GIS environment. Estimation of overland flow (C based on Cook methods (1942 and calculation of peak disccharge (Qmax based on rational method (Qmax = C. I. A were applied. Meanwhile, estimation of surface erosion was carried out using Universal Soil Loss Equation (USLE, A = R. K. L. S. CP. The sediment yield (Sy was estimated using seddiment delivery ratio ( SDR based on the following formula: Sy = [A + (25% x A] x SDR. Both pairs of C – Qmax and A – Sy, were utilized as the basis for monitoring and evaluation of the watershed. The combination of C – Qmax and A – Sy were also used as the basis for selection of stream gauge setting / AWLR within particular sub – catchment. It was found that the photomorphic analysis is only color/tone, slope aspects, pattern, and texture, unit boundaries between volcanic – origin landscape (Wilis volcanic complex and folded

  18. STUDY OF INFLUENCE OF EFFLUENT ON GROUND WATER USING REMOTE SENSING, GIS AND MODELING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    S. Pathak

    2012-07-01

    Full Text Available The area lies in arid zone of western Rajasthan having very scanty rains and very low ground water reserves. Some of the other problems that are faced by the area are disposal of industrial effluent posing threat to its sustainability of water resource. Textiles, dyeing and printing industries, various mechanical process and chemical/synthetic dyes are used and considerable wastewater discharged from these textile units contains about high amount of the dyes into the adjoining drainages. This has caused degradation of water quality in this water scarce semi-arid region of the country. Pali city is located South-West, 70 Kms from Jodhpur in western Rajasthan (India. There are four Common Effluent Treatment Plant (CETP treating wastewater to meet the pollutant level permissible to river discharge, a huge amount of effluent water of these factories directly meets the into the river Bandi – a tributary of river Luni. In order to monitor the impact of industrial effluents on the environment, identifying the extent of the degradation and evolving possible means of minimizing the impacts studies on quality of effluents, polluted river water and water of adjoining wells, the contamination migration of the pollutants from the river to ground water were studied. Remote sensing analysis has been carried out using Resourcesat −1 multispectral satellite data along with DEM derived from IRS P5 stereo pair. GIS database generated of various thematic layers viz. base layer – inventorying all waterbodies in the vicinity, transport network and village layer, drainage, geomorphology, structure, land use. Analysis of spatial distribution of the features and change detection in land use/cover carried out. GIS maps have been used to help factor in spatial location of source and hydro-geomorphological settings. DEM & elevation contour helped in delineation of watershed and identifying flow modelling boundaries. Litholog data analysis carried out for aquifer

  19. Applications of remote sensing to watershed management

    Science.gov (United States)

    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.

  20. Comparison of Aerial and Terrestrial Remote Sensing Techniques for Quantifying Forest Canopy Structural Complexity and Estimating Net Primary Productivity

    Science.gov (United States)

    Fahey, R. T.; Tallant, J.; Gough, C. M.; Hardiman, B. S.; Atkins, J.; Scheuermann, C. M.

    2016-12-01

    Canopy structure can be an important driver of forest ecosystem functioning - affecting factors such as radiative transfer and light use efficiency, and consequently net primary production (NPP). Both above- (aerial) and below-canopy (terrestrial) remote sensing techniques are used to assess canopy structure and each has advantages and disadvantages. Aerial techniques can cover large geographical areas and provide detailed information on canopy surface and canopy height, but are generally unable to quantitatively assess interior canopy structure. Terrestrial methods provide high resolution information on interior canopy structure and can be cost-effectively repeated, but are limited to very small footprints. Although these methods are often utilized to derive similar metrics (e.g., rugosity, LAI) and to address equivalent ecological questions and relationships (e.g., link between LAI and productivity), rarely are inter-comparisons made between techniques. Our objective is to compare methods for deriving canopy structural complexity (CSC) metrics and to assess the capacity of commonly available aerial remote sensing products (and combinations) to match terrestrially-sensed data. We also assess the potential to combine CSC metrics with image-based analysis to predict plot-based NPP measurements in forests of different ages and different levels of complexity. We use combinations of data from drone-based imagery (RGB, NIR, Red Edge), aerial LiDAR (commonly available medium-density leaf-off), terrestrial scanning LiDAR, portable canopy LiDAR, and a permanent plot network - all collected at the University of Michigan Biological Station. Our results will highlight the potential for deriving functionally meaningful CSC metrics from aerial imagery, LiDAR, and combinations of data sources. We will also present results of modeling focused on predicting plot-level NPP from combinations of image-based vegetation indices (e.g., NDVI, EVI) with LiDAR- or image-derived metrics of

  1. Optical remote sensing

    CERN Document Server

    Prasad, Saurabh; Chanussot, Jocelyn

    2011-01-01

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

  2. Remote sensing of water quality

    Science.gov (United States)

    Hovis, W. A.

    1978-01-01

    Remote sensing from aircraft has been used to determine water content in areas such as the New York Bight. Extension of the techniques developed to satellite sensing of the Chesapeake Bay will begin in 1978 with the launch of Nimbus-G. Remote sensing offers a number of interesting possibilities for investigating a reasonably large body of water, such as the Chesapeake Bay, coupled with some disadvantages. The chief advantage of remote sensing is that it offers the opportunity to cover large areas in relatively short periods of time. Low altitude satellites traveling at about 7 km/s can cover the Chesapeake Bay in about 1 minute so that the entire Bay can be studied under almost identical conditions of solar illumination.

  3. Remote Sensing of Environmental Pollution

    Science.gov (United States)

    North, G. W.

    1971-01-01

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

  4. Application of remote sensing, GIS and MCA techniques for delineating groundwater prospect zones in Kashipur block, Purulia district, West Bengal

    Science.gov (United States)

    Nag, S. K.; Kundu, Anindita

    2018-03-01

    Demand of groundwater resources has increased manifold with population expansion as well as with the advent of modern civilization. Assessment, planning and management of groundwater resource are becoming crucial and extremely urgent in recent time. The study area belongs to Kashipur block, Purulia district, West Bengal. The area is characterized with dry climate and hard rock terrain. The objective of this study is to delineate groundwater potential zone for the assessment of groundwater availability using remote sensing, GIS and MCA techniques. Different thematic layers such as hydrogeomorphology, slope and lineament density maps have been transformed to raster data in TNT mips pro2012. To assign weights and ranks to different input factor maps, multi-influencing factor (MIF) technique has been used. The weights assigned to each factor have been computed statistically. Weighted index overlay modeling technique was used to develop a groundwater potential zone map with three weighted and scored parameters. Finally, the study area has been categorized into four distinct groundwater potential zones—excellent 1.5% (6.45 sq. km), good 53% (227.9 sq. km), moderate 45% (193.5 sq. km.) and poor 0.5% (2.15 sq. km). The outcome of the present study will help local authorities, researchers, decision makers and planners in formulating proper planning and management of groundwater resources in different hydrogeological situations.

  5. Optical Remote Sensing Laboratory

    Data.gov (United States)

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

  6. Mapping of groundwater potential zones in Salem Chalk Hills, Tamil Nadu, India, using remote sensing and GIS techniques.

    Science.gov (United States)

    Thilagavathi, N; Subramani, T; Suresh, M; Karunanidhi, D

    2015-04-01

    This study proposes to introduce the remote sensing and geographic information system (GIS) techniques in mapping the groundwater potential zones. Remote sensing and GIS techniques have been used to map the groundwater potential zones in Salem Chalk Hills, Tamil Nadu, India. Charnockites and fissile hornblende biotite gneiss are the major rock types in this region. Dunites and peridodites are the ultramafic rocks which cut across the foliation planes of the gneisses and are highly weathered. It comprises magnesite and chromite deposits which are excavated by five mining companies by adopting bench mining. The thickness of weathered and fracture zone varies from 2.2 to 50 m in gneissic formation and 5.8 to 55 m in charnockite. At the contacts of gneiss and charnockite, the thickness ranges from 9.0 to 90.8 m favoring good groundwater potential. The mine lease area is underlined by fractured and sheared hornblende biotite gneiss where groundwater potential is good. Water catchment tanks in this area of 5 km radius are small to moderate in size and are only seasonal. They remain dry during summer seasons. As perennial water resources are remote, the domestic and agricultural activities in this region depend mainly upon the groundwater resources. The mines are located in gently slope area, and accumulation of water is not observed except in mine pits even during the monsoon period. Therefore, it is essential to map the groundwater potential zones for proper management of the aquifer system. Satellite imageries were also used to extract lineaments, hydrogeomorphic landforms, drainage patterns, and land use, which are the major controlling factors for the occurrence of groundwater. Various thematic layers pertaining to groundwater existence such as geology, geomorphology, land use/land cover, lineament, lineament density, drainage, drainage density, slope, and soil were generated using GIS tools. By integrating all the above thematic layers based on the ranks and

  7. Quantifying discontinuity orientation and persistence on high mountain rock slopes and large landslides using terrestrial remote sensing techniques

    Directory of Open Access Journals (Sweden)

    M. Sturzenegger

    2009-03-01

    Full Text Available This paper describes experience gained in the application of terrestrial digital photogrammetry and terrestrial laser scanning for the characterization of the structure of high mountain rock slopes and large landslides. A methodology allowing the creation and registration of 3-D models with limited access to high mountain rock slopes is developed and its accuracy verified. The importance of occlusion, ground resolution, scale and reflectivity are discussed. Special emphasis is given to the concept of observation scale and resulting scale bias and its influence on discontinuity characterization. The step-path geometry of persistent composite surfaces and its role in remote sensing measurements are described. An example of combined terrestrial digital photogrammetry and terrestrial laser scanning applied in the generation of a 3-D model of the South Peak of Turtle Mountain, the location of the Frank Slide, is presented. The advantages gained from the combined use of these techniques and the potential offered through long-range terrestrial digital photogrammetry, using high focal length lenses up to 400 mm is illustrated. Special emphasis is given to the potential of this specific technique, which has to the authors knowledge rarely been documented in the geotechnical literature.

  8. Quantifying discontinuity orientation and persistence on high mountain rock slopes and large landslides using terrestrial remote sensing techniques

    Science.gov (United States)

    Sturzenegger, M.; Stead, D.

    2009-03-01

    This paper describes experience gained in the application of terrestrial digital photogrammetry and terrestrial laser scanning for the characterization of the structure of high mountain rock slopes and large landslides. A methodology allowing the creation and registration of 3-D models with limited access to high mountain rock slopes is developed and its accuracy verified. The importance of occlusion, ground resolution, scale and reflectivity are discussed. Special emphasis is given to the concept of observation scale and resulting scale bias and its influence on discontinuity characterization. The step-path geometry of persistent composite surfaces and its role in remote sensing measurements are described. An example of combined terrestrial digital photogrammetry and terrestrial laser scanning applied in the generation of a 3-D model of the South Peak of Turtle Mountain, the location of the Frank Slide, is presented. The advantages gained from the combined use of these techniques and the potential offered through long-range terrestrial digital photogrammetry, using high focal length lenses up to 400 mm is illustrated. Special emphasis is given to the potential of this specific technique, which has to the authors knowledge rarely been documented in the geotechnical literature.

  9. Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

    Science.gov (United States)

    Yang, Senlin; Li, Xilong; Chong, Xin

    2017-10-01

    The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

  10. Remote Sensing in Archeology: Classifying Bajos of the Paten, Guatemala

    Science.gov (United States)

    Lowry, James D., Jr.

    1998-01-01

    This project focuses on the adaptation of human populations to their environments from prehistoric times to the present. It emphasizes interdisciplinary research to develop ecological baselines through the use of remotely sensed imagery, in situ field work, and the modeling of human population dynamics. It utilizes cultural and biological data from dated archaeological sites to assess the subsistence and settlement patterns of human societies in response to changing climatic and environmental conditions. The utilization of remote sensing techniques in archaeology is relatively new, exciting, and opens many doors.

  11. Potential of remote sensing techniques for tsunami hazard and vulnerability analysis – a case study from Phang-Nga province, Thailand

    Directory of Open Access Journals (Sweden)

    H. Römer

    2012-06-01

    Full Text Available Recent tsunami disasters, such as the 2004 Indian Ocean tsunami or the 2011 Japan earthquake and tsunami, have highlighted the need for effective risk management. Remote sensing is a relatively new method for risk analysis, which shows significant potential in conducting spatially explicit risk and vulnerability assessments. In order to explore and discuss the potential and limitations of remote sensing techniques, this paper presents a case study from the tsunami-affected Andaman Sea coast of Thailand. It focuses on a local assessment of tsunami hazard and vulnerability, including the socio-economic and ecological components. High resolution optical data, including IKONOS data and aerial imagery (MFC-3 camera as well as different digital elevation models, were employed to create basic geo-data including land use and land cover (LULC, building polygons and topographic data sets and to provide input data for the hazard and vulnerability assessment. Results show that the main potential of applying remote sensing techniques and data derives from a synergistic combination with other types of data. In the case of hazard analysis, detailed LULC information and the correction of digital surface models (DSMs significantly improved the results of inundation modeling. The vulnerability assessment showed that remote sensing can be used to spatially extrapolate field data on socio-economic or ecological vulnerability collected in the field, to regionalize exposure elements and assets and to predict vulnerable areas. Limitations and inaccuracies became evident regarding the assessment of ecological resilience and the statistical prediction of vulnerability components, based on variables derived from remote sensing data.

  12. Study the impact of rainfall on the United Arab Emirates dams using remote sensing and image processing techniques

    Science.gov (United States)

    Al Marzouqi, Fatima A.; Al Besher, Shaikha A.; Al Mansoori, Saeed H.

    2017-10-01

    The United Arab Emirates (UAE) has given great attention to the environment and sustainable development through applications of best practices of global standards that ensure optimal investment in natural resources. Since the UAE is located in an arid region which is known as dry, sandy and get a small amount of rainfall, thus the water resources are limited and accordingly, the government has initiated an integrated water resources management (IWRM) strategy to meet the increasing demands of water. Dams are considered as one of the important strategies that are suitable for this arid region. An event of rainfall if between heavy to severe in a short duration could cause flash floods and damages to population centers and areas of agriculture nearby. To prevent that from happening, several dams and barriers were built to protect human life and infrastructure. Besides contribution to enhance the water resources and use them optimally to irrigate the growing agricultural areas across the country. Geographically, most of the dams were located in the northern and eastern part of the UAE, around mountainous areas. This study aims to monitor the changes that occurred to five dams of the north-eastern region of the UAE during 2015 and 2016 through the use of remote sensing technology of optical images captured by "DubaiSat-2". The segmentation approach utilized in this study is based on a band ratio technique called Normalized Difference Water Index (NDWI). The experimental results revealed that the proposed approach is efficient in detecting dams from multispectral satellite images.

  13. Flood Hazard Assessment along the Western Regions of Saudi Arabia using GIS-based Morphometry and Remote Sensing Techniques

    KAUST Repository

    Shi, Qianwen

    2014-12-01

    Flash flooding, as a result of excessive rainfall in a short period, is considered as one of the worst environmental hazards in arid regions. Areas located in the western provinces of Saudi Arabia have experienced catastrophic floods. Geomorphologic evaluation of hydrographic basins provides necessary information to define basins with flood hazard potential in arid regions, especially where long-term field observations are scarce and limited. Six large basins (from North to South: Yanbu, Rabigh, Khulais, El-Qunfza, Baish and Jizan) were selected for this study because they have large surface areas and they encompass high capacity dams at their downstream areas. Geographic Information System (GIS) and remote sensing techniques were applied to conduct detailed morphometric analysis of these basins. The six basins were further divided into 203 sub-basins based on their drainage density. The morphometric parameters of the six basins and their associated 203 sub-basins were calculated to estimate the degree of flood hazard by combining normalized values of these parameters. Thus, potential flood hazard maps were produced from the estimated hazard degree. Furthermore, peak runoff discharge of the six basins and sub-basins were estimated using the Snyder Unit Hydrograph and three empirical models (Nouh’s model, Farquharson’s model and Al-Subai’s model) developed for Saudi Arabia. Additionally, recommendations for flood mitigation plans and water management schemes along these basins were further discussed.

  14. Remote Sensing and GIS Techniques for Evaluation of Groundwater Quality in Municipal Corporation of Hyderabad (Zone-V), India

    Science.gov (United States)

    Asadi, S. S.; Vuppala, Padmaja; Reddy, M. Anji

    2007-01-01

    Groundwater quality in Hyderabad has special significance and needs great attention of all concerned since it is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the ground water quality, relates it to the land use / land cover and maps such quality using Remote sensing and GIS techniques for a part of Hyderabad metropolis. Thematic maps for the study are prepared by visual interpretation of SOI toposheets and linearly enhanced fused data of IRS-ID PAN and LISS-III imagery on 1:50,000 scale using AutoCAD and ARC/INFO software. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared using curve fitting method in Arc View GIS software. Water Quality Index (WQI) was then calculated to find the suitability of water for drinking purpose. The overall view of the water quality index of the present study area revealed that most of the study area with > 50 standard rating of water quality index exhibited poor, very poor and unfit water quality except in places like Banjara Hills, Erragadda and Tolichowki. Appropriate methods for improving the water quality in affected areas have been suggested. PMID:17431315

  15. Application of remote-sensing techniques to hydrologic studies in selected coal-mine areas of southeastern Kansas

    Science.gov (United States)

    Kenny, J.F.; McCauley, J.R.

    1983-01-01

    Disturbances resulting from intensive coal mining in the Cherry Creek basin of southeastern Kansas were investigated using color and color-infrared aerial photography in conjunction with water-quality data from simultaneously acquired samples. Imagery was used to identify the type and extent of vegetative cover on strip-mined lands and the extent and success of reclamation practices. Drainage patterns, point sources of acid mine drainage, and recharge areas for underground mines were located for onsite inspection. Comparison of these interpretations with water-quality data illustrated differences between the eastern and western parts of the Cherry Creek basin. Contamination in the eastern part is due largely to circulation of water from unreclaimed strip mines and collapse features through the network of underground mines and subsequent discharge of acidic drainage through seeps. Contamination in the western part is primarily caused by runoff and seepage from strip-mined lands in which surfaces have frequently been graded and limed but are generally devoid of mature stands of soil-anchoring vegetation. The successful use of aerial photography in the study of Cherry Creek basin indicates the potential of using remote-sensing techniques in studies of other coal-mined regions. (USGS)

  16. Hyperspectral remote sensing

    CERN Document Server

    Eismann, Michael

    2012-01-01

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

  17. Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

    Science.gov (United States)

    Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

    2017-12-01

    Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire

  18. Remote sensing of wetlands applications and advances

    CERN Document Server

    Tiner, Ralph W; Klemas, Victor V

    2015-01-01

    Effectively Manage Wetland Resources Using the Best Available Remote Sensing Techniques Utilizing top scientists in the wetland classification and mapping field, Remote Sensing of Wetlands: Applications and Advances covers the rapidly changing landscape of wetlands and describes the latest advances in remote sensing that have taken place over the past 30 years for use in mapping wetlands. Factoring in the impact of climate change, as well as a growing demand on wetlands for agriculture, aquaculture, forestry, and development, this text considers the challenges that wetlands pose for remote sensing and provides a thorough introduction on the use of remotely sensed data for wetland detection. Taking advantage of the experiences of more than 50 contributing authors, the book describes a variety of techniques for mapping and classifying wetlands in a multitude of environments ranging from tropical to arctic wetlands including coral reefs and submerged aquatic vegetation. The authors discuss the advantages and di...

  19. A regression technique for evaluation and quantification for water quality parameters from remote sensing data

    International Nuclear Information System (INIS)

    Whitlock, C.H.; Kuo, C.Y.

    1979-01-01

    The paper attempts to define optical physics and/or environmental conditions under which the linear multiple-regression should be applicable. It is reported that investigation of the signal response shows that the exact solution for a number of optical physics conditions is of the same form as a linearized multiple-regression equation, even if nonlinear contributions from surface reflections, atmospheric constituents, or other water pollutants are included. Limitations on achieving this type of solution are defined. Laboratory data are used to demonstrate that the technique is applicable to water mixtures which contain constituents with both linear and nonlinear radiance gradients. Finally, it is concluded that instrument noise, ground-truth placement, and time lapse between remote sensor overpass and water sample operations are serious barriers to successful use of the technique

  20. Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

    Directory of Open Access Journals (Sweden)

    Thuan Chu

    2013-12-01

    Full Text Available The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre- and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.

  1. a Temporal and Spatial Analysis of Urban Heat Island in Basin City Utilizing Remote Sensing Techniques

    Science.gov (United States)

    Chang, Hsiao-Tung

    2016-06-01

    Urban Heat Island (UHI) has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city's UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST) at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls "sinking heat island". From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  2. A TEMPORAL AND SPATIAL ANALYSIS OF URBAN HEAT ISLAND IN BASIN CITY UTILIZING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    H.-T. Chang

    2016-06-01

    Full Text Available Urban Heat Island (UHI has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city’s UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls “sinking heat island”. From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.

  3. Estimation of gross primary production of the Amazon-Cerrado transitional forest by remote sensing techniques

    Directory of Open Access Journals (Sweden)

    Maísa Caldas Souza

    2014-03-01

    Full Text Available The gross primary production (GPP of ecosystems is an important variable in the study of global climate change. Generally, the GPP has been estimated by micrometeorological techniques. However, these techniques have a high cost of implantation and maintenance, making the use of orbital sensor data an option to be evaluated. Thus, the objective of this study was to evaluate the potential of the MODIS (Moderate Resolution Imaging Spectroradiometer MOD17A2 product and the vegetation photosynthesis model (VPM to predict the GPP of the Amazon-Cerrado transitional forest. The GPP predicted by MOD17A2 (GPP MODIS and VPM (GPP VPM were validated with the GPP estimated by eddy covariance (GPP EC. The GPP MODIS, GPP VPM and GPP EC have similar seasonality, with higher values in the wet season and lower in the dry season. However, the VPM performed was better than the MOD17A2 to estimate the GPP, due to use local climatic data for predict the light use efficiency, while the MOD17A2 use a global circulation model and the lookup table of each vegetation type to estimate the light use efficiency.

  4. Characterization and delineation of caribou habitat on Unimak Island using remote sensing techniques

    Science.gov (United States)

    Atkinson, Brain M.

    The assessment of herbivore habitat quality is traditionally based on quantifying the forages available to the animal across their home range through ground-based techniques. While these methods are highly accurate, they can be time-consuming and highly expensive, especially for herbivores that occupy vast spatial landscapes. The Unimak Island caribou herd has been decreasing in the last decade at rates that have prompted discussion of management intervention. Frequent inclement weather in this region of Alaska has provided for little opportunity to study the caribou forage habitat on Unimak Island. The overall objectives of this study were two-fold 1) to assess the feasibility of using high-resolution color and near-infrared aerial imagery to map the forage distribution of caribou habitat on Unimak Island and 2) to assess the use of a new high-resolution multispectral satellite imagery platform, RapidEye, and use of the "red-edge" spectral band on vegetation classification accuracy. Maximum likelihood classification algorithms were used to create land cover maps in aerial and satellite imagery. Accuracy assessments and transformed divergence values were produced to assess vegetative spectral information and classification accuracy. By using RapidEye and aerial digital imagery in a hierarchical supervised classification technique, we were able to produce a high resolution land cover map of Unimak Island. We obtained overall accuracy rates of 71.4 percent which are comparable to other land cover maps using RapidEye imagery. The "red-edge" spectral band included in the RapidEye imagery provides additional spectral information that allows for a more accurate overall classification, raising overall accuracy 5.2 percent.

  5. The possibility of using photogrammetric and remote sensing techniques to model lavaka (gully erosion) development in Madagascar

    Science.gov (United States)

    Raveloson, Andrea; Székely, Balázs; Molnár, Gábor; Rasztovits, Sascha

    2013-04-01

    Gully erosion is a worldwide problem for it has a number of undesirable effects and their development is hard to follow. Madagascar is one of the most affected countries for its highlands are densely covered with gullies named lavakas. Lavaka formation and development seems to be triggered by many regional and local causes but the actual reasons are still poorly understood. Furthermore lavakas differ from normal gullies due to their enormous size and special shape. Field surveys are time consuming and data from two-dimensional measurements and pictures (even aerial) might lack major information for morphologic studies. Therefore close range surveying technologies should be used to get three-dimensional information about these unusual and complex features. This contribution discusses which remote sensing and photogrammetric techniques are adequate to survey the development of lavakas, their volume change and sediment budget. Depending on the types and properties (such as volume, depth, shape, vegetation) of the lavaka different methods will be proposed showing pros and cons of each one of them. Our goal is to review techniques to model, survey and analyze lavakas development to better understand the cause of their formation, special size and shape. Different methods are evaluated and compared from field survey through data processing, analyzing cost-effectiveness, potential errors and accuracy for each one of them. For this purpose we will also consider time- and cost-effectiveness of the softwares able to render the images into 3D model as well as the resolution and accuracy of the outputs. Further studies will concentrate on using the three dimensional models of lavakas which will be later on used for geomorphological studies in order to understand their special shape and size. This is ILARG-contribution #07.

  6. Acoustic remote sensing of ocean flows

    Digital Repository Service at National Institute of Oceanography (India)

    Joseph, A.; Desa, E.

    surface layer of the ocean surface and hence these techniques are unusable for measurement of subsurface circulation. The three methods of ocean circulation measurement using acoustic remote sensing techniques are the Lagrangian, Eulerian and single...

  7. Documentation of the ground for the planned MERO-IKL oil pipeline using the remote sensing technique

    International Nuclear Information System (INIS)

    Kult, L.; Vavra, J.; Sara, V.

    1994-02-01

    Complete photographic documentation of the planned route for the Ingolstadt-Kralupy-Litvinov pipeline was obtained by remote sensing; the vegetation cover sites and their avitalities were identified and described. The documentation identifies areas of avital plants, and defines potentially hazardous sources of soil or water pollution along the planned route. (J.B.). 1 tab., 17 figs

  8. Near-earth orbital guidance and remote sensing

    Science.gov (United States)

    Powers, W. F.

    1972-01-01

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

  9. Integration of Remote Sensing Techniques for Intensity Zonation within a Landslide Area: A Case Study in the Northern Apennines, Italy

    Directory of Open Access Journals (Sweden)

    Veronica Tofani

    2014-01-01

    Full Text Available This paper describes the application of remote sensing techniques, based on SAR interferometry for the intensity zonation of the landslide affecting the Castagnola village (Northern Apennines of Liguria region, Italy. The study of the instability conditions of the landslide started in 2001 with the installation of conventional monitoring systems, such as inclinometers and crackmeters, ranging in time from April 2001 to April 2002, which allowed to define the deformation rates of the landslide and to locate the actual landslide sliding surface, as well as to record the intensity of the damages and cracks affecting the buildings located within the landslide perimeter. In order to investigate the past long-term evolution of the ground movements a PSI (Persistent Scatterers Interferometry analysis has been performed making use of a set of ERS1/ERS2 images acquired in 1992–2001 period. The outcome of the PSI analysis has allowed to confirm the landslide extension as mapped within the official landslide inventory map as well as to reconstruct the past line-of-sight average velocities of the landslide and the time-series deformations. Following the high velocities detected by the PSI, and the extensive damages surveyed in the buildings of the village, the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR system has been installed. The GBInSAR monitoring system has been equipped during October 2008 and three distinct campaigns have been carried out from October 2008 until March 2009. The interpretation of the data has allowed deriving a multi-temporal deformation map of the landslide, showing the up-to-date displacement field and the average landslide velocity. A new landslide boundary has been defined and two landslide sectors characterized by different displacement rates have been identified.

  10. Spatio Temporal Change of Selected Glaciers Along Karakoram Highway from 1994-2017 Using Remote Sensing and GIS Techniques

    Science.gov (United States)

    Anwar, Yasmeen; Iqbal, Javed

    2018-04-01

    With the acceleration of global warming glaciers are receding rapidly. Monitoring of glaciers are important because they caused outburst of floods the past. This research delivers a systematic approach for the assessment of glaciers i.e. Batura, Passu, Ghulkin and Gulmit cover along the Karakoram Highway. Main reason to select these glaciers was their closeness to Karakoram Highway which plays an important role in China-Pakistan economic corridor (CPEC). This study incorporates the techniques of Geographical Information System and Remote Sensing (GIS & RS). For this study, Landsat 4,5,7,8 images were taken for the years of 1994, 2002, 2009, 2013 and 2017. Using the said images supervised classification was done in ArcMap 10.3 version to identify the changes in glaciers. The area was categorized into six major classes' i.e. Fresh snow, Glaciers, Debris, Vegetation, Water bodies and Open land. Classified results showed a decrease in the area of Glaciers, almost 3.5% from 1994 to 2017. GLIMS data about boundary of glaciers of 1999 and 2007 was compared with the classified results which show decrease in terminus of glaciers. Batura glacier has been receded almost 0.6 km from 1999 to 2017, whereas Passu glaciers receded 0.3 km, whereas Gulmit and Ghulkin glaciers are more stable than Passu and Batura with the difference of -0.05 and +0.57 km respectively. At the end results from classified maps were compared with the climatic data. Wherein temperature is rapidly increasing resulting in melting of glaciers and can cause shrinkage of fresh water as well as destruction to Karakoram highway in case of outburst floods.

  11. A novel approach to model exposure of coastal-marine ecosystems to riverine flood plumes based on remote sensing techniques.

