WorldWideScience

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. 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 ...

  4. 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. ... Ethiopian Journal of Environmental Studies and Management ... It is in the interest of environmental monitoring and sustainable development that biomass change be constantly determined. There are ...

  5. 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) ...

  6. 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.

  7. 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 ...

  8. Remote sensing techniques aid in preattack planning for fire management

    Science.gov (United States)

    Lucy Anne Salazar

    1982-01-01

    Remote sensing techniques were investigated as an alternative for documenting selected prettack fire planning information. Locations of fuel models, road systems, and water sources were recorded by Landsat satellite imagery and aerial photography for a portion of the Six Rivers National Forest in northwestern California. The two fuel model groups used were from the...

  9. Remote Sensing

    CERN Document Server

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

    2012-01-01

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

  10. 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...

  11. Tunnel-Site Selection by Remote Sensing Techniques

    Science.gov (United States)

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

  12. 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

  13. 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.

  14. 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.

  15. Current Application of Remote Sensing Techniques in Land Use ...

    African Journals Online (AJOL)

    MICHAEL

    most efficient scientific tool in conjunction with ground truth and ... Data sources. Remote sensing image data: We used LANDSAT. (spatial resolution 30m), LISS III (spatial resolution. 23.5m) and ASTER data (spatial resolution 15m) for. 2008 in the study ... spectral remote sensing data is essential for analyzing land use and ...

  16. 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), ВТН (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

  17. 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...

  18. Bibliography of Remote Sensing Techniques Used in Wetland Research

    Science.gov (United States)

    1993-01-01

    Terchunian, A., Klemas, V., Segovio, A. et al. 1986. Mangrove mapping in Ecuador : the impact of shrimp pond construction. Environmental Manage- ment... Laguna de Bay through multispectral digital analysis of Landsat imageries. Proceedings of the twelfth international symposium on remote sensing of...Mangrove mapping in Ecuador : the impact of shrimp pond construction. Environmental Manage- ment. 10(3): 345-350. Weaver, M. G., Cross, G. H., and Mead, R

  19. Successful integration of remote sensing and ground based exploration techniques in an arid environment

    Energy Technology Data Exchange (ETDEWEB)

    Jones, R.F.E. (Clyde Expro plc, Ledbury (United Kingdom)); Oehlers, M. (Nigel Press and Associates Ltd., Edenbridge (United Kingdom))

    1995-03-06

    Twenty years ago, remote sensing promised to revolutionize exploration; unfortunately, many of the early promises made were unfulfilled and remote sensing tended to drop out of mainstream exploration. Both these extremes are unrealistic, and projects undertaken by Clyde in Yemen illustrate some of the ways remote sensing can become a successful and cost-effective part of an exploration program. Firstly, the remote sensed data, integrated with a minimum of ground control work, provided maps to use in subsequent fieldwork, a surface geology map, and a digital elevation model with its derived topographic contour maps. Secondly, the remote sensed data enabled the authors to create a structural contour map of a near surface horizon at a very low cost per square kilometer. Thirdly, the remote sensed data became a crucial planning tool for seismic operations to optimize data quality and minimize acquisition cost without having to resort to costly and time-consuming swath shooting or similar high-effort techniques. Finally, the surface geological map derived from the image interpretation enabled them to create geological cross sections along the shot seismic lines in a matter of hours without having a field geologist mapping along the lines. Remote sensing can provide highly cost-effective benefits to an exploration program in an arid region, and many of the applications can also be developed for use in areas with vegetation cover.

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

    OpenAIRE

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

    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 radiat...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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 ...

  6. Potential of using remote sensing techniques for global assessment of water footprint of crops

    NARCIS (Netherlands)

    Romaguera Albentosa, M.R.; Romaguera, Mireia; Hoekstra, Arjen Ysbert; Su, Zhongbo; Krol, Martinus S.; Salama, M.S.

    2010-01-01

    Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF)

  7. 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.

  8. 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.

  9. Urban Mapping and Growth Prediction using Remote Sensing and GIS Techniques, Pune, India

    OpenAIRE

    Sivakumar, V.

    2014-01-01

    This study aims to map the urban area in and around Pune region between the year 1991 and 2010, and predict its probable future growth using remote sensing and GIS techniques. The Landsat TM and ETM+ satellite images of 1991, 2001 and 2010 were used for analyzing urban land use class. Urban class was extracted / mapped using supervised classification technique with maximum likelihood classifier. The accuracy assessment was carried out for classified maps. The achieved overall accurac...

  10. 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 ...

  11. Robust satellite techniques for remote sensing of seismically active areas

    Directory of Open Access Journals (Sweden)

    S. Piscitelli

    2001-06-01

    Full Text Available Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity whose variable contributions to the investigated signal can be so high as to completely mask (or simulate the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observational field also in the presence of highly variable contributions from atmospheric (transmittance, surface (emissivity and morphology and observational (time/season, but also solar and satellite zenithal angles conditions.This work presents the first preliminary results, based on several years of NOAA/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.

  12. Discrimination of Coastal Sediments around Qatar Peninsula, Using Remote Sensing Techniques

    OpenAIRE

    Sadiq, A. Ali. M. [عبد العلي محمد صادق; El-Kassas, Ibrahim A.

    1999-01-01

    This paper aims at demonstrating the usedfulness of remote sensing techniques in identifying various types of coastal sediments around Qatar Peninusla. In this respect, Landsat-Thematic mapper (TM) multispectral data provide a valuable tool to detemine spectaral differences, applicalbe to discriminate coastal sediments, based on their physical characteristics, mineralogical constituents and chemical composition. Preprocessing of the Landsat-TM row dara was first perfourmed for rdiometric a...

  13. Air Pollution Determination Using Remote Sensing Technique: A Case Study In Quangninh Province, Vietnam

    OpenAIRE

    Le Hung Trinh

    2016-01-01

    Vietnam is a country rich in mineral resources, including coal, copper, oil, natural gas etc. Coal reserves, located mainly in the Quang Ninh province, have been estimated as high as 8.6 billion tons. Alongside with economic and social benefits, coal mining has negative impacts on the environment, such as air and water pollution. This article presents study on application of remote sensing technique for evaluation of air pollution influence on the mining area of Quang Ninh province, the north...

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

    Energy Technology Data Exchange (ETDEWEB)

    Weber, C; Tocho, J O; Rodriguez, E J [Centro de Investigaciones Opticas (CONICET La Plata-CIC) (Argentina); Acciaresi, H A, E-mail: cweber@ciop.unlp.edu.ar [Facultad de Ciencias Agrarias y Forestales UNLP (Argentina)

    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.

  15. Potential of Using Remote Sensing Techniques for Global Assessment of Water Footprint of Crops

    Directory of Open Access Journals (Sweden)

    Mireia Romaguera

    2010-04-01

    Full Text Available Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH. The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use.

  16. 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.

  17. 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.

  18. A Novel Graph Based Fuzzy Clustering Technique For Unsupervised Classification Of Remote Sensing Images

    Science.gov (United States)

    Banerjee, B.; Krishna Moohan, B.

    2014-11-01

    This paper addresses the problem of unsupervised land-cover classification of multi-spectral remotely sensed images in the context of self-learning by exploring different graph based clustering techniques hierarchically. The only assumption used here is that the number of land-cover classes is known a priori. Object based image analysis paradigm which processes a given image at different levels, has emerged as a popular alternative to the pixel based approaches for remote sensing image segmentation considering the high spatial resolution of the images. A graph based fuzzy clustering technique is proposed here to obtain a better merging of an initially oversegmented image in the spectral domain compared to conventional clustering techniques. Instead of using Euclidean distance measure, the cumulative graph edge weight is used to find the distance between a pair of points to better cope with the topology of the feature space. In order to handle uncertainty in assigning class labels to pixels, which is not always a crisp allocation for remote sensing data, fuzzy set theoretic technique is incorporated to the graph based clustering. Minimum Spanning Tree (MST) based clustering technique is used to over-segment the image at the first level. Furthermore, considering that the spectral signature of different land-cover classes may overlap significantly, a self-learning based Maximum Likelihood (ML) classifier coupled with the Expectation Maximization (EM) based iterative unsupervised parameter retraining scheme is used to generate the final land-cover classification map. Results on two medium resolution images establish the superior performance of the proposed technique in comparison to the traditional fuzzy c-means clustering technique.

  19. Mapping Glauconite Unites with Using Remote Sensing Techniques in North East of Iran

    Science.gov (United States)

    Ahmadirouhani, R.; Samiee, S.

    2014-10-01

    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.

  20. 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.

  1. 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.

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

    Science.gov (United States)

    Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell

    2017-01-01

    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.

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

    Science.gov (United States)

    'Ainullotfi, A. A.; Ibrahim, A. L.; Masron, T.

    2014-02-01

    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.

  4. Remote sensing of atmospheric NO2 by employing the continuous-wave differential absorption lidar technique.

    Science.gov (United States)

    Mei, Liang; Guan, Peng; Kong, Zheng

    2017-10-02

    Differential absorption lidar (DIAL) technique employed for remote sensing has been so far based on the sophisticated narrow-band pulsed laser sources, which require intensive maintenance during operation. In this work, a continuous-wave (CW) NO2 DIAL system based on the Scheimpflug principle has been developed by employing a compact high-power CW multimode 450 nm laser diode as the light source. Laser emissions at the on-line and off-line wavelengths of the NO2 absorption spectrum are implemented by tuning the injection current of the laser diode. Lidar signals are detected by a 45° tilted area CCD image sensor satisfying the Scheimpflug principle. Range-resolved NO2 concentrations on a near-horizontal path are obtained by the NO2 DIAL system in the range of 0.3-3 km and show good agreement with those measured by a conventional air pollution monitoring station. A detection sensitivity of ± 0.9 ppbv at 95% confidence level in the region of 0.3-1 km is achieved with 15-minute averaging and 700 m range resolution during hours of darkness, which allows accurate concentration measurement of ambient NO2. The low-cost and robust DIAL system demonstrated in this work opens up many possibilities for field NO2 remote sensing applications.

  5. 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%.

  6. Use of remote-sensing techniques to survey the physical habitat of large rivers

    Science.gov (United States)

    Edsall, Thomas A.; Behrendt, Thomas E.; Cholwek, Gary; Frey, Jeffery W.; Kennedy, Gregory W.; Smith, Stephen B.; Edsall, Thomas A.; Behrendt, Thomas E.; Cholwek, Gary; Frey, Jeffrey W.; Kennedy, Gregory W.; Smith, Stephen B.

    1997-01-01

    Remote-sensing techniques that can be used to quantitatively characterize the physical habitat in large rivers in the United States where traditional survey approaches typically used in small- and medium-sized streams and rivers would be ineffective or impossible to apply. The state-of-the-art remote-sensing technologies that we discuss here include side-scan sonar, RoxAnn, acoustic Doppler current profiler, remotely operated vehicles and camera systems, global positioning systems, and laser level survey systems. The use of these technologies will permit the collection of information needed to create computer visualizations and hard copy maps and generate quantitative databases that can be used in real-time mode in the field to characterize the physical habitat at a study location of interest and to guide the distribution of sampling effort needed to address other habitat-related study objectives. This report augments habitat sampling and characterization guidance provided by Meador et al. (1993) and is intended for use primarily by U.S. Geological Survey National Water Quality Assessment program managers and scientists who are documenting water quality in streams and rivers of the United States.

  7. 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.

  8. 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

  9. 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).

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Mohammad Haji Gholizadeh

    2016-08-01

    Full Text Available 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.

  12. An improved dual-frequency technique for the remote sensing of ocean currents and wave spectra

    Science.gov (United States)

    Schuler, D. L.; Eng, W. P.

    1984-01-01

    A two frequency microwave radar technique for the remote sensing of directional ocean wave spectra and surface currents is investigated. This technique is conceptually attractive because its operational physical principle involves a spatial electromagnetic scattering resonance with a single, but selectable, long gravity wave. Multiplexing of signals having different spacing of the two transmitted frequencies allows measurements of the entire long wave ocean spectrum to be carried out. A new scatterometer is developed and experimentally tested which is capable of making measurements having much larger signal/background values than previously possible. This instrument couples the resonance technique with coherent, frequency agility radar capabilities. This scatterometer is presently configured for supporting a program of surface current measurements.

  13. Wavelet-based image registration technique for high-resolution remote sensing images

    Science.gov (United States)

    Hong, Gang; Zhang, Yun

    2008-12-01

    Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints at different times or by different sensors. It is an important image processing procedure in remote sensing and has been studied by remote sensing image processing professionals for several decades. Nevertheless, it is still difficult to find an accurate, robust, and automatic image registration method, and most existing image registration methods are designed for a particular application. High-resolution remote sensing images have made it more convenient for professionals to study the Earth; however, they also create new challenges when traditional processing methods are used. In terms of image registration, a number of problems exist in the registration of high-resolution images: (1) the increased relief displacements, introduced by increasing the spatial resolution and lowering the altitude of the sensors, cause obvious geometric distortion in local areas where elevation variation exists; (2) precisely locating control points in high-resolution images is not as simple as in moderate-resolution images; (3) a large number of control points are required for a precise registration, which is a tedious and time-consuming process; and (4) high data volume often affects the processing speed in the image registration. Thus, the demand for an image registration approach that can reduce the above problems is growing. This study proposes a new image registration technique, which is based on the combination of feature-based matching (FBM) and area-based matching (ABM). A wavelet-based feature extraction technique and a normalized cross-correlation matching and relaxation-based image matching techniques are employed in this new method. Two pairs of data sets, one pair of IKONOS panchromatic images from different times and the other pair of images consisting of an IKONOS panchromatic image and a QuickBird multispectral image, are used to

  14. 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”.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. 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.

  19. Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

    Science.gov (United States)

    Yadav, Bechu K V; Nandy, S

    2015-05-01

    Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

  20. Remote Sensing

    Indian Academy of Sciences (India)

    observed that all bodies at temperatures above zero degrees absolute emit electromagnetic radiation at different wavelengths, as per Planck's law. 2. B(A, T) = 2hc ..... International co-operation of nations in evolving integrated global observa- tion for disaster studies is getting in place. Evolution of Remote Sensing in India.

  1. [Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

    Science.gov (United States)

    Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

    2006-08-01

    In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

  2. Remote sensing techniques in geo-archaeological research; Case studies in Turkey and Egypt

    Science.gov (United States)

    de Laet, V.; Paulissen, E.; Vertraeten, G.; Waelkens, M.; Willems, H.

    2009-04-01

    The launch of several very high spatial resolution satellite (VHSRS) systems (Ikonos-2, Quickbird-2 and others) in the recent past has provided new possibilities for archaeological research, especially in areas where aerial photography is hampered. This paper presents an overview of research in the field of archaeological prospecting based on VHSRS imagery and digital image analysis in SW Turkey (Hisar, Sagalassos and Tepe Düzen) and Middle Egypt (Dayr Al-Barshā). The general objective is to evaluate the possibilities of VHSRS remote sensing to detect and automatically classify archaeological features using visual enhancement techniques and pixel- and object-based classification techniques. Focus is also on comparison of the contribution of spectral characteristics and pixel resolution of Quickbird-2 and Ikonos-2 for automatic extraction of ancient features from VHSRS imagery. Various landscape elements, including archaeological remains, can be automatically classified when their spectral characteristics are different. However, major difficulties arise when extracting and classifying features such as remnants of wall structures, which are composed of the same material as the surrounding substrate. Additionally, archaeological structures do not have unique shape or colour characteristics, which could make the extraction more straightforward. For archaeological sites in general, the accuracy of the automatic extraction depends on several variables: the type and characteristics of VHSRS data, the classification method applied, the spectral variation within the site and the shape characteristics of the remnants. For Sagalassos and Quickbird-2 imagery, object-based extraction appears independent of the site characteristics, which largely influence extraction on Ikonos-2. This study shows that object-based extraction on Quickbird-2 imagery better performs for archaeological applications in general. In contrast to automatic extraction methods, a simple visual

  3. Urban Mapping and Growth Prediction using Remote Sensing and GIS Techniques, Pune, India

    Science.gov (United States)

    Sivakumar, V.

    2014-11-01

    This study aims to map the urban area in and around Pune region between the year 1991 and 2010, and predict its probable future growth using remote sensing and GIS techniques. The Landsat TM and ETM+ satellite images of 1991, 2001 and 2010 were used for analyzing urban land use class. Urban class was extracted / mapped using supervised classification technique with maximum likelihood classifier. The accuracy assessment was carried out for classified maps. The achieved overall accuracy and Kappa statistics were 86.33 % & 0.76 respectively. Transition probability matrix and area change were obtained using different classified images. A plug-in was developed in QGIS software (open source) based on Markov Chain model algorithm for predicting probable urban growth for the future year 2021. Based on available data set, the result shows that urban area is expected to grow much higher in the year 2021 when compared to 2010. This study provides an insight into understanding of urban growth and aids in subsequent infrastructure planning, management and decision-making.

  4. Dynamic drought risk assessment using crop model and remote sensing techniques

    Science.gov (United States)

    Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.

    2017-02-01

    Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.

  5. 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.

  6. 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.

  7. 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

  8. 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".

  9. Assessing grapevine canopy health in the Texas Hill Country with remote sensing and GIS techniques

    Science.gov (United States)

    Mathews, Adam J.

    Vineyards are typically managed uniformly over space, although known spatial variation exists in the performance of vines within and across vineyard blocks. Identifying spatial variability in crop performance at a large scale (one or a few vineyard blocks) is useful to vineyard managers wishing to address such variation by enacting separate management plans for differing areas of performance. Zonal management and the institution of precision viticultural practices (i.e. use of GIS and remote sensing techniques to study this spatial variation) has proven profitable for a number of reasons, namely zonal harvesting based on zone performance. This dissertation implements cutting-edge, practical, and low-cost equipment and techniques, specifically an unmanned aerial vehicle (UAV), digital cameras, and Structure from Motion (SfM), to identify spatial variation in grapevine canopy vigor at a vineyard in the Texas Hill Country American Viticultural Area. Three research objectives were addressed in this dissertation including: (1) the setup and implementation of a practical imaging system and processing methodology (digital cameras and a UAV) to produce very high spatial resolution orthophotomosaics of vineyards with visible and near-infrared bands, (2) observation of spatial and temporal variation in grapevine canopy vigor that can aid in improving vineyard management practice, and (3) development of a three-dimensional method for visualizing and quantifying vineyard canopy density. Results concluded that the low-cost tools and techniques outlined in this study provided a practical means by which to identify spatial variation in canopy vigor at the study vineyard. Of the three methods used to identify this variation, spectrally-based (NDVI), planimetrically-based (canopy extent), and three-dimensionally-derived (SfM point clouds), the latter two were most successful and would be recommended for future use. Most importantly, due to the low cost of the technology used to

  10. 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.

  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. A brief review of remote sensing data and techniques for wetlands identification

    CSIR Research Space (South Africa)

    Ritchie, M

    2015-09-01

    Full Text Available . Goodenough, D.G., Bhogal, P., Charlebois, D., Matwin, S. and Niemann, O., 1995, Intelligent data fusion for environmental monitoring, IEEE, 2157-2160. Hardisky, M.A., Gross, M.F. and Klemas, V., 1986, Remote Sensing of Coastal Wetlands, Bioscience, 36...

  14. 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.…

  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. 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.

  17. Estimation of high-resolution brightness temperature from auxiliary remote sensing products using transformation techniques

    Science.gov (United States)

    Cheney, T. H.; Nagarajan, K.; Judge, J.

    2010-12-01

    Passive microwave observations of brightness temperature (TB) at the L-band (1.4 GHz) are highly sensitive to near-surface soil moisture and have been widely used to retrieve them. The European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future NASA-Soil Moisture Active Passive (SMAP) missions will provide global observations of TB at 1.4 GHz every 3 days at spatial resolutions in the order of 40-50 kilometers . These observations need to be downscaled to 1 km to merge them with hydrometeorological models for data assimilation and to study the effects of land surface heterogeneity such as dynamic vegetation conditions. However, downscaling is an ill-posed problem and additional information regarding TB is required at finer scales. In this study, we investigate two methodologies that provide this information by transforming auxiliary remote sensing (RS) products such as Land Surface Temperature (LST), Vegetation Water Content (VWC), and Land Cover (LC), which are readily available at 1km, into initial estimates of TB at 1km. In the first method, a non-parametric probabilistic technique based on Baye's rule was used to estimate TB by embedding its functional relationship to the RS products in terms of conditional probability density functions. In the second method, the principle of local correlation was used to estimate TB by extracting structural information between TB and the RS products within local neighborhoods. Field observations obtained during the intensive field experiments conducted over growing seasons of corn and cotton in North Central Florida were used to compare and analyze the performance of the two methodologies. The impacts of limited training data on the accuracy and reliability of the two methodologies were also investigated.

  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. Predicting species cover of marine macrophyte and invertebrate species combining hyperspectral remote sensing, machine learning and regression techniques.

    Directory of Open Access Journals (Sweden)

    Jonne Kotta

    Full Text Available In order to understand biotic patterns and their changes in nature there is an obvious need for high-quality seamless measurements of such patterns. If remote sensing methods have been applied with reasonable success in terrestrial environment, their use in aquatic ecosystems still remained challenging. In the present study we combined hyperspectral remote sensing and boosted regression tree modelling (BTR, an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea. The BRT technique combined with remote sensing and traditional spatial modelling succeeded in identifying, constructing and testing functionality of abiotic environmental predictors on the coverage of benthic macrophyte and invertebrate species. Our models easily predicted a large quantity of macrophyte and invertebrate species cover and recaptured multitude of interactions between environment and biota indicating a strong potential of the method in the modelling of aquatic species in the large variety of ecosystems.

  20. 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.

  1. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    Science.gov (United States)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2017-07-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  2. Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

    OpenAIRE

    Elhag, Mohamed; Bahrawi, Jarbou A.

    2017-01-01

    Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soi...

