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Sample records for airborne multispectral imagery

  1. Comparison of Airborne Multispectral and Hyperspectral Imagery for Yield Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery is being used to monitor crop conditions and map yield variability. However, limited research has been conducted to compare the differences between these two types of imagery for assessing crop growth and yield. The objective of this study was to compare airbo...

  2. Employing airborne multispectral digital imagery to map Brazilian pepper infestation in south Texas.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A study was conducted in south Texas to determine the feasibility of using airborne multispectral digital imagery for differentiating the invasive plant Brazilian pepper (Schinus terebinthifolius) from other cover types. Imagery obtained in the visible, near infrared, and mid infrared regions of th...

  3. Deepwater Horizon oil spill monitoring using airborne multispectral infrared imagery

    NASA Astrophysics Data System (ADS)

    Shen, Sylvia S.; Lewis, Paul E.

    2011-06-01

    On April 28, 2010, the Environmental Protection Agency's (EPA) Airborne Spectral Photometric Environmental Collection Technology (ASPECT) aircraft was deployed to Gulfport, Mississippi to provide airborne remotely sensed air monitoring and situational awareness data and products in response to the Deepwater Horizon oil spill disaster. The ASPECT aircraft was released from service on August 9, 2010 after having flown over 85 missions that included over 325 hours of flight operation. This paper describes several advanced analysis capabilities specifically developed for the Deepwater Horizon mission to correctly locate, identify, characterize, and quantify surface oil using ASPECT's multispectral infrared data. The data products produced using these advanced analysis capabilities provided the Deepwater Horizon Incident Command with a capability that significantly increased the effectiveness of skimmer vessel oil recovery efforts directed by the U.S. Coast Guard, and were considered by the Incident Command as key situational awareness information.

  4. Using airborne multispectral imagery to monitor cotton root rot expansion within a growing season

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot is a serious and destructive disease that affects cotton production in the southwestern United States. Accurate delineation of cotton root rot infestations is important for cost-effective management of the disease. The objective of this study was to use airborne multispectral imagery...

  5. Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

    2016-06-01

    Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

  6. Spatial Modeling and Variability Analysis for Modeling and Prediction of Soil and Crop Canopy Coverage Using Multispectral Imagery from an Airborne Remote Sensing System

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Based on a previous study on an airborne remote sensing system with automatic camera stabilization for crop management, multispectral imagery was acquired using the MS-4100 multispectral camera at different flight altitudes over a 115 ha cotton field. After the acquired images were geo-registered an...

  7. Comparison of airborne multispectral and hyperspectral imagery for estimating grain sorghum yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Both multispectral and hyperspectral images are being used to monitor crop conditions and map yield variability, but limited research has been conducted to compare the differences between these two types of imagery for assessing crop growth and yields. The objective of this study was to compare airb...

  8. Comparison of different detection methods for citrus greening disease based on airborne multispectral and hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Citrus greening or Huanglongbing (HLB) is a devastating disease spread in many citrus groves since first found in 2005 in Florida. Multispectral (MS) and hyperspectral (HS) airborne images of citrus groves in Florida were taken to detect citrus greening infected trees in 2007 and 2010. Ground truthi...

  9. Mapping forest stand complexity for woodland caribou habitat assessment using multispectral airborne imagery

    NASA Astrophysics Data System (ADS)

    Zhang, W.; Hu, B.; Woods, M.

    2014-11-01

    The decline of the woodland caribou population is a result of their habitat loss. To conserve the habitat of the woodland caribou and protect it from extinction, it is critical to accurately characterize and monitor its habitat. Conventionally, products derived from low to medium spatial resolution remote sensing data, such as land cover classification and vegetation indices are used for wildlife habitat assessment. These products fail to provide information on the structure complexities of forest canopies which reflect important characteristics of caribou's habitats. Recent studies have employed the LiDAR system (Light Detection And Ranging) to directly retrieve the three dimensional forest attributes. Although promising results have been achieved, the acquisition cost of LiDAR data is very high. In this study, utilizing the very high spatial resolution imagery in characterizing the structural development the of forest canopies was exploited. A stand based image texture analysis was performed to predict forest succession stages. The results were demonstrated to be consistent with those derived from LiDAR data.

  10. Hydrological characterization of a riparian vegetation zone using high resolution multi-spectral airborne imagery

    NASA Astrophysics Data System (ADS)

    Akasheh, Osama Z.

    The Middle Rio Grande River (MRGR) is the main source of fresh water for the state of New Mexico. Located in an arid area with scarce local water resources, this has led to extensive diversions of river water to supply the high demand from municipalities and irrigated agricultural activities. The extensive water diversions over the last few decades have affected the composition of the native riparian vegetation by decreasing the area of cottonwood and coyote willow and increasing the spread of invasive species such as Tamarisk and Russian Olives, harmful to the river system, due to their high transpiration rates, which affect the river aquatic system. The need to study the river hydrological processes and their relation with its health is important to preserve the river ecosystem. To be able to do that a detailed vegetation map was produced using a Utah State University airborne remote sensing system for 286 km of river reach. Also a groundwater model was built in ArcGIS environment which has the ability to estimate soil water potential in the root zone and above the modeled water table. The Modified Penman-Monteith empirical equation was used in the ArcGIS environment to estimate riparian vegetation ET, taking advantage of the detailed vegetation map and spatial soil water potential layers. Vegetation water use per linear river reach was estimated to help decision makers to better manage and release the amount of water that keeps a sound river ecosystem and to support agricultural activities.