    Science.gov (United States)

    Álvarez-Romero, Jorge G; Devlin, Michelle; Teixeira da Silva, Eduardo; Petus, Caroline; Ban, Natalie C; Pressey, Robert L; Kool, Johnathan; Roberts, Jason J; Cerdeira-Estrada, Sergio; Wenger, Amelia S; Brodie, Jon

    2013-04-15

    Increased loads of land-based pollutants are a major threat to coastal-marine ecosystems. Identifying the affected marine areas and the scale of influence on ecosystems is critical to assess the impacts of degraded water quality and to inform planning for catchment management and marine conservation. Studies using remotely-sensed data have contributed to our understanding of the occurrence and influence of river plumes, and to our ability to assess exposure of marine ecosystems to land-based pollutants. However, refinement of plume modeling techniques is required to improve risk assessments. We developed a novel, complementary, approach to model exposure of coastal-marine ecosystems to land-based pollutants. We used supervised classification of MODIS-Aqua true-color satellite imagery to map the extent of plumes and to qualitatively assess the dispersal of pollutants in plumes. We used the Great Barrier Reef (GBR), the world's largest coral reef system, to test our approach. We combined frequency of plume occurrence with spatially distributed loads (based on a cost-distance function) to create maps of exposure to suspended sediment and dissolved inorganic nitrogen. We then compared annual exposure maps (2007-2011) to assess inter-annual variability in the exposure of coral reefs and seagrass beds to these pollutants. We found this method useful to map plumes and qualitatively assess exposure to land-based pollutants. We observed inter-annual variation in exposure of ecosystems to pollutants in the GBR, stressing the need to incorporate a temporal component into plume exposure/risk models. Our study contributes to our understanding of plume spatial-temporal dynamics of the GBR and offers a method that can also be applied to monitor exposure of coastal-marine ecosystems to plumes and explore their ecological influences. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. An Integrated Use of Experimental, Modeling and Remote Sensing Techniques to Investigate Carbon and Phosphorus Dynamics in the Humid Tropics

    Science.gov (United States)

    Townsend, Alan R.; Asner, Gregory P.; Bustamante, Mercedes M. C.

    2001-01-01

    Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.

  13. Plankton Biomass Models Based on GIS and Remote Sensing Technique for Predicting Marine Megafauna Hotspots in the Solor Waters

    Science.gov (United States)

    Putra, MIH; Lewis, SA; Kurniasih, EM; Prabuning, D.; Faiqoh, E.

    2016-11-01

    Geographic information system and remote sensing techniques can be used to assist with distribution modelling; a useful tool that helps with strategic design and management plans for MPAs. This study built a pilot model of plankton biomass and distribution in the waters off Solor and Lembata, and is the first study to identify marine megafauna foraging areas in the region. Forty-three samples of zooplankton were collected every 4 km according to the range time and station of aqua MODIS. Generalized additive model (GAM) we used to modelling zooplankton biomass response from environmental properties.Thirty one samples were used to build a model of inverse distance weighting (IDW) (cell size 0.01°) and 12 samples were used as a control to verify the models accuracy. Furthermore, Getis-Ord Gi was used to identify the significance of the hotspot and cold-spot for foraging area. The GAM models was explain 88.1% response of zooplankton biomass and percent to full moon, phytopankton biomassbeing strong predictors. The sampling design was essential in order to build highly accurate models. Our models 96% accurate for phytoplankton and 88% accurate for zooplankton. The foraging behaviour was significantly related to plankton biomass hotspots, which were two times higher compared to plankton cold-spots. In addition, extremely steep slopes of the Lamakera strait support strong upwelling with highly productive waters that affect the presence of marine megafauna. This study detects that the Lamakera strait provides the planktonic requirements for marine megafauna foraging, helping to explain why this region supports such high diversity and abundance of marine megafauna.

  14. Multi-platform in-situ and remote sensing techniques to derive Saharan dust properties during AMISOC-TNF 2013

    Science.gov (United States)

    Córdoba-Jabonero, Carmen; Andrey, Javier; Adame, José Antonio; Sorribas, Mar; Gómez, Laura; Cuevas, Emilio; Gil-Ojeda, Manuel

    2014-10-01

    In the framework of AMISOC (Atmospheric Minor Species relevant to the Ozone Chemistry) project, a multiinstrumented campaign was performed in the Canary Islands area in summer-time from 01 July to 11 August 2013. Both ground-based remote-sensing and airborne in-situ measurements were performed under dust loading conditions. Saharan dusty (DD) conditions were reported during 57% of the overall campaign period. Particular DD cases corresponded to a 2-day period with a progressively arriving Saharan dust intrusion over Tenerife on 31 July (weak incidence) and 01 August (strong incidence). As reference, the non-dusty (ND) situation on 30 July was also examined. Vertical size distributions (SD) for particles within an extended fine-to-coarse (0.16-2.8 μm) mode were provided by using aircraft aerosol PCASP sonde measurements. Extinction profiles and Lidar ratio (LR) values were derived from Micro Pulse Lidar measurements. Despite no MAXDOAS aerosol profiling retrievals were available, the potential of this technique has also been introduced. A good agreement is found between the optical and microphysical properties, showing dust particles confined in a wide layer of around 4.5 km thickness from 1.5 to 6 km height. Dust incidence mostly affected the Free Troposphere (FT). LR ranged between 50 and 55 sr, showing typical values for Saharan dust particles. In general, the dust impact on mass concentration was enhanced due to the increase of larger particles, affecting both the Boundary layer (BL) and FT, but showing differences depending on the dusty case. MAXDOAS profiles are expected to be included in an extended version of this work.

  15. The Changing Face of the of Former Soviet Cities: Elucidated by Remote Sensing and Machine Learning Techniques

    Science.gov (United States)

    Poghosyan, Armen

    2017-04-01

    Despite remote sensing of urbanization emerged as a powerful tool to acquire critical knowledge about urban growth and its effects on global environmental change, human-environment interface as well as environmentally sustainable urban development, there is lack of studies utilizing remote sensing techniques to investigate urbanization trends in the Post-Soviet states. The unique challenges accompanying the urbanization in the Post-Soviet republics combined with the expected robust urban growth in developing countries over the next several decades highlight the critical need for a quantitative assessment of the urban dynamics in the former Soviet states as they navigate towards a free market democracy. This study uses total of 32 Level-1 precision terrain corrected (L1T) Landsat scenes with 30-m resolution as well as further auxiliary population and economic data for ten cities distributed in nine former Soviet republics to quantify the urbanization patterns in the Post-Soviet region. Land cover in each urban center of this study was classified by using Support Vector Machine (SVM) learning algorithm with overall accuracies ranging from 87 % to 97 % for 29 classification maps over three time steps during the past twenty-five years in order to estimate quantities, trends and drivers of urban growth in the study area. The results demonstrated several spatial and temporal urbanization patterns observed across the Post-Soviet states and based on urban expansion rates the cities can be divided into two groups, fast growing and slow growing urban centers. The relatively fast-growing urban centers have an average urban expansion rate of about 2.8 % per year, whereas the slow growing cities have an average urban expansion rate of about 1.0 % per year. The total area of new land converted to urban environment ranged from as low as 26 km2 to as high as 780 km2 for the ten cities over the 1990 - 2015 period, while the overall urban land increase ranged from 11.3 % to 96

  16. Hyperspectral remote sensing

    National Research Council Canada - National Science Library

    Eismann, Michael Theodore

    2012-01-01

    ..., and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment...

  17. Remote Sensing Information Gateway

    Science.gov (United States)

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

  18. Preface: Remote Sensing in Coastal Environments

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-08-01

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

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

    OpenAIRE

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

    2016-01-01

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

  20. Using Remote Sensing and Spatial Analyses Techniques For Optimum Land Use Planning, West of Suez Canal, Egypt

    International Nuclear Information System (INIS)

    Elnahry, A.H.; Mohamed, E.S.; Nasar, N.

    2008-01-01

    The current study aims at using remote sensing (RS) and Geographic Information System (GIS) techniques for optimum landuse planning of the area located north Ismaillia - south Port Said Governorates on the western side of Suez Canal. It is bounded by longitudes 32 degree 10 and 32 degree 20 E and latitudes 30 0 4 rand 31 0 00' N. Great part of this area is under reclamation and suffering from improper landuse. Ten geomorphologic units were recognized i.e. clay flats, decantation basins, overflow basins, sand sheets, gypsiferous flats, old river terraces, sand flats, turtle backs, lake beds, and recent river terraces. Using US Soil Taxonomy, two soil orders could be identified; Entisols and Aridisols which are represented by ten great groups: Typic Haplosalids, Typic Haplogypsids, Typic Toriorthents, Vertic Argigypsids, Vertic Torrijluvents, Vertic Natrargids ,Typic Torripsamments, Typic Torrifluvens, Aquic Torriorthents and Typic Psammaquents. Surface and ground water with respect to salinity and alkalinity hazards were investigated ,where surface water of the main canals was classified as C2-S 1, C3-S 1 ,C4-S2 and C4-S4, meanwhile the ground water was classified as C3-S 1, C3 -S 1 ,C4-S2 ,C4-SI and C4-S4 .Optimum landuse planning of the studied area includes three approaches i.e., physical planning, optimum cropping pattern and other uses. Physical planning includes designing of three geospatial models. I-treatment plant site selection model. 2-central village site selection model and 3- shortest path for new Canal model. Current cropping pattern was obtained by matching the crop requirements with soil characteristics, where soils of high sand flats and low gypsiferrous flats are currently highly suitable (S2) for sugar beat, alfalfa and cotton, soils of low sand flats are currently highly suitable (S2) for olive, citrus and melon, soils of low recent river terraces are currently highly suitable (S2) for sugar beat, cotton, corn and rice ,soils of moderately

  1. Assessment of Soil Degradation in The Northern Part of Nile Delta, Egypt, Using Remote Sensing and Gis Techniques

    International Nuclear Information System (INIS)

    El Nahry, A.H.; Ibraheim, M.M.; El Baroudy, A.A.

    2008-01-01

    The present work aims at monitoring soil degradation process within the last two decades in the northern part of Nile Delta .The investigated area lies between longitudes 31 00 and 31 15 E and latitudes 31 00 and 31 37 N, covering an area of about 344584.01 feddans. Detecting soil degradation and recognizing its various types is a necessity to take the practical measures for combating it as well as conserving and keeping the agricultural soil healthy. Land degradation was assessed by adopting new approach through the integration of GLASOD/ FAa approach and Remote Sensing / GIS techniques .The main types of human induced soil degradation that observed in the studied area are salinity, alkalinity (sodicity), compaction and water logging .On the other hand water erosion because of sea rise is assessed. The obtained data showed that, areas that were affected by compaction increment have been spatially enlarged by 40.9 % and those affected by compaction decrease have been spatially reduced by 22.6 % of the total area, meanwhile areas that have been unchanged were estimated by 36.5% of the total area. The areas that were affected by water logging increase have been spatially enlarged by 52.2 % and those affected by water logging decrease have been spatially reduced by 10.1 % of the total area, meanwhile the areas which have been unchanged were represented by 37.7 % of the total area. Areas that were affected by salinity increase have been spatially enlarged by 31.4 % of the total area and those affected by salinity decrease have been reduced by 43.3 % of the total area. An area represented by 25.2 % of the total area has been unchanged. Alkalinization (sodicity) was expressed by the exchangeable sodium percentage (ESP).Areas that were affected by sodicity increase have been spatially enlarged by 33.7 %, meanwhile those affected by sodicity decrease have been spatially reduced by 33.6 % of the total area. An area represented by 32.6 % of the total area has been unchanged

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

    Directory of Open Access Journals (Sweden)

    Marc Cattet

    2010-11-01

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

  3. Remote sensing and water resources

    CERN Document Server

    Champollion, N; Benveniste, J; Chen, J

    2016-01-01

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

  4. Remote sensing of natural resources

    CERN Document Server

    Wang, Guangxing

    2013-01-01

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

  5. Infrared (IR) remote sensing of gases

    OpenAIRE

    López Martínez, Fernando

    2008-01-01

    The IR Imaging and Remote Sensing Laboratory – LIR-UC3M of Universidad Carlos III, has developed Multi and Hyper spectral Infrared (IR) analysis techniques for gas remote sensing. Design of specific sensors for the determination of gases and their concentration are proposed. Almost all gases (CO2, CO, NO2, O3, HC o NH, …) related to industrial, environmental or military safety can be detected. Companies or centres with interest in the use of specific application sensors are required.

  6. Introduction to remote sensing

    CERN Document Server

    Campbell, James B

    2012-01-01

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

  7. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

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

  8. Nasa's Operation Icebridge and Remote Sensing Techniques in the K-12 Classroom as a STEM Integration Project

    Science.gov (United States)

    McCarthy, K.

    2017-12-01

    NASA's Operation IceBridge (OIB), the largest airborne survey of Earth's polar ice uses remote sensing methods to collect data on changing sea and land ice. PolarTREC teacher Kelly McCarthy joined the team during the 2016 Spring Arctic Campaign. This presentation explores ways in which k-12 students were engaged in the work being done by OIB through classroom learning experiences, digital communications, and independent research. Initially, digital communication including chats via NASA's Mission Tools Suite for Education (MTSE) platform was leveraged to engage students in the daily work of OIB. Two lessons were piloted with student groups during the 2016-2017 academic year both for students who actively engaged in communications with the team during the expedition and those who had no prior connections to the field. All of the data collected on OIB missions is stored for public use in a digital portal on the National Snow and Ice Data Center (NSIDC) website. In one lesson, 10th-12th grade students were guided through a tutorial to learn how to access data and begin to develop a story about Greenland's Jakobshavn Glacier using pre-selected data sets, Google's MyMaps app, and independent research methods. In the second lesson, 8th grade students were introduced to remote sensing, first through a discussion on vocabulary using productive talk moves and then via a demonstration using Vernier motion detectors and a graph matching simulation. Students worked in groups to develop procedures to map a hidden surface region (boxed assortment of miscellaneous objects) using a Vernier motion sensor to simulate sonar. Students translated data points collected from the motion sensor into a vertical profile of the simulated surface region. Both lessons allowed students a way to engage in two of the most important components of OIB. The ability to work with real data collected by the OIB team provided a unique context through which students gained skill and overcame challenges in

  9. Remote sensing by satellite - Technical and operational implications for international cooperation

    Science.gov (United States)

    Doyle, S. E.

    1976-01-01

    International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.

  10. Comparative analysis of property taxation policies within Greece and Cyprus evaluating the use of GIS, CAMA, and remote sensing techniques

    Science.gov (United States)

    Dimopoulos, Thomas; Labropoulos, Tassos; Hadjimitsis, Diofantos G.

    2014-08-01

    This paper aims to examine how CAMA, GIS and Remote Sensing are integrated to assist property taxation. Real property tax apart from its fiscal dimension is directly linked to geographic location. The value of the land and other immovable features such as buildings and structures is determined from specific parameters. All these immovable assets are visible and have specific geographic location & coordinates, materials, occupied area, land-use & utility, ownership & occupancy status and finally a specific value (ad valorem property taxation system) according to which the property tax is levied to taxpayers. Of high importance in the tax imposing procedure is that the use of CAMA, GIS and Remote Sensing tools is capable of providing effective and efficient collection of this property value determining data. Furthermore, these tools can track changes during a property's lifecycle such parcel subdivision into plots, demolition of a building and development of a new one or track a change in the planning zone. The integration of these systems also supports a full range of business processes on revenue mobilization ranging from billing to taxpayers objections management.

  11. Section summary: Remote sensing

    Science.gov (United States)

    Belinda Arunarwati Margono

    2013-01-01

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

  12. Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

    Science.gov (United States)

    Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

    2016-12-01

    Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

  13. Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

    Science.gov (United States)

    Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

    2015-03-15

    Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate

  14. Time-sensitive remote sensing

    CERN Document Server

    Lippitt, Christopher; Coulter, Lloyd

    2015-01-01

    This book documents the state of the art in the use of remote sensing to address time-sensitive information requirements. Specifically, it brings together a group of authors who are both researchers and practitioners, who work toward or are currently using remote sensing to address time-sensitive information requirements with the goal of advancing the effective use of remote sensing to supply time-sensitive information. The book addresses the theoretical implications of time-sensitivity on the remote sensing process, assessments or descriptions of methods for expediting the delivery and improving the quality of information derived from remote sensing, and describes and analyzes time-sensitive remote sensing applications, with an emphasis on lessons learned. This book is intended for remote sensing scientists, practitioners (e.g., emergency responders or administrators of emergency response agencies), and students, but will also be of use to those seeking to understand the potential of remote sensing to addres...

  15. Microwave remote sensing laboratory design

    Science.gov (United States)

    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.

  16. THE USE OF REMOTE SENSING TECHNIQUES IN ASSESSING THE DISTRIBUTION TRENDS OF COMMIPHORA MYRRHA IN WAJIR COUNTY, KENYA

    Directory of Open Access Journals (Sweden)

    A. Luvanda

    2014-01-01

    Full Text Available A study was conducted to establish the current trend in distribution of Commiphora myrrha in its natural stands in Wajir County. Data was collected through observation, interviews and questionnaires, photographs (remote sensing images using a Global Positioning System (GPS to to mark the plant’s hot spots and locate the tree stand coordinates. A supervised classification of Land Sat images acquired in 2003, 2009 and 2011 was undetaken. The results show that C. myrrha covers an average area of 61,620.23Ha. The area under C. myrrha had declined between 2009 and 2011 and this could be attributed to human and environmental factors. It is therefore recommended that sustainable management and conservation strategies be adopted to ensure imprived tree cover.

  17. Characterization of Solang valley watershed in western Himalaya for bio-resource conservation using remote sensing techniques.

    Science.gov (United States)

    Kumar, Amit; Chawla, Amit; Rajkumar, S

    2011-08-01

    The development activities in mountainous region though provide comfort to the human being and enhance the socioeconomic status of the people but create pressure on the bio-resources. In this paper, the current status of land use/landcover and the vegetation communities of the Solang valley watershed in Himachal Pradesh of Indian western Himalaya has been mapped and presented using remote sensing. This watershed area was dominated by alpine and sub-alpine pastures (30.34%) followed by scree slopes (22.34%) and forests (21.06%). Many tree, shrub, and herb species identified in the study area are among the prioritized species for conservation in the Indian Himalayan Region. Thus, scientific interventions and preparation of action plans based on ecological survey are required for conservation of the Solang valley watershed.

  18. High Resolution Stratigraphic Mapping in Complex Terrain: A Comparison of Traditional Remote Sensing Techniques with Unmanned Aerial Vehicle - Structure from Motion Photogrammetry

    Science.gov (United States)

    Nesbit, P. R.; Hugenholtz, C.; Durkin, P.; Hubbard, S. M.; Kucharczyk, M.; Barchyn, T.

    2016-12-01

    Remote sensing and digital mapping have started to revolutionize geologic mapping in recent years as a result of their realized potential to provide high resolution 3D models of outcrops to assist with interpretation, visualization, and obtaining accurate measurements of inaccessible areas. However, in stratigraphic mapping applications in complex terrain, it is difficult to acquire information with sufficient detail at a wide spatial coverage with conventional techniques. We demonstrate the potential of a UAV and Structure from Motion (SfM) photogrammetric approach for improving 3D stratigraphic mapping applications within a complex badland topography. Our case study is performed in Dinosaur Provincial Park (Alberta, Canada), mapping late Cretaceous fluvial meander belt deposits of the Dinosaur Park formation amidst a succession of steeply sloping hills and abundant drainages - creating a challenge for stratigraphic mapping. The UAV-SfM dataset (2 cm spatial resolution) is compared directly with a combined satellite and aerial LiDAR dataset (30 cm spatial resolution) to reveal advantages and limitations of each dataset before presenting a unique workflow that utilizes the dense point cloud from the UAV-SfM dataset for analysis. The UAV-SfM dense point cloud minimizes distortion, preserves 3D structure, and records an RGB attribute - adding potential value in future studies. The proposed UAV-SfM workflow allows for high spatial resolution remote sensing of stratigraphy in complex topographic environments. This extended capability can add value to field observations and has the potential to be integrated with subsurface petroleum models.

  19. Remote sensing observation used in offshore wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

    2008-01-01

    Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

  20. Cooling Effect of Rivers on Metropolitan Taipei Using Remote Sensing

    OpenAIRE

    Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen

    2014-01-01

    This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface tempera...

  1. Hydraulic Geometry, GIS and Remote Sensing, Techniques against Rainfall-Runoff Models for Estimating Flood Magnitude in Ephemeral Fluvial Systems

    Directory of Open Access Journals (Sweden)

    Rafael Garcia-Lorenzo

    2010-11-01

    Full Text Available This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat‑TM5 and Landsat-ETM+7. Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas.

  2. Use of remote sensing techniques for mitigation and relief action of the main disaster concerns in Syria

    Science.gov (United States)

    Dalati, M.

    The main disaster concern in Syria is the Earthquakes since that Northwest of Syria is part of one of the very active deformation belt on the Earth today This area and the western part of Syria are located along the great rift Afro-Arabian rift System Those areas are tectonically active and cause time to time a lot of seismically events This faulting zone system represent a unique structural feature in the Mediterranean Region The system formed initially as a result of the break up of the Arabian plate from the African plate since the mid-Cenozoic The other disaster concern in Syria is Landslides whom caused significant damaging in Syria during the last decades especially in the Northwestern and Southwestern regions Landslide disasters killed some people and destroyed many mud and cement houses coastal mountains and cut off some roads few years ago It is known that many of the earthquakes and landslides that ever happened on our planet are located in active faults zones So it is of most important to obtain detailed information on regional tectonic structures The main approach of active faults survey at present is to use geological and geophysical methods such as in-situ measuring drilling and analysis of gravity and magnetic fields However because of the magnitude of the work there are still many uncertainties that we cannot figure out by traditional approaches Remote sensing has been brought forward for many years and has applications in many hazard

  3. Characterization of sediments in the Clinch River, Tennessee, using remote sensing and multi-dimensional GIS techniques

    International Nuclear Information System (INIS)

    Levine, D.A.; Hargrove, W.W.; Hoffman, F.

    1995-01-01

    Remotely-sensed hydro-acoustic data were used as input to spatial extrapolation tools in a GIS to develop two- and three-dimensional models of sediment densities in the Clinch River arm of Watts Bar Reservoir, Tennessee. This work delineated sediment deposition zones to streamline sediment sampling and to provide a tool for estimating sediment volumes and extrapolating contaminant concentrations throughout the system. The Clinch River arm of Watts Bar Reservoir has been accumulating sediment-bound contaminants from three Department of Energy (DOE) facilities on the Oak Ridge Reservation, Tennessee. Public concern regarding human and ecological health resulted in Watts Bar Reservoir being placed on the National Priorities List for SUPERFUND. As a result, DOE initiated and is funding the Clinch River Environmental Restoration Program (CR-ERP) to perform a remedial investigation to determine the nature and extent of sediment contamination in the Watts Bar Reservoir and the Clinch River and to quantify any human or ecological health risks. The first step in characterizing Clinch River sediments was to determine the locations of deposition zones. It was also important to know the sediment type distribution within deposition zones because most sediment-bound contaminants are preferentially associated to fine particles. A dual-frequency hydro-acoustic survey was performed to determine: (1) depth to the sediment water interface, (2) depth of the sediment layer, and (3) sediment characteristics (density) with depth (approximately 0.5-foot intervals). An array of geophysical instruments was used to meet the objectives of this investigation

  4. Physics teaching by infrared remote sensing of vegetation

    Science.gov (United States)

    Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

    2018-05-01

    Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

  5. The use of remote sensing and GIS techniques with special emphasis on the use of Arc hydro data model in characterizing Atbara River watershed

    International Nuclear Information System (INIS)

    Adam, M. H. M.

    2010-11-01

    Remote sensing and GIS techniques were used successfully to establish hydrological information platform for Atbara sub-basin which drains from Ethiopia and Eretria to Sudan with entire area of about 224299 Km 2 . The study area have strategic importance, for many reasons; rich in minerals wealth, agricultural resources, and endowed with a substantial amount of water resources but the spatial and temporal distribution of water resources is imbalance. Remote Sensing and Digital elevation models (DEMs) are known to be very useful data sources for the automated delineation of flow paths, sub watersheds and flow networks for hydrologic modeling and watershed characterization, Landsat ETM + 30 m and Digital Elevation Models SRTM 90 m data used in this project, many digital image processing techniques used to enhanced images, interpretation and extracted information from satellite images by using ERDAS imagine, wile Arc GIS and arc hydro tools were used to processing and extract information from DEMs, stream network and catchment delineation and creation of geo database. It is the main output of this project, ready made GIS layers used to complete watershed characterizations view. The results of this research present in creation Arc hydro data model, and many thematic maps for Atbara sub-basin characteristics. The use of remote sensing in the study give efficient qualitative and quantitative detailed information about geomorphologic features drainage patterns, addition to general overview for land cover and land use. Moreover, the use of Digital Elevation Models in addition to the delineation of stream network and catchment give valuable information on the pale-geography and pale-climate of the study area. River network and watersheds delineations proved that El Gash River was once joining the Atbara River and it was a part of Nile Basin System. This might indicate that pale climatic conditions in the area were wet than the present. Geo database and Arc hydro data model

  6. A remote sensing evaluation for agronomic land use mapping in ...

    African Journals Online (AJOL)

    The principal objective of this study is to identify, demarcate and map agricultural land use categories of Tehran province on basis of remote sensing survey technique. In this research, Landsat ETM images of July 2006 were used to expose the use of remote sensing technique in order to produce current land use map of the ...

  7. Comparison Study to the Use of Geophysical Methods at Archaeological Sites Observed by Various Remote Sensing Techniques in the Czech Republic

    Directory of Open Access Journals (Sweden)

    Roman Křivánek

    2017-09-01

    Full Text Available A combination of geophysical methods could be very a useful and a practical way of verifying the origin and precise localisation of archaeological situations identified by different remote sensing techniques. The results of different methods (and scales of monitoring these fully non-destructive methods provide distinct data and often complement each other. The presented examples of combinations of these methods/techniques in this study (aerial survey, LIDAR-ALS and surface magnetometer or resistivity survey could provide information on some specifics and may also be limitations in surveying different archaeological terrains, types of archaeological situations and activities. The archaeological site in this contribution is considered to be a material of this study. In case of Neolithic ditch enclosure near Kolín were compared aerial prospection data, magnetometer survey and aerial photo-documentation of excavated site. In the case of hillforts near Levousy we compared LIDAR data with aerial photography and large-scale magnetometer survey. In the case of the medieval castle Liběhrad we compared LIDAR data with geoelectric resistivity measurement. In case of a burial mound cemetery we combined LIDAR data with magnetometer survey. In the case of the production area near Rynartice we combined LIDAR data with magnetometer and resistivity measurements and result of archaeological excavation. Fortunately for successful combination of geophysical and remote sensing results, their conditions and factors for efficient use in archaeology are not the same. On the other hand, the quality and state of many prehistoric, early medieval, medieval and also modern archaeological sites is rapidly changing over time and both groups of techniques represent important support for their comprehensive and precise documentation and protection.

  8. Remote sensing prospection

    Directory of Open Access Journals (Sweden)

    Jeremy Bennett

    2012-12-01

    Full Text Available During the Capo Mannu Project 2011 fieldwork season, three separate sites were selected for remote sensing prospection: Su Pallosu (Beachfront and Upper Platform, Sa Rocca Tunda (Beachfront and Serra Is Araus. These areas have in common the presence of buried structures and/or ceramic deposits, and represent the favourite candidates for future excavations in the area. The level of success attained across the sites was not very high, which awkward topography and/or unusual geological circumstances hindering the usually reliant magnetometer survey method.

  9. Applications of Remote Sensing

    Science.gov (United States)

    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

  10. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

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

  11. Oil spill remote sensing sensors and aircraft

    International Nuclear Information System (INIS)

    Fingas, M.; Fruhwirth, M.; Gamble, L.

    1992-01-01

    The most common form of remote sensing as applied to oil spills is aerial remote sensing. The technology of aerial remote sensing, mainly from aircraft, is reviewed along with aircraft-mounted remote sensors and aircraft modifications. The characteristics, advantages, and limitations of optical techniques, infrared and ultraviolet sensors, fluorosensors, microwave and radar sensors, and slick thickness sensors are discussed. Special attention is paid to remote sensing of oil under difficult circumstances, such as oil in water or oil on ice. An infrared camera is the first sensor recommended for oil spill work, as it is the cheapest and most applicable device, and is the only type of equipment that can be bought off-the-shelf. The second sensor recommended is an ultraviolet and visible-spectrum device. The laser fluorosensor offers the only potential for discriminating between oiled and un-oiled weeds or shoreline, and for positively identifying oil pollution on ice and in a variety of other situations. However, such an instrument is large and expensive. Radar, although low in priority for purchase, offers the only potential for large-area searches and foul-weather remote sensing. Most other sensors are experimental or do not offer good potential for oil detection or mapping. 48 refs., 8 tabs

  12. Remote sensing in uranium exploration. Basic guidance

    International Nuclear Information System (INIS)

    1981-01-01

    The purpose of this publication is to provide the reader with a basis for making an intelligent approach to the use of remote sensing in uranium exploration. It includes: A description of the various techniques; specific applications in view of exploration strategy and selection of appropriate techniques, and some examples of applications; availability and costs; a bibliography

  13. Remote sensing from UAVs for hydrological monitoring

    DEFF Research Database (Denmark)

    Bandini, Filippo; Garcia, Monica; Bauer-Gottwein, Peter

    compared to other technologies: compared to field based techniques, remote sensing with UAVs is a non-destructive technique, less time consuming, ensures a reduced time between acquisition and interpretation of data and gives the possibility to access remote and unsafe areas. Compared to full...