  3. Soil Degradation Assessment in North Nile Delta Using Remote Sensing and GIS Techniques

    Science.gov (United States)

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

    2015-04-01

    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- & 31° 15- E and latitudes 31° 00' & 31° 37' N., covering an area of about 161760 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/FAO 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

  4. 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

  5. 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.

  6. 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.

  7. Flood Prediction for the Tam Nong District in Mekong Delta Using Hydrological Modelling and Hydrologic Remote Sensing Technique

    Science.gov (United States)

    Kappas, Martin; Nguyen Hong, Quang; Thanh, Nga Pham Thi; Thu, Hang Le Thi; Nguyen Vu, Giang; Degener, Jan; Rafiei Emam, Ammar

    2017-04-01

    There has been an increasing attention to the large trans-boundary Mekong river basin due to various problems related to water management and flood control, for instance. Vietnam Mekong delta is located at the downstream of the river basin where is affected most by this human-induced reduction in flows from the upstream. On the other hand, the flood plain of nine anastomosing channels is increasingly effected by the seawater intrusion due to sea level rising of climate change. This results in negative impacts of salinization, drought, and floods, while formerly flooding had frequently brought positive natural gain of irrigation water and alluvial aggradation. In this research, our aim is to predict flooding for the better water management adaptation and control. We applied the model HEC-SSP 2.1 to analyze flood flow frequency, two-dimensional unsteady flow calculations in HEC-RAS 5.0 for simulating a floodplain inundation. Remote sensing-based water level (Jason-2) and inundation map were used for validation and comparison with the model simulations. The results revealed a reduction of water level at all the monitoring stations, particularly in the last decade. In addition, a trend of the inundation extension gradually declined, but in some periods it remained severe due to water release from upstream reservoirs during the rainy season (October-November). We found an acceptable agreement between the HEC-RAS and remote sensing flooding maps (around 70%). Based on the flood routine analysis, we could conclude that the water level will continue lower and lead to a trend of drought and salinization harsher in the near future. Keywords: Mekong delta, flood control, inundation, water management, hydrological modelling, remote sensing

  8. 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.

  9. Application of remote sensing techniques for the identification of biotic stress in plum trees caused by the Plum pox virus

    Directory of Open Access Journals (Sweden)

    Krezhova Dora

    2015-12-01

    Full Text Available Two hyperspectral remote sensing techniques, spectral reflectance and chlorophyll fluorescence, were used for the identification of biotic stress (sharka disease in plum trees at an early stage without visible symptoms on the leaves. The research was focused on cultivars that are widely spread in Bulgaria: ‘Angelina’, ‘Black Diamond’ and ‘Mirabelle’. Hyperspectral reflectance and fluorescence data were collected by means of a portable multichannel fibre-optics spectrometer in the visible and near infrared spectral ranges (400-1000 nm. Statistical and deterministic analyses were applied for assessing the significance of the differences between the spectral data of healthy (control and infected plum leaves. Comparative analyses were performed with complementary serological test DAS-ELISA, broadly implemented in plant virology. The strong relationship that was found between the results from the two remote sensing techniques and serological analysis indicates the applicability of hyperspectral reflectance and fluorescence techniques for conducting health condition assessments of vegetation easily and without damage before the appearance of visible symptoms.

  10. 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.

  11. 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.

  12. 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.

  13. Remote sensing techniques used in hydrocarbon exploration - A state-of-the-art review

    Science.gov (United States)

    Gonzales, R. W.

    1983-01-01

    Lintz (1972) has defined remote sensing for petroleum exploration as the detection from a distance of variations of the earth's surface or properties. Possibilities foreseen by Lintz could be realized with the Lander satellite. When used in 'phase-one' exploration programs, Landsat data have been effective in 'zeroing-in' on potential hydrocarbon traps, and later, when supplemented by more conventional exploration procedures, have led to the discovery of these resources. The present investigation is concerned with an overview of the methods utilized in 'phase-one' hydrocarbon exploration programs. The considered methods are to serve as an initial tool to aid the more conventional exploration procedures. Attention is given to visual interpretations, digital image processing, lineament analysis, surface anomalies, and geomorphology and topography.

  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. 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.

  16. 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.

  17. 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)

  18. 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

  19. Flood Vulnerability Analysis of the part of Karad Region, Satara District, Maharashtra using Remote Sensing and Geographic Information System technique

    Science.gov (United States)

    Warghat, Sumedh R.; Das, Sandipan; Doad, Atul; Mali, Sagar; Moon, Vishal S.

    2012-07-01

    Karad City is situated on the bank of confluence of river Krishna & Koyana, which is severely flood prone area. The floodwaters enter the city through the roads and disrupt the infrastructure in the whole city. Furthermore, due to negligence of the authorities and unplanned growth of the city, the people living in the city have harnessed the natural flow of water by constructing unnecessary embankments in the river Koyna. Due to this reason now river koyna is flowing in the form of a narrow channel, which very easily over-flows during very minor flooding.Flood Vulnerabilty Analysis has been done for the karad region of satara district, maharashtra using remote sensing and geographic information system technique. The aim of this study is to identify flood vulnerability zone by using GIS and RS technique and an attempt has been to demonstrat the application of remote sensing and GIS in order to map flood vulnerabilty area by utilizing ArcMap, and Erdas software. Flood vulnerabilty analysis of part the Karad Regian of Satara District, Maharashtra has been carried out with the objectives - Identify the Flood Prone area in the Koyana and Krishna river basin, Calculate surface runoff and Delineate flood sensitive areas. Delineate classified hazard Map, Evaluate the Flood affected area, Prepare the Flood Vulnerability Map by utilizing Remote Sensing and GIS technique. (C.J. Kumanan;S.M. Ramasamy)The study is based on GIS and spatial technique is used for analysis and understanding of flood problem in Karad Tahsil. The flood affected areas of the different magnitude has been identified and mapped using Arc GIS software. The analysis is useful for local planning authority for identification of risk areas and taking proper decision in right moment. In the analysis causative factors for flooding in watershed are taken into account as annual rainfall, size of watershed, basin slope, drainage density of natural channels and land use. (Dinand Alkema; Farah Aziz.)This study of

  20. Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

    Science.gov (United States)

    Elhag, Mohamed; Bahrawi, Jarbou A.

    2017-03-01

    Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

  1. Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques

    Directory of Open Access Journals (Sweden)

    Victor Hugo de Morais Danelichen

    2014-12-01

    Full Text Available The direct estimation of the soil heat flux (G by remote sensing data is not possible. For this, several models have been proposed empirically from the relation of G measures and biophysical parameters of various types of coverage or not vegetated in different places on earth. Thus, the objective of this study was to evaluate the relation between G/Rn ratio and biophysical variables obtained by satellite sensors and evaluate the parameterization of different models to estimate G spatially in three sites with different soil cover types. The net radiation (Rn and G were measured directly in two pastures at Miranda Farm and Experimental Farm and and Monodominant Forest of Cambará. Rn, G, and G/Rn ratio and MODIS products, such as albedo (α, surface temperature (LST, vegetation index (NDVI and leaf area index (LAI varied seasonally at all sites and inter-sites. The sites were different from each other by presenting different relation between measures of Rn, G and G/Rn ratio and biophysical parameters. Among the original models, the model proposed by Bastiaanssen (1995 showed the best performance with r = 0.76, d = 0.95, MAE = 5.70 W m-2 and RMSE = 33.68 W m-2. As the reparameterized models, correlation coefficients had no significant change, but the coefficient Willmott (d increased and the MAE and RMSE had a small decrease.

  2. Prediction of a future washover landscape based on airborne remote sensing techniques

    Energy Technology Data Exchange (ETDEWEB)

    Eleveld, M.A. [International Institute for Aerospace Survey and Earth Sciences (ITC), Enschede (Netherlands)

    1997-06-01

    International recognition and protection of the Wadden Sea area was established after the {open_quote}Ramsar Convention on Wetlands of International Importance, Especially as Waterfowl Habitat{close_quote}. The Dutch government policy of dynamic preservation of the Dutch coast gives nature almost a free reign at locations designated as natural areas, e.g. the extremes of the Dutch Wadden islands. Management is involved in monitoring the coastal development with the purpose of gaining more insight in the processes affecting these areas, subsequently allowing prediction. An important process observed on the eastern ends of the Wadden islands is the occurrence of washovers. This geomorphological phenomenon, resulting in sand transport from the foredunes to the saltmarsh and tidal flats, has a major ecological impact, influencing among other things the species composition of the saltmarsh. To monitor the washovers several airborne sensors were used. Information on the formation and stabilization of washovers by vegetation, was extracted from multitemporal airborne videography and scanned aerial photographs. Based on the trends derived from these sequential images, digital elevation data and morphological parameters derived from laser altimetry, dynamic modelling in a GIS environment was applied, which resulted in the prediction of the place of washovers and the amount sediment that could be deposited on saltmarsh in the coming years. The general conclusion is that, the presence of washovers causes environmental heterogeneity resulting in a high species diversity. Multitemporal airborne remote sensing data are not only useful for monitoring the landscape but the data also support spatio-temporal modelling.

  3. Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

    Science.gov (United States)

    Srivastava, Ashok N.; Oza, Nikunj; Stroeve, Julienne

    2004-01-01

    Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

  4. 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.

  5. Modelling submerged coastal environments: Remote sensing technologies, techniques, and comparative analysis

    Science.gov (United States)

    Dillon, Chris

    Built upon remote sensing and GIS littoral zone characterization methodologies of the past decade, a series of loosely coupled models aimed to test, compare and synthesize multi-beam SONAR (MBES), Airborne LiDAR Bathymetry (ALB), and satellite based optical data sets in the Gulf of St. Lawrence, Canada, eco-region. Bathymetry and relative intensity metrics for the MBES and ALB data sets were run through a quantitative and qualitative comparison, which included outputs from the Benthic Terrain Modeller (BTM) tool. Substrate classification based on relative intensities of respective data sets and textural indices generated using grey level co-occurrence matrices (GLCM) were investigated. A spatial modelling framework built in ArcGIS(TM) for the derivation of bathymetric data sets from optical satellite imagery was also tested for proof of concept and validation. Where possible, efficiencies and semi-automation for repeatable testing was achieved using ArcGIS(TM) ModelBuilder. The findings from this study could assist future decision makers in the field of coastal management and hydrographic studies. Keywords: Seafloor terrain characterization, Benthic Terrain Modeller (BTM), Multi-beam SONAR, Airborne LiDAR Bathymetry, Satellite Derived Bathymetry, ArcGISTM ModelBuilder, Textural analysis, Substrate classification.

  6. Species identification of mixed algal bloom in the Northern Arabian Sea using remote sensing techniques.

    Science.gov (United States)

    Dwivedi, R; Rafeeq, M; Smitha, B R; Padmakumar, K B; Thomas, Lathika Cicily; Sanjeevan, V N; Prakash, Prince; Raman, Mini

    2015-02-01

    Oceanic waters of the Northern Arabian Sea experience massive algal blooms during winter-spring (mid Feb-end Mar), which prevail for at least for 3 months covering the entire northern half of the basin from east to west. Ship cruises were conducted during winter-spring of 2001-2012 covering different stages of the bloom to study the biogeochemistry of the region. Phytoplankton analysis indicated the presence of green tides of dinoflagellate, Noctiluca scintillans (=N. miliaris), in the oceanic waters. Our observations indicated that diatoms are coupled and often co-exist with N. scintillans, making it a mixed-species ecosystem. In this paper, we describe an approach for detection of bloom-forming algae N. scintillans and its discrimination from diatoms using Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data in a mixed-species environment. In situ remote sensing reflectance spectra were generated using Satlantic™ hyperspectral radiometer for the bloom and non-bloom waters. Spectral shapes of the reflectance spectra for different water types were distinct, and the same were used for species identification. Scatter of points representing different phytoplankton classes on a derivative plot revealed four diverse clusters, viz. N. scintillans, diatoms, non-bloom oceanic, and non-bloom coastal waters. The criteria developed for species discrimination were implemented on MODIS data and validated using inputs from a recent ship cruise conducted in March 2013.

  7. Textbooks and technical references for remote sensing

    Science.gov (United States)

    Rudd, R. D.; Bowden, L. W.; Colwell, R. N.; Estes, J. E.

    1980-01-01

    A selective bibliography is presented which cites 89 textbooks, monographs, and articles covering introductory and advanced remote sensing techniques, photointerpretation, photogrammetry, and image processing.

  8. 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

  9. Integrating Remote Sensing Data with Directional Two- Dimensional Wavelet Analysis and Open Geospatial Techniques for Efficient Disaster Monitoring and Management

    Directory of Open Access Journals (Sweden)

    Kuan-Wei Chen

    2008-02-01

    Full Text Available In Taiwan, earthquakes have long been recognized as a major cause oflandslides that are wide spread by floods brought by typhoons followed. Distinguishingbetween landslide spatial patterns in different disturbance regimes is fundamental fordisaster monitoring, management, and land-cover restoration. To circumscribe landslides,this study adopts the normalized difference vegetation index (NDVI, which can bedetermined by simply applying mathematical operations of near-infrared and visible-redspectral data immediately after remotely sensed data is acquired. In real-time disastermonitoring, the NDVI is more effective than using land-cover classifications generatedfrom remotely sensed data as land-cover classification tasks are extremely time consuming.Directional two-dimensional (2D wavelet analysis has an advantage over traditionalspectrum analysis in that it determines localized variations along a specific direction whenidentifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series ofsolutions developed based on Open Geospatial Consortium specifications that can beapplied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2Dwavelet analysis of real-time NDVI images to effectively identify landslide patterns andshare resulting patterns via open geospatial techniques. As a case study, this study analyzedNDVI images derived from SPOT HRV images before and after the ChiChi earthquake(7.3 on the Richter scale that hit the Chenyulan basin in Taiwan, as well as images aftertwo large typhoons (Xangsane and Toraji to delineate the spatial patterns of landslidescaused by major disturbances. Disturbed spatial patterns of landslides that followed theseevents were successfully delineated using 2D wavelet analysis, and results of patternrecognitions of

  10. 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

  11. Basic Remote Sensing Investigations for Beach Reconnaissance.

    Science.gov (United States)

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

  12. 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.

  13. 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

  14. 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.

  15. 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 (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.

  16. Remote-Sensing of Precipitation Characteristics Using Multi-frequency Microwave Links and Polarimetric Radar Techniques

    Science.gov (United States)

    Eastment, J. D.; Bradford, W. J.; Goddard, J. W.; Willis, M. J.

    2002-05-01

    The Radio Communications Research Unit at Rutherford Appleton Laboratory (RAL) currently operates two separate experimental studies aimed at characterising the properties of rainfall using microwave remote-sensing. The first study involves the use of dual-frequency microwave measurements of precipitation-induced attenuation on a number of radio paths spanning a river catchment area to estimate path-integrated rainfall rate. This data is of interest for hydrological research connected with urban drainage, river level management and flood forecasting. Dual-frequency attenuation measurements have been employed because theoretical modelling showed them to be far less sensitive to rainfall drop-size distribution effects than single-frequency data. The experimental network comprises 9 microwave links spanning the frequency range 13 to 38 GHz installed on 5 different paths covering the catchment area of the rivers Croal and Irwell near Bolton in North-West England. For each transmitter-receiver link, excess path attenuation relative to the clear-air value is determined from measurements of received signal power level at a rate of 1 Hz. These data are logged by local computers at each receiver site, and periodically downloaded by modem to RAL for archiving and quality control. Analysis by colleagues at the Universities of Essex and Salford has shown that, due to the path-integrated nature of the attenuation measurements and the wide area-coverage obtained by a suitable choice of the multiple-path geometry, a small number of dual-frequency links can provide comparable hydrological data to that obtained from the more conventional dense network of rain-gauges. The second study employs a scanning polarimetric Doppler radar developed by RAL to measure the spatial distribution of hydrometeors along various operational microwave and mm-wave communication links within a 50 km radius of the University of St. Andrews in South-East Scotland. The UK Radiocommunications Agency and

  17. 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

  18. Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

    Science.gov (United States)

    He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

    2015-06-01

    Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

  19. 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.

  20. A methodological framework for the assessment and monitoring of forest degradation under the REDD+ programme based on remote sensing techniques and field data

    Science.gov (United States)

    Romero Sanchez, Martin Enrique

    In this thesis, a methodological framework for the assessment and monitoring of forest degradation based on remote sensing techniques and field data, as part of the REDD+ programme, is presented. The framework intends to support the implementation of a national Monitoring, Verification and Report (MRV) system in developing countries. The framework proposed an operational definition of forest degradation and a set of indicators, namely Canopy Cover (CC), Aboveground Biomass (AGB) and Net Primary Productivity (NPP), derived from remote sensing data. The applicability of the framework is tested in a sub-deciduous tropical forest in the Southeast of Mexico. The results from the application of the methodological framework showed that the higher rates of forest degradation, 1596-2865 ha˙year-1, occur in areas with high population density. Estimations of aboveground biomass in these degraded areas span from 1 to 24 Mg˙ha-1, with a rate of carbon fixation ranging from 130 to 246 gC˙m2˙year. The results also showed that 43 % of the forests of the study area remain with no evident signs of degradation, as detected by the indicators selected, during the period evaluated. The integration of the different elements conforming the methodological framework for the assessment and monitoring of forest degradation enabled the identification of areas that maintain a stable condition and areas that change over the period evaluated. The methodology outlined in this thesis also allows for the identification of the temporal and spatial distributions of forest degradation based on the indicators selected, and it is expected to serve as the basis for operations of the REDD+ programme with the appropriate adaptations to the area in turn.

  1. An integrated study of earth resources in the state of California using remote sensing techniques. [planning and management of water resources

    Science.gov (United States)

    Colwell, R. N.; Churchman, C. W.; Burgy, R. H.; Schubert, G.; Estes, J. E.; Bowden, L. W.; Algazi, R.; Coulson, K. L. (Principal Investigator)

    1973-01-01

    The University of California has been conducting an investigation which seeks to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Most of the work has concentrated on California's water resources, but with some attention being given to other earth resources as well and to the interplay between them and California's water resources.

  2. Study of coal mine fire in Damodar River basin,India using thermal remote sensing technique

    Science.gov (United States)

    Chatterjee, Alokesh; Bhattacharya, Asis

    Coal mine fires are a serious socio-economic problem because of hazards to health and the environment including toxic fumes, and subsidence of surface infrastructures. Globally, thou-sands of inextinguishable mine fires are burning today, especially in China and India. In India, Damodar River basin is the repository of the 46The entire Damodar River basin exhibits in an almost linear fashion in the central part of the Jharkhand and western part of West Bengal States of India. The coal fields are adjacent to the Damodar River or its tributaries. The general trends of coalfields are nearly east-west and showing gentle dip towards south. The area is bounded within Latitude 2330 -2350N and Longitude 8456 -8648E. Since all the coal deposits of Damodar River basin were formed in almost similar sedimentary environmental condition and are of equivalent geologic age; and the coal grades are more or less comparable, it is highly probable that the other coal fields in this region are also vulnerable to mine fires. Aerial and Space borne Thermal Infra-Red Remote Sensing method has been proved to be the most cost effective and time saving method to find out the thermal anomalies present in an area. Here, an attempt has been made to find out the presence of coalmine fire and their aerial extent in Damodar River basin including the well known Jharia and Raniganj coalfields using Space borne single band thermal IR data of Landsat 7 Enhanced Thematic Mapper (ETM+) sensor. Two daytime Landsat ETM+ images (path / row:140/44), acquired on 07.03.2001 and 24.01.2003, covering visible, one near Infrared (NIR), two short wave infrared (SWIR), one thermal infrared (TIR) and a panchromatic band, were used for the present study. Standard procedure of calculating surface temperature from band 6 of Landsat ETM+ data was followed. These include atmospheric corrections, data normalization for sun elevation angle, conversion of image DN values to spectral radiance and spectral radiance to radiant

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. Urban remote sensing investigations.

    OpenAIRE

    Jean-Paul DONNAY; Binard, Marc; Marchal, Denis; Istvan NADASDI

    1995-01-01

    This paper deals with the research activities achieved by the team TELSAT/06-TELSAT/11/06-TELSAT/T3/D03 of the University of Liege, in the framework of the National research programme on satellite remote sensing (National Scientific Policy Office). The team specialized in urban remote sensing and especially in applications relevant to urban, land and country planning and the monitoring of enevironment. Besides a theoretical approach of the methods of remote sensing, those trends imply a good ...

  12. 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

  13. Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

    Science.gov (United States)

    Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

    2011-12-01

    Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (Nasturtium officinale), these species were chosen as indicative; nonetheless, common reed (Phragmites australis) was also classified in order to exclude it from the stream ROI. The procedure included: A. For both section and habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information

  14. 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...

  15. Romantic versus scientific perspective: the ruins of Radlin palace in Wielkopolska region in the light of remote sensing techniques

    Science.gov (United States)

    Wilgocka, Aleksandra; Ruciński, Dominik; RÄ czkowski, Włodzimierz

    2015-06-01

    Although ruins of palace in Radlin, localized in Wielkopolska Region (Poland), could have been a great inspiration for romantic landscape painters, they were hardly considered as the subject of artistic interest. Nevertheless they stand as a marker in a landscape as a romantic background for the village on one hand and a memento for the neighbouring graveyard on another. Small scale excavations carried out in late 1950s with historical maps and analysis of still standing remains gave a general idea about wings order, localisation of main entrance and communication routs inside courtyard. Those early research thereby were the first step to change the meaning of this place from romantic to more scientific. New remote sensing technology allows move even further into scientific direction. The ruins in Radlin have been included into project ArchEO - archaeological applications of Earth Observation techniques. The main aim of the project in case of Radlin is an attempt to answer the question to what extent very high resolution optical satellite imagery might allow better understanding the spatial structure of the place. The various processing techniques were applied to facilitate the detection of archaeological features' impact on the vegetation condition. It enabled to assess the usefulness of satellite based data in recognizing specific archaeological remains. Thus, potential and limitations of satellite imagery versus other sources of spatial information like historic maps, excavation results, aerial photographs and Lidar will be discussed.