  11. Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit.

    PubMed

    Virlet, Nicolas; Costes, Evelyne; Martinez, Sébastien; Kelner, Jean-Jacques; Regnard, Jean-Luc

    2015-09-01

    Genetic studies of response to water deficit in adult trees are limited by low throughput of the usual phenotyping methods in the field. Here, we aimed at overcoming this bottleneck, applying a new methodology using airborne multispectral imagery and in planta measurements to compare a high number of individuals.An apple tree population, grafted on the same rootstock, was submitted to contrasting summer water regimes over two years. Aerial images acquired in visible, near- and thermal-infrared at three dates each year allowed calculation of vegetation and water stress indices. Tree vigour and fruit production were also assessed. Linear mixed models were built accounting for date and year effects on several variables and including the differential response of genotypes between control and drought conditions.Broad-sense heritability of most variables was high and 18 quantitative trait loci (QTLs) independent of the dates were detected on nine linkage groups of the consensus apple genetic map. For vegetation and stress indices, QTLs were related to the means, the intra-crown heterogeneity, and differences induced by water regimes. Most QTLs explained 15-20% of variance.Airborne multispectral imaging proved relevant to acquire simultaneous information on a whole tree population and to decipher genetic determinisms involved in response to water deficit. PMID:26208644

  12. Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit

    PubMed Central

    Virlet, Nicolas; Costes, Evelyne; Martinez, Sébastien; Kelner, Jean-Jacques; Regnard, Jean-Luc

    2015-01-01

    Genetic studies of response to water deficit in adult trees are limited by low throughput of the usual phenotyping methods in the field. Here, we aimed at overcoming this bottleneck, applying a new methodology using airborne multispectral imagery and in planta measurements to compare a high number of individuals. An apple tree population, grafted on the same rootstock, was submitted to contrasting summer water regimes over two years. Aerial images acquired in visible, near- and thermal-infrared at three dates each year allowed calculation of vegetation and water stress indices. Tree vigour and fruit production were also assessed. Linear mixed models were built accounting for date and year effects on several variables and including the differential response of genotypes between control and drought conditions. Broad-sense heritability of most variables was high and 18 quantitative trait loci (QTLs) independent of the dates were detected on nine linkage groups of the consensus apple genetic map. For vegetation and stress indices, QTLs were related to the means, the intra-crown heterogeneity, and differences induced by water regimes. Most QTLs explained 15−20% of variance. Airborne multispectral imaging proved relevant to acquire simultaneous information on a whole tree population and to decipher genetic determinisms involved in response to water deficit. PMID:26208644

  13. An Assessment Of Meso-Scale Hydraulic And Vegetation Characteristics Of The Middle Rio Grande River Using High Resolution Multispectral Airborne Imagery

    NASA Astrophysics Data System (ADS)

    Akasheh, O. Z.; Neale, C. M.

    2004-12-01

    Middle Rio Grande River (MRGR) is the main source of fresh water for the population of New Mexico as well as for irrigated agriculture. Extensive water diversion over the last few decades has affected the composition of the native Riparian vegetation such as Cottonwood population and enhanced the spread of introduced species harmful to the river system like Tamarisk and Russian Olives. High resolution airborne remote sensing is a powerful technique for riparian vegetation mapping and monitoring. Airborne multispectral digital images were acquired over the riparian corridor of the MRGR, New Mexico in June 1999 and July 2001, using the Utah State University (USU) airborne digital imaging system. The imagery were corrected for vignetting effects, geometric lens distortions, rectified to a map base, mosaicked, verified in the field, classified and checked for accuracy. Areas of the vegetation classes and in-stream features were extracted and presented per reach of the river. In this paper a relationship was developed between the total surface water area mapped and both the river water flow rate and water table readings. The consequence of this relationship on riparian vegetation distribution along the river was studied and graphically demonstrated. Strong relationship was found between the total surface water area and water flow rate. In addition the reduction in surface water area resulted in reduction of native trees downstream.

  14. A fully-automated approach to land cover mapping with airborne LiDAR and high resolution multispectral imagery in a forested suburban landscape

    NASA Astrophysics Data System (ADS)

    Parent, Jason R.; Volin, John C.; Civco, Daniel L.