  14. Hyperspectral remote sensing techniques applied to the noninvasive investigation of mural paintings: a feasibility study carried out on a wall painting by Beato Angelico in Florence

    Science.gov (United States)

    Cucci, Costanza; Picollo, Marcello; Chiarantini, Leandro; Sereni, Barbara

    2015-06-01

    Nowadays hyperspectral imaging is a well-established methodology for the non-invasive diagnostics of polychrome surfaces, and is increasingly utilized in museums and conservation laboratories for documentation purposes and in support of restoration procedures. However, so far the applications of hyperspectral imaging have been mainly limited to easel paintings or paper-based artifacts. Indeed, specifically designed hyperspectral imagers, are usually used for applications in museum context. These devices work at short-distances from the targets and cover limited size surfaces. Instead, almost still unexplored remain the applications of hyperspectral imaging to the investigations of frescoes and large size mural paintings. For this type of artworks a remote sensing approach, based on sensors capable of acquiring hyperspectral data from distances of the order of tens of meters, is needed. This paper illustrates an application of hyperspectral remote sensing to an important wall-painting by Beato Angelico, located in the San Marco Museum in Florence. Measurements were carried out using a re-adapted version of the Galileo Avionica Multisensor Hyperspectral System (SIM-GA), an avionic hyperspectral imager originally designed for applications from mobile platforms. This system operates in the 400-2500 nm range with over 700 channels, thus guaranteeing acquisition of high resolution hyperspectral data exploitable for materials identification and mapping. In the present application, the SIM-GA device was mounted on a static scanning platform for ground-based applications. The preliminary results obtained on the Angelico's wall-painting are discussed, with highlights on the main technical issues addressed to optimize the SIM-GA system for new applications on cultural assets.

  15. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus......-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  16. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

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

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

  17. Geological remote sensing

    Science.gov (United States)

    Bishop, Charlotte; Rivard, Benoit; de Souza Filho, Carlos; van der Meer, Freek

    2018-02-01

    Geology is defined as the 'study of the planet Earth - the materials of which it is made, the processes that act on these materials, the products formed, and the history of the planet and its life forms since its origin' (Bates and Jackson, 1976). Remote sensing has seen a number of variable definitions such as those by Sabins and Lillesand and Kiefer in their respective textbooks (Sabins, 1996; Lillesand and Kiefer, 2000). Floyd Sabins (Sabins, 1996) defined it as 'the science of acquiring, processing and interpreting images that record the interaction between electromagnetic energy and matter' while Lillesand and Kiefer (Lillesand and Kiefer, 2000) defined it as 'the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation'. Thus Geological Remote Sensing can be considered the study of, not just Earth given the breadth of work undertaken in planetary science, geological features and surfaces and their interaction with the electromagnetic spectrum using technology that is not in direct contact with the features of interest.

  18. A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery.

    Science.gov (United States)

    Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

    2017-09-15

    Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.

  19. A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery

    Science.gov (United States)

    Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

    2017-01-01

    Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features. PMID:28914787

  20. High-throughput phenotyping of large wheat breeding nurseries using unmanned aerial system, remote sensing and GIS techniques

    Science.gov (United States)

    Haghighattalab, Atena

    Wheat breeders are in a race for genetic gain to secure the future nutritional needs of a growing population. Multiple barriers exist in the acceleration of crop improvement. Emerging technologies are reducing these obstacles. Advances in genotyping technologies have significantly decreased the cost of characterizing the genetic make-up of candidate breeding lines. However, this is just part of the equation. Field-based phenotyping informs a breeder's decision as to which lines move forward in the breeding cycle. This has long been the most expensive and time-consuming, though most critical, aspect of breeding. The grand challenge remains in connecting genetic variants to observed phenotypes followed by predicting phenotypes based on the genetic composition of lines or cultivars. In this context, the current study was undertaken to investigate the utility of UAS in assessment field trials in wheat breeding programs. The major objective was to integrate remotely sensed data with geospatial analysis for high throughput phenotyping of large wheat breeding nurseries. The initial step was to develop and validate a semi-automated high-throughput phenotyping pipeline using a low-cost UAS and NIR camera, image processing, and radiometric calibration to build orthomosaic imagery and 3D models. The relationship between plot-level data (vegetation indices and height) extracted from UAS imagery and manual measurements were examined and found to have a high correlation. Data derived from UAS imagery performed as well as manual measurements while exponentially increasing the amount of data available. The high-resolution, high-temporal HTP data extracted from this pipeline offered the opportunity to develop a within season grain yield prediction model. Due to the variety in genotypes and environmental conditions, breeding trials are inherently spatial in nature and vary non-randomly across the field. This makes geographically weighted regression models a good choice as a

  1. Structural modeling of the Zagros fold-and-thrust belt (Iraq) combining field work and remote sensing techniques

    Science.gov (United States)

    Reif, D.; Grasemann, B.; Faber, R.; Lockhart, D.

    2009-04-01

    contacts) from digital elevation models. The minimum vegetation cover in the investigated area allows an accurate picking of geological planes from the digital elevation model, which has been draped with LANDSAT and ASTER satellite images in order to enhance the contrast of lithological contacts. Geological planes of finite extent are interpolated in the Fault Trace module by virtual planes, which can be translated and rotated in any spatial direction. Comparison of measured data from the field with interpolated spatial orientations from the remote sensing data demonstrate that the calculated dip and strike values can be reproduced within the measurements error of a geological field compass.

  2. Application of remote sensing to agricultural field trials

    NARCIS (Netherlands)

    Clevers, J.G.P.W.

    1986-01-01

    Remote sensing techniques enable quantitative information about a field trial to be obtained instantaneously and non-destructively. The aim of this study was to identify a method that can reduce inaccuracies in field trial analysis, and to identify how remote sensing can support and/or

  3. Mapping of Landscape Cover Using Remote Sensing and GIS in ...

    African Journals Online (AJOL)

    Tadesse

    present study, Remote Sensing (RS) and Geographical Information System (GIS) techniques were used. Remotely sensed .... growing stock in Tahno range of Dehradun Forest Division. Okhandiara (2008) .... areas on an image by identifying 'training' sites of known targets and then extrapolating those spectral signatures to ...

  4. Remote sensing applications for monitoring rangeland vegetation ...

    African Journals Online (AJOL)

    Remote sensing techniques hold considerable promise for the inventory and monitoring of natural resources on rangelands. A significant lack of information concerning basic spectral characteristics of range vegetation and soils has resulted in a lack of rangeland applications. The parameters of interest for range condition ...

  5. Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

    Science.gov (United States)

    Jagge, Amy

    2016-01-01

    With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data

  6. A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications

    Directory of Open Access Journals (Sweden)

    A. Tretner

    2010-07-01

    Full Text Available Carbon dioxide (CO2 is the most important anthropogenic greenhouse gas (GHG causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times – primarily due to burning of fossil fuels – and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing satellite instruments such as SCIAMACHY/ENVISAT and TANSO/GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also constrain anthropogenic CO2 emissions. Here we present a promising satellite remote sensing concept based on spectroscopic measurements of reflected solar radiation and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the atmospheric CO2 column distribution at a spatial resolution of 2×2 km2 with a precision of 0.5% (2 ppm or better. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with a swath width of 500 km, each power plant (PP is overflown every 6 days or more frequent. Based on the MODIS cloud mask data product we conservatively estimate that typically 20 sufficiently cloud free overpasses per PP can be achieved every year. We found that for typical wind speeds in the range of 2–6 m/s the statistical uncertainty of the retrieved PP CO2 emission due to instrument noise is in the range 1.6–4.8 MtCO2/yr for single overpasses. This corresponds to 12–36% of the emission of a mid-size PP (13 MtCO2/yr. We have also determined the sensitivity to parameters which may result in systematic errors such as

  7. A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications

    Science.gov (United States)

    Bovensmann, H.; Buchwitz, M.; Burrows, J. P.; Reuter, M.; Krings, T.; Gerilowski, K.; Schneising, O.; Heymann, J.; Tretner, A.; Erzinger, J.

    2010-07-01

    Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas (GHG) causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times - primarily due to burning of fossil fuels - and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing satellite instruments such as SCIAMACHY/ENVISAT and TANSO/GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also constrain anthropogenic CO2 emissions. Here we present a promising satellite remote sensing concept based on spectroscopic measurements of reflected solar radiation and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the atmospheric CO2 column distribution at a spatial resolution of 2×2 km2 with a precision of 0.5% (2 ppm) or better. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with a swath width of 500 km, each power plant (PP) is overflown every 6 days or more frequent. Based on the MODIS cloud mask data product we conservatively estimate that typically 20 sufficiently cloud free overpasses per PP can be achieved every year. We found that for typical wind speeds in the range of 2-6 m/s the statistical uncertainty of the retrieved PP CO2 emission due to instrument noise is in the range 1.6-4.8 MtCO2/yr for single overpasses. This corresponds to 12-36% of the emission of a mid-size PP (13 MtCO2/yr). We have also determined the sensitivity to parameters which may result in systematic errors such as atmospheric transport and

  8. Dynamics Change of Honghu Lake's Water Surface Area and Its Driving Force Analysis Based on Remote Sensing Technique and TOPMODEL model

    International Nuclear Information System (INIS)

    Wen, X; Cao, B; Shen, S; Hu, D; Tang, X

    2014-01-01

    Honghu Lake is the largest freshwater lake in the Hubei Province of China. This paper introduces a remote sensing approach to monitor the lake's water surface area dynamics over the last 40 years by using multi-temporal remote sensing imagery including Landsat and HJ-1. Meanwhile, the daily precipitation and evaporation data provided by Honghu meteorological station since 1970s were also collected and used to analyze the influence of climate change factors. The typical situation for precipitation was selected as an input into the TOPMODEL model to simulate the hydrological process in Honghu Lake. The simulation result with the water surface area extracted from remote sensing imagery was analyzed. This experiment shows the precipitation and timing of precipitation effects changes in the lake with remote sensing data and it showed the potential of using TOPMODEL model to analyze the combined hydrological process in Honghu Lake

  9. Comparison of geostatistical interpolation and remote sensing techniques for estimating long-term exposure to ambient PM2.5 concentrations across the continental United States.

    Science.gov (United States)

    Lee, Seung-Jae; Serre, Marc L; van Donkelaar, Aaron; Martin, Randall V; Burnett, Richard T; Jerrett, Michael

    2012-12-01

    A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data. We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation. We developed a space-time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals. The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates. We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.

  10. Archeological methodology and remote sensing.

    Science.gov (United States)

    Gumerman, G J; Lyons, T R

    1971-04-09

    We have shown that the different spectral surveying techniques and the resultant imagery vary in their applicability to archeological prediction and exploration, but their applications are far broader than we have indicated. Their full potential, to a considerable extent, still remains unexplored. Table 1 is a chart of the more common sensor systems useful to archeological investigators. Several kinds of photography, thermal infrared imagery, and radar imagery are listed. Checks in various categories of direct and indirect utility in archeological research indicate that the different systems do provide varying degrees of input for studies in these areas. Photography and multispectral photography have the broadest applications in this field. Standard black-and-white aerial photography generally serves the purposes of archeological exploration and site analysis better than infrared scanner imagery, radar, or color photography. However, the real value of remotesensing experimentation lies in the utilization of different instruments and in the comparison and correlation of their data output. It can be stated without doubt that there is no one all-purpose remotesensing device on which the archeologist can rely that will reveal all evidence of human occupations. Remote-sensing data will not replace the traditional ground-based site survey, but, used judiciously, data gathered from aerial reconnaissance can reveal many cultural features unsuspected from the ground. The spectral properties of sites distinguishable by various types of remote sensors may perhaps be one of their most characteristic features, and yet the meaning of the differential discrimnination of features has not been determined for the most part, since such spectral properties are poorly understood at this date. The difficulty in isolating the causes of acceptable definition in certain portion of the spectrum and the lack of acceptable definition in others suggests that the evaluation of remote-sensing

  11. Mapping of groundwater prospective zones integrating remote sensing, geographic information systems and geophysical techniques in El-Qaà Plain area, Egypt

    Science.gov (United States)

    Abuzied, Sara M.; Alrefaee, Hamed A.

    2017-11-01

    The geospatial mapping of groundwater prospective zones is essential to support the needs of local inhabitants and agricultural activities in arid regions such as El-Qaà area, Sinai Peninsula, Egypt. The study aims to locate new wells that can serve to cope with water scarcity. The integration of remote sensing, geographic information systems (GIS) and geophysical techniques is a breakthrough for groundwater prospecting. Based on these techniques, several factors contributing to groundwater potential in El-Qaà Plain were determined. Geophysical data were supported by information derived from a digital elevation model, and from geologic, geomorphologic and hydrologic data, to reveal the promising sites. All the spatial data that represent the contributing factors were integrated and analyzed in a GIS framework to develop a groundwater prospective model. An appropriate weightage was specified to each factor based on its relative contribution towards groundwater potential, and the resulting map delineates the study area into five classes, from very poor to very good potential. The very good potential zones are located in the Quaternary deposits, with flat to gentle topography, dense lineaments and structurally controlled drainage channels. The groundwater potential map was tested against the distribution of groundwater wells and cultivated land. The integrated methodology provides a powerful tool to design a suitable groundwater management plan in arid regions.

  12. Developing a western Siberia reference site for tropospheric water vapour isotopologue observations obtained by different techniques (in situ and remote sensing

    Directory of Open Access Journals (Sweden)

    K. Gribanov

    2014-06-01

    water cycle, affected by changes in air mass origin, non-convective and convective processes and continental recycling. Novel remote sensing and in situ measuring techniques have recently offered opportunities for monitoring atmospheric water vapour isotopic composition. Recently developed infrared laser spectrometers allow for continuous in situ measurements of surface water vapour δDv and δ18Ov. So far, very few intercomparisons of measurements conducted using different techniques have been achieved at a given location, due to difficulties intrinsic to the comparison of integrated with local measurements. Nudged simulations conducted with high-resolution isotopically enabled general circulation models (GCMs provide a consistent framework for comparison with the different types of observations. Here, we compare simulations conducted with the ECHAM5-wiso model with two types of water vapour isotopic data obtained during summer 2012 at the forest site of Kourovka, western Siberia: hourly ground-based FTIR total atmospheric columnar δDv amounts, and in situ hourly Picarro δDv measurements. There is an excellent correlation between observed and predicted δDv at surface while the comparison between water column values derived from the model compares well with FTIR estimates.

  13. Signal processing for remote sensing

    CERN Document Server

    Chen, CH

    2007-01-01

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

  14. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

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

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

  15. Identification of Mangrove Areas by Remote Sensing: The ROC Curve Technique Applied to the Northwestern Mexico Coastal Zone Using Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Salvador Sánchez-Carrillo

    2011-07-01

    Full Text Available In remote sensing, traditional methodologies for image classification consider the spectral values of a pixel in different image bands. More recently, classification methods have used neighboring pixels to provide more information. In the present study, we used these more advanced techniques to discriminate between mangrove and non‑mangrove regions in the Gulf of California of northwestern Mexico. A maximum likelihood algorithm was used to obtain a spectral distance map of the vegetation signature characteristic of mangrove areas. Receiver operating characteristic (ROC curve analysis was applied to this map to improve classification. Two classification thresholds were set to determine mangrove and non-mangrove areas, and two performance statistics (sensitivity and specificity were calculated to express the uncertainty (errors of omission and commission associated with the two maps. The surface area of the mangrove category obtained by maximum likelihood classification was slightly higher than that obtained from the land cover map generated by the ROC curve, but with the difference of these areas to have a high level of accuracy in the prediction of the model. This suggests a considerable degree of uncertainty in the spectral signatures of pixels that distinguish mangrove forest from other land cover categories.

  16. Using Remote Sensing and GIS Techniques to Detect Changes to the Prince Alfred Hamlet Conservation Area in the Western Cape, South Africa

    Science.gov (United States)

    Duncan, P.; Lewarne, M.

    2016-06-01

    Understanding and identifying the spatial-temporal changes in the natural environment is crucial for monitoring and evaluating conservation efforts, as well as understanding the impact of human activities on natural resources, informing responsible land management, and promoting better decision-making. Conservation areas are often under pressure from expanding farming and related industry, invasive alien vegetation, and an ever-increasing human settlement footprint. This study focuses on detecting changes to the Prince Alfred Hamlet commonage, near Ceres in the Cape Floral Kingdom. It was chosen for its high conservation value and significance as a critical water source area. The study area includes a fast-growing human settlement footprint in a highly productive farming landscape. There are conflicting development needs as well as risks to agricultural production, and both of these threaten the integrity of the ecosystems which supply underlying services to both demands on the land. Using a multi-disciplinary approach and high-resolution satellite imagery, land use and land cover changes can be detected and classified, and the results used to support the conservation of biodiversity and wildlife, and protect our natural resources. The aim of this research is to study the efficacy of using remote sensing and GIS techniques to detect changes to critical conservation areas where disturbances can be understood, and therefore better managed and mitigated before these areas are degraded beyond repair.

  17. Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique

    Science.gov (United States)

    Pinto, Domingos; Shrestha, Sangam; Babel, Mukand S.; Ninsawat, Sarawut

    2017-03-01

    Groundwater plays an important role for socio-economic development of Comoro watershed in Timor Leste. Despite the significance of groundwater for sustainable development, it has not always been properly managed in the watershed. Therefore, this study seeks to identify groundwater potential zones in the Comoro watershed, using geographical information systems and remote sensing and analytic hierarchy process technique. The groundwater potential zones thus obtained were divided into five classes and validated with the recorded bore well yield data. It was found that the alluvial plain in the northwest along the Comoro River has very high groundwater potential zone which covers about 5.4 % (13.5 km2) area of the watershed. The high groundwater potential zone was found in the eastern part and along the foothills and covers about 4.8 % (12 km2) of the area; moderate zone covers about 2.0 % (5 km2) of the area and found in the higher elevation of the alluvial plain. The poor and very poor groundwater potential zone covers about 87.8 % (219.5 km2) of the watershed. The hilly terrain located in the southern and central parts of the study area has a poor groundwater potential zone due to higher degree of slope and low permeability of conglomerate soil type. The demarcation of groundwater potential zones in the Comoro watershed will be helpful for future planning, development and management of the groundwater resources.

  18. USING REMOTE SENSING AND GIS TECHNIQUES TO DETECT CHANGES TO THE PRINCE ALFRED HAMLET CONSERVATION AREA IN THE WESTERN CAPE, SOUTH AFRICA

    Directory of Open Access Journals (Sweden)

    P. Duncan

    2016-06-01

    Full Text Available Understanding and identifying the spatial-temporal changes in the natural environment is crucial for monitoring and evaluating conservation efforts, as well as understanding the impact of human activities on natural resources, informing responsible land management, and promoting better decision-making. Conservation areas are often under pressure from expanding farming and related industry, invasive alien vegetation, and an ever-increasing human settlement footprint. This study focuses on detecting changes to the Prince Alfred Hamlet commonage, near Ceres in the Cape Floral Kingdom. It was chosen for its high conservation value and significance as a critical water source area. The study area includes a fast-growing human settlement footprint in a highly productive farming landscape. There are conflicting development needs as well as risks to agricultural production, and both of these threaten the integrity of the ecosystems which supply underlying services to both demands on the land. Using a multi-disciplinary approach and high-resolution satellite imagery, land use and land cover changes can be detected and classified, and the results used to support the conservation of biodiversity and wildlife, and protect our natural resources. The aim of this research is to study the efficacy of using remote sensing and GIS techniques to detect changes to critical conservation areas where disturbances can be understood, and therefore better managed and mitigated before these areas are degraded beyond repair.

  19. Using remote sensing and gis techniques for detecting land cover changes of mangrove habitats in Goa, India

    Digital Repository Service at National Institute of Oceanography (India)

    Nagi, H.M.; Rodrigues, R.S.; ManiMurali, R.; Jagtap, T.G.

    changes in those regions. This is more easily obtainable using satellite imageries and thematic mapper techniques. However, ground truth data collection, literature reviews, visual map interpretation, and collateral and ancillary data are most...

  20. Remote sensing technology: symposium proceedings

    International Nuclear Information System (INIS)

    1985-01-01

    Papers were presented in four subject areas: applications of remote sensing; data analysis, digital and analog; acquisition systems; and general. Abstracts of individual items from the conference were prepared separately for the data base

  1. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available For this research, the researchers examine various existing image classification algorithms with the aim of demonstrating how these algorithms can be applied to remote sensing images. These algorithms are broadly divided into supervised...

  2. Remote Sensing Digital Image Analysis

    Science.gov (United States)

    Richards, John A.; Jia, Xiuping

    Remote Sensing Digital Image Analysis provides the non-specialist with an introduction to quantitative evaluation of satellite and aircraft derived remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations. Problems conclude each chapter. This fourth edition has been developed to reflect the changes that have occurred in this area over the past several years.

  3. Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

    Science.gov (United States)

    D'Agnese, F. A.; Faunt, C.C.; Turner, A.K.; ,

    1996-01-01

    The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter

  4. Inter-comparison of remote sensing-based shoreline mapping techniques at different coastal stretches of India.

    Science.gov (United States)

    Sunder, Swathy; Ramsankaran, Raaj; Ramakrishnan, Balaji

    2017-06-01

    Many techniques are available for detection of shorelines from multispectral satellite imagery, but the choice of a certain technique for a particular study area can be tough. Hence, for the first time in literature, an inter-comparison of the most widely used shoreline mapping techniques such as Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Improved Band Ratio (IBR) Method, and Automatic Water Extraction Index (AWEI) has been done along four different coastal stretches of India using multitemporal Landsat data. The obtained results have been validated with the high-resolution images of Cartosat-2 (panchromatic) and multispectral images from Google Earth. Performance of the above indices has been analyzed based on the statistics, such as overall accuracy, kappa coefficient, user's accuracy, producer's accuracy, and the average deviation from the reference line. It is observed that the performance of NDWI and IBR techniques are dependent on the physical characteristics of the sites, and therefore, it varies from one site to another. Results indicate that unlike these two indices, the AWEI algorithm performs consistently well followed by MNDWI irrespective of the land cover types.

  5. A global map of rainfed cropland areas at the end of last millennium using remote sensing and geospatial techniques

    Science.gov (United States)

    Biradar, C. M.; Thenkabail, P. S.; Turral, H.; Noojipady, P.; Li, Y. J.; Velpuri, M.; Dheeravath, V.; Vithanage, J.; Schull, M.; Cai, X. L.; Murali, K. G.; Rishiraj, D.

    2006-10-01

    Rainfed agriculture plays a critical role in most part of the tropics and subtropics of the world. Eighty percent of the agricultural land worldwide is under rainfed agriculture; and significant proportion of rural economy still depends on rainfed agriculture with characteristically low yield levels. In this context the International Water Management Institute (IWMI) produced the first satellite sensor based Global map of rainfed cropland areas at 10Km resolution (GMRCA10Km). The study used a mega-file of 159 global data layers involving the AVHRR and SPOT time-series, GTOPO30 DEM, mean monthly rainfall, and forest cover. A suite of innovative techniques were developed that begins with the image segmentation, quantitative spectral matching techniques (SMTs) and spectral correlation similarity (SCS R2). The SCS was found to be the most useful technique in grouping identical classes. Mixed classes were resolved using a decision trees, time series plots, and principal component analysis algorithms. A wide array of groundtruth data, and high-resolution images were used to identify and label classes. The outcome was the GMRCA10Km estimated to be 1.75 billion hectares for the main cropping period. The sub-pixel areas (SPAs) of GMRCA10Km provide more realistic estimates of the actual area cultivated unlike the full pixel areas (FPAs) often calculated from the raster datasets. Three distinct GMRCA10Km maps have been produced: viz., Aggregated 7-class, Dis-aggregated 18-class and Generic 255-class. The aggregated classes will suffice for broad range of users at global level. The GMRCA10Km product line consists of maps, images, area calculations, snap-shots, class characteristics, and animations.

  6. Optical property dimensionality reduction techniques for accelerated radiative transfer performance: Application to remote sensing total ozone retrievals

    Science.gov (United States)

    Efremenko, Dmitry; Doicu, Adrian; Loyola, Diego; Trautmann, Thomas

    2014-01-01

    In this paper, we introduce several dimensionality reduction techniques for optical parameters. We consider the principal component analysis, the local linear embedding methods (locality pursuit embedding, locality preserving projection, locally embedded analysis), and discrete orthogonal transforms (cosine, Legendre, wavelet). The principle component analysis has already been shown to be an effective and accurate method of enhancing radiative transfer performance for simulations in an absorbing and a scattering atmosphere. By linearizing the corresponding radiative transfer model, we analyze the applicability of the proposed methods to a practical problem of total ozone column retrieval from UV-backscatter measurements.

  7. Remote sensing application for delineating coastal vegetation - A case study

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.; Wagle, B.G.

    Remote sensing data has been used for mapping coastal vegetation along the Goa Coast, India. The study envisages the use of digital image processing techniques for delineating geomorphic features and associated vegetation, including mangrove, along...

  8. A framework for developing remote sensing applications

    International Nuclear Information System (INIS)

    Ahmad, T.; Hayat, M.F.; Afzal, M.; Asif, H.M.S.; Asif, K.H.

    2014-01-01

    Remote Sensing Application (RSA) is important as one of the critical enabler of e-systems such as e- governments, e-commerce, and e-sciences. In this study, we argued that owning to the specialized needs of RSA such as volatility and interactive nature, a customized Software Engineering (SE) approach should be adapted for their development. Based on this argument we have also identified the shortcomings of the conventional SE approaches and the classical waterfall software development life cycle model. In this study, we have proposed a modification to the classical waterfall software development life cycle model for proposing a customized software development Framework for RSAs. We have identified four (4) different types of changes that can occur to an already developed RS application. The proposed framework was capable to incorporate all four types of changes. Remote Sensing, software engineering, functional requirements, types of changes. (author)

  9. A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

    Science.gov (United States)

    Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

    2010-01-01

    Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling

  10. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    1997-01-01

    This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, s

  11. Searches over graphs representing geospatial-temporal remote sensing data

    Energy Technology Data Exchange (ETDEWEB)

    Brost, Randolph; Perkins, David Nikolaus

    2018-03-06

    Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

  12. Linear- and Repetitive-Feature Detection Within Remotely Sensed Imagery

    Science.gov (United States)

    2017-04-01

    Gonzalez, R. C, and R. E. Woods . 2002. Digital Image Processing . 2nd ed. Upper Saddle River, NJ: Prentice Hall. Grady, L. 2006. Random Walks for Image ...remotely sensed images that are in panchromatic or true-color formats. Image - processing techniques, in- cluding Hough transforms, machine learning, and...in the GIS analysis. This paper introduces image - processing techniques and tools that may help detect some of these features in remotely sensed

  13. Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

    Science.gov (United States)

    2017-04-01

    Gonzalez, R. C, and R. E. Woods . 2002. Digital Image Processing . 2nd ed. Upper Saddle River, NJ: Prentice Hall. Grady, L. 2006. Random Walks for Image ...remotely sensed images that are in panchromatic or true-color formats. Image - processing techniques, in- cluding Hough transforms, machine learning, and...in the GIS analysis. This paper introduces image - processing techniques and tools that may help detect some of these features in remotely sensed

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

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

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

  15. Accuracy assessment of water vapour measurements from in situ and remote sensing techniques during the DEMEVAP 2011 campaign at OHP

    Directory of Open Access Journals (Sweden)

    O. Bock

    2013-10-01

    Full Text Available The Development of Methodologies for Water Vapour Measurement (DEMEVAP project aims at assessing and improving humidity sounding techniques and establishing a reference system based on the combination of Raman lidars, ground-based sensors and GPS. Such a system may be used for climate monitoring, radiosonde bias detection and correction, satellite measurement calibration/validation, and mm-level geodetic positioning with Global Navigation Satellite Systems. A field experiment was conducted in September–October 2011 at Observatoire de Haute-Provence (OHP. Two Raman lidars (IGN mobile lidar and OHP NDACC lidar, a stellar spectrometer (SOPHIE, a differential absorption spectrometer (SAOZ, a sun photometer (AERONET, 5 GPS receivers and 4 types of radiosondes (Vaisala RS92, MODEM M2K2-DC and M10, and Meteolabor Snow White participated in the campaign. A total of 26 balloons with multiple radiosondes were flown during 16 clear nights. This paper presents preliminary findings from the analysis of all these data sets. Several classical Raman lidar calibration methods are evaluated which use either Vaisala RS92 measurements, point capacitive humidity measurements, or GPS integrated water vapour (IWV measurements. A novel method proposed by Bosser et al. (2010 is also tested. It consists in calibrating the lidar measurements during the GPS data processing. The methods achieve a repeatability of 4–5%. Changes in the calibration factor of IGN Raman lidar are evidenced which are attributed to frequent optical re-alignments. When modelling and correcting the changes as a linear function of time, the precision of the calibration factors improves to 2–3%. However, the variations in the calibration factor, and hence the absolute accuracy, between methods and types of reference data remain at the level of 7%. The intercomparison of radiosonde measurements shows good agreement between RS92 and Snow White measurements up to 12 km. An overall dry bias is found

  16. Boundary Layer Remote Sensing with Combined Active and Passive Techniques: GPS Radio Occultation and High-Resolution Stereo Imaging (WindCam) Small Satellite Concept

    Science.gov (United States)

    Mannucci, A.J.; Wu, D.L.; Teixeira, J.; Ao, C.O.; Xie, F.; Diner, D.J.; Wood, R.; Turk, Joe

    2012-01-01

    Objective: significant progress in understanding low-cloud boundary layer processes. This is the Single largest uncertainty in climate projections. Radio occultation has unique features suited to boundary layer remote sensing (1) Cloud penetrating (2) Very high vertical resolution (approximately 50m-100m) (3) Sensitivity to thermodynamic variables

  17. Comparison study to the use of geophysical methods at archaeological sites observed by various remote sensing techniques in the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Křivánek, Roman

    2017-01-01

    Roč. 7, č. 3 (2017), č. článku 81. ISSN 2076-3263 Grant - others:AV ČR(CZ) R300021421 Institutional support: RVO:67985912 Keywords : archaeological prospection * remote sensing * non-destructive archaeology * geophysical survey Subject RIV: AC - Archeology, Anthropology, Ethnology OBOR OECD: Archaeology http://www.mdpi.com/2076-3263/7/3/81/pdf

  18. Techniques of remote sensing and GIS as tools for visualizing impact of climate change-induced flood in the southern African region.