  16. 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.

  17. 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.

  18. 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.

  19. 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

    2007-03-01

    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.

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

    Science.gov (United States)

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

    2016-11-01

    The objective of the present study is to monitor reclamation activity in mining areas. Monitoring of these reclaimed sites in the vicinity of mining areas and on closed Over Burden (OB) dumps is critical for improving the overall environmental condition, especially in developing countries where area around the mines are densely populated. The present study evaluated the reclamation success in the Block II area of Jharia coal field, India, using Landsat satellite images for the years 2000 and 2015. Four image processing methods (support vector machine, ratio vegetation index, enhanced vegetation index, and normalized difference vegetation index) were used to quantify the change in vegetation cover between the years 2000 and 2015. The study also evaluated the relationship between vegetation health and moisture content of the study area using remote sensing techniques. Statistical linear regression analysis revealed that Normalized Difference Vegetation Index (NDVI) coupled with Normalized Difference Moisture Index (NDMI) is the best method for vegetation monitoring in the study area when compared to other indices. A strong linear relationship (r(2) > 0.86) was found between NDVI and NDMI. An increase of 21% from 213.88 ha in 2000 to 258.9 ha in 2015 was observed in the vegetation cover of the reclaimed sites for an open cast mine, indicating satisfactory reclamation activity. NDVI results indicated that vegetation health also improved over the years. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    M. Anji Reddy

    2007-03-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2005-10-01

    During the last thirty-five years the capital of Greece has suffered from an enormous internal immigration. Its population has overpassed the five millions and today almost the half population of Greece is squeezed in Athens metropolitan area. Because of the significant increase of population, the urban expansion in the basin of Athens was also excessive and in some cases catastrophic. Buildings have covered all the free places, new roads have been constructed, the drainage networks have been covered or disappeared and a lot of changes have been occurred to the landforms. The construction of the new airport (Elefterios Venizelos) at the beginning of this decade created a new commercial and urban pole at the eastern part of Athens and the constructive activity has been moved to new areas around the airport. Our aim was to detect and map all the changes that occurred in the urban area, estimate the urban expansion rate and the human interferences in the natural landscape, using GIS and remote sensing techniques. We have used satellite images from three different periods (1973, 1992, 2002) and topographic maps of 1:25.000 scale. The spatial resolution of all the satellite images ranges from 5 to 10 meters and is it acceptable for the monitoring and mapping of the urban growth. Supervised classification and on screen digitizing methods have been used in order to map the changes. Finally the qualitative and quantitative results of this study are presented in this paper.

  4. An information system design for watershed-wide modeling of water loss to the atmosphere using remote sensing techniques

    Science.gov (United States)

    Khorram, S.

    1977-01-01

    Results are presented of a study intended to develop a general location-specific remote-sensing procedure for watershed-wide estimation of water loss to the atmosphere by evaporation and transpiration. The general approach involves a stepwise sequence of required information definition (input data), appropriate sample design, mathematical modeling, and evaluation of results. More specifically, the remote sensing-aided system developed to evaluate evapotranspiration employs a basic two-stage two-phase sample of three information resolution levels. Based on the discussed design, documentation, and feasibility analysis to yield timely, relatively accurate, and cost-effective evapotranspiration estimates on a watershed or subwatershed basis, work is now proceeding to implement this remote sensing-aided system.

  5. APPLICATION OF REMOTE SENSING FOR TEMPERATURE MONITORING: THE TECHNIQUE FOR LAND SURFACE TEMPERATURE ANALYSIS

    OpenAIRE

    Teerawong Laosuwan; Torsak Gomasathit; Tanutdech Rotjanakusol

    2017-01-01

    This research aimed to present the technique for land surface temperature analysis with the data from Landsat-8 Operational Land Imager (OLI) /Thermal Infrared Sensors (TIR) in Meuang Maha Sarakham District, Maha Sarakham Province, Northeastern, Thailand. The research was conducted as following three steps: 1) Collecting the satellite data in thermal infrared band from Landsat-8 TIR satellite to adjust the value of Top of Atmosphere (ToA) Reflectance and then analyzing the land surface temper...

  6. An optical technique for remote sensing of near-surface turbulence

    Science.gov (United States)

    Bogucki, D.; Stramski, J.; Piskozub, D.

    2000-01-01

    Measurements of turbulent kinetic energy dissipation rates (TKE) or temperature dissipation rates of the the near-surface boundary layer are needed to understand air-sea exchange processes and rates. The capability to accurately estimate these variables by means of a remote technique is relevant to a number of questions ranging from the air-sea transfer of heat and gas to the fate of pollutants.

  7. 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.

  8. 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.

  9. Remote Sensing of Atmospheric and Ionospheric Disturbances using Radio Science Techniques

    Science.gov (United States)

    Yang, Y. M.; Paik, M.; Oudrhiri, K.; Buccino, D.; Kahan, D. S.

    2016-12-01

    Atmospheres and ionospheres can have significant impacts on radio frequency signal propagation such as Deep Space Network and Global Navigation Satellite System (GNSS, including Global Position System (GPS)) measurements. Previous studies indicate that Earth's atmospheric, surface, and interior processes, such as seismic activities, tsunamis, meteor impacts, and volcanic eruptions, are able to trigger atmospheric acoustic and gravity waves (AGWs), which potentially induce traveling ionospheric disturbances (TIDs) in the upper atmosphere. These perturbations are relatively small to the background of atmospheric and ionospheric profiles but detectable to radio frequency signals. In this research, we will demonstrate the ability of using ground- and space-based radio science techniques to detect and characterize atmospheric and ionospheric wave propagation from solid earth events including seismic activities and tsunamis. The detected wave trains with wave characteristics such as propagation speeds and wavelengths are classified through analysis of the line of sight (LOS) and radio occultation measurements made by different frequency radio waves. Dominant and different physical characteristics of AGW and TID propagations are found to be associated with specific surface wave propagations. In this research, we compare observations made by different frequency radio signals, corresponding model simulations, and other geophysical measurements of surface wave propagation such as seismometers, infrasound arrays and DART buoys. Results are shown to improve our understanding of the interactions between surface, atmosphere, and ionosphere. The better understanding of the coupling between planetary interior, surface, atmosphere, and ionosphere will benefit from innovative radio science techniques.

  10. Remote Sensing of Grass Response to Drought Stress Using Spectroscopic Techniques and Canopy Reflectance Model Inversion

    Directory of Open Access Journals (Sweden)

    Bagher Bayat

    2016-07-01

    Full Text Available The aim of this study was to follow the response to drought stress in a Poa pratensis canopy exposed to various levels of soil moisture deficit. We tracked the changes in the canopy reflectance (450–2450 nm and retrieved vegetation properties (Leaf Area Index (LAI, leaf chlorophyll content (Cab, leaf water content (Cw, leaf dry matter content (Cdm and senescent material (Cs during a drought episode. Spectroscopic techniques and radiative transfer model (RTM inversion were employed to monitor the gradual manifestation of drought effects in a laboratory setting. Plots of 21 cm × 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were divided into a well-watered control group and a group subjected to water stress for 36 days. In a regular weekly schedule, canopy reflectance and destructive measurements of LAI and Cab were taken. Spectral analysis indicated the first sign of stress after 4–5 days from the start of the experiment near the water absorption bands (at 1930 nm, 1440 nm and in the red (at 675 nm. Spectroscopic techniques revealed plant stress up to 6 days earlier than visual inspection. Of the water stress-related vegetation indices, the response of Normalized Difference Water Index (NDWI_1241 and Normalized Photochemical Reflectance Index (PRI_norm were significantly stronger in the stressed group than the control. To observe the effects of stress on grass properties during the drought episode, we used the RTMo (RTM of solar and sky radiation model inversion by means of an iterative optimization approach. The performance of the model inversion was assessed by calculating R2 and the Normalized Root Mean Square Error (RMSE between retrieved and measured LAI (R2 = 0.87, NRMSE = 0.18 and Cab (R2 = 0.74, NRMSE = 0.15. All parameters retrieved by model inversion co-varied with soil moisture deficit. However, the first strong sign of water stress on the retrieved grass properties was detected as a change of Cw

  11. 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.

  12. Detecting river sediments to assess hazardous materials at volcanic lake using advanced remote sensing techniques

    Science.gov (United States)

    Saepuloh, Asep; Fitrianingtyas, Chintya

    2016-05-01

    The Toba Caldera formed from large depression of Quaternary volcanism is a remarkable feature at the Earth surface. The last Toba super eruptions were recorded around 73 ka and produced the Youngest Toba Tuff about 2,800 km3. Since then, there is no record of significant volcanic seismicity at Toba Volcanic Complex (TVC). However, the hydrothermal activities are still on going as presented by the existence of hot springs and alteration zones at the northwest caldera. The hydrothermal fluids probably containing some chemical compositions mixed with surficial water pollutant and contaminated the Toba Lake. Therefore, an environmental issues related to the existence of chemical composition and degradation of water clearness in the lake had been raised in the local community. The pollutant sources are debatable between natural and anthropogenic influences because some human activities grow rapidly at and around the lake such as hotels, tourisms, husbandry, aquaculture, as well as urbanization. Therefore, obtaining correct information about the source materials floating at the surface of the Toba Lake is crucial for environmental and hazard mitigation purposes. Overcoming the problem, we presented this paper to assess the source possibility of floating materials at Toba Lake, especially from natural sources such as hydrothermal activities of TVC and river stream sediments. The Spectral Angle Mapper (SAM) techniques using atmospherically corrected of Landsat-8 and colour composite of Polarimetric Synthetic Aperture Radar (PolSAR) were used to map the distribution of floating materials. The seven ground truth points were used to confirm the correctness of proposed method. Based on the SAM and PolSAR techniques, we could detect the interface of hydrothermal fluid at the lake surfaces. Various distributions of stream sediment were also detected from the river mouth to the lake. The influence possibilities of the upwelling process from the bottom floor of Toba Lake were also

  13. Inside a Cucuteni Settlement: Remote Sensing Techniques for Documenting an Unexplored Eneolithic Site from Northeastern Romania

    Directory of Open Access Journals (Sweden)

    Andrei Asăndulesei

    2017-01-01

    Full Text Available This paper presents recent results of an integrated non-invasive investigation carried out in a previously unexplored settlement from northeastern Romania, belonging to the last great Eneolithic civilisation of Old Europe, the Cucuteni-Trypillia cultural complex. Although there is a long history of research concerning this culture, at only a handful of sites has archaeological research completed a comprehensive planimetric image. This makes it impossible to determine a typological evolution of the internal organisation of Cucutenian sites, both diachronically, across the three great phases of the culture (A, A−B and B for the Romanian area, and spatially, from SE Transylvania to the Republic of Moldova, and towards the steppes of the Ukraine. Accordingly, in certain environmental conditions, many essential behavioural aspects of Cucutenian communities are far from understood. Consequently, the generalisation and integration of non-invasive prospecting methods—Light Detection and Ranging (LiDAR, aerial photography, earth resistivity, magnetometry, and their integration through Geographic Information System (GIS—clearly represents a feasible alternative for deciphering the Cucuteni culture. These complementary investigation methods were applied for this case study, emphasis being put on the conjoint use of datasets from each technique. On the basis of results recently obtained from the Războieni–Dealul Mare/Dealul Boghiu site, innovative characteristics are described concerning intra-site spatial organisation, a typology of the fortification systems, the existence of ritual or delimitation ditches, and the presence of habitations outside fortified areas.

  14. APPLICATION OF REMOTE SENSING FOR TEMPERATURE MONITORING: THE TECHNIQUE FOR LAND SURFACE TEMPERATURE ANALYSIS

    Directory of Open Access Journals (Sweden)

    Teerawong Laosuwan

    2017-05-01

    Full Text Available This research aimed to present the technique for land surface temperature analysis with the data from Landsat-8 Operational Land Imager (OLI /Thermal Infrared Sensors (TIR in Meuang Maha Sarakham District, Maha Sarakham Province, Northeastern, Thailand. The research was conducted as following three steps: 1 Collecting the satellite data in thermal infrared band from Landsat-8 TIR satellite to adjust the value of Top of Atmosphere (ToA Reflectance and then analyzing the land surface temperature 2 Collecting multi-band data from Landsat-8 OLI satellite to adjust the value of Top of Atmosphere (ToA Reflectance and then analyzing values of Normalized Difference Vegetation Index (NDVI, Fractional Vegetation Cover (FVC and Land surface Emissivity (LSE 3 Bringing the results of 1 and 2 to analyze the land surface temperature with split window algorithm. The research results indicated that the analysis of the data from Landsat-8 OLI/TIR satellites in 18 March 2015 indicated a mean temperature of 33.57 °C.

  15. Using Remote Sensing Techniques to Measure Chl:C in the Santa Barbara Channel

    Science.gov (United States)

    Taylor, N.; Bausell, J.; Bell, T. W.; Kudela, R. M.; Scuderi, L. A.

    2016-12-01

    Giant Kelp (Macrocystis pyrifera) is an important primary producer along the west coast of North America. It provides critical habitat to a wide range of marine organisms. While satellite sensors can easily quantify canopy area of kelp, using similar techniques to gauge the physiological health of these macroalgae has proven more difficult. Bell et al. (2015) devised an algorithm that effectively estimated the chlorophyll to carbon ratio (Chl:C)—a proxy for kelp health—using AVIRIS imagery. A comparison of AVIRIS imagery of the Isla Vista kelp bed sampled in 2013 and 2015, before and during the recent El Nino-associated west coast `warm anomaly', indicates a decline in Chl:C in 2015 (student t-test pnutrient availability, and disturbance. However while AVIRIS imagery shows great potential in mapping kelp forest health, as an airborne sensor its availability is inconsistent over time, making it less ideal for continuous kelp forest monitoring. We therefore attempt to extend this method of determining Chl:C based on reflectance values to Landsat 8 satellite imagery. We found that although USGS Landsat 8 atmospherically corrected reflectance data does not accurately estimate kelp health, simulated Landsat 8 data from an AVIRIS image does. This suggests that although the spectral resolution of Landsat 8 is much lower than AVIRIS, with sufficient atmospheric correction the satellite will be able to classify kelp health.

  16. Monitoring of Emissions From a Refinery Tank Farm Using a Combination of Optical Remote Sensing Techniques

    Science.gov (United States)

    Polidori, A.; Tisopulos, L.; Pikelnaya, O.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Robinson, R. A.; Innocenti, F.; Finlayson, A.; Hashmonay, R.

    2016-12-01

    Despite great advances in reducing air pollution, the South Coast Air Basin (SCAB) still faces challenges to attain federal health standards for air quality. Refineries are large sources of ozone precursors and, hence contribute to the air quality problems of the region. Additionally, petrochemical facilities are also sources of other hazardous air pollutants (HAP) that adversely affect human health, for example aromatic hydrocarbons. In order to assure safe operation, decrease air pollution and minimize population exposure to HAP the South Coast Air Quality Management District (SCAQMD) has a number of regulations for petrochemical facilities. However, significant uncertainties still exist in emission estimates and traditional monitoring techniques often do not allow for real-time emission monitoring. In the fall of 2015 the SCAQMD, Fluxsense Inc., the National Physical Laboratory (NPL), and Atmosfir Optics Ltd. conducted a measurement study to characterize and quantify gaseous emissions from the tank farm of one of the largest oil refineries in the SCAB. Fluxsense used a vehicle equipped with Solar Occultation Flux (SOF), Differential Optical Absorption Spectroscopy (DOAS), and Extractive Fourier Transform Infrared (FTIR) spectroscopy instruments. Concurrently, NPL operated their Differential Absorption Lidar (DIAL) system. Both research groups quantified emissions from the entire tank farm and identified fugitive emission sources within the farm. At the same time, Atmosfir operated an Open Path FTIR (OP-FTIR) spectrometer along the fenceline of the tank farm. During this presentation we will discuss the results of the emission measurements from the tank farm of the petrochemical facility. Emission rates resulting from measurements by different ORS methods will be compared and discussed in detail.

  17. Annotated bibliography of remote sensing methods for monitoring desertification

    Science.gov (United States)

    Walker, A.S.; Robinove, Charles J.

    1981-01-01

    Remote sensing techniques are valuable for locating, assessing, and monitoring desertification. Remotely sensed data provide a permanent record of the condition of the land in a format that allows changes in land features and condition to be measured. The annotated bibliography of 118 items discusses remote sensing methods that may be applied to desertification studies.

  18. Application of optical remote sensing techniques to quantify emissions from urban oil wells, storage tanks, and other small stationary sources

    Science.gov (United States)

    Pikelnaya, O.; Polidori, A.; Tisopulos, L.; Mellqvist, J.; Samuelsson, J.; Robinson, R. A.; Innocenti, F.; Perry, S.

    2016-12-01

    Oil fields in the Los Angeles Basin remain very productive even after more than a century-long history of exploration. There are currently over 5,000 active oil wells the South Coast Air Basin (SCAB), with a large portion placed in close proximity of residences, schools and other sensitive receptors. Gaseous emissions from oil wells and equipment related to oil extraction can have a significant impact on air quality. The South Coast Air Quality Management District (SCAQMD) and other state regulatory agencies have a number of rules aimed to reduce Volatile Organic Compound (VOC) emissions and to minimize potential impacts to nearby communities. However, little information is available on the effectiveness of current control measures and magnitude of emissions remain largely unknown. To fill this knowledge gap, in the fall of 2015 the SCAQMD, Fluxsense Inc., the National Physical Laboratory (NPL), and Kassay Field Services Inc. conducted a comprehensive five-week study to measure gaseous emissions from oil wells, oil pumps, intermediate storage tanks, and other small point sources. A combination of optical remote sensing (ORS) techniques was used to detect and quantify emissions VOCs, methane, nitrogen oxides (NOx) and other gaseous pollutants. Fluxsense used Solar Occultation Flux (SOF), Differential Optical Absorption Spectroscopy (DOAS), and Extractive Fourier Transform Infrared (FTIR) spectroscopy to survey a large number of oil extraction sites and other small emission sources within SCAB. Similarly, Kassay Field Services carried out open-path FTIR measurements to complement observations provided by Fluxsense. Concurrently, NPL operated their Differential Absorption Lidar (DIAL) system on a smaller sub-set of sources to validate the emission results provided by Fluxsense and Kassay. During this presentation we will discuss the results of this joined measurement effort and the potential impacts of the observed emissions on neighboring communities. Additionally

  19. 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.

  20. 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.

  1. Monitoring land-use change by combining participatory land-use maps with standard remote sensing techniques: Showcase from a remote forest catchment on Mindanao, Philippines

    Science.gov (United States)

    Mialhe, François; Gunnell, Yanni; Ignacio, J. Andres F.; Delbart, Nicolas; Ogania, Jenifer L.; Henry, Sabine

    2015-04-01

    This paper combines participatory activities (PA) with remote sensing analysis into an integrated methodology to describe and explain land-cover changes. A remote watershed on Mindanao (Philippines) is used to showcase the approach, which hypothesizes that the accuracy of expert knowledge gained from remote sensing techniques can be further enhanced by inputs from vernacular knowledge when attempting to understand complex land mosaics and past land-use changes. Six participatory sessions based on focus-group discussions were conducted. These were enhanced by community-based land-use mapping, resulting in a final total of 21 participatory land-use maps (PLUMs) co-produced by a sample of stakeholders with different sociocultural and ecological perspectives. In parallel, seven satellite images (Landsat MSS, Landsat TM, Landsat ETM+, and SPOT4) were classified following standard techniques and provided snapshots for the years 1976, 1996, and 2010. Local knowledge and collective memory contributed to define and qualify relevant land-use classes. This also provided information about what had caused the land-use changes in the past. Results show that combining PA with remote-sensing analysis provides a unique understanding of land-cover change because the two methods complement and validate one another. Substantive qualitative information regarding the chronology of land-cover change was obtained in a short amount of time across an area poorly covered by scientific literature. The remote sensing techniques contributed to test and to quantify verbal reports of land-use and land-cover change by stakeholders. We conclude that the method is particularly relevant to data-poor areas or conflict zones where rapid reconnaissance work is the only available option. It provides a preliminary but accurate baseline for capturing land changes and for reporting their causes and consequences. A discussion of the main challenges encountered (i.e. how to combine different systems of

  2. 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

  3. 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.

  4. Remote Sensing Information Classification

    Science.gov (United States)

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  5. 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.

  6. REMOTE SENSING IN OCEANOGRAPHY.

    Science.gov (United States)

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

  7. An integrated study of earth resources in the state of California using remote sensing techniques. [water and forest management

    Science.gov (United States)

    Colwell, R. N.

    1974-01-01

    Progress and results of an integrated study of California's water resources are discussed. The investigation concerns itself primarily with the usefulness of remote sensing of relation to two categories of problems: (1) water supply; and (2) water demand. Also considered are its applicability to forest management and timber inventory. The cost effectiveness and utility of remote sensors such as the Earth Resources Technology Satellite for water and timber management are presented.

  8. Downscaling in remote sensing

    Science.gov (United States)

    Atkinson, Peter M.

    2013-06-01

    Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise.

  9. Integration of remote sensing and ground-based techniques for the study of land degradation phenomena in coastal areas.