    Science.gov (United States)

    This study employs remote sensing and Geographical Information Systems (GIS) data to visualize the impact of climate change caused by flooding in the Southern African region in order to assist decision makers’ plans for future occurrences. In pursuit of this objective, this study uses Digital Elevat...

  19. A comparison of two above-ground biomass estimation techniques integrating satellite-based remotely sensed data and ground data for tropical and semiarid forests in Puerto Rico

    Science.gov (United States)

    Iiames, J. S.; Riegel, J.; Lunetta, R.

    2013-12-01

    Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA) program. The U.S. Environmental Protection Agency (EPA) estimated above-ground forest biomass implementing methodology first posited by the Woods Hole Research Center developed for conterminous United States (National Biomass and Carbon Dataset [NBCD2000]). For EPA's effort, spatial predictor layers for above-ground biomass estimation included derived products from the U.S. Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) (landcover and canopy density), the USGS Gap Analysis Program (forest type classification), the USGS National Elevation Dataset, and the NASA Shuttle Radar Topography Mission (tree heights). In contrast, the U.S. Forest Service (USFS) biomass product integrated FIA ground-based data with a suite of geospatial predictor variables including: (1) the Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; (2) NLCD land cover proportions; (3) topographic variables; (4) monthly and annual climate parameters; and (5) other ancillary variables. Correlations between both data sets were made at variable watershed scales to test level of agreement. Notice: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S EPA funded and conducted the research described in this paper. Although this work was reviewed by the EPA and has been approved for publication, it may not necessarily reflect official Agency policy. Mention of any trade names or commercial products does not constitute endorsement or recommendation for use.

  20. Review of Remote Sensing Needs and Applications in Africa

    Science.gov (United States)

    Brown, Molly E.

    2007-01-01

    Remote sensing data has had an important role in identifying and responding to inter-annual variations in the African environment during the past three decades. As a largely agricultural region with diverse but generally limited government capacity to acquire and distribute ground observations of rainfall, temperature and other parameters, remote sensing is sometimes the only reliable measure of crop growing conditions in Africa. Thus, developing and maintaining the technical and scientific capacity to analyze and utilize satellite remote sensing data in Africa is critical to augmenting the continent's local weather/climate observation networks as well as its agricultural and natural resource development and management. The report Review of Remote Sensing Needs and Applications in Africa' has as its central goal to recommend to the US Agency for International Development an appropriate approach to support sustainable remote sensing applications at African regional remote sensing centers. The report focuses on "RS applications" to refer to the acquisition, maintenance and archiving, dissemination, distribution, analysis, and interpretation of remote sensing data, as well as the integration of interpreted data with other spatial data products. The report focuses on three primary remote sensing centers: (1) The AGRHYMET Regional Center in Niamey, Niger, created in 1974, is a specialized institute of the Permanent Interstate Committee for Drought Control in the Sahel (CILSS), with particular specialization in science and techniques applied to agricultural development, rural development, and natural resource management. (2) The Regional Centre for Maiming of Resources for Development (RCMRD) in Nairobi, Kenya, established in 1975 under the auspices of the United Nations Economic Commission for Africa and the Organization of African Unity (now the African Union), is an intergovernmental organization, with 15 member states from eastern and southern Africa. (3) The

  1. Remote sensing image enhancement integrating its local statistical characteristics

    Science.gov (United States)

    He, Qiang; Chu, Chee-Hung Henry

    2010-01-01

    Remote sensing is widely used to assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, the data collection of aerial digital images is constrained with bad weather, muzzy atmosphere, and unstable camera or camcorder. As a result, remote sensing imagery is shown as lowcontrast, blurred, and dark from time to time. Here, we introduce a new method integrating image local statistics and image natural characteristics to enhance remote sensing imagery. This method computes the adaptive histogram equalization to each distinct region of the input image and then redistributes the lightness values of the image. The natural characteristic of image is applied to adjust the restoration contrast. The experiments on real data show the effectiveness of the algorithm.

  2. Computer applications in remote sensing education

    Science.gov (United States)

    Danielson, R. L.

    1980-01-01

    Computer applications to instruction in any field may be divided into two broad generic classes: computer-managed instruction and computer-assisted instruction. The division is based on how frequently the computer affects the instructional process and how active a role the computer affects the instructional process and how active a role the computer takes in actually providing instruction. There are no inherent characteristics of remote sensing education to preclude the use of one or both of these techniques, depending on the computer facilities available to the instructor. The characteristics of the two classes are summarized, potential applications to remote sensing education are discussed, and the advantages and disadvantages of computer applications to the instructional process are considered.

  3. Review of oil spill remote sensing.

    Science.gov (United States)

    Fingas, Merv; Brown, Carl

    2014-06-15

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

  4. Remote Sensing and Geosciences for Archaeology

    Directory of Open Access Journals (Sweden)

    Deodato Tapete

    2018-01-01

    Full Text Available Archaeological remote sensing is not a novel discipline. Indeed, there is already a suite of geoscientific techniques that are regularly used by practitioners in the field, according to standards and best practice guidelines. However, (i the technological development of sensors for data capture; (ii the accessibility of new remote sensing and Earth Observation data; and (iii the awareness that a combination of different techniques can lead to retrieval of diverse and complementary information to characterize landscapes and objects of archaeological value and significance, are currently three triggers stimulating advances in methodologies for data acquisition, signal processing, and the integration and fusion of extracted information. The Special Issue “Remote Sensing and Geosciences for Archaeology” therefore presents a collection of scientific contributions that provides a sample of the state-of-the-art and forefront research in this field. Site discovery, understanding of cultural landscapes, augmented knowledge of heritage, condition assessment, and conservation are the main research and practice targets that the papers published in this Special Issue aim to address.

  5. Remote sensing to monitor uranium tailing sites

    International Nuclear Information System (INIS)

    1992-02-01

    This report concerns the feasibility of using remotely-sensed data for long-term monitoring of uranium tailings. Decommissioning of uranium mine tailings sites may require long-term monitoring to confirm that no unanticipated release of contaminants occurs. Traditional ground-based monitoring of specific criteria of concern would be a significant expense depending on the nature and frequency of the monitoring. The objective of this study was to evaluate whether available remote-sensing data and techniques were applicable to the long-term monitoring of tailings sites. This objective was met by evaluating to what extent the data and techniques could be used to identify and discriminate information useful for monitoring tailings sites. The cost associated with obtaining and interpreting this information was also evaluated. Satellite and aircraft remote-sensing-based activities were evaluated. A monitoring programme based on annual coverage of Landsat Thematic Mapper data is recommended. Immediately prior to and for several years after decommissioning of the tailings sites, airborne multispectral and thermal infrared surveys combined with field verification data are required in order to establish a baseline for the long-term satellite-based monitoring programme. More frequent airborne surveys may be required if rapidly changing phenomena require monitoring. The use of a geographic information system is recommended for the effective storage and manipulation of data accumulated over a number of years

  6. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

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

  7. Applications of airborne remote sensing in atmospheric sciences research

    Science.gov (United States)

    Serafin, R. J.; Szejwach, G.; Phillips, B. B.

    1984-01-01

    This paper explores the potential for airborne remote sensing for atmospheric sciences research. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. Promising candidates include Doppler radar and lidar, infrared short range radiometry, and microwave radiometry.

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

    Science.gov (United States)

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

    2017-06-12

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

  9. Mapping of coastal landforms and volumetric change analysis in the south west coast of Kanyakumari, South India using remote sensing and GIS techniques

    Directory of Open Access Journals (Sweden)

    S. Kaliraj

    2017-12-01

    Full Text Available The coastal landforms along the south west coast of Kanyakumari have undergone remarkable change in terms of shape and disposition due to both natural and anthropogenic interference. An attempt is made here to map the coastal landforms along the coast using remote sensing and GIS techniques. Spatial data sources, such as, topographical map published by Survey of India, Landsat ETM+ (30 m image, IKONOS image (0.82 m, SRTM and ASTER DEM datasets have been comprehensively analyzed for extracting coastal landforms. Change detection methods, such as, (i topographical change detection, (ii cross-shore profile analysis, (iii Geomorphic Change Detection (GCD using DEM of Difference (DoD were adopted for assessment of volumetric changes of coastal landforms for the period between 2000 and 2011. The GCD analysis uses ASTER and SRTM DEM datasets by resampling them into common scale (pixel size using pixel-by-pixel based Wavelet Transform and Pan-Sharpening techniques in ERDAS Imagine software. Volumetric changes of coastal landforms were validated with data derived from GPS-based field survey. Coastal landform units were mapped based on process of their evolution such as beach landforms including sandy beach, cusp, berm, scarp, beach terrace, upland, rockyshore, cliffs, wave-cut notches and wave-cut platforms; and the fluvial landforms. Comprising of alluvial plain, flood plains, and other shallow marshes in estuaries. The topographical change analysis reveals that the beach landforms have reduced their elevation ranging from 1 to 3 m probably due to sediment removal or flattening. Analysis of cross-shore profiles for twelve locations indicate varying degrees of loss or gain of coastal landforms. For example, the K3-K3′ profile across the Kovalam coast has shown significant erosion (−0.26 to −0.76 m of the sandy beaches resulting in the formation of beach cusps and beach scarps within a distance of 300 m from the shoreline. The volumetric change

  10. Remote sensing in the marine environment. A description of facilities, applications, needs and opportunities in South Africa

    CSIR Research Space (South Africa)

    Shannon, LV

    1988-01-01

    Full Text Available Against a background of the techniques and instrumentation available for remote sensing in the marine environment, this report considers the rationale for their use by the South African marine community. Local applications of remote sensing...

  11. Satellite Remote Sensing: Aerosol Measurements

    Science.gov (United States)

    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.

  12. Water management and remote sensing

    NARCIS (Netherlands)

    Assem, S. van den; Bastiaanssen, W.G.M.; Claassen, T.H.L.; Feddes, R.A.; Menenti, M.; Minderhoud, P.; Nieuwenhuis, G.J.A.; Nieuwkoop, J. van; Stokkom, H.T.C. van; Stokman, N.G.M.; Thunnissen, H.A.M.; Visser, T.N.M.

    1990-01-01

    In modern water management detailed information is required on processes that occur and on the state of water systems, including the way they are influenced by human activities. Remote sensing can contribute significantly to these information. For example, areal patterns of water quality parameters

  13. Remote Sensing of Water Pollution

    Science.gov (United States)

    White, P. G.

    1971-01-01

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

  14. Remote sensing for nuclear power plant siting

    International Nuclear Information System (INIS)

    Siegal, B.S.; Welby, C.W.

    1981-01-01

    Remote sensing techniques enhance the selection and evaluation process for nuclear power plant siting. The principal advantage is the synoptic view which improves recognition of linear features, possibly indicative of faults. The interpretation of such images, in conjunction with seismological studies, also permits delineation of seismo-tectonic provinces. In volcanic terrains, geomorphic-age boundaries can be delineated and volcanic centers identified, providing necessary guidance for field sampling and regional model derivation. The use of such techniques is considered for studies in the Philippines, Mexico, and Greece. 5 refs

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

    Science.gov (United States)

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

    2017-04-01

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

  16. Remote sensing of natural phenomena

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2014-06-01

    Full Text Available There has always been a need to directly perceive and study the events whose extent is beyond people's possibilities. In order to get new data and to make observations and studying much more objective in comparison with past syntheses - a new method of examination called remote sensing has been adopted. The paper deals with the principles and elements of remote sensing, as well as with the basic aspects of using remote research in examining meteorological (weather parameters and the conditions of the atmosphere. The usage of satellite images is possible in all phases of the global and systematic research of different natural phenomena when airplane and satellite images of different characteristics are used and their analysis and interpretation is carried out by viewing and computer added procedures. Introduction Remote sensing of the Earth enables observing and studying global and local events that occur on it. Satellite images are nowadays used in geology, agriculture, forestry, geodesy, meteorology, spatial and urbanism planning, designing of infrastructure and other objects, protection from natural and technological catastrophes, etc. It it possible to use satellite images in all phases of global and systematic research of different natural phenomena. Basics of remote sensing Remote sensing is a method of the acquisition and interpretation of information about remote objects without making a physical contact with them. The term Daljinska detekcija is a literal translation of the English term Remote Sensing. In French it isTeledetection, in German - Fernerkundung, in Russian - дистанционие иследования. We also use terms such as: remote survailance, remote research, teledetection, remote methods, and distance research. The basic elements included in Remote Sensing are: object, electromagnetic energy, sensor, platform, image, analysis, interpretation and the information (data, fact. Usage of satellite remote research in

  17. Sensitivity analysis in remote sensing

    CERN Document Server

    Ustinov, Eugene A

    2015-01-01

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

  18. Remote sensing and communications in random media

    Science.gov (United States)

    Papanicolaou, George

    2003-04-01

    Reliable, high-capacity communications in scattering media can be effectively established with some basic remote sensing techniques involving time reversal. I will formulate these problems and discuss the various mathematical approaches that can be used for analysis. It turns out that stochastic analysis plays an important role and, in some cases, gives very satisfactory results. One such result is the spectacular increase in communications capacity in a richly scattering environment. I will end with a discussion of applications and computational issues that arise in the realistic simulation of communication systems.

  19. Remote Sensing Information Science Research

    Science.gov (United States)

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

    2002-01-01

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

  20. Remote sensing for wind energy

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-06-15

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

  1. Geological remote sensing signatures of terrestrial impact craters

    Science.gov (United States)

    Garvin, J. B.; Schnetzler, C.; Grieve, R. A. F.

    1988-01-01

    Geological remote sensing techniques can be used to investigate structural, depositional, and shock metamorphic effects associated with hypervelocity impact structures, some of which may be linked to global Earth system catastrophies. Although detailed laboratory and field investigations are necessary to establish conclusive evidence of an impact origin for suspected crater landforms, the synoptic perspective provided by various remote sensing systems can often serve as a pathfinder to key deposits which can then be targetted for intensive field study. In addition, remote sensing imagery can be used as a tool in the search for impact and other catastrophic explosion landforms on the basis of localized disruption and anomaly patterns. In order to reconstruct original dimensions of large, complex impact features in isolated, inaccessible regions, remote sensing imagery can be used to make preliminary estimates in the absence of field geophysical surveys. The experienced gained from two decades of planetary remote sensing of impact craters on the terrestrial planets, as well as the techniques developed for recognizing stages of degradation and initial crater morphology, can now be applied to the problem of discovering and studying eroded impact landforms on Earth. Preliminary results of remote sensing analyses of a set of terrestrial impact features in various states of degradation, geologic settings, and for a broad range of diameters and hence energies of formation are summarized. The intention is to develop a database of remote sensing signatures for catastrophic impact landforms which can then be used in EOS-era global surveys as the basis for locating the possibly hundreds of missing impact structures. In addition, refinement of initial dimensions of extremely recent structures such as Zhamanshin and Bosumtwi is an important objective in order to permit re-evaluation of global Earth system responses associated with these types of events.

  2. Geological remote sensing signatures of terrestrial impact craters

    International Nuclear Information System (INIS)

    Garvin, J.B.; Schnetzler, C.; Grieve, R.A.F.

    1988-01-01

    Geological remote sensing techniques can be used to investigate structural, depositional, and shock metamorphic effects associated with hypervelocity impact structures, some of which may be linked to global Earth system catastrophies. Although detailed laboratory and field investigations are necessary to establish conclusive evidence of an impact origin for suspected crater landforms, the synoptic perspective provided by various remote sensing systems can often serve as a pathfinder to key deposits which can then be targetted for intensive field study. In addition, remote sensing imagery can be used as a tool in the search for impact and other catastrophic explosion landforms on the basis of localized disruption and anomaly patterns. In order to reconstruct original dimensions of large, complex impact features in isolated, inaccessible regions, remote sensing imagery can be used to make preliminary estimates in the absence of field geophysical surveys. The experienced gained from two decades of planetary remote sensing of impact craters on the terrestrial planets, as well as the techniques developed for recognizing stages of degradation and initial crater morphology, can now be applied to the problem of discovering and studying eroded impact landforms on Earth. Preliminary results of remote sensing analyses of a set of terrestrial impact features in various states of degradation, geologic settings, and for a broad range of diameters and hence energies of formation are summarized. The intention is to develop a database of remote sensing signatures for catastrophic impact landforms which can then be used in EOS-era global surveys as the basis for locating the possibly hundreds of missing impact structures

  3. Innovative progress and sustainable development of remote sensing for uranium geology

    International Nuclear Information System (INIS)

    Liu Dechang; Zhao Yingjun; Ye Fawang

    2009-01-01

    The paper reviewes the innovative process of remote sensing for the uranium geology in Beijing Research Institute of Uranium Geology (BRIUG), discusses the science and technology progress of uranium geology due to remote sensing technique, and the way how to keep sustainable development of the remote sensing for uranium geology so as to play an important role in the uranium geology in the future. (authors)

  4. Magnetoseismology ground-based remote sensing of Earth's magnetosphere

    CERN Document Server

    Menk, Frederick W

    2013-01-01

    Written by a researcher at the forefront of the field, this first comprehensive account of magnetoseismology conveys the physics behind these movements and waves, and explains how to detect and investigate them. Along the way, it describes the principles as applied to remote sensing of near-Earth space and related remote sensing techniques, while also comparing and intercalibrating magnetoseismology with other techniques. The example applications include advanced data analysis techniques that may find wider used in areas ranging from geophysics to medical imaging, and remote sensing using radar systems that are of relevance to defense surveillance systems. As a result, the book not only reviews the status quo, but also anticipates new developments. With many figures and illustrations, some in full color, plus additional computational codes for analysis and evaluation. Aimed at graduate readers, the text assumes knowledge of electromagnetism and physical processes at degree level, but introductory chapters wil...

  5. Hyperspectral remote sensing of wild oyster reefs

    Science.gov (United States)

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

    2016-04-01

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

  6. Optical Remote Sensing Potentials for Looting Detection

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-10-01

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

  7. Water area variations in seasonal lagoons from the Biosphere Reserve of "La Mancha Húmeda" (Spain) determined by remote sensing classification methods and data mining techniques

    Science.gov (United States)

    Dona, Carolina; Niclòs, Raquel; Chang, Ni-Bin; Caselles, Vicente; Sánchez, Juan Manuel; Camacho, Antonio

    2015-04-01

    La Mancha Húmeda is a wetland-rich area located in central Spain that was designated as a Biosphere reserve in 1980. This area includes several dozens of temporal lagoons, mostly saline, whose water level fluctuates and usually become dry during the warmest season. Water inflows into these lagoons come from both runoff of very small catchment and, in some cases, from groundwater although some of them also receive wastewater from nearby towns. Most lack surface outlets and they behave as endorheic systems, with the main water withdrawal due to evaporation causing salt accumulation in the lake beds. Under several law protection coverage additional to that of Biosphere Reserve, including Ramsar and Natura 2000 sites, management plans are being developed in order to accomplish the goals enforced by the European Water Framework Directive and the Habitats Directive, which establish that all EU countries have to achieve a good ecological status and a favorable conservation status of these sites, and especially of their water bodies. A core task to carry out the management plans is the understanding of the hydrological trend of these lagoons with a sound monitoring scheme. To do so, an estimation of the temporal evolution of the flooded area for each lagoon, and its relationship with meteorological patterns, which can be achieved using remote sensing technologies, is a key procedure. The current study aims to develop a remote sensing methodology capable of estimating the changing water coverage areas in each lagoon with satellite remote sensing images and ground truth data sets. ETM+ images onboard Landsat-7 were used to fulfill this goal. These images are useful to monitor small-to-medium size water bodies due to its 30-m spatial resolution. In this work several methods were applied to estimate the wet and dry pixels, such as water and vegetation indexes, single bands, supervised classification methods and genetic programming. All of the results were compared with ground

  8. Analyzing suitability for urban expansion under rapid coastal urbanization with remote sensing and GIS techniques: a case study of Linanyungang, China

    DEFF Research Database (Denmark)

    Zhao, Wenjun; Zhu, Xiaodong; Reenberg, Anette

    2010-01-01

    Beginning in 2000, Lianyungang's urbanization entered a period of rapid growth, spatially as well as economically. Rapid and intensive expansion of "construction land" imposed increasing pressures on regional environment. With the support of remote sensing data and GIS tools, this paper reports...... characterized by a combination of high-density expansion and sprawling development. The land use conversion driven by urbanization and industrialization has not occurred only in city districts, but also the surrounding areas that were spatially absorbed by urban growth, while closely associated and greatly...... a "present-capacity-potential" integrated suitability analysis framework, in order to characterize and evaluate the suitability of urban expansion in Lianyungang. We found that during the rapid coastal urbanization process from 2000 to 2008, the characteristics of physical expansion in the study area were...

  9. Analyzing suitability for urban expansion under rapid coastal urbanization with remote sensing and GIS techniques: a case study of Linanyungang, China

    DEFF Research Database (Denmark)

    Zhao, Wenjun; Zhu, Xiaodong; Reenberg, Anette

    2010-01-01

    Beginning in 2000, Lianyungang's urbanization entered a period of rapid growth, spatially as well as economically. Rapid and intensive expansion of "construction land" imposed increasing pressures on regional environment. With the support of remote sensing data and GIS tools, this paper reports...... characterized by a combination of high-density expansion and sprawling development. The land use conversion driven by urbanization and industrialization has not occurred only in city districts, but also the surrounding areas that were spatially absorbed by urban growth, while closely associated and greatly...... influenced by the explosive growth of industrial establishment. The over-consumption of land resources in the areas with low environmental carrying capacity, particularly in the eastern coastal area, should be strictly controlled. Compared to conventional land suitability analysis methods, the proposed...

  10. Using remote sensing technique for analyzing temporal changes of seagrass beds by human impacts in waters of Cam Ranh Bay, Vietnam

    Science.gov (United States)

    Minh Thu, Phan; Hoang Son, Tong Phuoc; Komatsu, Teruhisa

    2012-10-01

    Seagrass beds/meadows are very productive ecosystems with high biodiversities. However, they have been degraded under high pressures of human activities. Combining depth-invariance index and ground-truthing, distribution of seagrass beds in Cam Ranh Bay was identified by analyses of multi-remote sensing images such as LANDSAT, SPOT and ALOS AVNIR-2. Although coverage of seagrass meadows was1178 ha, the seagrass meadows were being degraded by illegal fishing methods, aquaculture and discharges from industries and living domestics. The reducing ratio of seagrass coverage has been increased in recent years. While the depth-invariance index method would help to detect the areas of seagrass beds, this method requires combination of field trip and absorption library methods to increase classification accuracy. Final maps of the status and changes of seagrass beds could help to integrate the sustainable development of economy with protection of natural resources.

  11. Study of the oxidation of uranium by external and diffuse reflectance FTIR spectroscopy using remote-sensing and evacuable cell techniques

    Science.gov (United States)

    Powell, G. L.; Dobbins, A.; Cristy, S. S.; Cliff, T. L.; Meyer, H. M., III; Lucania, J.; Milosevic, Milan

    1994-01-01

    This report describes the application of reflectance FTIR spectroscopy to the measurement of the oxidation rate of uranium by environmental gases near room temperature. It also describes very efficient evacuable cells designed for 75 degree(s) external reflectance with polarized light and for diffuse reflectance using mid-infrared FTIR spectroscopy. These cells, along with functionally similar remote sensing accessories, have been applied to the study of the oxidation of uranium metal in air, oxygen, and water vapor by precisely measuring the 575 cm-1 band of UO2 and other properties of the corrosion film such as absorbed water and reflective losses caused by film degradation related to pitting or nucleation phenomena.

  12. The Combined Use of Airborne Remote Sensing Techniques within a GIS Environment for the Seismic Vulnerability Assessment of Urban Areas: An Operational Application

    Directory of Open Access Journals (Sweden)

    Antonio Costanzo

    2016-02-01

    Full Text Available The knowledge of the topographic features, the building properties, and the road infrastructure settings are relevant operational tasks for managing post-crisis events, restoration activities, and for supporting search and rescue operations. Within such a framework, airborne remote sensing tools have demonstrated to be powerful instruments, whose joint use can provide meaningful analyses to support the risk assessment of urban environments. Based on this rationale, in this study, the operational benefits obtained by combining airborne LiDAR and hyperspectral measurements are shown. Terrain and surface digital models are gathered by using LiDAR data. Information about roads and roof materials are provided through the supervised classification of hyperspectral images. The objective is to combine such products within a geographic information system (GIS providing value-added maps to be used for the seismic vulnerability assessment of urban environments. Experimental results are gathered for the city of Cosenza, Italy.

  13. and remote sensing for multi-temporal analysis of sand ...

    African Journals Online (AJOL)

    dalel

    and soil erosion which is very critical especially in. Southern Tunisia. This necessitates mapping of wind erosion and sand encroachment evolution to help decision makers to undertake better management plans against desertification and to adapt sustainable land use policies. Remote sensing and GIS technologies are ...

  14. Sources of remotely sensed data

    Science.gov (United States)

    Applications Branch, EROS Data Center

    1978-01-01

    NCIC was established within the USGS to provide a single-point contact source for cartographic-related information, including remotely sensed data. A computerized indexing system, the Aerial Photography Summary Record System (APSRS), shows all holding for Federal agencies, with the long range goal of including data acquired on the state and local levels and (eventually) by private industry. The system directs the used to a particular agency which holds coverage over a particular unit area, based on the 7 1/2 minute USGS quadrangle system. The data will remain in the hands of the source agency.

  15. Remote sensing inputs to water demand modeling

    Science.gov (United States)

    Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

    1975-01-01

    In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

  16. Remote Sensing and Reflectance Profiling in Entomology.

    Science.gov (United States)

    Nansen, Christian; Elliott, Norman

    2016-01-01

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

  17. An improved IHS fusion for high resolution remote sensing images

    Science.gov (United States)

    Hu, Youjian; Zhang, Xiaohua

    2010-02-01

    Image fusion plays an important role in improving high resolution remote sensing images, as many Earth observation satellites provide both high-resolution panchromatic and multispectral images. To date, many image fusion techniques have been developed. Existing traditional image fusion techniques such as the intensity-hue-saturation (IHS) transform, wavelet transform and principal components analysis(PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as IKONOS and Quick Bird. However, the available algorithms can hardly meet a satisfactory fusion requirement for high resolution remote sensing images. Among the existing fusion algorithms, the IHS technique is the most widely used one technique. But the color distortion of this technique is often obvious, especially when high resolution multispectral images are fused with its panchromatic images. This study presents a new fusion approach that integrates both IHS and histogram match techniques to reduce the color distortion of high resolution remote sensing fusion results. Different high resolution remote sensing images have been fused with this new approach. The result proves that the concept of the proposed improved IHS is promising, and it does significantly improve the fusion quality compared to conventional IHS transform fusion techniques.

  18. Data Quality in Remote Sensing

    Science.gov (United States)

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

    2017-09-01

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

  19. Taiwan's second remote sensing satellite

    Science.gov (United States)

    Chern, Jeng-Shing; Ling, Jer; Weng, Shui-Lin

    2008-12-01

    FORMOSAT-2 is Taiwan's first remote sensing satellite (RSS). It was launched on 20 May 2004 with five-year mission life and a very unique mission orbit at 891 km altitude. This orbit gives FORMOSAT-2 the daily revisit feature and the capability of imaging the Arctic and Antarctic regions due to the high enough altitude. For more than three years, FORMOSAT-2 has performed outstanding jobs and its global effectiveness is evidenced in many fields such as public education in Taiwan, Earth science and ecological niche research, preservation of the world heritages, contribution to the International Charter: space and major disasters, observation of suspected North Korea and Iranian nuclear facilities, and scientific observation of the atmospheric transient luminous events (TLEs). In order to continue the provision of earth observation images from space, the National Space Organization (NSPO) of Taiwan started to work on the second RSS from 2005. This second RSS will also be Taiwan's first indigenous satellite. Both the bus platform and remote sensing instrument (RSI) shall be designed and manufactured by NSPO and the Instrument Technology Research Center (ITRC) under the supervision of the National Applied Research Laboratories (NARL). Its onboard computer (OBC) shall use Taiwan's indigenous LEON-3 central processing unit (CPU). In order to achieve cost effective design, the commercial off the shelf (COTS) components shall be widely used. NSPO shall impose the up-screening/qualification and validation/verification processes to ensure their normal functions for proper operations in the severe space environments.