    Science.gov (United States)

    Imbrenda, Vito; Coluzzi, Rosa; Calamita, Giuseppe; Luigia Giannossi, Maria; D'Emilio, Mariagrazia; Lanfredi, Maria; Makris, John; Palombo, Angelo; Pascucci, Simone; Santini, Federico; Margiotta, Salvatore; Emanuela Bonomo, Agnese; De Martino, Gregory; Perrone, Angela; Rizzo, Enzo; Pignatti, Stefano; Summa, Vito; Simoniello, Tiziana

    2015-04-01

    Land degradation processes, such as salinization and waterlogging, are increasingly affecting extensive areas devoted to agriculture threatening the sustainability of farming practices. Soil salinization typically appears as an excess accumulation of salt generally pronounced at the soil surface. Commonly, soil salinity is defined and measured by means of laboratory measurements of the electrical conductivity of liquid extracted from saturated soil-paste or different soil-water suspensions. Lab measurements are generally time consuming, costly, destructive, untimely for practical situations where the determination of the causes and/or the assessment of management practices are of interest. Recently, emerging survey techniques proved to be powerful tools to support soil salinity appraisal reducing costs and increasing the amount of spatial information. In the frame of PRO-LAND project (PO-FESR Basilicata 2007-2013) the research activities have been focused on the study of a complex salinization phenomenon occurring in a coastal environment of the Basilicata region (Southern Italy) as a result of natural and anthropic disturbances. The study area is located in the southernmost part of the Bradanic Trough along the sandy Ionian coastal plain. The hydrogeological conditions affect shallowness of the aquifer (45-50 cm below the ground) allowing the occurrence of seawater intrusion. Moreover, during last century, human activities, i.e. built-up of dams, the emergence of farms and industries, played a relevant role in the alteration of soil and groundwater quality of the area. In this work, both ground-based and remote sensing data were used. First, a geophysical mapping of electrical conductivity was carried out using a multi-frequency portable electro-magnetic induction (EMI) sensor. Based on the geophysical mapping and on optimization sampling approach, a number of locations were identified to collect soil samples for the geomineralogical characterization. Airborne

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

    Science.gov (United States)

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

    2010-01-01

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

  11. 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...

  12. 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...

  13. Introduction to remote sensing

    CERN Document Server

    Campbell, James B

    2012-01-01

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

  14. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

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

  15. Hyperspectral remote sensing for light pollution monitoring

    Directory of Open Access Journals (Sweden)

    P. Marcoionni

    2006-06-01

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

  16. 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.

  17. 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.

  18. Evaluating Damage Assessment of Breaches Along the Embankments of Indus River during Flood 2010 Using Remote Sensing Techniques

    Science.gov (United States)

    Ahmad, R.; Daniyal, D.

    2013-09-01

    Natural disasters cause human sufferings and property loss, if not managed properly. It cannot be prevented but their adverse impacts can be reduced through proper planning and disaster mitigation measures. The floods triggered by heavy rains during July 2010 in Pakistan caused swallowing of rivers causing human, agriculture, livestock and property losses in almost all over the country. The heavy rains in upper part of country were attributed to El-Nina effect. Accumulated water in the rivers floodplain overtopped and breached flood protective infrastructure. Flood damage particularly in Sindh province was caused by breaches in the embankments and even after months of flood recession in rivers, flood water affected settled areas in the province. This study evaluates the role of satellite remote sensing particularly in assessment of breaches and consequential damages as well as measures leading to minimize the effects of floods caused by breaches in flood protective infrastructure. More than 50 SPOT-5 imageries had been used for this purpose and breached areas were delineated using pre and post flood imageries, later on rehabilitation work were also monitored. A total 136 breaches were delineated out of which 60 were in the Punjab and 76 in Sindh province. The study demonstrates the potentials of satellite remote sensing for mapping and monitoring natural disasters and devising mitigation strategies.

  19. EVALUATING DAMAGE ASSESSMENT OF BREACHES ALONG THE EMBANKMENTS OF INDUS RIVER DURING FLOOD 2010 USING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Ahmad

    2013-09-01

    Full Text Available Natural disasters cause human sufferings and property loss, if not managed properly. It cannot be prevented but their adverse impacts can be reduced through proper planning and disaster mitigation measures. The floods triggered by heavy rains during July 2010 in Pakistan caused swallowing of rivers causing human, agriculture, livestock and property losses in almost all over the country. The heavy rains in upper part of country were attributed to El-Nina effect. Accumulated water in the rivers floodplain overtopped and breached flood protective infrastructure. Flood damage particularly in Sindh province was caused by breaches in the embankments and even after months of flood recession in rivers, flood water affected settled areas in the province. This study evaluates the role of satellite remote sensing particularly in assessment of breaches and consequential damages as well as measures leading to minimize the effects of floods caused by breaches in flood protective infrastructure. More than 50 SPOT-5 imageries had been used for this purpose and breached areas were delineated using pre and post flood imageries, later on rehabilitation work were also monitored. A total 136 breaches were delineated out of which 60 were in the Punjab and 76 in Sindh province. The study demonstrates the potentials of satellite remote sensing for mapping and monitoring natural disasters and devising mitigation strategies.

  20. EPA REMOTE SENSING RESEARCH

    Science.gov (United States)

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

  1. 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...

  2. 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

  3. 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.

  4. 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.

  5. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image Classification Objective of the study Classification algorithms by group Unsupervised algorithms Supervised classification algorithms Spatial... of remotely sensed images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image Classification Objective of the study Classification algorithms by group Unsupervised algorithms Supervised classification algorithms...

  6. 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...

  7. 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.

  8. 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

  9. Remote sensing in operational range management programs in Western Canada

    Science.gov (United States)

    Thompson, M. D.

    1977-01-01

    A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.

  10. On applications of remote sensing for environmental monitoring.

    Science.gov (United States)

    Spitzer, D

    1986-11-01

    Modern airborne and satellite remote sensing techniques offer attractive opportunities to coastal monitoring systems. Improvements of the evaluation of larger scales phenomena and processes due to the synopticity of the remote sensing data are of particular interest. However, some uncertainties and limitations about remote sensing must be considered. Microwave, infrared and visible radiation methods and their applications are briefly discussed and some applications are demonstrated. Special attention is paid to the remote sensing of various pollutants in the sea, in particular with respect to oil pollution.Promising developments of the remote sensing methods for coastal monitoring are to be expected from the European remote sensing satellite missions ERS 1 and ERS 2.Combination of these observations with simultaneous in situ measurements from ships (sea truth) appears to be most advantageous for the interpretation of the collected data.

  11. 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.

  12. 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 ...

  13. 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...

  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 program

    Science.gov (United States)

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

    1980-01-01

    A syllabus and training materials prepared and used in a series of one-day workshops to introduce modern remote sensing technology to selected groups of professional personnel in Vermont are described. Success in using computer compatible tapes, LANDSAT imagery and aerial photographs is reported for the following applications: (1) mapping defoliation of hardwood forests by tent caterpillar and gypsy moth; (2) differentiating conifer species; (3) mapping ground cover of major lake and pond watersheds; (4) inventorying and locating artificially regenerated conifer forest stands; (5) mapping water quality; (6) ascertaining the boat population to quantify recreational activity on lakes and waterways; and (7) identifying potential aquaculture sites.

  16. 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

  17. Remote Sensing and Imaging Physics

    Science.gov (United States)

    2012-03-07

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

  18. 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....

  19. 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....

  20. 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.

  1. 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

  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. 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

  4. 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.

  5. 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 ...

  6. 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

  7. Comparison of the resulting error in data fusion techniques when used with remote sensing, earth observation, and in-situ data sets for water quality applications

    Science.gov (United States)

    Ziemba, Alexander; El Serafy, Ghada

    2016-04-01

    Ecological modeling and water quality investigations are complex processes which can require a high level of parameterization and a multitude of varying data sets in order to properly execute the model in question. Since models are generally complex, their calibration and validation can benefit from the application of data and information fusion techniques. The data applied to ecological models comes from a wide range of sources such as remote sensing, earth observation, and in-situ measurements, resulting in a high variability in the temporal and spatial resolution of the various data sets available to water quality investigators. It is proposed that effective fusion into a comprehensive singular set will provide a more complete and robust data resource with which models can be calibrated, validated, and driven by. Each individual product contains a unique valuation of error resulting from the method of measurement and application of pre-processing techniques. The uncertainty and error is further compounded when the data being fused is of varying temporal and spatial resolution. In order to have a reliable fusion based model and data set, the uncertainty of the results and confidence interval of the data being reported must be effectively communicated to those who would utilize the data product or model outputs in a decision making process[2]. Here we review an array of data fusion techniques applied to various remote sensing, earth observation, and in-situ data sets whose domains' are varied in spatial and temporal resolution. The data sets examined are combined in a manner so that the various classifications, complementary, redundant, and cooperative, of data are all assessed to determine classification's impact on the propagation and compounding of error. In order to assess the error of the fused data products, a comparison is conducted with data sets containing a known confidence interval and quality rating. We conclude with a quantification of the performance

  8. 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.

  9. Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques

    Science.gov (United States)

    Jha, Madan K.; Chowdary, V. M.; Chowdhury, Alivia

    2010-11-01

    An approach is presented for the evaluation of groundwater potential using remote sensing, geographic information system, geoelectrical, and multi-criteria decision analysis techniques. The approach divides the available hydrologic and hydrogeologic data into two groups, exogenous (hydrologic) and endogenous (subsurface). A case study in Salboni Block, West Bengal (India), uses six thematic layers of exogenous parameters and four thematic layers of endogenous parameters. These thematic layers and their features were assigned suitable weights which were normalized by analytic hierarchy process and eigenvector techniques. The layers were then integrated using ArcGIS software to generate two groundwater potential maps. The hydrologic parameters-based groundwater potential zone map indicated that the `good' groundwater potential zone covers 27.14% of the area, the `moderate' zone 45.33%, and the `poor' zone 27.53%. A comparison of this map with the groundwater potential map based on subsurface parameters revealed that the hydrologic parameters-based map accurately delineates groundwater potential zones in about 59% of the area, and hence it is dependable to a certain extent. More than 80% of the study area has moderate-to-poor groundwater potential, which necessitates efficient groundwater management for long-term water security. Overall, the integrated technique is useful for the assessment of groundwater resources at a basin or sub-basin scale.

  10. 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.

  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.

    2017-05-01

    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. 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

  14. Remote Sensing of Mangrove Ecosystems: A Review

    Directory of Open Access Journals (Sweden)

    Stefan Dech

    2011-04-01

    Full Text Available Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove

  15. 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...

  16. 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

  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 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.

  20. Predicting Species Cover of Marine Macrophyte and Invertebrate Species Combining Hyperspectral Remote Sensing, Machine Learning and Regression Techniques

    National Research Council Canada - National Science Library

    Kotta, Jonne; Kutser, Tiit; Teeveer, Karolin; Vahtmäe, Ele; Pärnoja, Merli

    2013-01-01

    ...), an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea...

  1. Predicting species cover of marine macrophyte and invertebrate species combining hyperspectral remote sensing, machine learning and regression techniques

    National Research Council Canada - National Science Library

    Kotta, Jonne; Kutser, Tiit; Teeveer, Karolin; Vahtmäe, Ele; Pärnoja, Merli

    2014-01-01

    ...), an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea...

  2. 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

  3. Theory of microwave remote sensing

    Science.gov (United States)

    Tsang, L.; Kong, J. A.; Shin, R. T.

    1985-01-01

    Active and passive microwave remote sensing of earth terrains is studied. Electromagnetic wave scattering and emission from stratified media and rough surfaces are considered with particular application to the remote sensing of soil moisture. Radiative transfer theory for both the random and discrete scatterer models is examined. Vector radiative transfer equations for nonspherical particles are developed for both active and passive remote sensing. Single and multiple scattering solutions are illustrated with applications to remote sensing problems. Analytical wave theory using the Dyson and Bethe-Salpeter equations is employed to treat scattering by random media. The backscattering enhancement effects, strong permittivity fluctuation theory, and modified radiative transfer equations are addressed. The electromagnetic wave scattering from a dense distribution of discrete scatterers is studied. The effective propagation constants and backscattering coefficients are calculated and illustrated for dense media.

  4. Remote sensing of Earth terrain

    Science.gov (United States)

    Kong, J. A.

    1992-01-01

    Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

  5. Remote sensing of oil slicks

    Digital Repository Service at National Institute of Oceanography (India)

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

    Airborne remote sensing is very useful for oil-spill monitoring ans surveillance. It ranks very high among available methods due to its capability of large area coverage with good resolution and speed for detection of oil slicks. It overcomes...

  6. Radiative transfer and remote sensing

    Science.gov (United States)

    Conrath, B. J.

    1982-01-01

    Radiative transfer, the basic theoretical tool for the quantitative interpretation of planetary infrared spectra, is discussed. The function it plays in linking the remotely sensed data to the properties of the atmosphere (composition, thermal structure, dynamics, etc.), is inferred. A brief overview of the remote sensing problem as it pertains to the interpretation of planetary spectra is presented. The presentation is tutorial rather than exhaustive.

  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. REMOTE SENSING APPLICATIONS FOR SUSTAINABLE WATERSHED MANAGEMENT AND FOOD SECURITY

    Science.gov (United States)

    The integration of IKONOS satellite data, airborne color infrared remote sensing, visualization, and decision support tools is discussed, within the contexts of management techniques for minimizing non-point source pollution in inland waterways, such s riparian buffer restoration...

  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. Uncertainties associated with the use of optical remote sensing technique to estimate surface emissions in landfill applications.

    Science.gov (United States)

    Abichou, Tarek; Clark, Jeremy; Tan, Sze; Chanton, Jeffery; Hater, Gary; Green, Roger; Goldsmith, Doug; Barlaz, Morton A; Swan, Nathan

    2010-04-01

    Landfills represent a source of distributed emissions source over an irregular and heterogeneous surface. In the method termed "Other Test Method-10" (OTM-10), the U.S. Environmental Protection Agency (EPA) has proposed a method to quantify emissions from such sources by the use of vertical radial plume mapping (VRPM) techniques combined with measurement of wind speed to determine the average emission flux per unit area per time from nonpoint sources. In such application, the VRPM is used as a tool to estimate the mass of the gas of interest crossing a vertical plane. This estimation is done by fitting the field-measured concentration spatial data to a Gaussian or some other distribution to define a plume crossing the vertical plane. When this technique is applied to landfill surfaces, the VRPM plane may be within the emitting source area itself. The objective of this study was to investigate uncertainties associated with using OTM-10 for landfills. The spatial variability of emission in the emitting domain can lead to uncertainties of -34 to 190% in the measured flux value when idealistic scenarios were simulated. The level of uncertainty might be higher when the number and locations of emitting sources are not known (typical field conditions). The level of uncertainty can be reduced by improving the layout of the VRPM plane in the field in accordance with an initial survey of the emission patterns. The change in wind direction during an OTM-10 testing setup can introduce an uncertainty of 20% of the measured flux value. This study also provides estimates of the area contributing to flux (ACF) to be used in conjunction with OTM-10 procedures. The estimate of ACF is a function of the atmospheric stability class and has an uncertainty of 10-30%.

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

    Science.gov (United States)

    Bishop, Peter C.

    1990-01-01

    The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.

  12. 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

  13. Remote sensing of submerged habitats in the Dry Tortugas: A comparison of multiple sensors and classification techniques

    Science.gov (United States)

    Field, Donald William

    The advent of high resolution satellite imagery from platforms such as IKONOS, QuickBird, and OrbView, as well as host of new suborbital sensors has opened up new possibilities for mapping submerged coral, seagrass and algal communities. The research presented here examined the use of two of these platforms, IKONOS and QuickBird, as well as scanned aerial photographs, to map submerged habitats in the Dry Tortugas. Of the two satellite imagery sources, only QuickBird was tasked and imagery obtained specifically for this research. Upon examination and initial processing of the QuickBird imagery, it was discovered that an image anomaly, that will be referred to in this document as the green band miscalibration, had significant effects on some aspects of the image processing. To date, this anomaly has received no attention in the literature. Based mostly on issues associated with the green band miscalibration and the steps taken in this project to address them, the following document has two major areas of focus. After a brief introduction in Chapter one, Chapter 2 examines the use of the IKONOS and QuickBird imagery to obtain bathymetry information for the study area. Chapter 3 examines the use of the three image processing techniques on IKONOS and QuickBird imagery and manual interpretation of 1:24,000 nominal scale color aerial photography to classify submerged coral, seagrass, and algal habitats in the Dry Tortugas study area.

  14. Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

    Science.gov (United States)

    Zou, Zhengxia; Shi, Zhenwei

    2018-03-01

    We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

  15. Diachronic analysis of salt-affected areas using remote sensing techniques: the case study of Biskra area, Algeria

    Science.gov (United States)

    Afrasinei, Gabriela M.; Melis, Maria T.; Buttau, Cristina; Bradd, John M.; Arras, Claudio; Ghiglieri, Giorgio

    2015-10-01

    In the Wadi Biskra arid and semi-arid area, sustainable development is limited by land degradation, such as secondary salinization of soils. As an important high quality date production region of Algeria, it needs continuous monitoring of desertification indicators, since the bio-physical setting defines it as highly exposed to climate-related risks. For this particular study, for which little ground truth data was possible to acquire, we set up an assessment of appropriate methods for the identification and change detection of salt-affected areas, involving image interpretation and processing techniques employing Landsat imagery. After a first phase consisting of a visual interpretation study of the land cover types, two automated classification approaches were proposed and applied for this specific study: decision tree classification and principal components analysis (PCA) of Knepper ratios. Five of the indices employed in the Decision Tree construction were set up within the current study, among which we propose a salinity index (SMI) for the extraction of highly saline areas. The results of the 1984 to 2014 diachronic analysis of salt - affected areas variation were supported by the interpreted land cover map for accuracy estimation. Connecting the outputs with auxiliary bio-physical and socio-economic data, comprehensive results are discussed, which were indispensable for the understanding of land degradation dynamics and vulnerability to desertification. One aspect that emerged was the fact that the expansion of agricultural land in the last three decades may have led and continue to contribute to a secondary salinization of soils. This study is part of the WADIS-MAR Demonstration Project, funded by the European Commission through the Sustainable Water Integrated Management (SWIM) Program (www.wadismar.eu).

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

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

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

  17. Land use/ cover mapping of the dry and wet season of Kikuletwa catchment using GIS and remote sensing techniques

    Science.gov (United States)

    Msigwa, Anna; vangriensven, Ann; Komakech, Hans; Verbeiren, Boud

    2017-04-01

    Management of water resources has become complicated due to lack of reliable information on the water uses of different sectors. The quantification of water consumption has been concentrated to modified and cultivated areas, but often lacks a correct representation of agricultural water management practices (crop rotations, drip irrigation) while leaving out the water consumption from natural ecosystems (forest, barren land, grazed grassland and shrubland or thickets). A detailed land use map can help water resources scientists and managers to better quantify the water uses by these ecosystems. However, most of the time the hydrological seasons are not considered in developing the land use maps. The objective of this study was to develop a land use maps for the two main seasons (dry and wet season) of the semi-arid Kikuletwa catchment, Tanzania. Three Landsat 8 images of March, August and November 2016 were obtained and cloud masked. Ground truthing points and questionnaire surveys regarding cropping system were collected during the month of August 2016. Unsupervised and supervised techniques in ArcMap and ground truthing point with the aid of cropping calendar was used to classify the three images. About 20 land use/land cover classes were obtained. The dry season images seem to have higher accuracy than the wet season images having Maximum NDVI of 0.6. The results showed a clear difference of how the land is being used in the dry and wet seasons. The image obtained on March representing the wet season showed 74% of the total cultivated land is rainfed with supplemental irrigation while 60% of the cultivated land is irrigated in the dry seasons. Additionally, the results show differences in land size of the natural ecosystems like grazed grassland. The total grazed grassland for the dry month of August was 5.3% of the total catchment area while that of November was 5.1%. The change seen during the dry seasons between the month of August and November is due to

  18. 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

  19. On a possibility to use the remote sensing techniques for glaciological analysis in mountain regions of Uzbekistan

    Directory of Open Access Journals (Sweden)

    E. R. Semakova

    2017-01-01

    Full Text Available The ALOS/AVNIR-2 satellite data (2007–2010 allowed estimating areas of glaciers, change in the areas for 50 years, and the number and areas of new naturally-dammed lakes in the mountain regions of Uzbekistan. Boundaries of these gla‑ ciers together with the ALOS/PALSAR data (2010 were used as the basis to determine position of the firn line. It was revealed that since 1980s elevation range of the line gradually decreased. The relationship between average elevation of the firn line and the upper limit of the juniper tree occurrence as well as changing of this relation since 1980s are consid‑ ered. The revealed lakes served as the basis for verification of probabilistic model of the moraine-dammed lake forma‑ tions due to the glacier recessions in the basins under consideration. It was shown that the GIS-techniques based on the use of this model together with data on glaciation and the relief digital model may significantly simplify searching of new lakes. Application of a system of the mudflow movement modeling makes possible to estimate a risk level in a case of a lake bursting. Current information about changing elevations of the glacier surfaces was obtained duet to the radar inter‑ ferometry and the altimeter data. The digital model of the river Pskem upper course (the DEM had been built using the satellite TerraSAR‑X/TanDEM‑X data (2011–2012. All datasets of the elevations were checked for horizontal shifts of the relief digital models relative to the ICESat profiles (2003–2008. Evaluation of accuracy and morphological analysis of all the relief models for the investigated region were also made. DEMs differencing, the difference between ICESat measure‑ ments and DEM, nearby ICESat footprints within one track and between the tracks were carried out to assess the change in elevations of the glacier surfaces. Average rate of the surface lowering of an individual glacier with the maximal number of footprints (7 in the track

  20. 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...

  1. The Use of Remote Sensing Technique to Predict Gross Domestic Product (GDP): An Analysis of Built-Up Index and GDP in Nine Major Cities in Canada

    Science.gov (United States)

    Faisal, K.; Shaker, A.

    2014-09-01

    City/regional authorities are responsible to design and structure the urban morphology based on the desired land-use activities. One of the key concerns regarding urban planning is to establish certain development goals, such as Gross Domestic Product (GDP). In Canada, the gross national income mainly relies on mining and manufacturing industries. In order to facilitate new city development, this study aims to utilize remote sensing and GIS techniques to assess the relationship between the industrial area and the reported GDP in nine major cities in Canada. Free archive multi-temporal Landsat TM images and land use vector data were obtained for year 2005 and 2010 during the summer season, where the socio-economic data, such as GDP, population, and total employment are obtained from Metropolitan Housing Outlook for the same duration. The Landsat TM images were first atmospherically corrected and the built-up values were computed using the Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) from the Landsat images. The high built-up values within the industrial areas were acquired for further analysis. Finally, a correlation analysis was conducted between the GDP, Population, and Total Employment with respect to the built-up areas. Preliminary findings show that the R2 between the percentage of built-up areas and industrial area within the corresponding city is 0.82. In addition, the R2 between the built-up areas and GDP ranges from 0.73 to 0.78. Consistent findings are observed in the similar correlation between the built-up areas and population, as well as the built-up areas and the employment, where the R2 is within 0.72 to 0.73. With the correlation found, we believe that results can be used as a generic indication for the federal/municipals authorities, which are aiming or target for a specific GDP with respect to the planned industrial area.