  20. Introductory remote sensing principles and concepts principles and concepts

    CERN Document Server

    Gibson, Paul

    2013-01-01

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

  1. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    2007-01-01

    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  2. Microwave and millimeter-wave remote sensing for security applications

    CERN Document Server

    Nanzer, Jeffrey

    2012-01-01

    Microwave and millimeter-wave remote sensing techniques are fast becoming a necessity in many aspects of security as detection and classification of objects or intruders becomes more difficult. This groundbreaking resource offers you expert guidance in this burgeoning area. It provides you with a thorough treatment of the principles of microwave and millimeter-wave remote sensing for security applications, as well as practical coverage of the design of radiometer, radar, and imaging systems. You learn how to design active and passive sensors for intruder detection, concealed object detection,

  3. Using of Remote Sensing Techniques for Monitoring the Earthquakes Activities Along the Northern Part of the Syrian Rift System (LEFT-LATERAL),SYRIA

    Science.gov (United States)

    Dalati, Moutaz

    Earthquake mitigation can be achieved with a better knowledge of a region's infra-and substructures. High resolution Remote Sensing data can play a significant role to implement Geological mapping and it is essential to learn about the tectonic setting of a region. It is an effective method to identify active faults from different sources of Remote Sensing and compare the capability of some satellite sensors in active faults survey. In this paper, it was discussed a few digital image processing approaches to be used for enhancement and feature extraction related to faults. Those methods include band ratio, filtering and texture statistics . The experimental results show that multi-spectral images have great potentials in large scale active faults investigation. It has also got satisfied results when deal with invisible faults. Active Faults have distinct features in satellite images. Usually, there are obvious straight lines, circular structures and other distinct patterns along the faults locations. Remotely Sensed imagery Landsat ETM and SPOT XS /PAN are often used in active faults mapping. Moderate and high resolution satellite images are the best choice, because in low resolution images, the faults features may not be visible in most cases. The area under study is located Northwest of Syria that is part of one of the very active deformation belt on the Earth today. This area and the western part of Syria are located along the great rift system (Left-Lateral or African- Syrian Rift System). Those areas are tectonically active and caused a lot of seismically events. The AL-Ghab graben complex is situated within this wide area of Cenozoic deformation. The system formed, initially, as a result of the break up of the Arabian plate from the African plate. This action indicates that these sites are active and in a continual movement. In addition to that, the statistic analysis of Thematic Mapper data and the features from a digital elevation model ( DEM )produced from

  4. Toward interactive search in remote sensing imagery

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Do [Los Alamos National Laboratory; Harvey, Neal [Los Alamos National Laboratory; Theile, James [Los Alamos National Laboratory

    2010-01-01

    To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new design criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.

  5. Using remotely sensed data to construct and assess forest attribute maps and related spatial products

    Science.gov (United States)

    Ronald E. McRoberts; Warren B. Cohen; Erik Naesset; Stephen V. Stehman; Erkki O. Tomppo

    2010-01-01

    Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic...

  6. The use of remote sensing for landslide studies in Europe

    Science.gov (United States)

    Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

    2013-04-01

    The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best

  7. Analyzing suitability for urban expansion under rapid coastal urbanization with remote sensing and GIS techniques: a case study of Lianyungang, China

    Science.gov (United States)

    Zhao, Wenjun; Zhu, Xiaodong; Reenberg, Anette; Sun, Xiang

    2010-10-01

    Beginning in 2000, Lianyungang's urbanization entered a period of rapid growth, spatially as well as economically. Rapid and intensive expansion of "construction land" imposed increasing pressures on regional environment. With the support of remote sensing data and GIS tools, this paper reports a "present-capacity-potential" integrated suitability analysis framework, in order to characterize and evaluate the suitability of urban expansion in Lianyungang. We found that during the rapid coastal urbanization process from 2000 to 2008, the characteristics of physical expansion in the study area were characterized by a combination of high-density expansion and sprawling development. The land use conversion driven by urbanization and industrialization has not occurred only in city districts, but also the surrounding areas that were spatially absorbed by urban growth, while closely associated and greatly influenced by the explosive growth of industrial establishment. The over-consumption of land resources in the areas with low environmental carrying capacity, particularly in the eastern coastal area, should be strictly controlled. Compared to conventional land suitability analysis methods, the proposed integrated approach could better review the potential environmental impacts of urban expansion and provide guidance for decision makers.

  8. Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India

    Directory of Open Access Journals (Sweden)

    Amit Bera

    2017-07-01

    Full Text Available Soil erosion is a most severe environmental problem in humid sub-tropical hilly state Tripura. The present study is carried out on Muhuri river basin of Tripura state, North east India having an area of 614.54 Sq.km. In this paper, Universal Soil Loss Equation (USLE model, with Geographic Information System (GIS and Remote Sensing (RS have been used to quantify the soil loss in the Muhuri river basin. Five essential parameters such as Runoff-rainfall erosivity factor (R, soil erodibility Factor (K, slope length and steepness (LS, cropping management factor (C, and support practice factor (P have been used to estimate soil loss amount in the study area. All of these layers have been prepared in GIS and RS platform (Mainly Arc GIS 10.1 using various data sources and data preparation methods. In these study DEM and LISS satellite data have been used. The daily rainfall data (2001-2010 of 6 rain gauge stations have been used to predict the R factor. Soil erodibility (K factor in Basin area ranged from 0.15 to 0.36. The spatial distribution map of soil loss of Muhuri river basin has been generated and classified into six categories according to intensity level of soil loss. The average annual predicted soil loss ranges between 0 to and 650 t/ha/y. Low soil loss areas (70 t/ha/y of soil erosion was found along the main course of Muhuri River.

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

    Directory of Open Access Journals (Sweden)

    A.M. Saleh

    2015-10-01

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

  10. A New GIS based Application of Sequential Technique to Prospect Karstic Groundwater using Remotely Sensed and Geoelectrical Methods in Karstified Tepal Area, Shahrood, Iran

    Directory of Open Access Journals (Sweden)

    Fereydoun Sharifi

    2015-06-01

    Full Text Available In this research, recognition of karstic water-bearing zones using the management of exploration data in Kal-Qorno valley, situated in the Tepal area of Shahrood, has been considered. For this purpose, the sequential exploration method was conducted using geological evidences and applying remote sensing and geoelectrical resistivity methods in two major phases including the regional and local scales. Thus, geological structures and lithological units in regional scale have been investigated for groundwater potential. In this regard, suitable potential maps have been provided in the geographical information system (GIS environment, using fuzzy data-driven and knowledge-driven methods. To obtain the final karstic water potential model, the prepared maps were combined using fuzzy ‘AND’ operator. In the local scale, geoelectrical surveys were conducted in the recognized high potential zones. Consequently, the results of geological investigations, analysis of lineaments extracted from satellite imagery and geoelectrical resistivity data modeling and interpretation were integrated to decide on the position of high yield extraction wells. As a result, karstic water zones in the study area were identified, and based on that, two suitable drilling locations to access and extract karstic groundwater in the study area have been suggested.

  11. Validation of remotely-sensed evapotranspiration and NDWI using ...

    African Journals Online (AJOL)

    Remote sensing techniques and products have recently been developed for the estimation of water balance variables. The objective of this study was to test the reliability of LandSAF (Land Surface Analyses Satellite Applications Facility) evapotranspiration (ET) and SPOT-Vegetation Normalised Difference Water Index ...

  12. Integrated ancillary and remote sensing data for land use ...

    African Journals Online (AJOL)

    Full Name

    MATLAB is a programming language just like C, C++, and python. In this research, a computer program implemented in MATLAB is used to experiment the. Gaussian mixture model algorithm. Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test ...

  13. Automated lineament mapping from remotely sensed data: case ...

    African Journals Online (AJOL)

    ... this study suggested that the more the input data and the adopted techniques, the higher and more reliable are the resultant lineaments. Moreover, SPOT DEM proved to be the most efficient among the input optical datasets. Keywords: Remote Sensing, Lineaments, Hydrogeology, Image Processing, Edge Enhancement ...

  14. Remote Sensing and GIS Assessment of Flood Vulnerability of ...

    African Journals Online (AJOL)

    Lokoja, the Kogi state capital, is located at the Niger-Benue confluence. Hazards erupt when human activities in the confluence area are not properly managed. This article uses the Remote Sensing and GIS technique to assess the flood vulnerability zones of the town using the bench mark minimum and maximum water ...

  15. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  16. Remote Sensing of Plastic Debris

    Science.gov (United States)

    Garaba, S. P.; Dierssen, H. M.

    2016-02-01

    Plastic debris is becoming a nuisance in the environment and as a result there has been a dire need to synoptically detect and quantify them in the ocean and on land. We investigate the possible utility of spectral information determined from hand held, airborne and satellite remote sensing tools in the detection and identification polymer source of plastic debris. Sampled debris will be compared to our derived spectral library of typical raw polymer sources found at sea and in household waste. Additional work will be to determine ways to estimate the abundance of plastic debris in target areas. Implications of successful remote detection, tracking and quantification of plastic debris will be towards validating field observations over large areas and at repeated time intervals both on land and at sea.

  17. Lunar remote sensing and measurements

    Science.gov (United States)

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

    1980-01-01

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

  18. Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis

    Science.gov (United States)

    Welle, Paul

    Policy analyses of agricultural and environmental systems are often limited due to data constraints. Measurement campaigns can be costly, especially when the area of interest includes oceans, forests, agricultural regions or other dispersed spatial domains. Satellite based remote sensing offers a way to increase the spatial and temporal resolution of policy analysis concerning these systems. However, there are key limitations to the implementation of satellite data. Uncertainty in data derived from remote-sensing can be significant, and traditional methods of policy analysis for managing uncertainty on large datasets can be computationally expensive. Moreover, while satellite data can increasingly offer estimates of some parameters such as weather or crop use, other information regarding demographic or economic data is unlikely to be estimated using these techniques. Managing these challenges in practical policy analysis remains a challenge. In this dissertation, I conduct five case studies which rely heavily on data sourced from orbital sensors. First, I assess the magnitude of climate and anthropogenic stress on coral reef ecosystems. Second, I conduct an impact assessment of soil salinity on California agriculture. Third, I measure the propensity of growers to adapt their cropping practices to soil salinization in agriculture. Fourth, I analyze whether small-scale desalination units could be applied on farms in California in order mitigate the effects of drought and salinization as well as prevent agricultural drainage from entering vulnerable ecosystems. And fifth, I assess the feasibility of satellite-based remote sensing for salinity measurement at global scale. Through these case studies, I confront both the challenges and benefits associated with implementing satellite based-remote sensing for improved policy analysis.

  19. Natural Resource Information System. Remote Sensing Studies.

    Science.gov (United States)

    Leachtenauer, J.; And Others

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

  20. Remote sensing for nuclear power plant siting

    International Nuclear Information System (INIS)

    Siegal, B.S.; Welby, C.W.

    1981-01-01

    It is shown that satellite remote sensing provides timely and cost-effective information for siting and site evaluation of nuclear power plants. Side-looking airborne radar (SLAR) imagery is especially valuable in regions of prolonged cloud cover and haze, and provides additional assurance in siting and licensing. In addition, a wide range of enhancement techniques should be employed and different types of image should be color-combined to provide structural and lithologic information. Coastal water circulation can also be studied through repetitive coverage and the inherently synoptic nature of imaging satellites. Among the issues discussed are snow cover, sun angle, and cloud cover, and actual site evaluation studies in the Bataan peninsula of the Philippines and Laguna Verde, California

  1. Proceedings of the Eleventh International Symposium on Remote Sensing of Environment, volume 2. [application and processing of remotely sensed data

    Science.gov (United States)

    1977-01-01

    Application and processing of remotely sensed data are discussed. Areas of application include: pollution monitoring, water quality, land use, marine resources, ocean surface properties, and agriculture. Image processing and scene analysis are described along with automated photointerpretation and classification techniques. Data from infrared and multispectral band scanners onboard LANDSAT satellites are emphasized.

  2. TRACKING FARM MANAGEMENT PRACTICES WITH REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    J. P. Stals

    2017-11-01

    Full Text Available Earth observation (EO data is effective in monitoring agricultural cropping activity over large areas. An example of such an application is the GeoTerraImage crop type classification for the South African Crop Estimates Committee (CEC. The satellite based classification of crop types in South Africa provides a large scale, spatial and historical record of agricultural practices in the main crop growing areas. The results from these classifications provides data for the analysis of trends over time, in order to extract valuable information that can aid decision making in the agricultural sector. Crop cultivation practices change over time as farmers adapt to demand, exchange rate and new technology. Through the use of remote sensing, grain crop types have been identified at field level since 2008, providing a historical data set of cropping activity for the three most important grain producing provinces of Mpumalanga, Freestate and North West province in South Africa. This historical information allows the analysis of farm management practices to identify changes and trends in crop rotation and irrigation practices. Analysis of crop type classification over time highlighted practices such as: frequency of cultivation of the same crop on a field, intensified cultivation on centre pivot irrigated fields with double cropping of a winter grain followed by a summer grain in the same year and increasing cultivation of certain types of crops over time such as soyabeans. All these practices can be analysed in a quantitative spatial and temporal manner through the use of the remote sensing based crop type classifications.

  3. Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

    Science.gov (United States)

    Yueh, Simon H.

    2004-01-01

    Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

  4. Best practices in Remote Sensing for REDD+

    DEFF Research Database (Denmark)

    Dons, Klaus; Grogan, Kenneth

    2012-01-01

    due to steep terrain, • phenological gradients across natural, agricultural and forestry ecosystems including plantations and • the need to serve the REDD-specific context of deforestation and forest degradation across spatial and temporal scales make remote sensing based approaches particularly...... be expected from remote sensing imagery and the provided information shall help to better anticipate problems that will be encountered when acquiring, analyzing and interpreting remote sensing data. Beyond remote sensing, it may be a good point of departure for a large group of scientists with a diverse...... and governance, and deforestation and forest degradation processes. The second part summarizes the available literature on remote sensing based good practices for REDD. It largely draws from the documents of the Intergovernmental Panel on Climate Change (IPCC), the United Nations Framework Convention on Climate...

  5. First European Workshop on 'Remote sensing in mineral exploration'

    International Nuclear Information System (INIS)

    Van Wambeke, L.; Sanderson, D.J.; Dolan, J.M.

    1986-01-01

    The First European Workshop on 'Remote sensing in mineral exploration' organized by the Commission of the European Communities in February 1985 took stock of the results obtained within the European Community on the application of remote sensing techniques in exploration. The papers presented in this publication are essentially based on data obtained with the first generation of satellites and some airborne experiments. Important progress in data processing and interpretation has been made in the EEC since 1979 and is continuing to be made. The main aim is to provide the EC mining industry with a new tool for exploration. Significant results have already been obtained with the EEC playing an important role in the promotion of this relatively new technique. The main R and D trend is towards an integration of multidata sets (remote sensing, geochemical, geophysical and other data) to improve the methodology for delineating new targets in exploration. Another general trend is the participation of mining companies in remote sensing experiments. Further improvement for exploration is expected in the near future with the thematic mapper and the spot imageries as well as new airborne sensors

  6. Remote sensing of sagebrush canopy nitrogen

    Science.gov (United States)

    Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.

    2012-01-01

    This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.

  7. Digital methods and remote sensing in archaeology archaeology in the age of sensing

    CERN Document Server

    Campana, Stefano

    2016-01-01

    This volume debuts the new scope of Remote Sensing, which was first defined as the analysis of data collected by sensors that were not in physical contact with the objects under investigation (using cameras, scanners, and radar systems operating from spaceborne or airborne platforms). A wider characterization is now possible: Remote Sensing can be any non-destructive approach to viewing the buried and nominally invisible evidence of past activity. Spaceborne and airborne sensors, now supplemented by laser scanning, are united using ground-based geophysical instruments and undersea remote sensing, as well as other non-invasive techniques such as surface collection or field-walking survey. Now, any method that enables observation of evidence on or beneath the surface of the earth, without impact on the surviving stratigraphy, is legitimately within the realm of Remote Sensing. The new interfaces and senses engaged in Remote Sensing appear throughout the book. On a philosophical level, this is about the landscap...

  8. Effects Of Oil Spillage On Vegetation, Land And Water(Odu-Gboro, Sagamu,Ogun State, South-Western, Nigeria) Using Remote Sensing And Gis Techniques

    Science.gov (United States)

    Oseni, O.

    2017-12-01

    This paper explores the impacts of oil spill on the physical environment (soil, water and plants) with particular attention paid to the NNPC/PPMC pipeline system. It focuses on the environmental impacts of oil pollution in Nigeria, and discusses the increasing environmental contradictions of the area, and its influence on global warming. The discovery of oil in Nigeria in 1956, the country has been suffering the negative environmental consequences of oil exploration and exploitation. Between 1976 and 1996 a total of 4647 incidents resulted in the spill of approximately 2,369,470 barrels of oil into the environment. In addition, between 1997 and 2001, Nigeria also recorded a total number of 2,097 oil spill incidents. The study traces the effects of the oil spillage on the environment in order to determine whether oil spill is a major factor responsible for environmental pollution. By the use of remotely sensed data and other ancillary data, it identified the major causes of oil spill in the region; the presence of total petroleum hydrocarbon (TPH) in the environment, and it also determined the environmental impacts on land and water. Personal interview, field observation and laboratory analysis of soil and water were used. Gas chromatography was used to determine the TPH concentration in soil extract and water extracts. Liquid-liquid extraction method was used for water and spectro-radiometer which is a very efficient process commonly used to determine spectral signature of various soil, water and plant samples obtained from the study area.Values of analyzed soil and water samples in the oil impacted area were compared to the control area (region with no spill). Based largely onthe GISanalysis, the findings showed that the main cause of oil spill is vandalism along the pipeline right of way; Vandalism which is an act of sabotage had the highest percentage compared to equipment failure, accident from oil tankers and accidental discharge during pipeline repairs

  9. Effects of Oil Spillage on Vegetation, Land and Water Odu-Gboro Sagamu, Ogun State, South-Western Nigeria) Using Remote Sensing and GIS Techniques.

    Science.gov (United States)

    Oseni, O.

    2016-12-01

    This paper explores the impacts of oil spill on the physical environment with particular attention paid to the NNPC/PPMC pipeline system. It focuses on the environmental impacts of oil pollution in Nigeria, and discusses the increasing environmental contradictions of the area, and its influence on global warming. Nigeria's economy is highly dependent on earnings from the oil sector, which provides 20% of GDP, 95% of foreign exchange earnings, and about 65% of budgetary revenues. Since the discovery of oil in Nigeria in 1956, the country has been suffering the negative environmental consequences of oil exploration and exploitation. Between 1976 and 1996 a total of 4647 incidents resulted in the spill of approximately 2,369,470 barrels of oil into the environment. The study traces the effects of the oil spillage on the environment to determine whether oil spill is a major factor responsible for environmental pollution. By the use of remotely sensed data and other ancillary data, the major causes of oil spill in the region were identified; the presence of total petroleum hydrocarbon (TPH) in the environment, and it also determined the environmental impacts on land and water. Field observation and laboratory analysis of soil and water were used. Gas chromatography was used to determine the TPH concentration in soil extract and water extracts. Liquid-liquid extraction method was used for water and spectro-radiometer which is a very efficient process commonly used to determine spectral signature of various soil, water and plant samples obtained from the study area. Based largely on the GIS analysis, the findings showed that the main cause of oil spill is vandalism along the pipeline right of way; Vandalism which is an act of sabotage had the highest percentage compared to equipment failure, accident from oil tankers and accidental discharge during pipeline repairs. TPH were present at the site with soil samples having the high values, and the environmental impact on soil

  10. In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

    Science.gov (United States)

    Russell, P. B.; Segal-Rozenhaimer, M.; Schmid, B.; Redemann, J.; Livingston, J. M.; Flynn, C.J.; Johnson, R. R.; Dunagan, S. E.; Shinozuka, Y.; Kacenelenbogen, M.; hide

    2014-01-01

    Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our

  11. In-situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

    Science.gov (United States)

    Segal-Rosenhaimer, M.; Russell, P. B.; Schmid, B.; Redemann, J.; Livingston, J. M.; Flynn, C. J.; Johnson, R. R.; Dunagan, S. E.; Shinozuka, Y.; Kacenelenbogen, M. S.; Chatfield, R. B.

    2014-12-01

    Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori "ground-truth" labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and expert input and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as

  12. Applications of Remote Sensing to Alien Invasive Plant Studies

    Directory of Open Access Journals (Sweden)

    Gregory P. Asner

    2009-06-01

    Full Text Available Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions.

  13. Cooling Effect of Rivers on Metropolitan Taipei Using Remote Sensing

    Science.gov (United States)

    Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen

    2014-01-01

    This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature. PMID:24464232

  14. Cooling Effect of Rivers on Metropolitan Taipei Using Remote Sensing

    Directory of Open Access Journals (Sweden)

    Yen-Chang Chen

    2014-01-01

    Full Text Available This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.

  15. Cooling effect of rivers on metropolitan Taipei using remote sensing.

    Science.gov (United States)

    Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen

    2014-01-23

    This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.

  16. Advanced and applied remote sensing of environmental conditions

    Science.gov (United States)

    Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.

    2013-01-01

    "Remote sensing” is a general 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 U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

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

    Directory of Open Access Journals (Sweden)

    Gui-Song Xia

    2015-11-01

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

  18. Paleovalleys mapping using remote sensing

    Science.gov (United States)

    Baibatsha, A. B.

    2014-06-01

    For work materials used multispectral satellite imagery Landsat (7 channels), medium spatial resolution (14,25-90 m) and a digital elevation model (data SRTM). For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the "Niagara" type. The term is obviously best reflects the mechanism of formation of these ores.

  19. Paleovalleys mapping using remote sensing

    Directory of Open Access Journals (Sweden)

    A. B. Baibatsha

    2014-06-01

    Full Text Available For work materials used multispectral satellite imagery Landsat (7 channels, medium spatial resolution (14,25–90 m and a digital elevation model (data SRTM. For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the "Niagara" type. The term is obviously best reflects the mechanism of formation of these ores.

  20. Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

    Science.gov (United States)

    Cetin, Haluk

    1999-01-01

    The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and

  1. Remote Sensing in Human Health: A 10-Year Bibliometric Analysis

    Directory of Open Access Journals (Sweden)

    João Viana

    2017-11-01

    Full Text Available A mixed methods bibliometric analysis was performed to ascertain the characteristic of scientific literature published in a 10-year period (2007–2016 regarding the application of remote sensing data in human health. A search was performed on the Scopus database, followed by manual revision using synthesis studies’ techniques, requiring the authors to sort through more than 8000 medical concepts to create the query, and to manually select relevant papers from over 2000 documents. From the initial 2752 papers identified, 520 articles were selected for analysis, showing that the United States ranked first, with a total of 250 (48.1% of the total documents, followed by France and the United Kingdom, with 67 (12.9% of the total and 54 (10.4% of the total documents, respectively. When considering authorship, the top three authors were Vounatsou P (22 articles, Utzinger J (19 articles, and Vignolles C (13 articles. Regarding disease-specific keywords, malaria, dengue, and schistosomiasis were the most frequent keywords, occurring 142, 34, and 24 times, respectively. For some infectious diseases and other highly pathogenic or emerging infectious diseases, remote sensing has become a very powerful instrument. Also, several studies relate different environmental factors retrieved by remote sensing data with other diseases, such as asthma exacerbations. Health-related remote sensing publications are increasing and this paper highlights the importance of these related technologies toward better information and, ideally, better provision of healthcare. On the other hand, this paper provides an overall picture of the state of the research regarding the application of remote sensing data in human health and identifies the most active stakeholders e.g., authors and institutions in the field, informing possible new collaboration research groups.

  2. Biophysical applications of satellite remote sensing

    CERN Document Server

    Hanes, Jonathan

    2014-01-01

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

  3. NOAA Coastal Mapping Remote Sensing Data

    Data.gov (United States)

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

  4. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  5. Comprehensive, integrated, remote sensing at DOE sites

    International Nuclear Information System (INIS)

    Lackey, J.G.; Burson, Z.G.

    1985-01-01

    The Department of Energy has established a program called Comprehensive, Integrated Remote Sensing (CIRS). The overall objective of the program is to provide a state-of-the-art data base of remotely sensed data for all users of such information at large DOE sites. The primary types of remote sensing provided, at present, consist of the following: large format aerial photography, video from aerial platforms, multispectral scanning, and airborne nuclear radiometric surveys. Implementation of the CIRS Program by EG and G Energy Measurements, Inc. began with field operations at the Savannah River Plant in 1982 and is continuing at that DOE site at a level of effort of about $1.5 m per year. Integrated remote sensing studies were subsequently extended to the West Valley Demonstration Project in this summer and fall of 1984. It is expected that the Program will eventually be extended to cover all large DOE sites on a continuing basis

  6. GNSS remote sensing theory, methods and applications

    CERN Document Server

    Jin, Shuanggen; Xie, Feiqin

    2014-01-01

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

  7. Remote sensing of multimodal transportation systems.

    Science.gov (United States)

    2016-09-01

    Hyperspectral remote sensing is an emerging field with many potential applications in the observation, management, and maintenance of the global transportation infrastructure. This report describes the development of an affordable framework to captur...

  8. A Review of Oil Spill Remote Sensing.

    Science.gov (United States)

    Fingas, Merv; Brown, Carl E

    2017-12-30

    The technical aspects of oil spill remote sensing are examined and the practical uses and drawbacks of each technology are given with a focus on unfolding technology. The use of visible techniques is ubiquitous, but limited to certain observational conditions and simple applications. Infrared cameras offer some potential as oil spill sensors but have several limitations. Both techniques, although limited in capability, are widely used because of their increasing economy. The laser fluorosensor uniquely detects oil on substrates that include shoreline, water, soil, plants, ice, and snow. New commercial units have come out in the last few years. Radar detects calm areas on water and thus oil on water, because oil will reduce capillary waves on a water surface given moderate winds. Radar provides a unique option for wide area surveillance, all day or night and rainy/cloudy weather. Satellite-carried radars with their frequent overpass and high spatial resolution make these day-night and all-weather sensors essential for delineating both large spills and monitoring ship and platform oil discharges. Most strategic oil spill mapping is now being carried out using radar. Slick thickness measurements have been sought for many years. The operative technique at this time is the passive microwave. New techniques for calibration and verification have made these instruments more reliable.

  9. Intercomparisons between passive and active microwave remote sensing, and hydrological modeling for soil moisture

    Science.gov (United States)

    Wood, E. F.; Lin, D.-S.; Mancini, M.; Thongs, D.; Troch, P. A.; Jackson, T. J.; Famiglietti, J. S.; Engman, E. T.

    1993-01-01

    Soil moisture estimations from a distributed hydrological model and two microwave sensors were compared with ground measurements collected during the MAC-HYDRO'90 experiment. The comparison was done with the purpose of evaluating the performance of the hydrological model and examining the limitations of remote sensing techniques used in soil moisture estimation. An image integration technique was used to integrate and analyze rainfall, soil properties, land cover, topography, and remote sensing imagery. Results indicate that the hydrological model and microwave sensors successfully picked up temporal variations of soil moisture and that the spatial soil moisture pattern may be remotely sensed with reasonable accuracy using existing algorithms.

  10. Freeware for GIS and Remote Sensing

    OpenAIRE

    Lena Halounová

    2007-01-01

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

  11. Freeware for GIS and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Lena Halounová

    2007-12-01

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

  12. Remote sensing, imaging, and signal engineering

    Energy Technology Data Exchange (ETDEWEB)

    Brase, J.M.

    1993-03-01

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

  13. Archaeological and Environmental Research of the Peten, Guatemala, Using Remote Sensing/GIS Research

    Science.gov (United States)

    Sever, Thomas L.

    2000-01-01

    The Peten, northern Guatemala, was once inhabited by a population of several million Maya before their collapse in the 9th century AD. Although the seventh and eight centuries were a time of crowning glory for millions of Maya; by 930 A.D. only a few scattered houses remained. What is known, is that at the time of their collapse, the Maya had cut down most of their trees. After centuries of regeneration the Peten now represent the largest remaining tropical forest in Central America but is experiencing rapid deforestation in the wake of an invasion of settlers. The successful adaptive techniques of the indigenous population are being abandoned in favor of the destructive techniques of monoculture and cattle raising. These techniques also contribute to the destruction and looting of unrecorded archeological sites. Remote sensing and GIS analysis are being used to address issues in Maya archeology as well as monitor the effects of increasing deforestation in the area today. One thousand years ago the forests of the Peten were nearly destroyed by the ancient Maya, who, after centuries of successful adaptation, finally overused their resources. Current inhabitants are threatening to do the same thing today in a shorter time period with a lesser population. Through the use of remote sensing/GIS analysis we are attempting to answer questions about the past in order to protect the resources of the future.

  14. Super-resolution imaging in remote sensing

    Science.gov (United States)

    Luo, Qiuhua; Shao, Xiaopeng; Peng, Ligen; Wang, Yi; Wang, Lin

    2015-05-01

    A new effective image super resolution (SR) algorithm which is a hybrid of multiple frame Variational Bayesian (VB) reconstruction and single frame Dictionary Learning (DL) reconstruction method is developed to reconstruct a high resolution (HR) satellite image in this article. Firstly, by employing a variational Bayesian analysis, the unknown high resolution image, the acquisition process, the motion parameters and the unknown model parameters are built together in a single mathematical model with a Bayesian formula, and then the distributions of all unknowns are jointly estimated. Without any parameter adjustment, an HR image is adaptively reconstructed from multiple frame low resolution (LR) images. Secondly, by taking the above HR image as input, a higher resolution image can be rebuilt utilizing the statistical correlation between the HR and LR images which is obtained via the DL method. The VB method effectively uses non-redundant information between LR images to recover HR satellite images. Benefit from the dictionary training of magnanimity image, the DL algorithm is able to provide more high-frequency image details, which means this hybrid of VB and DL method combines the above advantages. The experiments show that this proposed algorithm can effectively increase the image resolution of remote sensing images by 0.5times at least comparing with low resolution image.

  15. Anomaly Detection from Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Qiandong Guo

    2016-12-01

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

  16. Application of remote sensing to estimating soil erosion potential

    Science.gov (United States)

    Morris-Jones, D. R.; Kiefer, R. W.

    1980-01-01

    A variety of remote sensing data sources and interpretation techniques has been tested in a 6136 hectare watershed with agricultural, forest and urban land cover to determine the relative utility of alternative aerial photographic data sources for gathering the desired land use/land cover data. The principal photographic data sources are high altitude 9 x 9 inch color infrared photos at 1:120,000 and 1:60,000 and multi-date medium altitude color and color infrared photos at 1:60,000. Principal data for estimating soil erosion potential include precipitation, soil, slope, crop, crop practice, and land use/land cover data derived from topographic maps, soil maps, and remote sensing. A computer-based geographic information system organized on a one-hectare grid cell basis is used to store and quantify the information collected using different data sources and interpretation techniques. Research results are compared with traditional Universal Soil Loss Equation field survey methods.

  17. Application of remote sensing in aquatic ecosystems

    Science.gov (United States)

    Yousef, Foad

    I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll alpha and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.

  18. Super-Resolution Reconstruction for Multi-Angle Remote Sensing Images Considering Resolution Differences

    Directory of Open Access Journals (Sweden)

    Hongyan Zhang

    2014-01-01

    Full Text Available Multi-angle remote sensing images are acquired over the same imaging scene from different angles, and share similar but not identical information. It is therefore possible to enhance the spatial resolution of the multi-angle remote sensing images by the super-resolution reconstruction technique. However, different sensor shooting angles lead to different resolutions for each angle image, which affects the effectiveness of the super-resolution reconstruction of the multi-angle images. In view of this, we propose utilizing adaptive weighted super-resolution reconstruction to alleviate the limitations of the different resolutions. This paper employs two adaptive weighting themes. The first approach uses the angle between the imaging angle of the current image and that of the nadir image. The second is closely related to the residual error of each low-resolution angle image. The experimental results confirm the feasibility of the proposed method and demonstrate the effectiveness of the proposed adaptive weighted super-resolution approach.

  19. Remote sensing; Proceedings of the Meeting, Orlando, FL, Apr. 3, 4, 1986

    Science.gov (United States)

    Menzies, Robert T. (Editor)

    1986-01-01

    Advances in optical technology for remote sensing are discussed in reviews and reports of recent experimental investigations. Topics examined include industrial applications, laser diagnostics for combustion research, laser remote sensing for ranging and altimetry, and imaging systems for terrestrial remote sensing from space. Consideration is given to LIF in forensic diagnostics, time-resolved laser-induced-breakdown spectrometry for rapid analysis of alloys, CARS in practical combustion environments, airborne inertial surveying using laser tracking and profiling techniques, earth-resources instrumentation for the EOS polar platform of the Space Station, and the SAR for EOS.

  20. Institutional issues affecting the integration and use of remotely sensed data and geographic information systems

    Science.gov (United States)

    Lauer, D.T.; Estes, J.E.; Jensen, J.R.; Greenlee, D.D.

    1991-01-01

    The developers as well as the users of remotely sensed data and geographic information system (GIS) techniques are associated with nearly all types of institutions in government, industry, and academia. Individuals in these various institutions often find the barriers to accepting remote sensing and GIS are not necessarily technical in nature, but can be attributed to the institutions themselves. Several major institutional issues that affect the technologies of remote sensing and GIS are data availability, data marketing and costs, equipment availability and costs, standards and practices, education and training, and organizational infrastructures. Not only are problems associated with these issues identified, but needs and opportunities also are discussed. -from Authors

  1. Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

    Science.gov (United States)

    Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

    2013-01-01

    Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

  2. Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

    Energy Technology Data Exchange (ETDEWEB)

    Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

    1993-01-01

    Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI`s obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics.

  3. Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

    International Nuclear Information System (INIS)

    Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

    1993-01-01

    Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI's obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics

  4. Literature relevant to remote sensing of water quality

    Science.gov (United States)

    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.

  5. Developing status of satellite remote sensing and its application

    International Nuclear Information System (INIS)

    Zhang Wanliang; Liu Dechang

    2005-01-01

    This paper has discussed the latest development of satellite remote sensing in sensor resolutions, satellite motion models, load forms, data processing and its application. The authors consider that sensor resolutions of satellite remote sensing have increased largely. Valid integration of multisensors is a new idea and technology of satellite remote sensing in the 21st century, and post-remote sensing application technology is the important part of deeply applying remote sensing information and has great practical significance. (authors)

  6. Remote sensing of land surface temperature: The directional viewing effect

    International Nuclear Information System (INIS)

    Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.

    1997-01-01

    Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied

  7. Adaptive Management Using Remote Sensing and Ecosystem Modeling in Response to Climate Variability and Invasive Aquatic Plants for the California Sacramento-San Joaquin Delta Water Resource

    Science.gov (United States)

    Bubenheim, D.; Potter, C. S.; Zhang, M.; Madsen, J.

    2017-12-01

    The California Sacramento-San Joaquin River Delta is the hub for California's water supply and supports important ecosystem services, agriculture, and communities in Northern and Southern California. Expansion of invasive aquatic plants in the Delta coupled with impacts of changing climate and long-term drought is detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California to develop science-based, adaptive-management strategies for invasive aquatic plant management in the California Sacramento-San Joaquin Delta. Specific mapping tools developed utilizing satellite and airborne platforms provide regular assessments of population dynamics on a landscape scale and support both strategic planning and operational decision making for resource managers. San Joaquin and Sacramento River watersheds water quality input to the Delta is modeled using the Soil-Water Assessment Tool (SWAT) and a modified SWAT tool has been customized to account for unique landscape and management of agricultural water supply and drainage within the Delta. Environmental response models for growth of invasive aquatic weeds are being parameterized and coupled with spatial distribution/biomass density mapping and water quality to study ecosystem response to climate and aquatic plant management practices. On the water validation and operational utilization of these tools by management agencies and how they improve decision making, management effectiveness and efficiency will be discussed. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and water resource managers make science-informed decisions regarding management and outcomes.

  8. The Study of Mining Activities and their Influences in the Almaden Region Applying Remote Sensing Techniques; Estudio de la Influencia de las Actividades Mineras de Mercurio en la Comarca de Almaden Aplicando Tecnicas de Teledeteccion

    Energy Technology Data Exchange (ETDEWEB)

    Rico, C.; Schmid, T.; Millan, R.; Gumuzzio, J.

    2010-11-17

    This scientific-technical report is a part of an ongoing research work carried out by Celia Rico Fraile in order to obtain the Diploma of Advanced Studies as part of her PhD studies. This work has been developed in collaboration with the Faculty of Science at The Universidad Autonoma de Madrid and the Department of Environment at CIEMAT. The main objective of this work was the characterization and classification of land use in Almaden (Ciudad Real) during cinnabar mineral exploitation and after mining activities ceased in 2002, developing a methodology focused on the integration of remote sensing techniques applying multispectral and hyper spectral satellite data. By means of preprocessing and processing of data from the satellite images as well as data obtained from field campaigns, a spectral library was compiled in order to obtain representative land surfaces within the study area. Monitoring results show that the distribution of areas affected by mining activities is rapidly diminishing in recent years. (Author) 130 refs.

  9. First observations of tropospheric δD data observed by ground- and space-based remote sensing and surface in-situ measurement techniques at MUSICA's principle reference station (Izaña Observatory, Spain)

    Science.gov (United States)

    González, Yenny; Schneider, Matthias; Christner, Emanuel; Rodríguez, Omaira E.; Sepúlveda, Eliezer; Dyroff, Christoph; Wiegele, Andreas

    2013-04-01

    The main goal of the project MUSICA (Multiplatform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi global tropospheric water vapor isototopologue dataset of a good and well-documented quality. Therefore, new ground- and space-based remote sensing observations (NDACC-FTIR and IASI/METOP) are combined with in-situ measurements. This work presents the first comparison between in-situ and remote sensing observations made at the Izaña Atmospheric Research Centre (Tenerife, Canary Islands, Spain). The in-situ measurements are made by a Picarro L2120-i water vapor isotopologue analyzer. At Izaña the in-situ data are affected by local small-scale mixing processes: during daylight, the thermally buoyant upslope flow prompts the mixing between the Marine Boundary Layer (MBL) and the low Free Troposphere (FT). However, the remote sensors detect δD values averaged over altitudes that are more representative for the free troposphere. This difference has to be considered for the comparison. In general, a good agreement between the MUSICA remote sensing and the in situ H2O-versus-δD plots is found, which demonstrates that the MUSICA δD remote sensing products add scientifically valuable information to the H2O data.

  10. Techniques for assessing water resource potentials in the developing countries: with emphasis on streamflow, erosion and sediment transport, water movement in unsaturated soils, ground water, and remote sensing in hydrologic applications

    Science.gov (United States)

    Taylor, George C.

    1971-01-01

    . Nuclear methodology in hydrologic applications is generally more complex than the conventional and hence requires a high level of technical expertise for effective use. Application of nuclear techniques to hydrologic problems in the developing countries is likely to be marginal for some years to come, owing to the higher costs involved and expertise required. Nuclear techniques, however, would seem to have particular promise in studies of water movement in unsaturated soils and of erosion and sedimentation where conventional techniques are inadequate, inefficient and in some cases costly. Remote sensing offers great promise for synoptic evaluations of water resources and hydrologic processes, including the transient phenomena of the hydrologic cycle. Remote sensing is not, however, a panacea for deficiencies in hydrologic data programs in the developing countries. Rather it is a means for extending and augmenting on-the-ground observations ans surveys (ground truth) to evaluated water resources and hydrologic processes on a regionall or even continental scale. With respect to economic growth goals in developing countries, there are few identifiable gaps in existing hydrologic instrumentation and methodology insofar as appraisal, development and management of available water resources are concerned. What is needed is acceleration of institutional development and professional motivation toward more effective use of existing and proven methodology. Moreover, much sophisticated methodology can be applied effectively in the developing countries only when adequate levels of indigenous scientific skills have been reached and supportive institutional frameworks are evolved to viability.

  11. Photogrammetry and remote sensing education subjects

    Science.gov (United States)

    Lazaridou, Maria A.; Karagianni, Aikaterini Ch.

    2017-09-01

    The rapid technologic advances in the scientific areas of photogrammetry and remote sensing require continuous readjustments at the educational programs and their implementation. The teaching teamwork should deal with the challenge to offer the volume of the knowledge without preventing the understanding of principles and methods and also to introduce "new" knowledge (advances, trends) followed by evaluation and presentation of relevant applications. This is of particular importance for a Civil Engineering Faculty as this in Aristotle University of Thessaloniki, as the framework of Photogrammetry and Remote Sensing is closely connected with applications in the four educational Divisions of the Faculty. This paper refers to the above and includes subjects of organizing the courses in photogrammetry and remote sensing in the Civil Engineering Faculty of Aristotle University of Thessaloniki. A scheme of the general curriculum as well the teaching aims and methods are also presented.

  12. Remote sensing applications in environmental research

    CERN Document Server

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

    2014-01-01

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

  13. REMOTE SENSING TECHNIQUES TO ASSESS POST-FIRE EFFECTS AT THE HILLSLOPE AND SUB-BASIN SCALES VIA MULTI-SCALE MODEL

    Directory of Open Access Journals (Sweden)

    A. Brook

    2017-05-01

    Full Text Available Post-fire environmental footprint is expected at varying scales in space and in time and demands development of multi-scale monitoring approaches. In this paper, a spatially and temporally explicit multi-scale model that reveals the physical and morphological indicators affecting hillslope susceptibility at varying scales, is explained and demonstrated. The qualitative and quantitative suitability classification procedures are adapted to translate the large-scale space-borne data supplied by satellite systems (Landsat OLS8 and Sentinel 2 and 3 to local scale produced by a regional airborne survey performed by unmanned aerial vehicle (UAV. At the smallest spatial and temporal resolution, a daily airborne imagery collection by UAV is linked to micro-topography model, using statistical and mathematical approaches.

  14. Thermal infrared remote sensing sensors, methods, applications

    CERN Document Server

    Kuenzer, Claudia

    2013-01-01

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

  15. Space remote sensing systems an introduction

    CERN Document Server

    Chen, H S

    1985-01-01

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

  16. Remote sensing of land surface phenology

    Science.gov (United States)

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

    2014-01-01

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

  17. Monitoring water quality by remote sensing

    Science.gov (United States)

    Brown, R. L. (Principal Investigator)

    1977-01-01

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

  18. [Remote sensing resource monitoring on Atractylodes lancea].

    Science.gov (United States)

    Sun, Yu-Zhang; Guo, Lan-Ping; Zhu, Wen-Quan; Huang, Lu-Qi; Gu, Xiao-He; Han, Li-Jian; Pan, Yao-Zhong

    2008-02-01

    Remote sensing technology was used for investigation of the resources of Atractylodes lancea. Firstly, the general situation of Jiangshu Maoshan and A. lancea in Maoshan was introduced; Secondly, the methods of remote sensing on the resource of the wild drugs were explained. Thirdly, the TM images were interpret according to the differences of the objects reflex spectrum, and growth environments in Damao mountain, Ermao mountain and Xiaomao mountain were divided into different sub-areas according to the results of the field investigations. Finally, the resource of A. lancea in Jiangshu Maoshan was estimated.

  19. Offshore winds mapped from satellite remote sensing

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    2014-01-01

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

  20. Statistical Similarity Based Change Detection for Multitemporal Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Mumu Aktar

    2017-01-01

    Full Text Available Change detection (CD of any surface using multitemporal remote sensing images is an important research topic since up-to-date information about earth surface is of great value. Abrupt changes are occurring in different earth surfaces due to natural disasters or man-made activities which cause damage to that place. Therefore, it is necessary to observe the changes for taking necessary steps to recover the subsequent damage. This paper is concerned with this issue and analyzes statistical similarity measure to perform CD using remote sensing images of the same scene taken at two different dates. A variation of normalized mutual information (NMI as a similarity measure has been developed here using sliding window of different sizes. In sliding window approach, pixels’ local neighborhood plays a significant role in computing the similarity compared to the whole image. Thus the insignificant global characteristics containing noise and sparse samples can be avoided when evaluating the probability density function. Therefore, NMI with different window sizes is proposed here to identify changes using multitemporal data. Experiments have been carried out using two separate multitemporal remote sensing images captured one year apart and one month apart, respectively. Experimental analysis reveals that the proposed technique can detect up to 97.71% of changes which outperforms the traditional approaches.

  1. Remote Sensing for Mineral Exploration in Central Portugal

    Directory of Open Access Journals (Sweden)

    Ricardo Manuel

    2017-09-01

    Full Text Available Central Portugal is well known for the existence of Sn-W and Au-Ag mineral occurrences primarily associated with hydrothermal processes. Despite the economic and strategic importance of such occurrences, the detailed geology of this particular region is poorly known and there is an obvious absence of geological mapping at an adequate scale. Remote sensing techniques were used in order to increase current geological knowledge of the Góis–Castanheira de Pêra area (600 km2 and to guide future exploration stages by targeting and prioritising potential locations. Digital image processing algorithms, such as Red, Green, Blue (RGB colour composites, digital spatial filters, band ratios and Principal Components Analysis, were applied to Landsat 8 imagery and elevation data. Lineaments were extracted relying on geological photointerpretation criteria, allowing the identification of new geological–structural elements. Fieldwork was carried out in order to validate the remote sensing interpretations. Integration of remote sensing data with other information sources led to the definition of locations possibly suitable for hosting Sn-W and Au-Ag mineral occurrences. These areas were ranked according to their mineral potential. Targeting the most promising locations resulted in a reduction to less than 10% of the original study area (50.5 km2.

  2. Applications of airborne remote sensing in atmospheric sciences research

    Science.gov (United States)

    Serafin, Robert J.; Szejwach, Gerard; Phillips, Byron B.

    1986-02-01

    The potential for airborne remote sensing for atmospheric sciences research and in particular for research over the oceans is explored. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. There exists promising candidates of both active and passive types in the electromagnetic spectrum from microwave to visible wavelengths. Short-range, rapid response measurements of temperature, water vapor, winds, and turbulence are all possible using infrared radiometry and Doppler lidar velocimetry. Pulsed Doppler radar for measurements of the three-dimensional structures of winds and hydrometeors in precipitating systems has been clearly established. Pulsed Doppler lidar is less well developed in comparison to Doppler radar but promises to be an important complement to radar observations by providing wind measurements in the nonprecipitating and cloud free atmosphere. It is possible now to equip a single aircraft or several aircraft with a variety of remote sensing instruments that together form a powerful, highly mobile atmospheric observing system for measurement of fundamental meteorological variables in three dimensions on a variety of spatial scales. This capability is of major importance to the study of mesoscale systems, particularly to those over the ocean, where the deployment of surface based sensors is exceedingly difficult, if not impossible, and costly.

  3. The Science and Technology in Future Remote Sensing Space Missions of Alenia Aerospazio

    Science.gov (United States)

    Angino, G.; Borgarelli, L.

    1999-12-01

    The Space Division of Alenia Aerospazio, a Finmeccanica company, is the major Italian space industry. It has, in seven plants, design facilities and laboratories for advanced technological research that are amongst the most modern and well equipped in Europe. With the co-ordinated companies Alenia Aerospazio is one of Europe's largest space industries. In the field of Remote Sensing, i.e. the acquisition of information about objects without being in physical contact with them, the Space Division has proven their capability to manage all of the techniques from space (ranging from active instruments as Synthetic Aperture Radar, Radar Altimeter, Scatterometer, etc… to passive ones as radiometer) in different programs with the main international industries and agencies. Space techniques both for Monitoring/Observation (i.e. operational applications) and Exploration (i.e. research for science demonstration) according to the most recent indication from international committees constitute guidelines. The first is devoted to market for giving innovation, added-value to services and, globally, enhancement of quality of life. The second has the basic purpose of pursuing the scientific knowledge. Advanced technology allows to design for multi-functions instruments (easy in configuration, adaptable to impredictable environment), to synthesise, apparently, opposite concepts (see for instance different requirement from military and civil applications). Space Division of Alenia Aerospazio has knowledge and capability to face the challenge of new millennium in space missions sector. In this paper, it will be described main remote sensing missions in which Space Division is involved both in terms of science and technology definition. Two main segments can be defined: Earth and interplanetary missions. To the first belong: ENVISAT (Earth surface), LIGHTSAR (Earth imaging), CRYOSAT (Earth ice) and to the second: CASSINI (study of Titan and icy satellites), MARS EXPRESS (detection

  4. Orbital remote sensing - Space technology applications in south-east Asia

    Science.gov (United States)

    Malingreau, J.-P.

    1985-01-01

    The evolution of remote sensing techniques in the developing countries of southeast Asia is reviewed. The use of the images for monitoring soil, water, and vegetation resources, in order to develop a national policy for conservation of the resources, is described. The remote sensing data are helpful in observing deforestation in southeast Asia; however, excessive cloud coverage does not allow accurate evaluation of the rice crop. The effects of the capabilities of the developing countries to process the data and remote sensing program of industrial countries on the future application of satellite imagery in developing countries are studied. The need for improved data banking and dissemination of the imagery is analyzed. Agreements on proprietary rights due to the improved ground resolution of orbital sensors are required. The designing of remote sensing equipment to meet the requirements of its users is discussed.

  5. A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

    Science.gov (United States)

    Liu, Likun

    2018-01-01

    In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

  6. Using remote sensing to predict earthquake impacts

    Science.gov (United States)

    Fylaktos, Asimakis; Yfantidou, Anastasia

    2017-09-01

    Natural hazards like earthquakes can result to enormous property damage, and human casualties in mountainous areas. Italy has always been exposed to numerous earthquakes, mostly concentrated in central and southern regions. Last year, two seismic events near Norcia (central Italy) have occurred, which led to substantial loss of life and extensive damage to properties, infrastructure and cultural heritage. This research utilizes remote sensing products and GIS software, to provide a database of information. We used both SAR images of Sentinel 1A and optical imagery of Landsat 8 to examine the differences of topography with the aid of the multi temporal monitoring technique. This technique suits for the observation of any surface deformation. This database is a cluster of information regarding the consequences of the earthquakes in groups, such as property and infrastructure damage, regional rifts, cultivation loss, landslides and surface deformations amongst others, all mapped on GIS software. Relevant organizations can implement these data in order to calculate the financial impact of these types of earthquakes. In the future, we can enrich this database including more regions and enhance the variety of its applications. For instance, we could predict the future impacts of any type of earthquake in several areas, and design a preliminarily model of emergency for immediate evacuation and quick recovery response. It is important to know how the surface moves, in particular geographical regions like Italy, Cyprus and Greece, where earthquakes are so frequent. We are not able to predict earthquakes, but using data from this research, we may assess the damage that could be caused in the future.

  7. Remote Sensing for Hazard Mitigation and Resource Protection in Pacific Latin America: New NSF sponsored initiative at Michigan Tech.

    Science.gov (United States)

    Rose, W. I.; Bluth, G. J.; Gierke, J. S.; Gross, E.

    2005-12-01

    Though much of the developing world has the potential to gain significantly from remote sensing techniques in terms of public health and safety and, eventually, economic development, they lack the resources required to advance the development and practice of remote sensing. Both developed and developing countries share a mutual interest in furthering remote sensing capabilities for natural hazard mitigation and resource development, and this common commitment creates a solid foundation upon which to build an integrated education and research project. This will prepare students for careers in science and engineering through their efforts to solve a suite of problems needing creative solutions: collaboration with foreign agencies; living abroad immersed in different cultures; and adapting their academic training to contend with potentially difficult field conditions and limited resources. This project makes two important advances: (1) We intend to develop the first formal linkage among geoscience agencies from four Pacific Latin American countries (Guatemala, El Salvador, Nicaragua and Ecuador), focusing on the collaborative development of remote sensing tools for hazard mitigation and water resource development; (2) We will build a new educational system of applied research and engineering, using two existing educational programs at Michigan Tech: a new Peace Corp/Master's International (PC/MI) program in Natural Hazards which features a 2-year field assignment, and an "Enterprise" program for undergraduates, which gives teams of geoengineering students the opportunity to work for three years in a business-like setting to solve real-world problems This project will involve 1-2 post-doctoral researchers, 3 Ph.D., 9 PC/MI, and roughly 20 undergraduate students each year.

  8. Review: Estimating evapotranspiration using remote sensing and ...

    African Journals Online (AJOL)

    Review: Estimating evapotranspiration using remote sensing and the Surface Energy Balance System – A South African perspective. ... It is therefore recommended that any further research using the SEBS model in South Africa should be limited to agricultural areas where accurate vegetation parameters can be obtained, ...

  9. REMOTE SENSING FOR ENVIRONMENTAL COMPLIANCE MONITORING

    Science.gov (United States)

    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...

  10. OPTICAL REMOTE SENSING FOR AIR QUALITY MONITORING

    Science.gov (United States)

    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...

  11. Annual Report Remote Sensing Activities Utrecht University

    NARCIS (Netherlands)

    Jong, S.M. de; Jetten, V.G.; Kwast, J. van der; Addink, E.A.

    2010-01-01

    The Faculty of Geosciences of Utrecht University in The Netherlands is a suc-cessful research and educational organi-sation (www.geo.uu.nl). The Faculty has four departments: Physical Geography, Earth Sciences, Human Geography & Planning and Innovation & Environmental Sciences. The remote sensing,

  12. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

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

  13. Satellite Remote Sensing in Offshore Wind Energy

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  14. Passive microwave remote sensing of soil moisture

    International Nuclear Information System (INIS)

    Jackson, T.J.; Schmugge, T.J.

    1986-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive microwave soil moisture sensors currently considered for space operation are in the range 10–20 km. The most useful frequency range for soil moisture sensing is 1–5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations

  15. A review and analysis of neural networks for classification of remotely sensed multispectral imagery

    Science.gov (United States)

    Paola, Justin D.; Schowengerdt, Robert A.

    1993-01-01

    A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

  16. A macroecological analysis of SERA derived forest heights and implications for forest volume remote sensing.

    Directory of Open Access Journals (Sweden)

    Matthew Brolly

    Full Text Available Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to

  17. A macroecological analysis of SERA derived forest heights and implications for forest volume remote sensing.

    Science.gov (United States)

    Brolly, Matthew; Woodhouse, Iain H; Niklas, Karl J; Hammond, Sean T

    2012-01-01

    Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing

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

    Science.gov (United States)

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

    2014-11-01

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

  19. Vertical variability of aerosol single-scattering albedo and equivalent black carbon concentration based on in-situ and remote sensing techniques during the iAREA campaigns in Ny-Ålesund

    Science.gov (United States)

    Markowicz, K. M.; Ritter, C.; Lisok, J.; Makuch, P.; Stachlewska, I. S.; Cappelletti, D.; Mazzola, M.; Chilinski, M. T.

    2017-09-01

    This work presents a methodology for obtaining vertical profiles of aerosol single scattering properties based on a combination of different measurement techniques. The presented data were obtained under the iAREA (Impact of absorbing aerosols on radiative forcing in the European Arctic) campaigns conducted in Ny-Ålesund (Spitsbergen) during the spring seasons of 2015-2017. The retrieval uses in-situ observations of black carbon concentration and absorption coefficient measured by a micro-aethalometer AE-51 mounted onboard a tethered balloon, as well as remote sensing data obtained from sun photometer and lidar measurements. From a combination of the balloon-borne in-situ and the lidar data, we derived profiles of single scattering albedo (SSA) as well as absorption, extinction, and aerosol number concentration. Results have been obtained in an altitude range from about 400 m up to 1600 m a.s.l. and for cases with increased aerosol load during the Arctic haze seasons of 2015 and 2016. The main results consist of the observation of increasing values of equivalent black carbon (EBC) and absorption coefficient with altitude, and the opposite trend for aerosol concentration for particles larger than 0.3 μm. SSA was retrieved with the use of lidar Raman and Klett algorithms for both 532 and 880 nm wavelengths. In most profiles, SSA shows relatively high temporal and altitude variability. Vertical variability of SSA computed from both methods is consistent; however, some discrepancy is related to Raman retrieval uncertainty and absorption coefficient estimation from AE-51. Typically, very low EBC concentration in Ny-Ålesund leads to large error in the absorbing coefficient. However, SSA uncertainty for both Raman and Klett algorithms seems to be reasonable, e.g. SSA of 0.98 and 0.95 relate to an error of ±0.01 and ± 0.025, respectively.

  20. Recent observations of carbon and sulfur gas emissions from Tavurvur, Bagana and Ulawun (Papua New Guinea) with a combination of ground- and air-borne direct and remote sensing techniques

    Science.gov (United States)

    Arellano, Santiago; Galle, Bo; Mulina, Kila; Wallius, Julia; McCormick, Brendan; Salem, Lois; D'aleo, Roberto; Itikarai, Ima; Tirpitz, Lukas; Bobrowski, Nicole; Aiuppa, Alessandro

    2017-04-01

    Satellite observations reveal that volcanoes from Papua New Guinea contributed with ca. 15{%} of the global emission of volcanic sulfur dioxide (SO2) during the period 2005-2014. Relatively little is known about their carbon dioxide (CO2) outputs and more recent levels and dynamics of degassing activity. During September 2016 we conducted measurements of the CO2/SO2 ratio and the SO2 flux from Tavurvur, Bagana and Ulawun volcanoes using a combination of remote sensing and direct sampling techniques. Tavurvur exhibits low-level passive degassing from a modestly active vent and few other intra-crater fumaroles, which made access possible for direct measurements of the CO2/SO2 ratio with a compact Multi-GAS instrument. A wide-field of view pointing DOAS monitor was deployed for longer term monitoring of the SO2 flux from a distance of about 2 km. Bagana degasses continuously with occasional emissions of ash, and its SO2 flux, plume velocity and height was constrained by simultaneous scanning and dual-beam DOAS measurements. Molar ratios in the plume of Bagana were measured by the compact Multi-GAS aboard a multi-rotor UAV, up to a height of 1.6 km above ground. Ulawun showed continuous passive degassing and measurements with the UAV, up to an altitude of ca. 1.8 km, and mobile-DOAS traverses from a car were used to constrain its gas emission. Here we present an overview of the challenging conditions, measurement strategies and results of this campaign that forms part of the ongoing international effort DECADE aiming to better quantify the global gas emission of carbon- and sulfur containing species from volcanoes.

  1. Remote Sensing Characteristics of Wave Breaking Rollers

    Science.gov (United States)

    Haller, M. C.; Catalan, P.

    2006-12-01

    The wave roller has a primary influence on the balances of mass and momentum in the surf zone (e.g. Svendsen, 1984; Dally and Brown, 1995; Ruessink et al., 2001). In addition, the roller area and its angle of inclination on the wave front are important quantities governing the dissipation rates in breaking waves (e.g Madsen et al., 1997). Yet, there have been very few measurements published of individual breaking wave roller geometries in shallow water. A number of investigators have focused on observations of the initial jet-like motion at the onset of breaking before the establishment of the wave roller (e.g. Basco, 1985; Jansen, 1986), while Govender et al. (2002) provide observations of wave roller vertical cross-sections and angles of inclination for a pair of laboratory wave conditions. Nonetheless, presently very little is known about the growth, evolution, and decay of this aerated region of white water as it propagates through the surf zone; mostly due to the inherent difficulties in making the relevant observations. The present work is focused on analyzing observations of the time and space scales of individual shallow water breaking wave rollers as derived from remote sensing systems. Using a high-resolution video system in a large-scale laboratory facility, we have obtained detailed measurements of the growth and evolution of the wave breaking roller. In addition, by synchronizing the remote video with in-situ wave gages, we are able to directly relate the video intensity signal to the underlying wave shape. Results indicate that the horizontal length scale of breaking wave rollers differs significantly from the previous observations of Duncan (1981), which has been a traditional basis for roller model parameterizations. The overall approach to the video analysis is new in the sense that we concentrate on individual breaking waves, as opposed to the more commonly used time-exposure technique. In addition, a new parameter of interest, denoted Imax, is

  2. Optical/Infrared Signatures for Space-Based Remote Sensing

    National Research Council Canada - National Science Library

    Picard, R. H; Dewan, E. M; Winick, J. R; O'Neil, R. R

    2007-01-01

    This report describes work carried out under the Air Force Research Laboratory's basic research task in optical remote-sensing signatures, entitled Optical / Infrared Signatures for Space-Based Remote Sensing...