  2. Evaluating synergy effects of combined close-range and remote sensing techniques for the monitoring of a deep-seated landslide (Schmirn, Austria)

    Science.gov (United States)

    Rutzinger, Martin; Zieher, Thomas; Pfeiffer, Jan; Schlögel, Romy; Darvishi, Mehdi; Toschi, Isabella; Remondino, Fabio

    2017-04-01

    In the recent past, studies on the monitoring of deep-seated landslides included a multitude of measuring techniques. Direct and indirect methods are applied for displacement measurements at points, along lines or area-wide. In particular close-range and remote sensing has proven to be feasible for the detection of displacements featuring a high accuracy (range of cm to dm) while covering the whole area of interest. However, a combination of supplementing methods is preferable to confirm the observations and to overcome their individual drawbacks and limitations. In the present study, displacements of a deep-seated landslide situated in the Schmirn valley (Tyrol, Austria) are assessed by (i) image correlation of existing orthophoto series, (ii) multi-temporal data acquisitions using a terrestrial laser scanner (TLS) and (iii) repeated measurements with the help of a differential global positioning system (DGPS). The study focusses on evaluating the synergy effects of the tested methods in quantifying the landslide's movement. Limitations concerning their spatial resolution and accuracy are addressed in specific detail. The landslide's activity is likely controlled by hillslope hydrology and its seasonality. Phases of enhanced movement are expected in the course of snowmelt and after exceptional rainfall events. Preliminary results of the image correlation reveal mean annual horizontal displacement rates of 0.75 m (±0.45 m; one standard deviation), which is confirmed by the DGPS measurements. The first results also suggest constant annual displacement rates for the period of 2004 to 2015. Further comparisons with the multi-temporal TLS data will reveal detailed spatial patterns of displacement rates and deepen the understanding of the landslide's kinematics. This research is conducted within the project LEMONADE (http://lemonade.mountainresearch.at) funded by the Euregio Science Fund.

  3. A self-trained semisupervised SVM approach to the remote sensing land cover classification

    Science.gov (United States)

    Liu, Ying; Zhang, Bai; Wang, Li-min; Wang, Nan

    2013-09-01

    Support vector machines (SVM) are nowadays receiving increasing attention in remote sensing applications although this technique is very sensitive to the parameters setting and training set definition. Self-training is an effective semisupervised method, which can reduce the effort needed to prepare the training set by training the model with a small number of labeled examples and an additional set of unlabeled examples. In this study, a novel semisupervised SVM model that uses self-training approach is proposed to address the problem of remote sensing land cover classification. The key characteristics of this approach are that (1) the self-adaptive mutation particle swarm optimization algorithm is introduced to get the optimum parameters that improve the generalization performance of the SVM classifier, and (2) the Gustafson-Kessel fuzzy clustering algorithm is proposed for the selection of unlabeled points to reduce the impact of ineffective labels. The effectiveness of the proposed technique is evaluated firstly with samples from remote sensing data and then by identifying different land cover regions in the remote sensing imagery. Experimental results show that accuracy level is increased by applying this learning scheme, which results in the smallest generalization error compared with the other schemes.

  4. 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.

  5. 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.

  6. Remote sensing activities in Asia

    Science.gov (United States)

    Murai, Shunji

    An overview of remote sensing activities in Asia is given, with the history of the annual Asian Conference on Remote Sensing (ACRS) showing how cooperation between Asian remote sensing scientists and their related organizations has improved remarkably since the first ACRS in 1980 In 1981, the Asian Association on Remote Sensing (AARS) was founded with five member countries As of 1991, there are now 18 ordinary members and 5 associate members. United Nations organization such as ESCAP, UNDP, UNEP, UNCRD etc. have been and are contributing to developing countries in Asia in the fields of education, training and/or pilot projects in conjunction or in cooperation with AARS activities. The key Asian countries in remote sensing such as Japan, China, India, Thailand etc. are promoting not only national projects but also regional cooperation through personnel exchange, joint research, international workshops and international training through ACRS. The following article is a summary of the author's activities for the twelve years since 1980 aimed at fostering regional cooperation in Asia.

  7. 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.

  8. CSIR-NLC mobile LIDAR for atmosphere remote sensing

    CSIR Research Space (South Africa)

    Sivakumar, V

    2009-07-01

    Full Text Available Africa. 2Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Lynwood Road, Pretoria 0002, South Africa. 3Tshwane University of Technology, Pretoria 0001, South Africa. ABSTRACT A mobile LIDAR (LIght Detection... obtained using the CSIR-NLC mobile LIDAR in a 23 hour field campaign at the University of Pretoria. Index Terms— Atmospheric measurements, Remote sensing, Aerosols, Air pollution, Meteorology 1. INTRODUCTION Remote sensing is a technique...

  9. Using remotely-sensed data for optimal field sampling

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-09-01

    Full Text Available M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical... studies are: where to sample, what to sample and how many samples to obtain. Conventional sampling techniques are not always suitable in environmental studies and scientists have explored the use of remotely-sensed data as ancillary information to aid...

  10. 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....

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Jiayin Liu

    2017-06-01

    Full Text Available 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.

  13. 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...

  14. Monitoring land use changes in the Upper Ganga Basin, India by using Remote Sensing and GIS techniques on Landsat 5 TM data

    Science.gov (United States)

    Tsarouchi, Georgia-Marina; Buytaert, Wouter

    2013-04-01

    The Green Revolution represents one of the largest environmental changes in India over the last century. The Upper Ganga basin is experiencing rapid rates of change of land use and irrigation practices. In combination with exploitation of groundwater resources in the northern Indian plains, this causes variations in recharge and fundamentally affects surface and groundwater resources, threatening India's water supplies. In this study, we have developed a methodology to map and investigate land-use change by applying Remote Sensing and Geographic Information Systems (GIS) techniques on 30m resolution multi-temporal Landsat 5 Thematic Mapper (TM) data for 1984, 1998 and 2010. Firstly, an automated protocol was applied to effectively correct the images for radiometric effects and remove atmospheric interference during the pre-processing analysis of satellite images. Afterwards, maximum likelihood supervised classifications were carried out on Landsat 5 TM colour composites of 1984, 1998 and 2010 with the aid of ground truth data. Post-classification change detection techniques were applied to Landsat images in order to map land cover changes in the Upper Ganga basin. Change vectors of NDVI and Tasseled Cap brightness, greenness and wetness of Landsat Thematic Mapper (TM) images are compared with those values from the initial date of imagery to detect change from no change. Ground truth information and historic images were used to assess the accuracy of the classification results. We find that most of the land-use change is conversion from forest and barren land to agricultural areas. Results indicate that between 1984 and 2010 agricultural areas have increased by more than 150% while forest areas decreased by 28%. The classification accuracy is also examined. Results confirm the importance of field-based accuracy assessment to identify problems in a land-use map and to improve area estimates for each class. The results quantify the land cover change patterns in the

  15. 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

  16. 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.

  17. 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

  18. What is a picture worth? A history of remote sensing

    Science.gov (United States)

    Moore, Gerald K.

    1979-01-01

    Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.

  19. Oil pollution signatures by remote sensing.

    Science.gov (United States)

    Catoe, C. E.; Mclean, J. T.

    1972-01-01

    Study of the possibility of developing an effective remote sensing system for oil pollution monitoring which would be capable of detecting oil films on water, mapping the areal extent of oil slicks, measuring slick thickness, and identifying the oil types. In the spectral regions considered (ultraviolet, visible, infrared, microwave, and radar), the signatures were sufficiently unique when compared to the background so that it was possible to detect and map oil slicks. Both microwave and radar techniques are capable of operating in adverse weather. Fluorescence techniques show promise in identifying oil types. A multispectral system will be required to detect oil, map its distribution, estimate film thickness, and characterize the oil pollutant.

  20. 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...... will be able to record the spectral signatures of water and land surfaces with a pixel resolution of around 15 cm, whereas the thermal camera will sense water and land surface temperature with a resolution of 40 cm. Post-processing of data from the thermal camera will allow retrieving vegetation and soil...

  1. 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

  2. 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

  3. On strategies for inverting remote sensing data

    Science.gov (United States)

    Jeffrey, W.; Rosner, R.

    1986-01-01

    Attention is given to a number of methods for inverting remote sensing data obtained in a variety of astronomical applications. Applications include image restoration, inversion of helioseismological data to obtain the internal rotation rate of stars such as the sun, fitting of spectra (especially thermal line spectra) to grating or other dispersed observed spectra, differential emission measure analysis, and reconstruction of images derived from interferometric observations. The results consider the tradeoff between resolution and variance and the stability properties for each method and propose an inversion stragegy using the available techniques.

  4. 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...

  5. 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.

  6. 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.

  7. 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)

  8. 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...

  9. 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.

  10. Remote sensing strategies for global resource exploration and environmental management

    Science.gov (United States)

    Henderson, Frederick B.

    Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources

  11. COMET: a planned airborne mission to simultaneously measure CO2 and CH4 columns using airborne remote sensing and in-situ techniques

    Science.gov (United States)

    Fix, A.; Amediek, A.; Büdenbender, C.; Ehret, G.; Wirth, M.; Quatrevalet, M.; Rapp, M.; Gerilowski, K.; Bovensmann, H.; Gerbig, C.; Pfeilsticker, K.; Zöger, M.; Giez, A.

    2013-12-01

    To better predict future trends in the cycles of the most important anthropogenic greenhouse gases, CO2 and CH4, there is a need to measure and understand their distribution and variation on various scales. To address these requirements it is envisaged to deploy a suite of state-of-the-art airborne instruments that will be capable to simultaneously measure the column averaged dry-air mixing ratios (XGHG) of both greenhouse gases along the flight path. As the measurement platform serves the research aircraft HALO, a modified Gulfstream G550, operated by DLR. This activity is dubbed CoMet (CO2 and Methane Mission). The instrument package of CoMet will consist of active and passive remote sensors as well as in-situ instruments to complement the column measurements by highly-resolved profile information. As an active remote sensing instrument CHARM-F, the integrated-path differential absorption lidar currently under development at DLR, will provide both, XCO2 and XCH4, below flight altitude. The lidar instrument will be complemented by MAMAP which is a NIR/SWIR absorption spectrometer developed by University of Bremen and which is also capable to derive XCH4 and XCO2. As an additional passive instrument, mini-DOAS operated by University of Heidelberg will contribute with additional context information about the investigated air masses. In order to compare the remote sensing instruments with integrated profile information, in-situ instrumentation is indispensable. The in-situ package will therefore comprise wavelength-scanned Cavity-Ring-Down Spectroscopy (CRDS) for the detection of CO2, CH4, CO and H2O and a flask sampler for collection of atmospheric samples and subsequent laboratory analysis. Furthermore, the BAsic HALO Measurement And Sensor System (BAHAMAS) will provide an accurate set of meteorological and aircraft state parameters for each scientific flight. Within the frame of the first CoMet mission scheduled for the 2015 timeframe it is planned to concentrate

  12. Quantification of Permafrost Creep by Remote Sensing

    Science.gov (United States)

    Roer, I.; Kaeaeb, A.

    2008-12-01

    Rockglaciers and frozen talus slopes are distinct landforms representing the occurrence of permafrost conditions in high mountain environments. The interpretation of ongoing permafrost creep and its reaction times is still limited due to the complex setting of interrelating processes within the system. Therefore, a detailed monitoring of rockglaciers and frozen talus slopes seems advisable to better understand the system as well as to assess possible consequences like rockfall hazards or debris-flow starting zones. In this context, remote sensing techniques are increasingly important. High accuracy techniques and data with high spatial and temporal resolution are required for the quantification of rockglacier movement. Digital Terrain Models (DTMs) derived from optical stereo, synthetic aperture radar (SAR) or laser scanning data are the most important data sets for the quantification of permafrost-related mass movements. Correlation image analysis of multitemporal orthophotos allow for the quantification of horizontal displacements, while vertical changes in landform geometry are computed by DTM comparisons. In the European Alps the movement of rockglaciers is monitored over a period of several decades by the combined application of remote sensing and geodetic methods. The resulting kinematics (horizontal and vertical displacements) as well as spatio-temporal variations thereof are considered in terms of rheology. The distinct changes in process rates or landform failures - probably related to permafrost degradation - are analysed in combination with data on surface and subsurface temperatures and internal structures (e.g., ice content, unfrozen water content).

  13. 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.

  14. Biogeochemical cycling and remote sensing

    Science.gov (United States)

    Peterson, D. L.

    1985-01-01

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

  15. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  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. LWIR Microgrid Polarimeter for Remote Sensing Studies

    Science.gov (United States)

    2010-02-28

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

  18. 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.

  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. Data Quality in Remote Sensing

    Science.gov (United States)

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

    2017-09-01

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

  1. Levee Health Monitoring With Radar Remote Sensing

    Science.gov (United States)

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

    2012-12-01

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

  2. The global troposphere - Biogeochemical cycles, chemistry, and remote sensing

    Science.gov (United States)

    Levine, J. S.; Allario, F.

    1982-01-01

    The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions are reviewed. Future thrusts in remote sensing of the troposphere are also considered.

  3. 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

  4. Quarterly literature review of the remote sensing of natural resources

    Science.gov (United States)

    Fears, C. B. (Editor); Inglis, M. H. (Editor)

    1977-01-01

    The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports.

  5. 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,

  6. Remote Sensing Techniques Applying Neural Networks for Effective Retrieval of Harmful Algal Blooms in the West Florida Shelf from VIIRS Satellite Observations, without the need for a Fluorescence Channel, and their comparisons with other Techniques.

    Science.gov (United States)

    El-habashi, A.; Ahmed, S.; Lovko, V. J.

    2016-02-01

    Remote sensing approaches using neural networks (NN), are described that make use of the Ocean Color Remote Sensing Reflectances (OC Rrs) available from Visible Infrared Imaging Radiometer Suite (VIIRS) satellite bands at 486, 551 and 671nm to detect and retrieve Karenia brevis (KB) Harmful Algal Blooms (HABs) that plague West Florida Shelf (WFS) coasts impacting the environment and tourism. This approach is necessitated because VIIRS, unfortunately, unlike the Moderate Resolution Imaging Spectroradiometer (MODIS), does not have a 678 nm chlorophyll-a fluorescence channel that is normally effectively used with the normalized fluorescence height (nFLH) algorithm for detecting KB HABs in the WFS. We describe here the application of neural networks (NNs) previously reported by us for Chesapeake Bay chlorophyll retrievals, for the retrieval of phytoplankton absorption at 443 nm (aph443) in VIIRS images of the WFS using the existing VIIRS 486, 551 and 671nm bands. These NN retrieved aph443 values, are then converted to equivalent [Chla] values using known empirical relationships between them for the WFS. Now waters compatible with KB HABS in the WFS are known to be characterized by a minimum permissible [Chla] and a maximum permissible particulate backscatter bbp at 551nm (and therefore a maximum permissible VIIRS Rrs 551 nm). These two limiting criteria are then used to create exclusion masks which are then consecutively applied as filters to retrieved VIIRS Rrs551nm images and then to VIIRS [Chla] images (obtained from equivalent NN retrieved aph443 images). The residual [Chla] image after application of the filters then shows values compatible with KB HABS in the WFS having satisfied both maximum Rrs551nm and minimum [Chla] criteria. The residual images of KB compatible [Chla] values are then used to identify, delineate and quantify the existing KB HABS. Comparisons with in-situ measurements and other techniques, including nFLH with MODIS, are presented, and confirm

  7. 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...

  8. Tools and Methods for the Registration and Fusion of Remotely Sensed Data

    Science.gov (United States)

    Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

    2010-01-01

    Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

  9. 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.

  10. 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

  11. Modeling tropical land-use and land-cover change related to sugarcane crops using remote sensing and soft computing techniques

    Science.gov (United States)

    Vicente, L. E.; Koga-Vicente, A.; Friedel, M. J.; Zullo, J.; Victoria, D.; Gomes, D.; Bayma, G.

    2013-12-01

    Agriculture is closely related to land-use/cover changes (LUCC). The increase in demand for ethanol necessitates the expansion of areas occupied by corn and sugar cane. In São Paulo state, the conversion of this land raises concern for impacts on food security, such as the decrease in traditional food crop production areas. We used remote sensing data to train and evaluate future land-cover scenarios using a machine-learning algorithm. The land cover classification procedure was based on Landsat 5 TM images, obtained from the Global Land Survey, covering three time periods over twenty years (1990 - 2010). Landsat images were segmented into homogeneous objects, which represent areas on the ground with similar spatial and spectral characteristics. These objects are related to the distinct land cover types that occur in each municipality. Based on the object shape, texture and spectral characteristics, land use/cover was visually identified, considering the following classes: sugarcane plantations, pasture lands, natural cover, forest plantation, permanent crop, short cycle crop, water bodies and urban areas. Results for the western regions of São Paulo state indicate that sugarcane crop area advanced mostly upon pasture areas with few areas of food crops being replaced by sugarcane.

  12. Local bleaching thresholds established by remote sensing techniques vary among reefs with deviating bleaching patterns during the 2012 event in the Arabian/Persian Gulf.

    Science.gov (United States)

    Shuail, Dawood; Wiedenmann, Jörg; D'Angelo, Cecilia; Baird, Andrew H; Pratchett, Morgan S; Riegl, Bernhard; Burt, John A; Petrov, Peter; Amos, Carl

    2016-04-30

    A severe bleaching event affected coral communities off the coast of Abu Dhabi, UAE in August/September, 2012. In Saadiyat and Ras Ghanada reefs ~40% of the corals showed signs of bleaching. In contrast, only 15% of the corals were affected on Delma reef. Bleaching threshold temperatures for these sites were established using remotely sensed sea surface temperature (SST) data recorded by MODIS-Aqua. The calculated threshold temperatures varied between locations (34.48 °C, 34.55 °C, 35.05 °C), resulting in site-specific deviations in the numbers of days during which these thresholds were exceeded. Hence, the less severe bleaching of Delma reef might be explained by the lower relative heat stress experienced by this coral community. However, the dominance of Porites spp. that is associated with the long-term exposure of Delma reef to elevated temperatures, as well as the more pristine setting may have additionally contributed to the higher coral bleaching threshold for this site. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

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

    African Journals Online (AJOL)

    Full Name

    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 the Gaussian mixture model algorithm. For the purpose of ...

  20. Preface: Remote Sensing in Flood Monitoring and Management

    Directory of Open Access Journals (Sweden)

    Guy J-P. Schumann

    2015-12-01

    Full Text Available This Special Issue is a collection of papers studying the use of remote sensing data and methods for flood monitoring and management. The articles contributed span a wide range of topics and present novel processing techniques, review methods and discuss limitations, and also report on current capabilities and outline emerging needs. This preface provides a brief overview of the content. [...

  1. 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 ...

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

    African Journals Online (AJOL)

    2014-02-28

    Feb 28, 2014 ... 5CETA, Facultad de Ciencias Físicas Exactas y Naturales, Av Filloy S/N, Campus Univ. Nacional de Córdoba, C.P 5000, Argentina. ABSTRACT. Quantification of the water cycle components is key to managing water resources. Remote sensing techniques and products have recently been developed for ...

  3. Remote Sensing of Ocean Color

    Science.gov (United States)

    Dierssen, Heidi M.; Randolph, Kaylan

    The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats

  4. Planning and Implementation of Remote Sensing Experiments.

    Science.gov (United States)

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

  5. 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…

  6. Some guidelines for remote sensing in hydrology

    Science.gov (United States)

    Robinove, Charles J.; Anderson, Daniel G.

    1969-01-01

    Remote sensing in the field of hydrology is beginning to be applied to significant problems, such as thermal pollution, in many programs of the Federal and State Governments as well as in operation of many private organizations. The purpose of this paper is to guide the hydrologist to a better understanding of how he may collect, synthesize, and interpret remote sensing data.

  7. 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.

  8. Land Conversion Dynamics in the Borana Rangelands of Southern Ethiopia: An Integrated Assessment Using Remote Sensing Techniques and Field Survey Data

    Directory of Open Access Journals (Sweden)

    Michael Elias

    2015-01-01

    Full Text Available Conversion of rangelands into cultivated land is one of the main challenges affecting the management of rangelands in Ethiopia. In order to inform policy makers about trends in land-use conversion, this study examined the drivers, trends, and impacts of land conversions in five locations selected in the Borana rangelands of Southern Ethiopia. This study integrated survey interviews from agro-pastoralists, participatory appraisals, rainfall data, and remotely sensed satellite data from Landsat images taken in 1985 and 2011. Results indicate that there is a marked increase in cultivated land in some of the study sites while in the other sites there is a slight reduction. The bare lands increased in some parts of the study sites though there was slight recovery of grassland in some of the degraded areas. Settlement areas with permanent housing increased. Woodland vegetation decreased except on mountain escarpments where there were slight gains. The results further show that, during this period, bushland decreased while at the same time grassland increased. Shrub/grassland with seasonally flooded areas increased in the bottomlands. Inhabitants interviewed in the study areas perceived land use and land cover changes to be driven by interplay of recurrent drought, loss of pasture, food insecurity, and decline in income. Changes in policies that govern natural resources have influence the land use change in this area and the expansion of cultivation. Expansion of cultivation practices upon rangelands has resulting in significant loss of vegetation biomass and soil erosion, thereby precipitating rangeland degradation. The results provide comprehensive insights regarding the influence of internal and external drivers of land conversion that should be considered when making decisions for land use planning.

  9. Integration of New Observation Techniques, Remote Sensing, and High Resolution Modelling for Improved Quantification of Rapid Environmental Change at a Canadian Arctic Watershed

    Science.gov (United States)

    Marsh, P.; Toure, A.; Baltzer, J. L.; Sonnentag, O.; Berg, A. A.; Derksen, C.; Walker, B.; Wilcox, E.

    2016-12-01

    Multi-decade observations at a research watershed in the western Canadian Arctic has demonstrated rapid environmental change, but has also shown that our quantification of, and understanding of, these changes is greatly limited by both the large errors involved in many observation data sets and the limitations of standard models to operate at the extremely high resolution required. This paper will outline an expanding research program being developed at the Trail Valley Creek research watershed south of Tuktoyaktuk, NWT with the gaol to overcome these limitations. Although this watershed has existing high quality observations, the following example will illustrate the challenges faced in understanding the ongoing changes. As might be expected, the climate at this location is dramatically warming, but it is also drying, and the active layer is deepening, shrub patches are both infilling and expanding, the end of winter snow cover is expanding in shrub patches and possibly decreasing in slope drifts, and snowmelt rate is changing. However, the resulting decrease in streamflow and delayed melt runoff, is unexpected and hard to explain. Although we can postulate why these changes are occurring, the observations at this site, among the best in the Canadian Arctic, are not sufficient to allow us to fully explain the ongoing changes. Our experience at Trail Valley Creek suggests that in order to improve our understanding and predictive ability, we need enhanced field observations and models. This paper will outline how we are developing such a program at Trail Valley Creek with field observations across a range of scales (a network of cosmic ray sensors, eddy covariance measurements, and sap flow sensors for example); enhanced remote sensing using lidar, optical and radar methods from Unmanned Aerial Systems, aircraft and satellites; and high resolution, physics based, snow, permafrost and hydrologic models.

  10. 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...

  11. Image enhancement and performance evaluation using various filters for IRS-P6 Satellite Liss IV remotely sensed data

    OpenAIRE

    Kumar, T. Ganesh; Murugan, D.; Rajalakshmi, K.; Manish, T. I.

    2015-01-01

    This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic filter and selected noises salt and pepper and Gaussian noise used with filter. Selected images tested...

  12. 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

  13. 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

  14. 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

  15. 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

  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. 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

  18. Microwave remote sensing from space

    Science.gov (United States)

    Carver, K. R.; Elachi, C.; Ulaby, F. T.

    1985-01-01

    Spaceborne microwave remote sensors provide perspectives of the earth surface and atmosphere which are of unique value in scientific studies of geomorphology, oceanic waves and topography, atmospheric water vapor and temperatures, vegetation classification and stress, ice types and dynamics, and hydrological characteristics. Microwave radars and radiometers offer enhanced sensitivities to the geometrical characteristics of the earth's surface and its cover, to water in all its forms - soil and vegetation moisture, ice, wetlands, oceans, and atmospheric water vapor, and can provide high-resolution imagery of the earth's surface independent of cloud cover or sun angle. A brief review of the historical development and principles of active and passive microwave remote sensing is presented, with emphasis on the unique characteristics of the information obtainable in the microwave spectrum and the value of this information to global geoscientific studies. Various spaceborne microwave remote sensors are described, with applications to geology, planetology, oceanography, glaciology, land biology, meteorology, and hydrology. A discussion of future microwave remote sensor technological developments and challenges is presented, along with a summary of future missions being planned by several countries.

  19. 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.

  20. 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.

  1. Hyperspectral remote sensing for terrestrial applications

    Science.gov (United States)

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

    2015-01-01

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

  2. An international organization for remote sensing

    Science.gov (United States)

    Helm, Neil R.; Edelson, Burton I.

    1991-01-01

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

  3. Vibration measurement on large structures by microwave remote sensing

    Science.gov (United States)

    Gentile, Carmelo

    2012-06-01

    Recent advances in radar techniques and systems have led to the development of microwave interferometers, suitable for the non-contact vibration monitoring of large structures. In the first part of the paper, the main techniques adopted in microwave remote sensing are described, so that advantages and potential issues of these techniques are addressed and discussed. Subsequently, the results of past and recent tests of full-scale structures are presented, in order to demonstrate the reliability and accuracy of microwave remote sensing; furthermore, the simplicity of use of the radar technology is exemplified in practical cases, where the access with conventional techniques is uneasy or even hazardous, such as the stay cables of cable-stayed bridges.

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

    OpenAIRE

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

    2013-01-01

    Based on Landsat image, the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) uses radiation change detection method for image processing and offers the surface reflectivity products for ecosystem carbon sequestration and carbon reserves. As the accumulation of massive remote sensing data, the traditional serial LEDAPS for image processing has a long cycle that make a lot of difficulties in practical application. For this problem, this paper design a high performance parallel ...

  5. 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.

  6. 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.

  7. Remote Sensing Wind and Wind Shear System.

    Science.gov (United States)

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

  8. 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...

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. Preface: Remote Sensing of Water Resources

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-02-01

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

  14. 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.

  15. Remote sensing of euphotic depth in shallow tropical inland waters of Lake Naivasha using MERIS data

    CSIR Research Space (South Africa)

    Majozi, NP

    2014-05-01

    Full Text Available Freshwater resources are deteriorating rapidly due to human activities and climate change. Remote sensing techniques have shown potential for monitoring water quality in shallow inland lakes, especially in data-scarce areas. The purpose...

  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. 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.

  18. Training state agency personnel in satellite remote sensing technology - Solutions to a special problem

    Science.gov (United States)

    Short, N. M.

    1980-01-01

    To aid state/local agencies in starting effective programs to apply Landsat and other remote sensing data, NASA's Eastern Regional Remote Sensing Applications Center (ERRSAC) has developed a comprehensive training program as part of its technology transfer mission. Skills in data processing and interpretation are produced through 'hands-on' experience with computer techniques used to conduct practical applications involving state-oriented projects, conducted jointly by agencies and ERRSAC. In time, ERRSAC will shift much of these training activities to universities where future agency personnel can obtain a broader foundation in remote sensing.

  19. Remote sensing applications to support sustainable natural resource management

    Science.gov (United States)

    Brewer, Charles Kenneth

    The original design of this dissertation project was relatively simple and straightforward. It was intended to produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems encountered during the first phase of the original design transformed this project into an extensive analysis of the nature of these problems and a decade-long remote sensing applications development endeavor. What evolved from this applications development process is a portion of what has become a "system of systems" to inform and support natural resource management. This dissertation presents the progression of work that sequentially developed a suite of remote sensing applications designed to address different aspects of the problems encountered with the original project. These remote sensing applications feature different resource issues, and resource components and are presented in separate chapters. Chapter one provides an introduction and description of the project evolution and chapter six provides a summary of the work and concluding discussion. Chapters two through five describe remote sensing applications that represent related, yet independent studies that are presented essentially as previously published. Chapter two evaluates different approaches to classifying and mapping fire severity using multi-temporal Landsat TM data. The recommended method currently represents the analytical basis for fire severity data produced by the USDA Forest Service and the US Geological Survey. Chapter three also uses multi-temporal Landsat data and compares quantitative, remote-sensing-based change detection methods for forest management related canopy change. The recommended method has been widely applied for a variety of forest health and disaster response applications

  20. 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.

  1. Laser Remote Sensing: FY07 Summary Report

    Energy Technology Data Exchange (ETDEWEB)

    Harper, Warren W.; Strasburg, Jana D.; Golovich, Elizabeth C.; Thompson, Jason S.; Stewart, Timothy L.; Batdorf, Michael T.; Mendoza, Albert

    2007-09-30

    Standoff detection and characterization of chemical plumes using Frequency Modulated Differential Absorption Lidar (FM-DIAL) is a promising technique for the detection of nuclear proliferation activities. For the last several years Pacific Northwest National Laboratory (PNNL) has been developing an FM-DIAL based remote sensing system as part of PNNL's Infrared Sensors project within NA-22's Enabling Technologies portfolio. In FY06 the remote sensing effort became a stand-alone project within the Plutonium Production portfolio with the primary goal of transitioning technology from the laboratory to the user community. Current systems remotely detect trace chemicals in the atmosphere over path lengths of hundreds of meters for monostatic operation (without a retro-reflector target) and up to ten kilometers for bistatic operation (with a retro-reflector target). The FM-DIAL sensor is sensitive and highly selective for chemicals with narrow-band absorption features on the order of 1-2 cm-1; as a result, the FM-DIAL sensors are best suited to simple di-atomic or tri-atomic molecules and other molecules with unusually narrow absorption features. A broadband sensor is currently being developed. It is designed to detect chemicals with spectral features on the order of several 10s of wavenumbers wide. This will expand the applicability of this technology to the detection of more complicated molecules. Our efforts in FY07 focused on the detection of chemicals associated with the PUREX process. The highest value performance measure for FY07, namely the demonstration of the Broadband Laser Spectrometer (BLS) during chemical release experiments, was successfully achieved in June, July and August of this year. Significant advancements have been made with each of the other tasks as well. A short-wave infrared version of the miniature FM-DIAL (FM-Mini) instrument was successfully demonstrated during field tests in June. During FY07 another version of the FM-Mini was

  2. 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.

  3. Remote Sensing of Water Quality in a Tropical Freshwater Impoundment

    Science.gov (United States)

    Campbell, G.; Phinn, S. R.; Dekker, A. G.; Brando, V. E.

    2010-12-01

    The purpose of this study was to investigate how techniques developed for the remote sensing of water quality parameters (chlorophyll a, tripton and coloured dissolved organic matter (CDOM)) in inland waters in temperate northern hemisphere environments could be adapted or improved to allow them to be applied to tropical and sub-tropical water bodies. The Matrix Inversion Method (MIM) with a semi analytic model of the anisotropy of the in-water light field was applied to MERIS images of Burdekin Falls Dam, Australia, a tropical freshwater impoundment. The performance of the conventional three band exact solution of the MIM was compared to that of over determined solutions that used constant and differential weighting for each sensor band. The results of the application of the MIM algorithm showed that the best weighting scheme had a mean chlorophyll a retrieval error of 1.0 μgl-1, the conventional three band scheme had a mean error of 4.2 μgl-1 and the constant weight scheme had a mean error of 5.5 μgl-1. For tripton, the best performed weighting scheme had a mean error of 1.2 mgl-1, the three band scheme had a mean error of 3.4 mgl-1 and the constant weight scheme had a mean error of 1.8 mgl-1. For the CDOM retrieval, the mean error was found to be 0.12 m-1 for the best performed weighting scheme, 0.25 m-1 for the three band scheme and 0.52 m-1 for the constant weight scheme. It was found that significant improvements in the accuracy and precision of retrieved water quality parameter values can be obtained by using semi-analytically estimated values for the anisotropic factor and that over-determined systems of equations can be used to mitigate the effect of unknown and endemic sources of error in the remote sensing system. These more reliable estimates of water quality parameters will allow water resource managers to improve their monitoring regimes.

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

    Science.gov (United States)

    Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

    2014-05-01

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

  5. Assessment of Watershed Drought Using Remote Sensing

    Science.gov (United States)

    Chataut, S.; Piechota, T.

    2005-12-01

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

  6. Far Ultraviolet Remote Sensing: Challenges and Opportunities

    Science.gov (United States)

    Paxton, L. J.

    2004-12-01

    The far ultraviolet is commonly taken to be that spectral range from 115 nm to 185 nm. This definition reflects the practical nature and origin of the measurement technique. The short wavelength cut-off is defined by the transmittance cut-off of window materials (about 115 nm). The long wavelength end of the region is defined by the desire to exclude the orders-of-magnitude brighter signal at around 195 nm, which, happily, coincides with the fall-off in CsI photocathode efficiency at around 185 nm. The FUV allows us to probe the atmosphere down to about 130 km (as low as 80 km in H Lyman alpha). In this paper I will discuss what we have learned by using a novel imager, GUVI, on TIMED to study the ionosphere-thermosphere (IT) system, how we see the IT coupled to geospace and the solar input, and what we can learn from a future FUV system. In particular, I want to stress that FUV remote sensing is an important COMPONENT of a complete system for exploring the connections between the Sun, geospace, and the IT system. To that end, I will briefly discuss how those data need to be integrated into a virtual observatory that will enable new investigations into the near-Earth environment.

  7. Remote sensing for rural development planning in Africa

    Science.gov (United States)

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

    1983-01-01

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

  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. On multidisciplinary research on the application of remote sensing to water resources problems. [Wisconsin

    Science.gov (United States)

    Clapp, J. L.

    1973-01-01

    Research objectives during 1972-73 were to: (1) Ascertain the extent to which special aerial photography can be operationally used in monitoring water pollution parameters. (2) Ascertain the effectiveness of remote sensing in the investigation of nearshore mixing and coastal entrapment in large water bodies. (3) Develop an explicit relationship of the extent of the mixing zone in terms of the outfall, effluent and water body characteristics. (4) Develop and demonstrate the use of the remote sensing method as an effective legal implement through which administrative agencies and courts can not only investigate possible pollution sources but also legally prove the source of water pollution. (5) Evaluate the field potential of remote sensing techniques in monitoring algal blooms and aquatic macrophytes, and the use of these as indicators of lake eutrophication level. (6) Develop a remote sensing technique for the determination of the location and extent of hydrologically active source areas in a watershed.

  10. PHOTOGRAMMETRY – REMOTE SENSING AND GEOINFORMATION

    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou

    2012-07-01

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

  11. 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.

  12. 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.

  13. 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, David; Potter, Christopher; Zhang, Minghua; Madsen, John

    2017-01-01

    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 to 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 in the 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 are improving 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.

  14. Additional development of remote sensing techniques for observing morphology, microphysics, and radiative properties of clouds and tests using a new, robust CO{sub 2} lidar. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Eberhard, W.L.; Brewer, W.A.; Intrieri, J.M.

    1998-09-28

    A three-year project with a goal of advancing CO{sub 2} lidar technology and measurement techniques for cloud studies was successfully completed. An eyesafe, infrared lidar with good sensitivity and improved Doppler accuracy was designed, constructed, and demonstrated. Dual-wavelength operation was achieved. A major leap forward in robustness was demonstrated. CO{sub 2} lidars were operated as part of two Intensive Operations Periods at the Southern Great Plains CART site. The first used an older lidar and was intended primarily for measurement technique development. The second used the new lidar and was primarily a demonstration and evaluation of its performance. Progress was demonstrated in the development, evaluation, and application of measurement techniques using CO{sub 2} lidar.

  15. Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

    Science.gov (United States)

    2014-09-30

    resolution remote sensing imagery pixels, such as MODIS . APPROACH Key Particpants: Chris Polashenski (Research Geophysicist, ERDC-CRREL) Elias Deeb...the imagery to identify surface types - using calibrated spectral albedo measurements from prior field work for different surface types to create a...techniques lie at the core of recent developments in lower resolution remote sensing of ponds using MODIS (i.e. Rosel et al., 2014) raising serious

  16. 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.

  17. Remote sensing applications in environmental research

    CERN Document Server

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

    2014-01-01

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

  18. Assessment of some remote sensing techniques used to detect land use/land cover changes in South-East Transilvania, Romania.

    Science.gov (United States)

    Vorovencii, Iosif

    2014-05-01

    This paper assesses the image differencing technique for the Normalized Difference Vegetation Index (NDVI), the second principal component (PC2), and the TM 4 band (TM 4), as well as the post-classification comparison (PCC) in order to analyze the land use/land cover changes in the South-East Transilvania, Romania. The analysis was performed using two frames from Landsat 5 TM satellite images acquired on August 5, 1993 and July 24, 2009. After applying the NDVI, PC2, and TM 4 image differencing techniques, the images obtained were transformed into change/no change maps. The thresholds identified to highlight the changes were set at 0.6 s for NDVI and 0.7 s for PC2 and TM 4. Before applying the PCC technique, the satellite images were classified through the supervised classification method. The overall accuracy obtained was 85.91 % and the kappa statistics 0.8249 for 1993, 88.18 % and 0.8497 for 2009, respectively. The assessment of the changes detection methods in the studied area shows that the first place is occupied by NDVI image differencing with an overall accuracy of 83.80 %, followed by PCC method with 83.20 %, PC2 difference with an overall accuracy of 81.60 %, and TM 4 difference with an overall accuracy of 79.40 %.

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

    Science.gov (United States)

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

    2016-04-01

    Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project

  20. Remote sensing of land surface phenology

    Science.gov (United States)

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

    2014-01-01

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

  1. 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

  2. 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...

  3. 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.

  4. Current NASA Earth Remote Sensing Observations

    Science.gov (United States)

    Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin; hide

    2011-01-01

    This slide presentation reviews current NASA Earth Remote Sensing observations in specific reference to improving public health information in view of pollen sensing. While pollen sampling has instrumentation, there are limitations, such as lack of stations, and reporting lag time. Therefore it is desirable use remote sensing to act as early warning system for public health reasons. The use of Juniper Pollen was chosen to test the possibility of using MODIS data and a dust transport model, Dust REgional Atmospheric Model (DREAM) to act as an early warning system.

  5. 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

  6. [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.

  7. Optical remote sensing of lakes: an overview on Lake Maggiore

    Directory of Open Access Journals (Sweden)

    Claudia Giardino

    2013-08-01

    Full Text Available Optical satellite remote sensing represents an opportunity to integrate traditional methods for assessing water quality of lakes: strengths of remote sensing methods are the good spatial and temporal coverage, the possibility to monitor many lakes simultaneously and the reduced costs. In this work we present an overview of optical remote sensing techniques applied to lake water monitoring. Then, examples of applications focused on lake Maggiore, the second largest lake in Italy are discussed by presenting the temporal trend of chlorophyll-a (chl-a, suspended particulate matter (SPM, coloured dissolved organic matter (CDOM and the z90 signal depth (the latter indicating the water depth from which 90% of the reflected light comes from as estimated from the images acquired by the Medium Resolution Imaging Spectrometer (MERIS in the pelagic area of the lake from 2003 to 2011. Concerning the chl-a trend, the results are in agreement with the concentration values measured during field surveys, confirming the good status of lake Maggiore, although occasional events of water deterioration were observed (e.g., an average increase of chl-a concentration, with a decrease of transparency, as a consequence of an anomalous phytoplankton occurred in summer 2011. A series of MERIS-derived maps (summer period 2011 of the z90 signal are also analysed in order to show the spatial variability of lake waters, which on average were clearer in the central pelagic zones. We expect that the recently launched (e.g., Landsat-8 and the future satellite missions (e.g., Sentinel-3 carrying sensors with improved spectral and spatial resolution are going to lead to a larger use of remote sensing for the assessment and monitoring of water quality parameters, by also allowing further applications (e.g., classification of phytoplankton functional types to be developed.

  8. Mid-Latitude Snowmelt Onset Detection Via Microwave Remote Sensing

    Science.gov (United States)

    Vuyovich, C.; Jacobs, J. M.; Osborne, D.; Hunsaker, A. G.; Tuttle, S. E.

    2016-12-01

    The timing and magnitude of spring snowmelt events are critical for understanding the winter-to-spring transition of the hydrologic cycle and ecosystem processes. Melt timing determination is challenging because snowpack ripening observations are seldom available. Remotely sensed passive microwave observations show promise for determining snowpack wetting and melt onset at global scales. Studies performed in northern latitude regions verify the theoretical concept of microwave snowmelt detection methods under ideal conditions. However, early winter snowmelt events within mid-latitude regions introduce large regional climate differences that add considerable amounts of noise to the microwave observations. Diurnal Amplitude Variation (DAV), Frequency Difference (FD) and Polarization Ratio (PR) are three methods that use remotely sensed passive microwave observations to determine snowpack wetting and melt onset. This study evaluates the performance of these approaches to determine spring melt onset and early winter flood events in mid-latitudes. The suitability of microwave remote sensing techniques to detect snowmelt was found to vary regionally. Physical characteristics including basin latitude, regional air temperatures, snow depth, snow covered area, forest density, and rain intensity were examined to understand how and why the observed microwave signatures associated with snow cover vary over contrasting regions.

  9. Combining Remote Sensing with in situ Measurements for Riverine Characterization

    Science.gov (United States)

    Calantoni, J.; Palmsten, M. L.; Simeonov, J.; Dobson, D. W.; Zarske, K.; Puleo, J. A.; Holland, K. T.

    2014-12-01

    At the U.S. Naval Research Laboratory we are employing a wide variety of novel remote sensing techniques combined with traditional in situ sampling to characterize riverine hydrodynamics and morphodynamics. Surface currents were estimated from particle image velocimetry (PIV) using imagery from visible to infrared bands, from both fixed and airborne platforms. Terrestrial LIDAR has been used for subaerial mapping from a fixed platform. Additionally, LIDAR has been combined with hydrographic surveying (multibeam) in mobile scanning mode using a small boat. Hydrographic surveying (side scan) has also been performed using underwater autonomous vehicles. Surface drifters have been deployed in combination with a remotely operated, floating acoustic Doppler current profiler. Other fixed platform, in situ sensors, such as pencil beam and sector scanning sonars, acoustic Doppler velocimeters, and water level sensors have been deployed. We will present an overview of a variety of measurements from different rivers around the world focusing on validation examples of remotely sensed quantities with more traditional in situ measurements. Finally, we will discuss long-term goals to use remotely sensed data within an integrated environmental modeling framework.

  10. 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.

  11. Proxies for soil organic carbon derived from remote sensing

    Science.gov (United States)

    Rasel, S. M. M.; Groen, T. A.; Hussin, Y. A.; Diti, I. J.