  3. Forest structural assessment using remote sensing technologies: an ...

    African Journals Online (AJOL)

    -Natal and MONDI Business Paper have recently embarked on a remote sensing cooperative. The primary focus of this cooperative is to explore the potential benefits associated with using remote sensing for forestry-related activities.

  4. Advances in Remote Sensing Approaches for Hazard Mitigation and Natural Resource Protection in Pacific Latin America: A Workshop for Advanced Graduate Students, Post- Doctoral Researchers, and Junior Faculty

    Science.gov (United States)

    Gierke, J. S.; Rose, W. I.; Waite, G. P.; Palma, J. L.; Gross, E. L.

    2008-12-01

    Though much of the developing world has the potential to gain significantly from remote sensing techniques in terms of public health and safety, they often lack resources for advancing the development and practice of remote sensing. All countries share a mutual interest in furthering remote sensing capabilities for natural hazard mitigation and resource development. With National Science Foundation support from the Partnerships in International Research and Education program, we are developing a new educational system of applied research and engineering for advancing collaborative linkages among agencies and institutions in Pacific Latin American countries (to date: Guatemala, El Salvador, Nicaragua, Costa Rica, Panama, and Ecuador) in the development of remote sensing tools for hazard mitigation and water resources management. The project aims to prepare students for careers in science and engineering through their efforts to solve suites of problems needing creative solutions: collaboration with foreign agencies; living abroad immersed in different cultures; and adapting their academic training to contend with potentially difficult field conditions and limited resources. The ultimate goal of integrating research with education is to encourage cross-disciplinary, creative, and critical thinking in problem solving and foster the ability to deal with uncertainty in analyzing problems and designing appropriate solutions. In addition to traditional approaches for graduate and undergraduate research, we have built new educational systems of applied research and engineering: (1) the Peace Corp/Master's International program in Natural Hazards which features a 2-year field assignment during service in the U.S. Peace Corps, (2) the Michigan Tech Enterprise program for undergraduates, which gives teams of students from different disciplines the opportunity to work for three years in a business-like setting to solve real-world problems, and (3) a unique university exchange

  5. Remote sensing techniques for mangrove mapping

    NARCIS (Netherlands)

    Vaiphasa, C.

    2006-01-01

    Mangroves, important components of the world's coastal ecosystems, are threatened by the expansion of human settlements, the boom in commercial aquaculture, the impact of tidal waves and storm surges, etc. Such threats are leading to the increasing demand for detailed mangrove maps for the purpose

  6. Innovative Remote Sensing techniques for vegetation monitoring

    International Nuclear Information System (INIS)

    Borfecchia, F.; De Cecco, L.; Della Rocca, A.B.; Farneti, A.; La Porta, L.; Martini, S.; Giordano, L.; Trotta, C.; Marcoccia, S.

    2008-01-01

    This paper describes methods developed for using ASPIS (Advanced Spectroscopic Imaging System) to monitor biophysical parameters in studying the effects of climatic change, desertification and land degradation on semi-natural and agricultural vegetation in the Mediterranean region [it

  7. Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

    Directory of Open Access Journals (Sweden)

    Angela Lausch

    2016-12-01

    Full Text Available Anthropogenic stress and disturbance of forest ecosystems (FES has been increasing at all scales from local to global. In rapidly changing environments, in-situ terrestrial FES monitoring approaches have made tremendous progress but they are intensive and often integrate subjective indicators for forest health (FH. Remote sensing (RS bridges the gaps of these limitations, by monitoring indicators of FH on different spatio-temporal scales, and in a cost-effective, rapid, repetitive and objective manner. In this paper, we provide an overview of the definitions of FH, discussing the drivers, processes, stress and adaptation mechanisms of forest plants, and how we can observe FH with RS. We introduce the concept of spectral traits (ST and spectral trait variations (STV in the context of FH monitoring and discuss the prospects, limitations and constraints. Stress, disturbances and resource limitations can cause changes in FES taxonomic, structural and functional diversity; we provide examples how the ST/STV approach can be used for monitoring these FES characteristics. We show that RS based assessments of FH indicators using the ST/STV approach is a competent, affordable, repetitive and objective technique for monitoring. Even though the possibilities for observing the taxonomic diversity of animal species is limited with RS, the taxonomy of forest tree species can be recorded with RS, even though its accuracy is subject to certain constraints. RS has proved successful for monitoring the impacts from stress on structural and functional diversity. In particular, it has proven to be very suitable for recording the short-term dynamics of stress on FH, which cannot be cost-effectively recorded using in-situ methods. This paper gives an overview of the ST/STV approach, whereas the second paper of this series concentrates on discussing in-situ terrestrial monitoring, in-situ RS approaches and RS sensors and techniques for measuring ST/STV for FH.

  8. Towards operational environmental applications using terrestrial remote sensing

    NARCIS (Netherlands)

    Veldkamp JG; Velde RJ van de; LBG

    1996-01-01

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

  9. History and future of remote sensing technology and education

    Science.gov (United States)

    Colwell, R. N.

    1980-01-01

    A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.

  10. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

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

  11. Fractals and Spatial Methods for Mining Remote Sensing Imagery

    Science.gov (United States)

    Lam, Nina; Emerson, Charles; Quattrochi, Dale

    2003-01-01

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

  12. Remote sensing of growing conditions of rice plants by landsat MSS data and color IR aerial photograph

    International Nuclear Information System (INIS)

    Miyama, K.; Sato, H.

    1985-01-01

    Remote sensing is the technique of deriving information about an object or a phenomenon on the ground without actually coming in contact with it. The quantity measured in remote sensing systems is the electromagnetic energy which is reflected or radiated from the object of interest. Therefore, the remote sensing data rare usually collected by the remote-senser on board the airplane or the satellite. This technique is very useful for the measurement or investigation of earth surface conditions, for example, in the field of agriculture, geology, environment, etc., and the practical application of this technique is expected

  13. Teaching remote sensing to elementary students

    Science.gov (United States)

    Jonsson, J.

    I was asked if I could help a local elementary school to set up and operate a weather satellite receiving station. Since I am myself studying Space Engineering at the Luleå University of Technology, I accepted the task. With two fellow students I set out to investigate the receiving station. To be honest, we did not know much about satellite receiving systems ourselves, since we had only taken general engineering classes so far, but stimulated by our interest in the subject and the challenge to solve a task different from ordinary assignments, we quickly learned how to set up the equipment. After a while we could receive quite decent pictures from the NOAA polar orbiting weather satellites. The pupils, focusing on grades 5-6, did not have much previous knowledge in physics and technology, and - quite naturally - did not know much about space and satellites. At their age it is probably difficult to understand the services satellites provide us with high up in the sky, watching the earth and the weather. On the other hand, this was part of the challenge we accepted. It was intriguing to observe how the pupils adapted to the situation, initially perhaps uneasy with it, but then enthusiastic about learning how to operate the equipment. They could see what happened if they did something differently. They could compare the actual weather outside the window and the weather images on the screen in front of them. The efforts invested in understanding the system were rewarded by the results achieved. The pupils will be able to use this system in many areas in their education. As it turned out, it was easy to operate when it was once properly set up. Through this system, the students are exposed to ,,hands-on'' education and experience with meteorology, remote sensing, geography and many other areas and applications. It is our hope that we may contribute to make these young pupils aware of the vast knowledge available to them through their efforts at school, to make them

  14. Remote sensing using MIMO systems

    Science.gov (United States)

    Bikhazi, Nicolas; Young, William F; Nguyen, Hung D

    2015-04-28

    A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.

  15. Best practices in Remote Sensing for REDD+

    DEFF Research Database (Denmark)

    Dons, Klaus; Grogan, Kenneth

    2012-01-01

    due to steep terrain, • phenological gradients across natural, agricultural and forestry ecosystems including plantations and • the need to serve the REDD-specific context of deforestation and forest degradation across spatial and temporal scales make remote sensing based approaches particularly...... and governance, and deforestation and forest degradation processes. The second part summarizes the available literature on remote sensing based good practices for REDD. It largely draws from the documents of the Intergovernmental Panel on Climate Change (IPCC), the United Nations Framework Convention on Climate...... Change (UNFCCC) and the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) methods sourcebook. These documents provide a generic framework on methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses...

  16. Advances in Remote Sensing of Flooding

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2015-11-01

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

  17. NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

    Science.gov (United States)

    Chirayath, Ved

    2018-01-01

    We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and

  18. Photographic Remote Sensing of Sick Citrus Trees

    Science.gov (United States)

    Gausman, H. W.

    1971-01-01

    Remote sensing with infrared color aerial photography (Kodak Ektachrome Infrared Aero 8443 film) for detecting citrus tree anomalies is described. Illustrations and discussions are given for detecting nutrient toxicity symptoms, for detecting foot rot and sooty mold fungal diseases, and for distinguishing among citrus species. Also, the influence of internal leaf structure on light reflectance, transmittance, and absorptance are considered; and physiological and environmental factors that affect citrus leaf light reflectance are reviewed briefly and illustrated.

  19. An Overview of GNSS Remote Sensing

    Science.gov (United States)

    2014-08-27

    vital information for studies of deep-ocean circulation and boundary currents, the mid-ocean gyres, tsunamis and ocean currents on synoptic to global...tracks associated with four GPS satellites, colourised by reflected signal power. The picture was generated by Google Earth and GPS Visualizer. Yu et al...not from satellite plat- forms. There are no geodetic services producing GNSS remote sensing products on a continuous, synoptic basis. From the IAG’s

  20. Benchmarking of Remote Sensing Segmentation Methods

    Czech Academy of Sciences Publication Activity Database

    Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.

    2015-01-01

    Roč. 8, č. 5 (2015), s. 2240-2248 ISSN 1939-1404 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : benchmark * remote sensing segmentation * unsupervised segmentation * supervised segmentation Subject RIV: BD - Theory of Information Impact factor: 2.145, year: 2015 http://library.utia.cas.cz/separaty/2015/RO/haindl-0445995.pdf

  1. Application of Remote Sensing in Agriculture

    Science.gov (United States)

    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.

  2. A Review of Wetland Remote Sensing.

    Science.gov (United States)

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

    2017-04-05

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

  3. Remote Sensing of Landscapes with Spectral Images

    Science.gov (United States)

    Adams, John B.; Gillespie, Alan R.

    2006-05-01

    Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures

  4. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

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

  5. Remote sensing methods for power line corridor surveys

    Science.gov (United States)

    Matikainen, Leena; Lehtomäki, Matti; Ahokas, Eero; Hyyppä, Juha; Karjalainen, Mika; Jaakkola, Anttoni; Kukko, Antero; Heinonen, Tero

    2016-09-01

    To secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments

  6. Remote sensing and geo processing techniques applied to decision making for the implantation of wind parking; Tecnicas de sensoriamento remoto e geoprocessamento aplicadas no auxilio a tomada de decisao na implantacao de parques eolicos

    Energy Technology Data Exchange (ETDEWEB)

    Lahm, Regis Alexandre [Pontificia Univ. Catolica do Rio Grande do Sul (PUCRS), Porto Alegre, RS (Brazil). Lab. de Tratamento de Imagens e Geoprocessamento (LTIG); Ale, Jorge Antonio Villar [Pontificia Univ. Catolica do Rio Grande do Sul (PUCRS), Porto Alegre, RS (Brazil). Nucleo Tecnologico de Energia e Meio Ambiente (NUTEMA); Bottezini, Dilane [Pontificia Univ. Catolica do Rio Grande do Sul (PUCRS), Porto Alegre, RS (Brazil)

    2004-07-01

    The paper presents a methodology for decision making help for wind turbines positioning on previously selected sites and presenting potential for wind parking installation. 1:50,000 scale elaborated by DSG topographic charts and also orbital image from the Landsat 7 ETM were used. Based on those materials and through remote sensing and geo processing a digital relief model and rugosity charts were elaborated.

  7. Water Quality Assessment using Satellite Remote Sensing

    Science.gov (United States)

    Haque, Saad Ul

    2016-07-01

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

  8. Hyperspectral remote sensing analysis of short rotation woody crops grown with controlled nutrient and irrigation treatments

    Energy Technology Data Exchange (ETDEWEB)

    Im, Jungho; Jensen, John R.; Coleman, Mark; Nelson, Eric

    2009-08-01

    Abstract - Hyperspectral remote sensing research was conducted to document the biophysical and biochemical characteristics of controlled forest plots subjected to various nutrient and irrigation treatments. The experimental plots were located on the Savannah River Site near Aiken, SC. AISA hyperspectral imagery were analysed using three approaches, including: (1) normalized difference vegetation index based simple linear regression (NSLR), (2) partial least squares regression (PLSR) and (3) machine-learning regression trees (MLRT) to predict the biophysical and biochemical characteristics of the crops (leaf area index, stem biomass and five leaf nutrients concentrations). The calibration and cross-validation results were compared between the three techniques. The PLSR approach generally resulted in good predictive performance. The MLRT approach appeared to be a useful method to predict characteristics in a complex environment (i.e. many tree species and numerous fertilization and/or irrigation treatments) due to its powerful adaptability.

  9. An overview of ICA (independent component analysis) applications in remote sensed data

    Science.gov (United States)

    Chen, C. H.; Wang, Zhenhai

    2005-10-01

    ICA has been a well studied subject in recent years. Its implementation may employ neural networks or adaptive learning techniques. In contrast to PCA, the objective of ICA is to extract components with high-order statistical independence. The concept and process of deriving the independent components have had motivated the development of many mathematical algorithms. In fact it is not necessary to achieve perfect statistical independence in this process. ICA is particularly, perhaps uniquely also, useful in blind source separation problem which is to determine from the received signals the original signals from different physical sources which are considered as independent. ICA has significant impact on many applications such as in remote sensing, medical testing, face recognition, direction of arrival estimatin and other areas The purpose of this paper is to examine some of these applications including SAR images, sonar signals, and exploration seismic data.

  10. Remote Sensing and Capacity Building to Improve Food Security

    Science.gov (United States)

    Husak, G. J.; Funk, C. C.; Verdin, J. P.; Rowland, J.; Budde, M. E.

    2012-12-01

    The Famine Early Warning Systems Network (FEWS NET) is a U.S. Agency for International Development (USAID) supported project designed to monitor and anticipate food insecurity in the developing world, primarily Africa, Central America, the Caribbean and Central Asia. This is done through a network of partners involving U.S. government agencies, universities, country representatives, and partner institutions. This presentation will focus on the remotely sensed data used in FEWS NET activities and capacity building efforts designed to expand and enhance the use of FEWS NET tools and techniques. Remotely sensed data are of particular value in the developing world, where ground data networks and data reporting are limited. FEWS NET uses satellite based rainfall and vegetation greenness measures to monitor and assess food production conditions. Satellite rainfall estimates also drive crop models which are used in determining yield potential. Recent FEWS NET products also include estimates of actual evapotranspiration. Efforts are currently underway to assimilate these products into a single tool which would indicate areas experiencing abnormal conditions with implications for food production. FEWS NET is also involved in a number of capacity building activities. Two primary examples are the development of software and training of institutional partners in basic GIS and remote sensing. Software designed to incorporate rainfall station data with existing satellite-derived rainfall estimates gives users the ability to enhance satellite rainfall estimates or long-term means, resulting in gridded fields of rainfall that better reflect ground conditions. Further, this software includes a crop water balance model driven by the improved rainfall estimates. Finally, crop parameters, such as the planting date or length of growing period, can be adjusted by users to tailor the crop model to actual conditions. Training workshops in the use of this software, as well as basic GIS and

  11. Assessing soil carbon stocks under pastures through orbital remote sensing

    Directory of Open Access Journals (Sweden)

    Gabor Gyula Julius Szakács

    2011-10-01

    Full Text Available The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI measured in the field (LAIfield and derived by satellite (LAIsatellite as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+ sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804 and LAIsatellite (R² = 0.9812 was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.

  12. [Preliminary exploring of hyperspectral remote sensing experiment for nitrogen and phosphorus in water].

    Science.gov (United States)

    Gong, Shao-Qi; Huang, Jia-Zhu; Li, Yun-Mei; Lu, Wan-Ning; Wang, Hai-Jun; Wang, Guo-Xiang

    2008-04-01

    The content of nitrogen and phosphorus in the waters is an important index to measure water quality, and the technique of remote sensing plays a large role in monitoring the change in environment. The reflectance spectra of nitrogen and phosphorus with different concentrations were measured to discover their special features under pure water condition in the laboratory by hyperspectral remote sensing technique. The result shows that nitrogen has reflectance peaks at 404 and 477 nm, and phosphorus at 350 nm, and these reflectance peaks have a good correlation with their concentrations, then a quantitative retrieval model was deduced for nitrogen and phosphorus based on that. These results will lay an important basis for further monitoring nitrogen and phosphorus by remote sensing technique in the big inland lakes, reservoirs and rivers.

  13. Remote Sensing Tertiary Education Meets High Intensity Interval Training

    Science.gov (United States)

    Joyce, K. E.; White, B.

    2015-04-01

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

  14. Preface to the special issue of JVGR, Pattern to Process: Remotely Sensed Observations of Volcanic Deposits and Their Implications for Surface Processes

    Science.gov (United States)

    Whelley, Patrick L.; Kerber, Laura; de Silva, Shanaka

    2017-08-01

    Volcanic deposit morphology contains information about flow emplacement, deformation, and erosion. When careful observations and measurements of deposits and features are made, some eruptive and/or flow parameters can be estimated. In addition, degradation and burial mechanisms can be assessed. Such interpretations are crucial to understanding planetary surfaces but remain challenging on bodies beyond Earth. Since the early days of civilian satellite observations, it has been recognized that remote sensing data are well suited for morphologic investigations because it is in plan view that the scale and context of volcanic deposits can be observed. Furthermore, remote sensing techniques that are effective for investigating terrestrial volcanoes can be adapted for use on other planets. However, limitations persist.

  15. Linking climate change education through the integration of a kite-borne remote sensing system

    Directory of Open Access Journals (Sweden)

    Yichun Xie

    2014-09-01

    Full Text Available A majority of secondary science teachers are found to include the topic of climate change in their courses. However, teachers informally and sporadically discuss climate change and students rarely understand the underlying scientific concepts. The project team developed an innovative pedagogical approach, in which teachers and students learn climate change concepts by analyzing National Aeronautics and Space Administration (NASA global data collected through satellites and by imitating the NASA data collection process through NASA Airborne Earth Research Observation Kites And Tethered Systems (AEROKATS, a kite-borne remote sensing system. Besides AEROKATS, other major components of this system include a web-collection of NASA and remote sensing data and related educational resources, project-based learning for teacher professional development, teacher and student field trips, iOS devices, smart field data collector apps, portable weather stations, probeware, and a virtual teacher collaboratory supported with a GIS-enabled mapping portal. Three sets of research instruments, the NASA Long-Term Experience –Educator End of Event Survey, the Teacher End of Project Survey, and the pre-and-post-Investigating Climate Change and Remote Sensing (ICCARS project student exams, are adapted to study the pedagogical impacts of the NASA AEROKATS remote sensing system. These findings confirm that climate change education is more effective when both teachers and students actively participate in authentic scientific inquiry by collecting and analyzing remote sensing data, developing hypotheses, designing experiments, sharing findings, and discussing results.

  16. A Ground Systems Template for Remote Sensing Systems

    Science.gov (United States)

    McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

    2002-10-01

    Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS.

  17. A ground systems template for remote sensing systems

    International Nuclear Information System (INIS)

    McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

    2002-01-01

    Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS

  18. Modeling Global Urbanization Supported by Nighttime Light Remote Sensing

    Science.gov (United States)

    Zhou, Y.

    2015-12-01

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

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

    Science.gov (United States)

    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.

  20. Improvements in agricultural water decision support using remote sensing

    Science.gov (United States)

    Marshall, M. T.

    2012-12-01

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

  1. Analysis of remote sensing data for evaluation of vegetation resources

    Science.gov (United States)

    1970-01-01

    Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.

  2. Scalability Issues for Remote Sensing Infrastructure: A Case Study

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-04-01

    Full Text Available For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging. Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

  3. STANDARDIZING QUALITY ASSESSMENT OF FUSED REMOTELY SENSED IMAGES

    Directory of Open Access Journals (Sweden)

    C. Pohl

    2017-09-01

    Full Text Available The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

  4. Standardizing Quality Assessment of Fused Remotely Sensed Images

    Science.gov (United States)

    Pohl, C.; Moellmann, J.; Fries, K.

    2017-09-01

    The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

  5. Scalability Issues for Remote Sensing Infrastructure: A Case Study.

    Science.gov (United States)

    Liu, Yang; Picard, Sean; Williamson, Carey

    2017-04-29

    For the past decade, a team of University of Calgary researchers has operated a large "sensor Web" to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system's memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

  6. OSIS: remote sensing code for estimating aerosol optical properties in urban areas from very high spatial resolution images.

    Science.gov (United States)

    Thomas, Colin; Briottet, Xavier; Santer, Richard

    2011-10-01

    The achievement of new satellite or airborne remote sensing instruments enables the more precise study of cities with metric spatial resolutions. For studies such as the radiative characterization of urban features, knowledge of the atmosphere and particularly of aerosols is required to perform first an atmospheric compensation of the remote sensing images. However, to our knowledge, no efficient aerosol characterization technique adapted both to urban areas and to very high spatial resolution images has yet been developed. The goal of this paper is so to present a new code to characterize aerosol optical properties, OSIS, adapted to urban remote sensing images of metric spatial resolution acquired in the visible and near-IR spectral domains. First, a new aerosol characterization method based on the observation of shadow/sun transitions is presented, offering the advantage to avoid the assessment of target reflectances. Its principle and the modeling of the signal used to solve the retrieval equation are then detailed. Finally, a sensitivity study of OSIS from synthetic images simulated by the radiative transfer code AMARTIS v2 is also presented. This study has shown an intrinsic precision of this tool of Δτ(a)=0.1.τ(a) ± (0.02 + 0.4.τ(a)) for retrieval of aerosol optical thicknesses. This study shows that OSIS is a powerful tool for aerosol characterization that has a precision similar to satellite products for the aerosol optical thicknesses retrieval and that can be applied to every very high spatial resolution instrument, multispectral or hyperspectral, airborne or satellite.

  7. Estimating reforestation by means of remote sensing

    Science.gov (United States)

    Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.

    1981-01-01

    LANDSAT imagery at the scale of 1:250.000 and obtained from bands 5 and 7 as well as computer compatible tapes were used to evaluate the effectiveness of remotely sensed orbital data in inventorying forests in a 462,100 area of Brazil emcompassing the cities of Ribeirao, Altinopolis Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Santa Rita do Passa Quatro, and Santa Rosa do Viterbo. Visual interpretation of LANDSAT imagery shows that 37,766 hectares (1977) and 38,003.75 hectares (1979) were reforested areas of pine and eucalyptus species. An increment of 237.5 hectares was found during this two-year time lapse.

  8. Remote sensing and actuation using unmanned vehicles

    CERN Document Server

    Chao, Haiyang

    2012-01-01

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

  9. Remote sensing of coastal and ocean studies

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.

    , in modern space sciences, its usage is restricted to mean detection of features at or near the earth's surface from space using electromagnetic radiation. Remote sensing is often considered as opposite of astronomy. In astronomy, we observe the space from... the entire area in one day, nor afford 100 ships stationed in such an area (one ship per 10 sq. km.). Satellite on the other hand, circle the entire earth in a couple of hours and simultaneously send all observationa to a ground receiving station for online...

  10. The Federal Oil Spill Team for Emergency Response Remote Sensing (FOSTERRS)

    Science.gov (United States)

    Stough, T.; Jones, C. E.; Leifer, I.; Lindsay, F. E.; Murray, J. J.; Ramirez, E. M.; Salemi, A.; Streett, D.

    2014-12-01

    Oil spills can cause enormous ecological and economic devastation, necessitating application of the best science and technology available, for which remote sensing plays a critical role in detection and monitoring of oil spills. The FOSTERRS interagency working group seeks to ensure that during an oil spill, remote sensing assets (satellite/aircraft) and analysis techniques are quickly, effectively and seamlessly available to oil spills responders. FOSTERRS enables cooperation between agencies with core environmental remote sensing assets and capabilities and academic and industry experts to act as an oil spill remote sensing information clearinghouse. The US government and its collaborators have a broad variety of aircraft and satellite sensors, imagery interrogation techniques and other technology that can provide indispensable remote sensing information to agencies, emergency responders and the public during an oil spill. Specifically, FOSTERRS will work to ensure that (1) suitable aircraft and satellite imagery and radar observations are quickly made available in a manner that can be integrated into oil spill detection and mitigation efforts, (2) existing imagery interrogation techniques are in the hands of those who will provide the 24 x 7 operational support and (3) efforts are made to develop new technology where the existing techniques do not provide oil spills responders with important information they need. The FOSTERRS mission goal places it in an ideal place for identification of critical technological needs, and identifying bottlenecks in technology acceptance. The core FOSTERRS team incorporates representation for operations and science for agencies with relevant instrumental and platform assets (NASA, NOAA, USGS, NRL). FOSTERRS membership will open to a wide range of end-user agencies and planned observer status from industry and academic experts, and eventually international partners. Through these collaborations, FOSTERRS facilitates interagency

  11. End-to-End Airplane Detection Using Transfer Learning in Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Zhong Chen

    2018-01-01

    Full Text Available Airplane detection in remote sensing images remains a challenging problem due to the complexity of backgrounds. In recent years, with the development of deep learning, object detection has also obtained great breakthroughs. For object detection tasks in natural images, such as the PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning VOC (Visual Object Classes Challenge, the major trend of current development is to use a large amount of labeled classification data to pre-train the deep neural network as a base network, and then use a small amount of annotated detection data to fine-tune the network for detection. In this paper, we use object detection technology based on deep learning for airplane detection in remote sensing images. In addition to using some characteristics of remote sensing images, some new data augmentation techniques have been proposed. We also use transfer learning and adopt a single deep convolutional neural network and limited training samples to implement end-to-end trainable airplane detection. Classification and positioning are no longer divided into multistage tasks; end-to-end detection attempts to combine them for optimization, which ensures an optimal solution for the final stage. In our experiment, we use remote sensing images of airports collected from Google Earth. The experimental results show that the proposed algorithm is highly accurate and meaningful for remote sensing object detection.

  12. Semi-supervised classification for hyperspectral remote sensing image based on PCA and kernel FCM algorithm

    Science.gov (United States)

    Liu, Xiaofang; He, Binbin; Li, Xiaowen

    2008-10-01

    Hyperspectral remote sensing image classification is a challenging task in remote sensing applications because this image always has some information redundancy and is easy to be affected by noise or lack of the separability. A semi-supervised classification method based on principal component analysis (PCA) method and kernel fuzzy C-means (KFCM) algorithm for hyperspectral remote sensing image is proposed in this paper. First the PCA method finds an effective representation of spectral signature in a reduced dimensional feature space. Then a semi-supervised kernel-based FCM algorithm, called SSKFCM algorithm by introducing semi-supervised learning technique and the kernel trick simultaneously into conventional fuzzy C-means algorithm, is introduced to classify the feature vectors. Finally numerical experiments are conducted on a hyperspectral remote sensing image that provides digital images of 80 spectral bands with wavelength rang from 455 nm to 1642 nm. Classification performance is estimated by classification accuracy and kappa coefficient. The simulation results show that the proposed approach can be effectively applied to hyperspectral remote sensing image classification.

  13. INTERACTIVE CHANGE DETECTION USING HIGH RESOLUTION REMOTE SENSING IMAGES BASED ON ACTIVE LEARNING WITH GAUSSIAN PROCESSES

    Directory of Open Access Journals (Sweden)

    H. Ru

    2016-06-01

    Full Text Available Although there have been many studies for change detection, the effective and efficient use of high resolution remote sensing images is still a problem. Conventional supervised methods need lots of annotations to classify the land cover categories and detect their changes. Besides, the training set in supervised methods often has lots of redundant samples without any essential information. In this study, we present a method for interactive change detection using high resolution remote sensing images with active learning to overcome the shortages of existing remote sensing image change detection techniques. In our method, there is no annotation of actual land cover category at the beginning. First, we find a certain number of the most representative objects in unsupervised way. Then, we can detect the change areas from multi-temporal high resolution remote sensing images by active learning with Gaussian processes in an interactive way gradually until the detection results do not change notably. The artificial labelling can be reduced substantially, and a desirable detection result can be obtained in a few iterations. The experiments on Geo-Eye1 and WorldView2 remote sensing images demonstrate the effectiveness and efficiency of our proposed method.

  14. Ontology-based classification of remote sensing images using spectral rules

    Science.gov (United States)

    Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

    2017-05-01

    Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

  15. Remote sensing water observation for supporting Lake Victoria weed management.

    Science.gov (United States)

    Cavalli, Rosa Maria; Laneve, Giovanni; Fusilli, Lorenzo; Pignatti, Stefano; Santini, Federico

    2009-05-01

    This paper aims to assess the suitability of remote sensing for enhancing the management of water body resources and for providing an inexpensive way to gather, on a wide area, weed infestation extent and optical parameter linked to the water body status. Remotely sensed satellite images and ancillary ground true data were used to produce land cover maps, trough classification techniques, and water compounds maps, applying radiative transfer models. The study proposed within the framework of the cooperation between Italian Foreign Affair Ministry (through the University of Rome) and Kenyan Authorities has been carried out on the Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few years environmental challenges and human impact have perturbed the ecological balance affecting the biodiversity. The objective of this research study is to define the thematic products, retrievable from satellite images, like weed abundance maps and water compound concentrations. These products, if provided with an appropriate time frequency, are useful to identify the preconditions for the occurrence of hazard events like abnormal macrophyte proliferation and to develop an up-to-date decision support system devoted to an apprised territory, environment and resource management.