    2017-07-01

    The possibility of carbon storage in soils is of interest because compared to vegetation it contains more carbon. Estimation of soil carbon through remote sensing based techniques can be a cost effective approach, but is limited by available methods. This study aims to develop a model based on remotely sensed variables (elevation, forest type and above ground biomass) to estimate soil carbon stocks. Field observations on soil organic carbon, species composition, and above ground biomass were recorded in the subtropical forest of Chitwan, Nepal. These variables were also estimated using LiDAR data and a WorldView 2 image. Above ground biomass was estimated from the LiDAR image using a novel approach where the image was segmented to identify individual trees, and for these trees estimates of DBH and Height were made. Based on AIC (Akaike Information Criterion) a regression model with above ground biomass derived from LiDAR data, and forest type derived from WorldView 2 imagery was selected to estimate soil organic carbon (SOC) stocks. The selected model had a coefficient of determination (R2) of 0.69. This shows the scope of estimating SOC with remote sensing derived variables in sub-tropical forests.

  12. 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

  13. 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.

  14. Modeling Chemical Detection Sensitivities of Active and Passive Remote Sensing Systems

    Energy Technology Data Exchange (ETDEWEB)

    Scharlemann, E T

    2003-07-28

    During nearly a decade of remote sensing programs under the auspices of the U. S. Department of Energy (DOE), LLNL has developed a set of performance modeling codes--called APRS--for both Active and Passive Remote Sensing systems. These codes emphasize chemical detection sensitivity in the form of minimum detectable quantities with and without background spectral clutter and in the possible presence of other interfering chemicals. The codes have been benchmarked against data acquired in both active and passive remote sensing programs at LLNL and Los Alamos National Laboratory (LANL). The codes include, as an integral part of the performance modeling, many of the data analysis techniques developed in the DOE's active and passive remote sensing programs (e.g., ''band normalization'' for an active system, principal component analysis for a passive system).

  15. 3-D visualisation of palaeoseismic trench stratigraphy and trench logging using terrestrial remote sensing and GPR - combining techniques towards an objective multiparametric interpretation

    Science.gov (United States)

    Schneiderwind, S.; Mason, J.; Wiatr, T.; Papanikolaou, I.; Reicherter, K.

    2015-09-01

    Two normal faults on the Island of Crete and mainland Greece were studied to create and test an innovative workflow to make palaeoseismic trench logging more objective, and visualise the sedimentary architecture within the trench wall in 3-D. This is achieved by combining classical palaeoseismic trenching techniques with multispectral approaches. A conventional trench log was firstly compared to results of iso cluster analysis of a true colour photomosaic representing the spectrum of visible light. Passive data collection disadvantages (e.g. illumination) were addressed by complementing the dataset with active near-infrared backscatter signal image from t-LiDAR measurements. The multispectral analysis shows that distinct layers can be identified and it compares well with the conventional trench log. According to this, a distinction of adjacent stratigraphic units was enabled by their particular multispectral composition signature. Based on the trench log, a 3-D-interpretation of GPR data collected on the vertical trench wall was then possible. This is highly beneficial for measuring representative layer thicknesses, displacements and geometries at depth within the trench wall. Thus, misinterpretation due to cutting effects is minimised. Sedimentary feature geometries related to earthquake magnitude can be used to improve the accuracy of seismic hazard assessments. Therefore, this manuscript combines multiparametric approaches and shows: (i) how a 3-D visualisation of palaeoseismic trench stratigraphy and logging can be accomplished by combining t-LiDAR and GRP techniques, and (ii) how a multispectral digital analysis can offer additional advantages and a higher objectivity in the interpretation of palaeoseismic and stratigraphic information. The multispectral datasets are stored allowing unbiased input for future (re-)investigations.

  16. 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.

  17. Microwave remote sensing of natural stratification

    Science.gov (United States)

    Imperatore, Pasquale; Iodice, Antonio; Riccio, Daniele

    2011-11-01

    The response of natural stratification to electromagnetic wave has received much attention in last decades, due to its crucial role played in the remote sensing arena. In this context, when the superficial structure of the Earth, whose formation is inherently layered, is concerned, the most general scheme that can be adopted includes the characterization of layered random media. Moreover, a key issue in remote sensing of Earth and other Planets is to reveal the content under the surface illuminated by the sensors. For such a purpose, a quantitative mathematical analysis of wave propagation in three-dimensional layered rough media is fundamental in understanding intriguing scattering phenomena in such structures, especially in the perspective of remote sensing applications. Recently, a systematic formulation has been introduced to deal with the analysis of a layered structure with an arbitrary number of rough interfaces. Specifically, the results of the Boundary Perturbation Theory (BPT) lead to polarimetric, formally symmetric and physical revealing closed form analytical solutions. The comprehensive scattering model based on the BPT methodologically permits to analyze the bi-static scattering patterns of 3D multilayered rough media. The aim of this paper is to systematically show how polarimetric models obtainable in powerful BPT framework can be successfully applied to several situations of interest, emphasizing its wide relevance in the remote sensing applications scenario. In particular, a proper characterization of the relevant interfacial roughness is adopted resorting to the fractal geometry; numerical examples are then presented with reference to representative of several situations of interest.

  18. 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, ...

  19. 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...

  20. Remote sensing information sciences research group

    Science.gov (United States)

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

    1988-01-01

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

  1. 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...

  2. 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...

  3. Spectrodirectional Remote Sensing: From Pixels to Processes

    NARCIS (Netherlands)

    Schaepman, M.E.

    2007-01-01

    This paper discusses the historical evolution of imaging spectroscopy in Earth observation as well as directional (or multiangular) research leading to current achievements in spectrodirectional remote sensing. It elaborates on the evolution from two separate research areas into a common approach to

  4. Experiences of a WEB based test site platform for landslide susceptibility and the use of remote sensing interferometric techniques for monitoring landslide movements in Sweden

    Science.gov (United States)

    Löfroth, H.; Hultén, C.; Ledwith, M.; Nisser-Larsson, M.; Righini, G.

    2009-04-01

    prerequisites for landslides. Susceptibility map 1b is a map showing built up areas considered to have unsatisfactory stability. The results from Stage 2 of the Swedish methodology are normally presented as cross-sections representing calculated factors of safety. Within susceptibility map 2, the results have been visualised though stability classes division. The stability classes are based on the calculated factors of safety from the detailed stability investigations in representative sections. In addition to these susceptibility maps, a proposal for the prioritization of landslide susceptible areas has been developed. The proposal is in the form of a table for prioritization. This priority table is based on the stability conditions assessed in sub-stage 1b of the Swedish methodology, i.e. susceptibility map 1b. The Differential Interferometric SAR (DIFSAR) method for movement detection has not previously been used in Sweden. From a Swedish point of view, participation in the Preview project has given the opportunity to evaluate this method with respect to detecting early movements of deep seated, rapid landslides in clay and silt (typical to Scandinavia). Based on the DIFSAR analysis of the landslide in Vagnhärad in 1997, it has not been possible to detect any movements prior to the actual landslide. One possible explanation is that landslides in Sweden often occur rapidly and are fast moving. However, the analysis indicated other small movements within the Vagnhärad area. The DIFSAR analysis of the Sundsvall area was hindered by the lack of coherent points within the area of the two landslides. This is primarily due to the lack of permanent structures, as radar benchmarks, (e.g. houses or buildings) in the vicinity. The results from the DIFSAR analysis of these landslides exposed the difficulties in detecting the minor movements prior to slides in clay and silt in Sweden. However, the DIFSAR technique has potential in Sweden for applications pertaining to other ground

  5. [Biogeocenosis thermodynamics based on remote sensing].

    Science.gov (United States)

    Sandlerskiĭ, R B; Puzachenko, Iu G

    2009-01-01

    Methodological issues in the studies of spatial and temporal variations in the energy conversion are shown to be solvable on the basis of information thermodynamic approach using the remote sensing techniques. A possibility of evaluation of the main components of the energy balance of a biogeocenosis, considered as an open thermodynamic system maintaining its structure through the conversion of solar energy, is demonstrated by analysis of the southern taiga landscapes of Valdai Hills. Analysis of the ratio of thermodynamic variables for the different types of biogeocenosis shows that the energy flow absorbed by the surface, is being redistributed among balance components by various mechanisms, and it depends on the structure of the redistribution system expressed by the non-equilibrium. Non-equilibrium of the solar energy transformation is determined before all by the energy costs in the synthesis of biological products, and has a little impact on exergy of the solar radiation, i.e., the cost of energy to evaporation. Invariance of energy conversion by landscape as a whole and generalized types of biogeocenoses are estimated. The ability of the taiga landscapes to maintain energy absorbed invariants, exergy and temperatures forms a naturally determined series similar to a succession trend: meadows--falls--deciduous forests--coniferous forest. Anthropogenic objects are shown to possess the weakest autoregulation ability. Raised bogs keep high heating of the territory and preserve precipitation in the subsurface runoff, in contrast to the forests carrying out moisture transport from the soil into the atmosphere. The bog's ability to maintain the level of biological production is comparable to that of coniferous forests. The role of forest vegetation in climate regulation is estimated; it is shown that the absence of forests increases the surface temperature by 4 degrees C.

  6. Sediment grain size estimation using airborne remote sensing, field sampling, and robust statistic.

    Science.gov (United States)

    Castillo, Elena; Pereda, Raúl; Luis, Julio Manuel de; Medina, Raúl; Viguri, Javier

    2011-10-01

    Remote sensing has been used since the 1980s to study parameters in relation with coastal zones. It was not until the beginning of the twenty-first century that it started to acquire imagery with good temporal and spectral resolution. This has encouraged the development of reliable imagery acquisition systems that consider remote sensing as a water management tool. Nevertheless, the spatial resolution that it provides is not adapted to carry out coastal studies. This article introduces a new methodology for estimating the most fundamental physical property of intertidal sediment, the grain size, in coastal zones. The study combines hyperspectral information (CASI-2 flight), robust statistic, and simultaneous field work (chemical and radiometric sampling), performed over Santander Bay, Spain. Field data acquisition was used to build a spectral library in order to study different atmospheric correction algorithms for CASI-2 data and to develop algorithms to estimate grain size in an estuary. Two robust estimation techniques (MVE and MCD multivariate M-estimators of location and scale) were applied to CASI-2 imagery, and the results showed that robust adjustments give acceptable and meaningful algorithms. These adjustments have given the following R(2) estimated results: 0.93 in the case of sandy loam contribution, 0.94 for the silty loam, and 0.67 for clay loam. The robust statistic is a powerful tool for large dataset.

  7. 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

  8. 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

  9. 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

  10. 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

  11. [Progress in leaf area index retrieval based on hyperspectral remote sensing and retrieval models].

    Science.gov (United States)

    Zhang, Jia-Hua; Du, Yu-Zhang; Liu, Xu-Feng; He, Zhen-Ming; Yang, Li-Min

    2012-12-01

    The leaf area index (LAI) is a very important parameter affecting land-atmosphere exchanges in land-surface processes; LAI is one of the basic feature parameters of canopy structure, and one of the most important biophysical parameters for modeling ecosystem processes such as carbon and water fluxes. Remote sensing provides the only feasible option for mapping LAI continuously over landscapes, but existing methodologies have significant limitations. To detect LAI accurately and quickly is one of tasks in the ecological and agricultural crop yield estimation study, etc. Emerging hyperspectral remote sensing sensor and techniques can complement existing ground-based measurement of LAI. Spatially explicit measurements of LAI extracted from hyperspectral remotely sensed data are component necessary for simulation of ecological variables and processes. This paper firstly summarized LAI retrieval method based on different level hyperspectral remote sensing platform (i. e., airborne, satelliteborne and ground-based); and secondly different kinds of retrieval model were summed up both at home and abroad in recent years by using hyperspectral remote sensing data; and finally the direction of future development of LAI remote sensing inversion was analyzed.

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

    Science.gov (United States)

    Mishra, Deepak R.

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

  13. 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.

  14. Remote sensing of natural resources

    Science.gov (United States)

    1976-01-01

    Quarterly literature review compiles citations and abstracts from eight major abstracting and indexing services. Each issue contains author/keyword index. Includes data obtained or techniques used from space, aircraft, or ground-based stations.

  15. 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

  16. Water quality monitoring using remote sensing technique

    Science.gov (United States)

    Adsavakulchai, Suwannee; Panichayapichet, Paweena

    2003-03-01

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

  17. Coastal remote sensing – towards integrated coastal research and management

    CSIR Research Space (South Africa)

    Lück-Vogel, Melanie

    2012-10-01

    Full Text Available coastal resources and anthropogenic infrastructure for a safer future. What is the role of remote sensing? The coastal zone connects terrestrial biophysical systems with marine systems. Some marine ecosystems cannot function without intact inland... for the development of sound integrated management solutions. To date, however, remote sensing applications usually focus on areas landward from the highwater line (?terrestrial? remote sensing), while ?marine? remote sensing does not pay attention to the shallow...

  18. 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.

  19. 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.

  20. 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…

  1. 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

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

    Science.gov (United States)

    Lindenlaub, J. C.; Russell, J.

    1974-01-01

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

  3. Remote sensing and lake eutrophication

    Science.gov (United States)

    Wrigley, R. C.; Horne, A. J.

    1974-01-01

    An infrared photograph of part of Clear Lake, Cal., shows complex patterns of blue-green algal blooms which were not observed by conventional limnological techniques. Repeated observations of patterns such as these can be used to chart the surface movement of these buoyant algae and can also be used to help control algal scums in eutrophic lakes. Although it is believed that most of the observed patterns resulted from Aphanizomenon (a few were also observed which resulted from suspended sediment), spectral signatures of the algal patterns varied.

  4. Photoacoustic remote sensing microscopy with lock-in amplification

    Science.gov (United States)

    Shi, Wei; Hajireza, Parsin; Bell, Kevan; Zemp, Roger

    2017-03-01

    High sensitive detection with lock-in amplification can provide high signal noise ratio even when noise is in orders of magnitude higher than the signal. Here we report to combine lock-in amplification with a novel photoacoustic remote sensing (PARS) technology to achieve high resolution, high contrast, all optical non-contact photoacoustic imaging at depth beyond optical scattering limitation. We demonstrate phantom measurements from PARS with lock-in technology were several orders of magnitude more sensitive than those from PARS with the broadband detection techniques.

  5. 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...

  6. 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

  7. 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.

  8. Microwave Radiometry in Remote Sensing

    DEFF Research Database (Denmark)

    Gudmandsen, Preben

    1982-01-01

    an international workshop was organized in June 1982 with the object of reviewing the state-o-the-art in applications and techniques and to suggest future development work in data processing and application, systems principles and performance and in component development including the antenna system....... proves useful for measurement of atmospheric parameters. Examples are detection of rain cells and frontal systems, temperature and humidity profiles and content of minor constituents in the atmosphere foremost above the troposphere. The above examples have been demonstrated from radiometer measurements...... from ballon, aircraft and spacecraft and it is expected that the next generation of spacecraft may encompass microwave radiometers in the frequency range from perhaps 1.4 GHz to 700 GHz taking advantage of a number of new developments. With the purpose of identifying the necessary developments...

  9. 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

  10. Ocean Remote Sensing Using Ambient Noise

    Science.gov (United States)

    2015-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Ocean Remote Sensing Using Ambient Noise Michael G...approximation to the transient Green’s function G(xA|xB, t) between locations xA and xB is estimated by cross-correlating records of ambient noise...Williams, N. A. Zabotin, L. Zabotina and G. J. Banker, 2014, Acoustic Green’s function extraction from ambient noise in a coastal ocean environment

  11. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

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

  12. The Fundamental Framework of Remote Sensing Validation System

    Science.gov (United States)

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

    2009-04-01

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

  13. 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

  14. A Review of Wetland Remote Sensing

    Directory of Open Access Journals (Sweden)

    Meng Guo

    2017-04-01

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

  15. 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.

  16. 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.

  17. A Review of Wetland Remote Sensing

    Science.gov (United States)

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

    2017-01-01

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

  18. Combining remotely sensed data using aggregation algorithms

    Directory of Open Access Journals (Sweden)

    W. J. Shuttleworth

    1998-01-01

    Full Text Available This paper describes a strategic approach for providing documentation of the surface energy exchange for heterogeneous land surfaces via the simultaneous, four-dimensional assimilation of several streams of remotely sensed data into a coupled land surface-atmosphere model. The basic concepts and underlying theory behind this proposed approach are presented with the intent that this will guide, facilitate, and stimulate future research focused on its practical implementation when appropriate data from the Earth Observing System (EOS become available. The theoretical concepts that underlie the approach are derived from relationships between the values of parameters which control surface exchanges at pixel (or patch scale and the area-average value of equivalent parameters applicable at larger, grid scale. A three-step implementation method is proposed which involves (a estimating grid-average surface radiation fluxes from appropriate remotely sensed data; (b absorbing these radiation flux estimates into a four-dimensional data assimilation model in which grid-average values of vegetation-related parameters are calculated from pertinent remotely sensed data using the equations that link pixel and grid scales; and (c improving the resulting estimate of the surface energy balance-again using scale-linking equations by estimating the effect of soil-moisture availability, perhaps assuming that cloud-free pixels are an unbiased subsample of all the pixels in the grid square.

  19. The cross time and space features in remote sensing applications

    Science.gov (United States)

    Lu, J. X.; Song, W. L.; Qu, W.; Fu, J. E.; Pang, Z. G.

    2015-08-01

    Remote sensing is one subject of the modern geomatics, with a high priority for practical applications in which cross time and space analysis is one of its significant features. Object recognition and/or parameter retrieval are normally the first step in remote sensing applications, whereas cross time and space change analysis of those surface objects and/or parameters will make remote sensing applications more valuable. Based on a short review on the historic evolution of remote sensing and its current classification system, the cross time and space features commonly existing in remote sensing applications were discussed. The paper, aiming at improving remote sensing applications and promoting development of the remote sensing subject from a new vision, proposed a methodology based subject classification approach for remote sensing and then suggest to establish the theory of cross time and space remote sensing applications. The authors believe that such a new cross time and space concept meets the demand for new theories and new ideas from remote sensing subject and is of practical help to future remote sensing applications.

  20. 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.

  1. Copyright protection of remote sensing imagery by means of digital watermarking

    Science.gov (United States)

    Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella; Zanini, R.

    2001-12-01

    The demand for remote sensing data has increased dramatically mainly due to the large number of possible applications capable to exploit remotely sensed data and images. As in many other fields, along with the increase of market potential and product diffusion, the need arises for some sort of protection of the image products from unauthorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred and effective means of data exchange. An important issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. Before applying watermarking techniques developed for multimedia applications to remote sensing applications, it is important that the requirements imposed by remote sensing imagery are carefully analyzed to investigate whether they are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: (1) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection; (2) discussion of a case study where the performance of two popular, state-of-the-art watermarking techniques are evaluated by the light of the requirements at the previous point.

  2. Remote Sensing Time Series Product Tool

    Science.gov (United States)

    Prados, D.; Ryan, R. E.; Ross, K. W.

    2006-12-01

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

  3. Footprint Representation of Planetary Remote Sensing Data

    Science.gov (United States)

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

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

  4. Remote sensing and GIS integration for land cover analysis, a case study: Bozcaada Island.

    Science.gov (United States)

    Bektas, F; Goksel, C

    2005-01-01

    In this study, remote sensing and geographic information system (GIS) techniques were used in order to accomplish land cover change of Bozcaada Island, Turkey, by using multitemporal Landsat Thematic Mapper data. Digital image processing techniques were conducted for the processes of image enhancement, manipulation, registration and classification for land cover change analysis. The land cover changes between two different dates were visualized and analyzed by using Geographic Information System techniques. The results showed that remotely sensed data and GIS are effective and powerful tools for carrying out changes on land cover of the island and monitoring of its impact on the environment.

  5. [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.

  6. 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.

  7. Remote sensing image classification by mean shift and colour quantization

    Science.gov (United States)

    Taud, Hind; Couturier, Stéphane; Carrillo-Rivera, José Joel

    2012-11-01

    Remote sensing imagery involves large amounts of data acquired by several kinds of airborne, sensors, wavelengths spatial resolutions, and temporal frequencies. To extract the thematic information from this data, many algorithms and techniques for segmentation and classification have been proposed. The representation of the different multispectral bands as true or false color imaging has been widely employed for visual interpretation and classification. On the other hand, the color quantization, which is a well-known method for data compression, has been utilized for color image segmentation and classification in computer vision application. The number of colors in the original image is reduced by minimizing the distortion between the quantified and the original image with the aim of conserving the pattern representation. Considering the density estimation in the color or feature space, similar samples are grouped together to identify patterns by any clustering techniques. Mean shift algorithm has been successfully applied to different applications as the basis for nonparametric unsupervised clustering techniques. Based on an iterative manner, mean shift detects modes in a probability density function. In this article, the contribution consists in providing an unsupervised color quantization method for image classification based on mean shift. To avoid its high computational cost, the integral image is used. The method is evaluated on Landsat satellite imagery as a case study to underline forest mapping. A comparison between the proposed method and the simple mean shift is carried out. The results prove that the proposed method is useful in multispectral remote sensing image classification study.

  8. 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.

  9. Satellite Remote Sensing Detection of Wastewater Plumes in Southern California

    Science.gov (United States)

    Trinh, R. C.; Holt, B.; Pan, B. J.; Rains, C.; Gierach, M. M.

    2014-12-01

    Wastewater discharged through ocean outfalls can surface near coastlines and beaches, posing a threat to the marine environment and human health. Coastal waters of the Southern California Bight (SCB) are an ecologically important marine habitat and a valuable resource in terms of commercial fishing and recreation. Two of the largest wastewater treatment plants along the U.S. West Coast discharge into the SCB, including the Hyperion Wastewater Treatment Plant (HWTP) and the Orange County Sanitation District (OCSD). In 2006, HWTP conducted an internal inspection of its primary 8 km outfall pipe (60 m depth), diverting treated effluent to a shorter 1.2 km pipe (18 m depth) from Nov. 28 to Nov. 30. From Sep. 11 - Oct. 4, 2012, OCSD conducted a similar diversion, diverting effluent from their 7 km outfall pipe to a shallower 2.2 km pipe, both with similar depths to HWTP. Prevailing oceanographic conditions in the SCB, such as temporally reduced stratification and surface circulation patterns, increased the risk of effluent being discharged from these shorter and shallower pipes surfacing and moving onshore. The aim of this study was to evaluate the capabilities of satellite remote sensing data (i.e., sea surface roughness from SAR, sea surface temperature from MODIS-Aqua and ASTER-Terra, chlorophyll-a and water leaving radiance from MODIS-Aqua) in the identification and tracking of wastewater plumes during the 2006 HWTP and 2012 OCSD diversion events. Satellite observations were combined with in situ, wind, and current data taken during the diversion events, to validate remote sensing techniques and gain surface to subsurface context of the nearshore diversion events. Overall, it was found that satellite remote sensing data were able to detect surfaced wastewater plumes along the coast, providing key spatial information that could inform in situ field sampling during future diversion events, such as the planned 2015 HWTP diversion, and thereby constrain costs.