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

    Directory of Open Access Journals (Sweden)

    IACOB I. CIPRIAN

    2012-11-01

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

  17. Underwater topography acquired by remote sensing based on SOFM

    Science.gov (United States)

    Zhao, Jianhu; Zhou, Fengnian; Zhang, Hongmei; Li, Juanjuan

    2008-12-01

    In large-scope marine investigation, the traditional bathymetric measurement can not meet the requirement of rapid data acquisition with lower cost of financial and material resources, while remote sensing (RS) technology provides a perfect way in the work. RS can not only provide quickly and efficiently the information of underwater topography with respect to the traditional method, but also present corresponding underwater topography with different-period RS images. In this paper, we depict in detail the procedures and some key techniques in acquiring underwater topography by remote sensing inversion technology based on self-organization feature mapping (SOFM). Firstly, we introduce some basic theories about the acquisition of underwater topography by the RS inversion technology. Besides, we discuss the data acquisition and preparation in the work. Moreover, we implement correlation analysis and find out the sensitive bands used for building RS inversion model. In virtue of SOFM, we construct the mapping relation between water depth and the reflectivity of sensitive band in the studied area, and test the it in two experimental water areas. The model achieves satisfying accuracy and can meet the requirement of given bathymetric scale. Finally the mapping relation is used for the water depth inversion in the studied water area. We also use the water depth from the model to draw the underwater topographic map in the water area.

  18. Use of Remote Sensing Products for the SERVIR Project

    Science.gov (United States)

    Policelli, Frederick S.

    2010-01-01

    The United Nations University (UNU) estimates that floods presently impacts greater than 520 million people per year worldwide, resulting in up to 25,000 annual deaths, extensive homelessness, disaster-induced disease, crop and livestock damage, famine, and other serious harm. Meanwhile, aid agencies such as the International Federation of Red Cross and Red Crescent Societies (IFRC) are increasingly seeking better information concerning flood hazards in order to plan for and help mitigate the effects of damaging floods. There is fertile ground to continue development of better remote sensing and modeling techniques to help manage flood related disasters. Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid flood mapping and distribution, and e) validation of flood forecasting and detection products.

  19. Atmospheric Radiative Transfer for Satellite Remote Sensing: Validation and Uncertainty

    Science.gov (United States)

    Marshak, Alexander

    2007-01-01

    My presentation will begin with the discussion of the Intercomparison of three-dimensional (3D) Radiative Codes (13RC) project that has been started in 1997. I will highlight the question of how well the atmospheric science community can solve the 3D radiative transfer equation. Initially I3RC was focused only on algorithm intercomparison; now it has acquired a broader identity providing new insights and creating new community resources for 3D radiative transfer calculations. Then I will switch to satellite remote sensing. Almost all radiative transfer calculations for satellite remote sensing are one-dimensional (1D) assuming (i) no variability inside a satellite pixel and (ii) no radiative interactions between pixels. The assumptions behind the 1D approach will be checked using cloud and aerosol data measured by the MODerate Resolution Imaging Spectroradiometer (MODIS) on board of two NASA satellites TERRA and AQUA. In the discussion, I will use both analysis technique: statistical analysis over large areas and time intervals, and single scene analysis to validate how well the 1D radiative transfer equation describes radiative regime in cloudy atmospheres.

  20. Some Insights on Grassland Health Assessment Based on Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dandan Xu

    2015-01-01

    Full Text Available Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  1. Some insights on grassland health assessment based on remote sensing.

    Science.gov (United States)

    Xu, Dandan; Guo, Xulin

    2015-01-29

    Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  2. Automatic Registration and Mosaicking System for Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    Emiliano Castejon

    2006-04-01

    Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.

  3. Radar and optical remote sensing in offshore domain to detect, characterize, and quantify ocean surface oil slicks

    Science.gov (United States)

    Angelliaume, S.; Ceamanos, X.; Viallefont-Robinet, F.; Baqué, R.; Déliot, Ph.; Miegebielle, V.

    2017-10-01

    Radar and optical sensors are operationally used by authorities or petroleum companies for detecting and characterizing maritime pollution. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as the oil real fraction, which is critical for both exploration purposes and efficient cleanup operations. Today state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI, the airborne system developed by ONERA, during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this data set lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the electromagnetic spectrum. Specific processing techniques have been developed in order to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows to estimate slick surface properties such as the spatial abundance of oil and the relative concentration of hydrocarbons on the sea surface.

  4. Remote sensing programs and courses in engineering and water resources

    Science.gov (United States)

    Kiefer, R. W.

    1981-01-01

    The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

  5. Online sparse representation for remote sensing compressed-sensed video sampling

    Science.gov (United States)

    Wang, Jie; Liu, Kun; Li, Sheng-liang; Zhang, Li

    2014-11-01

    Most recently, an emerging Compressed Sensing (CS) theory has brought a major breakthrough for data acquisition and recovery. It asserts that a signal, which is highly compressible in a known basis, can be reconstructed with high probability through sampling frequency which is well below Nyquist Sampling Frequency. When applying CS to Remote Sensing (RS) Video imaging, it can directly and efficiently acquire compressed image data by randomly projecting original data to obtain linear and non-adaptive measurements. In this paper, with the help of distributed video coding scheme which is a low-complexity technique for resource limited sensors, the frames of a RS video sequence are divided into Key frames (K frames) and Non-Key frames (CS frames). In other words, the input video sequence consists of many groups of pictures (GOPs) and each GOP consists of one K frame followed by several CS frames. Both of them are measured based on block, but at different sampling rates. In this way, the major encoding computation burden will be shifted to the decoder. At the decoder, the Side Information (SI) is generated for the CS frames using traditional Motion-Compensated Interpolation (MCI) technique according to the reconstructed key frames. The over-complete dictionary is trained by dictionary learning methods based on SI. These learning methods include ICA-like, PCA, K-SVD, MOD, etc. Using these dictionaries, the CS frames could be reconstructed according to sparse-land model. In the numerical experiments, the reconstruction performance of ICA algorithm, which is often evaluated by Peak Signal-to-Noise Ratio (PSNR), has been made compared with other online sparse representation algorithms. The simulation results show its advantages in reducing reconstruction time and robustness in reconstruction performance when applying ICA algorithm to remote sensing video reconstruction.

  6. Some problems on remote sensing geology for uranium prospecting

    International Nuclear Information System (INIS)

    Yang Tinghuai.

    1988-01-01

    Remote sensing is a kind of very effective method which can be used in all stages of geological prospecting. Geological prospecting with remote sensing method must be based on different genetic models of ore deposits, characteristics of geology-landscape and comprehensive analysis for geophysical and geochemical data, that is, by way of conceptual model prospecting. The prospecting results based on remote sensing geology should be assessed from three aspects such as direct, indirect and potential ones

  7. An Overview on Data Mining of Nighttime Light Remote Sensing

    Directory of Open Access Journals (Sweden)

    LI Deren

    2015-06-01

    Full Text Available When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future

  8. Model-based acoustic remote sensing of seafloor characteristics

    Digital Repository Service at National Institute of Oceanography (India)

    De, Ch.; Chakraborty, B.

    =UTF-8 3868 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 49, NO. 10, OCTOBER 2011 Model-Based Acoustic Remote Sensing of Seafloor Characteristics Chanchal De and Bishwajit Chakraborty, Member, IEEE Abstract—The characterization... of the estimated values of seafloor roughness spectrum parameters with the values of sediment mean grain size are compared with published information available in the literature. Index Terms—Acoustic remote sensing, backscatter model, echo envelope, inversion, mean...

  9. Coastal remote sensing – towards integrated coastal research and management

    CSIR Research Space (South Africa)

    Lück-Vogel, Melanie

    2012-10-01

    Full Text Available million (UNESCO, 2009). The destructive forces of storms mainly results from the impact of: ? Waves, leading to shoreline erosion ? Wind ? Flooding. Coastal areas which are low-lying and sandy are particularly vulnerable, as can be found along most... such as shoreline erosion or flooding. Coastal remote sensing, as we define it, is bridging the gap between classic terrestrial and marine remote sensing. However, to date, coastal remote sensing competency and applications are very scarce and undeveloped...

  10. Needs and emerging trends of remote sensing

    Science.gov (United States)

    McNair, Michael

    2014-06-01

    From the earliest need to be able to see an enemy over a hill to sending semi-autonomous platforms with advanced sensor packages out into space, humans have wanted to know more about what is around them. Issues of distance are being minimized through advances in technology to the point where remote control of a sensor is useful but sensing by way of a non-collocated sensor is better. We are not content to just sense what is physically nearby. However, it is not always practical or possible to move sensors to an area of interest; we must be able to sense at a distance. This requires not only new technologies but new approaches; our need to sense at a distance is ever changing with newer challenges. As a result, remote sensing is not limited to relocating a sensor but is expanded into possibly deducing or inferring from available information. Sensing at a distance is the heart of remote sensing. Much of the sensing technology today is focused on analysis of electromagnetic radiation and sound. While these are important and the most mature areas of sensing, this paper seeks to identify future sensing possibilities by looking beyond light and sound. By drawing a parallel to the five human senses, we can then identify the existing and some of the future possibilities. A further narrowing of the field of sensing causes us to look specifically at robotic sensing. It is here that this paper will be directed.

  11. Remote sensing applied in uranium exploration

    International Nuclear Information System (INIS)

    Conradsen, K.; Nilsson, G.; Thyrsted, T.

    1985-01-01

    A research project, aiming at investigation the use of remote sensing in uranium exploration, has been accomplished on data from South Greenland. During the project, analyses have been done on pure remote sensing data (Landsat MSS) and on integrated data of various types, including geochemical, aeromagnetic, radiometric and geological data in addition to the MSS data. Ratioing, factor analysis and discriminant analysis were used for enhancement of colour anomalies which correspond to oxidation zones. Some of the anomalies coincide with U and Nb mineralizations. Lineaments were mapped visually from photoprints, digitized and analysed statistically. A sinusoidal model could be applied to the general directional frequency distribution and was used to define ten classes of significant directions. Three of these directions were of major geological significance. Thus some of the major alkaline intrusions are situated at the intersections of some of the lineaments, a particular NE-SW trending lineament coincides with a geochemical boundary and pitchblende occurrences may be related to a WNW-ESE direction. The various types of data set were brought onto format of the Landsat images and collected in a data base. Representing three different types of data (Landsat MSS-band 7, aeromagnetic data and the geochemical Fe-content of stream sediments) on basis of intensity, hue and saturation revealed new features among which can be mentioned a possible indication of a subsurface continuation of one of the major alkaline intrusions. (author)

  12. Remote sensing application for property tax evaluation

    Science.gov (United States)

    Jain, Sadhana

    2008-02-01

    This paper presents a study for linking remotely sensed data with property tax related issues. First, it discusses the key attributes required for property taxation and evaluates the capabilities of remote sensing technology to measure these attributes accurately at parcel level. Next, it presents a detailed case study of six representative wards of different characteristics in Dehradun, India, that illustrates how measurements of several of these attributes supported by field survey can be combined to address the issues related to property taxation. Information derived for various factors quantifies the property taxation contributed by an average dwelling unit of the different income groups. Results show that the property tax calculated in different wards varies between 55% for the high-income group, 32% for the middle-income group, 12% for the low-income group and 1% for squatter units. The study concludes that higher spatial resolution satellite data and integrates social survey helps to assess the socio-economic status of the population for tax contribution purposes.

  13. Wetlands Evapotranspiration Using Remotely Sensed Solar Radiation

    Science.gov (United States)

    Jacobs, J. M.; Myers, D. A.; Anderson, M. C.

    2001-12-01

    The application of remote sensing methods to estimate evapotranspiration has the advantage of good spatial resolution and excellent spatial coverage, but may have the disadvantage of infrequent sampling and considerable expense. The GOES satellites provide enhanced temporal resolution with hourly estimates of solar radiation and have a spatial resolution that is significantly better than that available from most ground-based pyranometer networks. As solar radiation is the primary forcing variable in wetland evapotranspiration, the opportunity to apply GOES satellite data to wetland hydrologic analyses is great. An accuracy assessment of the remote sensing product is important and the subsequent validation of the evapotranspiration estimates are a critical step for the use of this product. A wetland field experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. Evapotranspiration and other surface energy balance components of a wet prairie community dominated by Panicum hemitomon (maiden cane), Ptilimnium capillaceum (mock bishop's weed), and Eupatorium capillifolium (dog fennel) were investigated. Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The satellite solar radiation, derived net radiation and estimated evapotranspiration estimates were compared to measured data at 30-min intervals and daily times scales.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  15. Remote sensing image segmentation using active contours based on intercorrelation of nonsubsampled contourlet coefficients

    Science.gov (United States)

    Fang, Lingling; Wang, Xianghai; Sun, Yang; Xu, Kainan

    2016-11-01

    Considering that remote sensing images contain rich scale-dependent information and geographical detailed information, segmentation process must be carried out under the multiscale case. The vector-valued C-V active contour model is an effective image segmentation method, but the model cannot segment the nonhomogeneous remote sensing images well. The image processing methods based on nonsubsampled contourlet transform (NSCT) can fully use the detailed information of remote sensing images. The interscale distribution characteristics of NSCT coefficients at finer scale is first analyzed and then a statistical model of signal singularities combining the coefficient correlation between intrascale and interscale is proposed. Based on the above, the vector-valued C-V active contour model is then applied to the statistical characteristics for segmenting images. Consequently, the proposed method can preserve detailed information of images and other desirable properties of active contour model. Numerical examples indicate that the proposed method is very competitive with several state-of-the-art techniques.

  16. Remote sensing in Michigan for land resource management: Highway impact assessment

    Science.gov (United States)

    1972-01-01

    An existing section of M-14 freeway constructed in 1964 and a potential extension from Ann Arbor to Plymouth, Michigan provided an opportunity for investigating the potential uses of remote sensing techniques in providing projective information needed for assessing the impact of highway construction. Remote sensing data included multispectral scanner imagery and aerial photography. Only minor effects on vegetation, soils, and land use were found to have occurred in the existing corridor. Adverse changes expected to take place in the corridor proposed for extension of the freeway can be minimized by proper design of drainage ditches and attention to good construction practices. Remote sensing can be used to collect and present many types of data useful for highway impact assessment on land use, vegetation categories and species, soil properties and hydrologic characteristics.

  17. Practical Approach To Building A Mid-Wave Remote Sensing System

    Energy Technology Data Exchange (ETDEWEB)

    Pyke, Benjamin J. [Univ. of Arizona, Tucson, AZ (United States)

    2017-01-01

    The purpose of this project, Laser Active Transmitter & Receiver (LATR), was to build a mobile ground based remote sensing system that can detect, identify and quantify a specific gaseous species using Differential Absorption LIDAR (DIAL). This thesis project is concerned with the development and field testing of a mid-wave infrared active remote sensing system, capable of identifying and quantifying emissions in the 3.2 – 3.5 micron range. The goal is to give a brief description of what remote sensing is about and the specific technique used to analyze the collected data. The thesis will discuss the transmitter and the associated subsystems used to create the required wavelength, and the receiver used to collect the returns. And finally, the thesis will discuss the process of collecting the data and some of the results from field and lab collections.

  18. Aerospace remote sensing of the coastal zone for water quality and biotic productivity applications

    Science.gov (United States)

    Pritchard, E. B.; Harriss, R. C.

    1981-01-01

    Remote sensing can provide the wide area synoptic coverage of surface waters which is required for studies of such phenomena as river plume mixing, phytoplankton dynamics, and pollutant transport and fate, but which is not obtainable by conventional oceanographic techniques. The application of several remote sensors (aircraftborne and spacecraftborne multispectral scanners, passive microwave radiometers, and active laser systems) to coastal zone research is discussed. Current measurement capabilities (particulates, chlorophyll a, temperature, salinity, ocean dumped materials, other pollutants, and surface winds and roughness) are defined and the results of recent remote sensing experiments conducted in the North Atlantic coastal zone are presented. The future development of remote sensing must rely on an integrated laboratory research program in optical physics. Recent results indicate the potential for separation of particulates into subsets by remote sensors.

  19. Proceedings of the sixth circumpolar symposium on remote sensing of polar environments. CD-ROM ed.

    International Nuclear Information System (INIS)

    Taylor, D.

    2000-09-01

    This international conference focused on the application of remote sensing to monitor morphological and environmental changes in polar environments to better understand the impacts of climatic change. Remote sensing included the use of satellite image mapping, LANDSAT imagery, and digitized aerial photography. The conference was divided into several sessions entitled: (1) techniques, (2) wildlife habitat, (3) regional mapping, (4) environment and climate, (5) geographical information systems (GIS) modeling, (6) geology and geomorphology, (7) snow and ice, and (8) monitoring. The work presented at this conference indicates that remote sensing, photogrammetry, GIS and cartography are cost-effective means to monitor hard to reach polar regions. A total of 27 papers were presented at this conference. Four have been processed separately for inclusion on the database. refs., tabs,. figs

  20. Remote sensing and earthquake risk: A (re)insurance perspective

    Science.gov (United States)

    Smolka, Anselm; Siebert, Andreas

    2013-04-01

    The insurance sector is faced with two issues regarding earthquake risk: the estimation of rarely occurring losses from large events and the assessment of the average annual net loss. For this purpose, knowledge is needed of actual event losses, of the distribution of exposed values, and of their vulnerability to earthquakes. To what extent can remote sensing help the insurance industry fulfil these tasks, and what are its limitations? In consequence of more regular and high-resolution satellite coverage, we have seen earth observation and remote sensing methods develop over the past years to a stage where they appear to offer great potential for addressing some shortcomings of the data underlying risk assessment. These include lack of statistical representativeness and lack of topicality. Here, remote sensing can help in the following areas: • Inventories of exposed objects (pre- and post-disaster) • Projection of small-scale ground-based vulnerability classification surveys to a full inventory • Post-event loss assessment But especially from an insurance point of view, challenges remain. The strength of airborne remote sensing techniques lies in outlining heavily damaged areas where damage is caused by easily discernible structural failure, i.e. total or partial building collapse. Examples are the Haiti earthquake (with minimal insured loss) and the tsunami-stricken areas in the Tohoku district of Japan. What counts for insurers, however, is the sum of monetary losses. The Chile, the Christchurch and the Tohoku earthquakes each caused insured losses in the two-digit billion dollar range. By far the greatest proportion of these insured losses were due to non-structural damage to buildings, machinery and equipment. Even with the Tohoku event, no more than 30% of the total material damage was caused by the tsunami according to preliminary surveys, and this figure includes damage due to earthquake shock which was unrecognisable after the passage of the tsunami

  1. Method of determining forest production from remotely sensed forest parameters

    Science.gov (United States)

    Corey, J.C.; Mackey, H.E. Jr.

    1987-08-31

    A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

  2. [Advances in the research on hyperspectral remote sensing in biodiversity and conservation].

    Science.gov (United States)

    He, Cheng; Feng, Zhong-Ke; Yuan, Jin-Jun; Wang, Jia; Gong, Yin-Xi; Dong, Zhi-Hai

    2012-06-01

    With the species reduction and the habitat destruction becoming serious increasingly, the biodiversity conservation has become one of the hottest topics. Remote sensing, the science of non-contact collection information, has the function of corresponding estimates of biodiversity, building model between species diversity relationship and mapping the index of biodiversity, which has been used widely in the field of biodiversity conservation. The present paper discussed the application of hyperspectral technology to the biodiversity conservation from two aspects, remote sensors and remote sensing techniques, and after, enumerated successful applications for emphasis. All these had a certain reference value in the development of biodiversity conservation.

  3. Satellite Altimetry and SAR Remote Sensing for Monitoring Inundation in the Pantanal Wetland

    Science.gov (United States)

    Dettmering, Denise; Strehl, Franziska; Schwatke, Christian; Seitz, Florian

    2016-08-01

    Large wetlands are an important component of the global water cycle and the knowledge of water flow and storage dynamics within these regions is valuable for many applications such as flood risk assessment and water availability studies. Most of the inundation areas are remote regions without significant infrastructure, especially without in-situ gauging observations. Remote sensing techniques can help to provide highly valuable information for hydrological questions.Combining water level and water extent from different remote sensing sensors allows for the quantification of water volume changes in remote inundation areas.

  4. Array Independent Component Analysis with Application to Remote Sensing

    Science.gov (United States)

    Kukuyeva, Irina A.

    2012-11-01

    There are three ways to learn about an object: from samples taken directly from the site, from simulation studies based on its known scientific properties, or from remote sensing images. All three are carried out to study Earth and Mars. Our goal, however, is to learn about the second largest storm on Jupiter, called the White Oval, whose characteristics are unknown to this day. As Jupiter is a gas giant and hundreds of millions of miles away from Earth, we can only make inferences about the planet from retrieval algorithms and remotely sensed images. Our focus is to find latent variables from the remotely sensed data that best explain its underlying atmospheric structure. Principal Component Analysis (PCA) is currently the most commonly employed technique to do so. For a data set with more than two modes, this approach fails to account for all of the variable interactions, especially if the distribution of the variables is not multivariate normal; an assumption that is rarely true of multispectral images. The thesis presents an overview of PCA along with the most commonly employed decompositions in other fields: Independent Component Analysis, Tucker-3 and CANDECOMP/PARAFAC and discusses their limitations in finding unobserved, independent structures in a data cube. We motivate the need for a novel dimension reduction technique that generalizes existing decompositions to find latent, statistically independent variables for one side of a multimodal (number of modes greater than two) data set while accounting for the variable interactions with its other modes. Our method is called Array Independent Component Analysis (AICA). As the main question of any decomposition is how to select a small number of latent variables that best capture the structure in the data, we extend the heuristic developed by Ceulemans and Kiers in [10] to aid in model selection for the AICA framework. The effectiveness of each dimension reduction technique is determined by the degree of

  5. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

    OpenAIRE

    West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-01-01

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tama...

  6. Remote sensing as a tool for estimating soil erosion potential

    Science.gov (United States)

    Morris-Jones, D. R.; Morgan, K. M.; Kiefer, R. W.

    1979-01-01

    The Universal Soil Loss Equation is a frequently used methodology for estimating soil erosion potential. The Universal Soil Loss Equation requires a variety of types of geographic information (e.g. topographic slope, soil erodibility, land use, crop type, and soil conservation practice) in order to function. This information is traditionally gathered from topographic maps, soil surveys, field surveys, and interviews with farmers. Remote sensing data sources and interpretation techniques provide an alternative method for collecting information regarding land use, crop type, and soil conservation practice. Airphoto interpretation techniques and medium altitude, multi-date color and color infrared positive transparencies (70mm) were utilized in this study to determine their effectiveness for gathering the desired land use/land cover data. Successful results were obtained within the test site, a 6136 hectare watershed in Dane County, Wisconsin.

  7. Remote sensing of spider mite damage in California peach orchards

    Science.gov (United States)

    Luedeling, Eike; Hale, Adam; Zhang, Minghua; Bentley, Walter J.; Dharmasri, L. Cecil

    2009-08-01

    Remote sensing techniques can decrease pest monitoring costs in orchards. To evaluate the feasibility of detecting spider mite damage in orchards, we measured visible and near infrared reflectance of 1153 leaves and 392 canopies in 11 peach orchards in California. Pairs of significant wavelengths, identified by Partial Least Squares regression, were combined into normalized difference indices. These and 9 previously published indices were evaluated for correlation with mite damage. Eight spectral regions for leaves and two regions for canopies (at blue and red wavelengths) were significantly correlated with mite damage. These findings were tested by calculating normalized difference indices from the Red and Blue bands of six multispectral aerial images. Index values were linearly correlated with mite damage ( R2 = 0.47), allowing identification of mite hotspots in orchards. However, better standardization of aerial imagery and accounting for perturbing environmental factors will be necessary for making this technique applicable for early mite detection.

  8. Remote sensing applied to numerical modelling. [water resources pollution

    Science.gov (United States)

    Sengupta, S.; Lee, S. S.; Veziroglu, T. N.; Bland, R.

    1975-01-01

    Progress and remaining difficulties in the construction of predictive mathematical models of large bodies of water as ecosystems are reviewed. Surface temperature is at present the only variable than can be measured accurately and reliably by remote sensing techniques, but satellite infrared data are of sufficient resolution for macro-scale modeling of oceans and large lakes, and airborne radiometers are useful in meso-scale analysis (of lakes, bays, and thermal plumes). Finite-element and finite-difference techniques applied to the solution of relevant coupled time-dependent nonlinear partial differential equations are compared, and the specific problem of the Biscayne Bay and environs ecosystem is tackled in a finite-differences treatment using the rigid-lid model and a rigid-line grid system.

  9. Remote Sensing Training for Middle School through the Center of Excellence in Remote Sensing Education

    Science.gov (United States)

    Hayden, L. B.; Johnson, D.; Baltrop, J.

    2012-12-01

    Remote sensing has steadily become an integral part of multiple disciplines, research, and education. Remote sensing can be defined as the process of acquiring information about an object or area of interest without physical contact. As remote sensing becomes a necessity in solving real world problems and scientific questions an important question to consider is why remote sensing training is significant to education and is it relevant to training students in this discipline. What has been discovered is the interest in Science, Technology, Engineering and Mathematics (STEM) fields, specifically remote sensing, has declined in our youth. The Center of Excellence in Remote Sensing Education and Research (CERSER) continuously strives to provide education and research opportunities on ice sheet, coastal, ocean, and marine science. One of those continued outreach efforts are Center for Remote Sensing of Ice Sheets (CReSIS) Middle School Program. Sponsored by the National Science Foundation CReSIS Middle School Program offers hands on experience for middle school students. CERSER and NSF offer students the opportunity to study and learn about remote sensing and its vital role in today's society as it relate to climate change and real world problems. The CReSIS Middle School Program is an annual two-week effort that offers middle school students experience with remote sensing and its applications. Specifically, participants received training with Global Positioning Systems (GPS) where the students learned the tools, mechanisms, and applications of a Garmin 60 GPS. As a part of the program the students were required to complete a fieldwork assignment where several longitude and latitude points were given throughout campus. The students had to then enter the longitude and latitude points into the Garmin 60 GPS, navigate their way to each location while also accurately reading the GPS to make sure travel was in the right direction. Upon completion of GPS training the

  10. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

    Science.gov (United States)

    West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-10-11

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

  11. Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

    Science.gov (United States)

    West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-01-01

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

  12. Landscape Archeology: Remote Sensing Investigation of the Ancient Maya in the Peten Rainforest of Northern Guatemala

    Science.gov (United States)

    Sever, Thomas L.; Irwin, Daniel E.; Arnold, James E. (Technical Monitor)

    2002-01-01

    Through the use of airborne and satellite imagery we are improving our ability to investigate ancient Maya settlement, subsistence, and landscape modification in this dense forest region. Today the area is threatened by encroaching settlement and deforestation. However, it was in this region that the Maya civilization began, flourished, and abruptly disappeared for unknown reasons in the 9th century AD. At the time of their collapse they had attained one of the highest population densities in human history. How the Maya were able to successfully manage water and feed this dense population is not well understood at this time. A NASA-funded project used remote sensing technology to investigate large seasonal swamps (bajos) that make up 40 percent of the landscape. Through the use of remote sensing, ancient Maya features such as sites, roadways, canals and water reservoirs have been detected and verified through ground reconnaissance. The results of this preliminary research cast new light on the adaptation of the ancient Maya to their environment. Microenvironmental variation within the wetlands was elucidated and the different vegetation associations identified in the satellite imagery. More than 70 new archeological sites within and at the edges of the bajo were mapped and tested. Modification of the landscape by the Maya in the form of dams and reservoirs in the Holmul River and its tributaries and possible drainage canals in bajos was demonstrated. The use of Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM), one-meter IKONOS satellite imagery, as well as high resolution airborne STAR-3i radar imagery--2.5 meter backscatter/10 meter Digital Elevation Model (DEM)--are opening new possibilities for understanding how a civilization was able to survive for centuries upon a karat topographic landscape. This understanding is critical for the current population that is currently experiencing rapid population growth and destroying the landscape through

  13. Remote sensing for wind power potential: a prospector's handbook

    Energy Technology Data Exchange (ETDEWEB)

    Wade, J.E.; Maule, P.A.; Bodvarsson, G.; Rosenfeld, C.L.; Woolley, S.G.; McClenahan, M.R.

    1983-02-01

    Remote sensing can aid in identifying and locating indicators of wind power potential from the terrestrial, marine, and atmospheric environments (i.e.: wind-deformed trees, white caps, and areas of thermal flux). It is not considered as a tool for determining wind power potential. A wide variety of remotely sensed evidence is described in terms of the scale at which evidence of wind power can be identified, and the appropriate remote sensors for finding such evidence. Remote sensing can be used for regional area prospecting using small-scale imagery. The information from such small-scale imagery is most often qualitative, and if it is transitory, examination of a number of images to verify presistence of the feature may be required. However, this evidence will allow rapid screening of a large area. Medium-scale imagery provides a better picture of the evidence obtained from small-scale imagery. At this level it is best to use existing imagery. Criteria relating to land use, accessibility, and proximity of candidate sites to nearby transmission lines can also be effectively evaluated from medium-scale imagery. Large-scale imagery provides the most quantitative evidence of the strength of wind. Wind-deformed trees can be identified at a large number of sites using only a few hours in locally chartered aircraft. A handheld 35mm camera can adequately document any evidence of wind. Three case studies that employ remote sensing prospecting techniques are described. Based on remotely sensed evidence, the wind power potential in three geographically and climatically diverse areas of the United States is estimated, and the estimates are compared to actual wind data in those regions. In addition, the cost of each survey is discussed. The results indicate that remote sensing for wind power potential is a quick, cost effective, and fairly reliable method for screening large areas for wind power potential.

  14. Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

    Science.gov (United States)

    John Hogland; Nedret Billor; Nathaniel Anderson

    2013-01-01

    Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

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