  10. Buried Treasure: Using Distributed Ground Temperature Sensors to Test Remote Sensing of Fractional Snow Cover

    Science.gov (United States)

    Raleigh, M. S.; Rittger, K. E.; Lundquist, J. D.

    2012-12-01

    Despite being the dominant source of streamflow in many mountainous regions around the world, seasonal snow cover is poorly sampled by most ground-based observational networks. Satellite remote sensing supplements spatiotemporal knowledge of snow conditions in these rugged locations where ground observations are sparse or absent. However, the low density of ground-based observations also detracts from the value of remote sensing, as few ground-based datasets exist with sufficient spatial density to test remotely sensed snow cover across heterogeneous mountain terrain. Datasets with high spatial density are needed to test remote sensing because snow processes exhibit considerable spatial variability due to topographic and vegetation effects. Where ground-based observation stations exist, they are typically located in flat clearings, which are not likely to represent conditions in neighboring sloped and forested terrain. Forests cover as much as 40% to 50% of the seasonal snow zone in North America, and thus the accuracy of remote sensing in a major portion of the snow zone has been ill-quantified. Continued testing with ground-based observations adds value and confidence to remotely sensed snow cover, but dense ground observations are needed. Here we demonstrate that daily fractional snow covered area (fSCA) data can be derived in a study area with a network of buried temperature sensors. 37 to 90 self-logging temperature sensors were buried shallowly (MODSCAG) algorithm and find that the selected vegetation correction approach impacts MODSCAG accuracy. We also show the limitations of using single snow pillows for validation of remote sensing, as these point measurement typically did not represent the areal timing of snow disappearance observed by the ground temperature sensors at the study sites. Future satellite validation studies may benefit from this dataset or from application of this measurement technique.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. NEON Airborne Remote Sensing of Terrestrial Ecosystems

    Science.gov (United States)

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

    2012-12-01

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

  18. Retrieving Leaf Area Index (LAI Using Remote Sensing: Theories, Methods and Sensors

    Directory of Open Access Journals (Sweden)

    Guang Zheng

    2009-04-01

    Full Text Available The ability to accurately and rapidly acquire leaf area index (LAI is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

  19. 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.

  20. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.

    Science.gov (United States)

    Zheng, Guang; Moskal, L Monika

    2009-01-01

    The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

  1. 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.

  2. Remote sensing of coastal and ocean studies

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.

    -red and microwave radiation find use in remote sensing. Coastal and open oceans are commonly studied by ships. These studies involve measurement and interpretation of physical, chemical, biological and geological parameters of the ocean in different seasons. While... the ships are slow and expensive, oceans are vast and dJnamic. It is thus not possible to have simultaneous measurements of any oceanic parameter even over a region as small as 1000 sq. km. One can neither make a single ship move fast enough to cover...

  3. Introduction to Remote Sensing Image Registration

    Science.gov (United States)

    Le Moigne, Jacqueline

    2017-01-01

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

  4. 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.

  5. Microwave remote sensing of ionized air.

    Energy Technology Data Exchange (ETDEWEB)

    Liao, S.; Gopalsami, N.; Heifetz, A.; Elmer, T.; Fiflis, P.; Koehl, E. R.; Chien, H. T.; Raptis, A. C. (Nuclear Engineering Division)

    2011-07-01

    We present observations of microwave scattering from ambient room air ionized with a negative ion generator. The frequency dependence of the radar cross section of ionized air was measured from 26.5 to 40 GHz (Ka-band) in a bistatic mode with an Agilent PNA-X series (model N5245A) vector network analyzer. A detailed calibration scheme is provided to minimize the effect of the stray background field and system frequency response on the target reflection. The feasibility of detecting the microwave reflection from ionized air portends many potential applications such as remote sensing of atmospheric ionization and remote detection of radioactive ionization of air.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

    Science.gov (United States)

    Coughlan, Joseph C.

    2005-01-01

    NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

  13. Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

    Science.gov (United States)

    Giardino, Marco J.; Haley, Bryan S.

    2005-01-01

    Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously

  14. 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.

  15. 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.

  16. Uncertainty Management in Remote Sensing of Climate Data. Summary of A Workshop

    Science.gov (United States)

    McConnell, M.; Weidman, S.

    2009-01-01

    Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis (NRC, 2007). Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data, including statistical methods used to calibrate and validate satellite instruments, lack an overall mathematically based framework.

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

    Directory of Open Access Journals (Sweden)

    Duk-jin Kim

    2015-09-01

    Full Text Available Coastal lands and nearshore marine areas are productive and rapidly changing places. However, these areas face many environmental challenges related to climate change and human-induced impacts. Space-borne remote sensing systems may be restricted in monitoring these areas because of their spatial and temporal resolutions. In situ measurements are also constrained from accessing the area and obtaining wide-coverage data. In these respects, airborne remote sensing sensors could be the most appropriate tools for monitoring these coastal areas. In this study, a cost-effective airborne remote sensing system with synthetic aperture radar and thermal infrared sensors was implemented to survey coastal areas. Calibration techniques and geophysical model algorithms were developed for the airborne system to observe the topography of intertidal flats, coastal sea surface current, sea surface temperature, and submarine groundwater discharge.

  18. 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.

  19. 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.

  20. 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.

  1. SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

    Science.gov (United States)

    The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

  2. Some operative applications of remote sensing

    Directory of Open Access Journals (Sweden)

    A. Tonelli

    2000-06-01

    Full Text Available Among the methods of applied geophysics, remote sensing plays a major and an ancillary role, at the same time. The major role deals with the acquisition and processing of data with the aim of describing the properties of the surfaces and their subsurface mass. The ancillary one consists in furnishing indications to address specific geophysical surveys. The paper presents some operative applications of remote sensing by stations fixed on ground and by airborne surveys: monitoring the biogas vents and evaluating their flow in waste disposal sites, analyzing the stability of rocky walls, studying the moisture content of soils for the most general purposes and in particular to contribute to archaeological prospecting. Single and multitemporal collection of data are taken into consideration to describe polarizing properties of the surfaces and to define the heat capacity in the thermal infrared domain and the presence of luminescent phenomena in the visible range. The use of environmental indicators, like vegetation, is also discussed with the aim of revealing through superficial seepages the pattern of underlying mass.

  3. Laser remote sensing of underwater objects

    Science.gov (United States)

    Wojtanowski, J.; Mierczyk, Z.; Zygmunt, M.

    2008-10-01

    Theoretical and practical aspects of laser application in the field of underwater remote sensing have been presented. A multi-level analysis and computational results dealing with 0.532 μm laser wavelength were performed to determine the expected capabilities of underwater laser penetration with regard to the Lidar system developed in Optoelectronics Institute of Military University of Technology in Warsaw. Since the device is to perform underwater measurements from above the water level, the influence of the water-atmosphere interface had to be included in the analysis. Sea water characteristics concerning electromagnetic radiation propagation have been widely considered covering the mechanisms of absorption, scattering and the effective attenuation typical for representative types of sea waters. Software application developed in Mathcad environment enabled to model the impact of both absorption and scattering coefficients of different types of sea water on geometrical and energetic parameters of laser beam propagating in the underwater environment. The impact of reflectance properties of the remotely sensed underwater object on the reflected signal level has been investigated as well. Analytical approach covered both "echo" signal reflected from an underwater object and background noise signal level generated mainly by the sunlight and diffuse atmospheric illumination.

  4. A Terminal Area Icing Remote Sensing System

    Science.gov (United States)

    Reehorst, Andrew L.; Serke, David J.

    2014-01-01

    NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

  5. Progress in remote sensing (1972-1976)

    Science.gov (United States)

    Fischer, W. A.; Hemphill, W.R.; Kover, Allan

    1976-01-01

    This report concerns the progress in remote sensing during the period 1972–1976. Remote sensing has been variously defined but is basically the art or science of telling something about an object without touching it. During the past four years, the major research thrusts have been in three areas: (1) computer-assisted enhancement and interpretation systems; (2) earth science applications of Landsat data; (3) and investigations of the usefulness of observations of luminescence, thermal infrared, and microwave energies. Based on the data sales at the EROS Data Center, the largest users of the Landsat data are industrial companies, followed by government agencies (both national and foreign), and academic institutions. Thermal surveys from aircraft have become largely operational, however, significant research is being undertaken in the field of thermal modeling and analysis of high altitude images. Microwave research is increasing rapidly and programs are being developed for satellite observations. Microwave research is concentrating on oil spill detection, soil moisture measurement, and observations of ice distributions. Luminescence investigations offer promise for becoming a quantitative method of assessing vegetation stress and pollutant concentrations.

  6. Airborne multidimensional integrated remote sensing system

    Science.gov (United States)

    Xu, Weiming; Wang, Jianyu; Shu, Rong; He, Zhiping; Ma, Yanhua

    2006-12-01

    In this paper, we present a kind of airborne multidimensional integrated remote sensing system that consists of an imaging spectrometer, a three-line scanner, a laser ranger, a position & orientation subsystem and a stabilizer PAV30. The imaging spectrometer is composed of two sets of identical push-broom high spectral imager with a field of view of 22°, which provides a field of view of 42°. The spectral range of the imaging spectrometer is from 420nm to 900nm, and its spectral resolution is 5nm. The three-line scanner is composed of two pieces of panchromatic CCD and a RGB CCD with 20° stereo angle and 10cm GSD(Ground Sample Distance) with 1000m flying height. The laser ranger can provide height data of three points every other four scanning lines of the spectral imager and those three points are calibrated to match the corresponding pixels of the spectral imager. The post-processing attitude accuracy of POS/AV 510 used as the position & orientation subsystem, which is the aerial special exterior parameters measuring product of Canadian Applanix Corporation, is 0.005° combined with base station data. The airborne multidimensional integrated remote sensing system was implemented successfully, performed the first flying experiment on April, 2005, and obtained satisfying data.

  7. 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.

  8. Domestic parking estimation using remotely sensed data

    Science.gov (United States)

    Ramzi, Ahmed

    2012-10-01

    Parking is an integral part of the traffic system everywhere. Provision of parking facilities to meet peak of demands parking in cities of millions is always a real challenge for traffic and transport experts. Parking demand is a function of population and car ownership which is obtained from traffic statistics. Parking supply in an area is the number of legal parking stalls available in that area. The traditional treatment of the parking studies utilizes data collected either directly from on street counting and inquiries or indirectly from local and national traffic censuses. Both methods consume time, efforts, and funds. Alternatively, it is reasonable to make use of the eventually available data based on remotely sensed data which might be flown for other purposes. The objective of this work is to develop a new approach based on utilization of integration of remotely sensed data, field measurements, censuses and traffic records of the studied area for studying domestic parking problems in residential areas especially in informal areas. Expected outcomes from the research project establish a methodology to manage the issue and to find the reasons caused the shortage in domestics and the solutions to overcome this problems.

  9. Remotely Sensing the Photochemical Reflectance Index (PRI)

    Science.gov (United States)

    Vanderbilt, Vern

    2015-01-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.

  10. 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

  11. [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.

  12. 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.

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

    Science.gov (United States)

    Kiang, Richard; Adimi, Farida; Kempler, Steven

    2008-01-01

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

  14. Adaptive optical filtering techniques

    Science.gov (United States)

    Psaltis, D.

    1985-05-01

    The purpose of this study was to examine the potential of using optical information processing technology for adaptive antenna beamforming and null steering. The adaptive beamforming/null steering problem consists of estimation of the covariance matrix of the noise field and inversion of the covariance matrix to obtain the antenna element weights which optimize the antenna's directional characteristics (gain pattern). This report examines the adaptive beamforming/nulling problem in view of the capabilities of optics and identifies areas where optics can be used to benefit. Benefits and drawbacks of various optical implementations of open and closed loop adaptive algorithms are discussed as well as the issues involved with optically processing digital binary numbers.

  15. 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.

  16. The Sophia-Antipolis Conference: General presentation and basic documents. [remote sensing for agriculture, forestry, water resources, and environment management in France

    Science.gov (United States)

    1980-01-01

    The procedures and techniques used in NASA's aerospace technology transfer program are reviewed for consideration in establishing priorities and bases for joint action by technicians and users of remotely sensed data in France. Particular emphasis is given to remote sensing in agriculture, forestry, water resources, environment management, and urban research.

  17. Classification of remote sensed data using Artificial Bee Colony algorithm

    Directory of Open Access Journals (Sweden)

    J. Jayanth

    2015-06-01

    Full Text Available The present study employs the traditional swarm intelligence technique in the classification of satellite data since the traditional statistical classification technique shows limited success in classifying remote sensing data. The traditional statistical classifiers examine only the spectral variance ignoring the spatial distribution of the pixels corresponding to the land cover classes and correlation between various bands. The Artificial Bee Colony (ABC algorithm based upon swarm intelligence which is used to characterise spatial variations within imagery as a means of extracting information forms the basis of object recognition and classification in several domains avoiding the issues related to band correlation. The results indicate that ABC algorithm shows an improvement of 5% overall classification accuracy at 6 classes over the traditional Maximum Likelihood Classifier (MLC and Artificial Neural Network (ANN and 3% against support vector machine.

  18. GNSS Reflectometry and Remote Sensing: New Objectives and Results

    CERN Document Server

    Jin, Shuanggen; 10.1016/j.asr.2010.01.014.

    2010-01-01

    The Global Navigation Satellite System (GNSS) has been a very powerful and important contributor to all scientific questions related to precise positioning on Earth's surface, particularly as a mature technique in geodesy and geosciences. With the development of GNSS as a satellite microwave (L-band) technique, more and wider applications and new potentials are explored and utilized. The versatile and available GNSS signals can image the Earth's surface environments as a new, highly precise, continuous, all-weather and near-real-time remote sensing tool. The refracted signals from GNSS Radio Occultation satellites together with ground GNSS observations can provide the high-resolution tropospheric water vapor, temperature and pressure, tropopause parameters and ionospheric total electron content (TEC) and electron density profile as well. The GNSS reflected signals from the ocean and land surface could determine the ocean height, wind speed and wind direction of ocean surface, soil moisture, ice and snow thick...

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. Adaptive cancellation techniques

    Science.gov (United States)

    1983-11-01

    An adaptive signal canceller has been evaluated for the enhancement of pulse signal reception during the transmission of a high power ECM jamming signal. The canceller design is based on the use of DRFM(Digital RF Memory) technology as part of an adaptive multiple tapped delay line. The study includes analysis of relationship of tap spacing and waveform bandwidth, survey of related documents in areas of sidelobe cancellers, transversal equalizers, and adaptive filters, and derivation of control equations and corresponding control processes. The simulation of overall processes included geometric analysis of the multibeam transmitting antenna, multiple reflection sources and the receiving antenna; waveforms, tap spacings and bandwidths; and alternate control algorithms. Conclusions are provided regarding practical system control algorithms, design characteristics and limitations.

  4. 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.

  5. Use of remote sensing for monitoring deforestation in tropical and subtropical latitudes

    Science.gov (United States)

    Talbot, J. J.; Pettinger, Lawrence R.

    1981-01-01

    Of the three types of remotely sensed data discussed here, Landsat data offers the greatest potential for monitoring broad changes in extensive tropical forest environments because of its low-cost, synoptic, repetitive coverage. Scientists from developing countries can choose from a variety of Landsat data classification techniques, thus enabling each country to satisfy limitations on available funding, trained personnel, and equipment.

  6. Remote sensing and simulation modeling for on-demand irrigation systems management

    NARCIS (Netherlands)

    Urso, D' G.; Menenti, M.; Santini, A.

    1995-01-01

    This paper describes a procedure for monitoring and improving the performance of on-demand irrigation networks, based on the integration of remote sensing techniques and simulation modelling of water flow in each component of the system. In order to adequately reproduce the actual operation of an

  7. Remote sensing and simulation modelling for on-demand irrigation systems management

    NARCIS (Netherlands)

    Urso, D' G.; Menenti, M.; Santini, A.

    1996-01-01

    This paper describes a procedure for monitoring and improving the performance of on-demand irrigation networks, based on the integration of remote sensing techniques and simulation modelling of water flow in each component of the system. In order to adequately reproduce the actual operation of an

  8. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  9. Fusion of Remote Sensing and Non-Authoritative Data for Flood Disaster and Transportation Infrastructure Assessment

    Science.gov (United States)

    Schnebele, Emily K.

    2013-01-01

    Flooding is the most frequently occurring natural hazard on Earth; with catastrophic, large scale floods causing immense damage to people, property, and the environment. Over the past 20 years, remote sensing has become the standard technique for flood identification because of its ability to offer synoptic coverage. Unfortunately, remote sensing…

  10. 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...

  11. Establishing a sea bottom model by applying a multi-sensor acoustic remote sensing approach

    NARCIS (Netherlands)

    Siemes, K.

    2013-01-01

    Detailed information about the oceanic environment is essential for many applications in the field of marine geology, marine biology, coastal engineering, and marine operations. Especially, knowledge of the properties of the sediment body is often required. Acoustic remote sensing techniques have

  12. Identification of expansive soils using remote sensing and in-situ field measurements : phase I.

    Science.gov (United States)

    2012-10-01

    Researchers at the University of Arkansas have conducted research on the suitability of using remote sensing techniques (radar and LIDAR) to monitor the shrink-swell behavior of an expansive clay material in a field test site as part of the Mack Blac...

  13. Remote sensing of euphotic depth in shallow tropical inland waters of Lake Naivasha using MERIS data

    NARCIS (Netherlands)

    Majozi, N.P.; Salama, M.S.; Bernard, S.; Harper, D.M.; Habte, M.G.

    2014-01-01

    Freshwater resources are deteriorating rapidly due to human activities and climate change. Remote sensing techniques have shown potential for monitoring water quality in shallow inland lakes, especially in data-scarce areas. The purpose of this study was to determine the spectral diffuse attenuation

  14. Remote sensing for non-renewable resources - Satellite and airborne multiband scanners for mineral exploration

    Science.gov (United States)

    Goetz, Alexander F. H.

    1986-01-01

    The application of remote sensing techniques to mineral exploration involves the use of both spatial (morphological) as well as spectral information. This paper is directed toward a discussion of the uses of spectral image information and emphasizes the newest airborne and spaceborne sensor developments involving imaging spectrometers.

  15. Remote sensing study of soil hazards for Odendaalsrus in the Free ...

    African Journals Online (AJOL)

    Patrick Cole

    study examined ASTER satellite data, combined with standard remote sensing techniques, namely band ratios, in ... ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were selected for .... The process of using or designing band ratios based on mineral spectra can be effective at identifying ...

  16. Application of remote sensing and GIS inland use/land cover ...

    African Journals Online (AJOL)

    The results show that disturbed/degraded forest constituted the most extensive type of land use/land cover in the study area. The increasing population and economic activities were noted to be putting pressure on the available land resources. This paper highlights the importance of remote sensing and GIS techniques in ...

  17. The remote sensing of tropospheric composition from space

    Energy Technology Data Exchange (ETDEWEB)

    Burrows, John P. [Bremen Univ. (DE). Inst. fuer Umweltphysik (IUP); Platt, Ulrich [Heidelberg Univ. (Germany). Inst. fuer Umweltphysik; Borrell, Peter (eds.) [P and PMB Consultants, Newcastle-under-Lyme (United Kingdom)

    2011-07-01

    The impact of anthropogenic activities on our atmospheric environment is of growing public concern and satellite-based techniques now provide an essential component of observational strategies on regional and global scales. The purpose of this book is to summarise the state of the art in the field in general, while describing both key techniques and findings in particular. It opens with an historical perspective of the field together with the basic principles of remote sensing from space. Three chapters follow on the techniques and on the solutions to the problems associated with the various spectral regions in which observations are made. The particular challenges posed by aerosols and clouds are covered in the next two chapters. Of special importance is the accuracy and reliability of remote sensing data and these issues are covered in a chapter on validation. The final section of the book is concerned with the exploitation of data, with chapters on observational aspects, which includes both individual and synergistic studies, and on the comparison of global and regional observations with chemical transport and climate models and the added value that the interaction brings to both. The book concludes with scientific needs and likely future developments in the field, and the necessary actions to be taken if we are to have the global observation system that the Earth needs in its present, deteriorating state. The appendices provide a comprehensive list of satellite instruments, global representations of some ancillary data such as fire counts and light pollution, a list of abbreviations and acronyms, and a set of colourful timelines indicating the satellite coverage of tropospheric composition in the foreseeable future. Altogether, this book will be a timely reference and overview for anyone working at the interface of environmental, atmospheric and space sciences. (orig.)

  18. Method to analyze remotely sensed spectral data

    Science.gov (United States)

    Stork, Christopher L [Albuquerque, NM; Van Benthem, Mark H [Middletown, DE

    2009-02-17

    A fast and rigorous multivariate curve resolution (MCR) algorithm is applied to remotely sensed spectral data. The algorithm is applicable in the solar-reflective spectral region, comprising the visible to the shortwave infrared (ranging from approximately 0.4 to 2.5 .mu.m), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 .mu.m). For example, employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, MCR can be used to successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. Further, MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of a gas plume component near the minimum detectable quantity.

  19. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  20. RIVER SEDIMENT MONITORING USING REMOTE SENSING AND GIS (CASE STUDY KARAJ WATERSHED

    Directory of Open Access Journals (Sweden)

    M. Shafaie

    2015-12-01

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