    2015-06-01

    Information on land cover is essential for guiding land management decisions and supporting landscape-level ecological research. In recent years, airborne light detection and ranging (LiDAR) and high resolution aerial imagery have become more readily available in many areas. These data have great potential to enable the generation of land cover at a fine scale and across large areas by leveraging 3-dimensional structure and multispectral information. LiDAR and other high resolution datasets must be processed in relatively small subsets due to their large volumes; however, conventional classification techniques cannot be fully automated and thus are unlikely to be feasible options when processing large high-resolution datasets. In this paper, we propose a fully automated rule-based algorithm to develop a 1 m resolution land cover classification from LiDAR data and multispectral imagery. The algorithm we propose uses a series of pixel- and object-based rules to identify eight vegetated and non-vegetated land cover features (deciduous and coniferous tall vegetation, medium vegetation, low vegetation, water, riparian wetlands, buildings, low impervious cover). The rules leverage both structural and spectral properties including height, LiDAR return characteristics, brightness in visible and near-infrared wavelengths, and normalized difference vegetation index (NDVI). Pixel-based properties were used initially to classify each land cover class while minimizing omission error; a series of object-based tests were then used to remove errors of commission. These tests used conservative thresholds, based on diverse test areas, to help avoid over-fitting the algorithm to the test areas. The accuracy assessment of the classification results included a stratified random sample of 3198 validation points distributed across 30 1 × 1 km tiles in eastern Connecticut, USA. The sample tiles were selected in a stratified random manner from locations representing the full range of

  15. Automated oil spill detection with multispectral imagery

    NASA Astrophysics Data System (ADS)

    Bradford, Brian N.; Sanchez-Reyes, Pedro J.

    2011-06-01

    In this publication we present an automated detection method for ocean surface oil, like that which existed in the Gulf of Mexico as a result of the April 20, 2010 Deepwater Horizon drilling rig explosion. Regions of surface oil in airborne imagery are isolated using red, green, and blue bands from multispectral data sets. The oil shape isolation procedure involves a series of image processing functions to draw out the visual phenomenological features of the surface oil. These functions include selective color band combinations, contrast enhancement and histogram warping. An image segmentation process then separates out contiguous regions of oil to provide a raster mask to an analyst. We automate the detection algorithm to allow large volumes of data to be processed in a short time period, which can provide timely oil coverage statistics to response crews. Geo-referenced and mosaicked data sets enable the largest identified oil regions to be mapped to exact geographic coordinates. In our simulation, multispectral imagery came from multiple sources including first-hand data collected from the Gulf. Results of the simulation show the oil spill coverage area as a raster mask, along with histogram statistics of the oil pixels. A rough square footage estimate of the coverage is reported if the image ground sample distance is available.

  16. Multispectral Analysis of NMR Imagery

    NASA Technical Reports Server (NTRS)

    Butterfield, R. L.; Vannier, M. W. And Associates; Jordan, D.

    1985-01-01

    Conference paper discusses initial efforts to adapt multispectral satellite-image analysis to nuclear magnetic resonance (NMR) scans of human body. Flexibility of these techniques makes it possible to present NMR data in variety of formats, including pseudocolor composite images of pathological internal features. Techniques do not have to be greatly modified from form in which used to produce satellite maps of such Earth features as water, rock, or foliage.

  17. Multispectral scanner imagery for plant community classification.

    NASA Technical Reports Server (NTRS)

    Driscoll, R. S.; Spencer, M. M.

    1973-01-01

    Optimum channel selection among 12 channels of multispectral scanner imagery identified six as providing the best information for computerized classification of 11 plant communities and two nonvegetation classes. Intensive preprocessing of the spectral data was required to eliminate bidirectional reflectance effects of the spectral imagery caused by scanner view angle and varying geometry of the plant canopy. Generalized plant community types - forest, grassland, and hydrophytic systems - were acceptably classified based on ecological analysis. Serious, but soluble, errors occurred with attempts to classify specific community types within the grassland system. However, special clustering analyses provided for improved classification of specific grassland communities.

  18. Image processing of underwater multispectral imagery

    USGS Publications Warehouse

    Zawada, D.G.

    2003-01-01

    Capturing in situ fluorescence images of marine organisms presents many technical challenges. The effects of the medium, as well as the particles and organisms within it, are intermixed with the desired signal. Methods for extracting and preparing the imagery for analysis are discussed in reference to a novel underwater imaging system called the low-light-level underwater multispectral imaging system (LUMIS). The instrument supports both uni- and multispectral collections, each of which is discussed in the context of an experimental application. In unispectral mode, LUMIS was used to investigate the spatial distribution of phytoplankton. A thin sheet of laser light (532 nm) induced chlorophyll fluorescence in the phytoplankton, which was recorded by LUMIS. Inhomogeneities in the light sheet led to the development of a beam-pattern-correction algorithm. Separating individual phytoplankton cells from a weak background fluorescence field required a two-step procedure consisting of edge detection followed by a series of binary morphological operations. In multispectral mode, LUMIS was used to investigate the bio-assay potential of fluorescent pigments in corals. Problems with the commercial optical-splitting device produced nonlinear distortions in the imagery. A tessellation algorithm, including an automated tie-point-selection procedure, was developed to correct the distortions. Only pixels corresponding to coral polyps were of interest for further analysis. Extraction of these pixels was performed by a dynamic global-thresholding algorithm.

  19. Airborne multispectral detection of regrowth cotton fields

    NASA Astrophysics Data System (ADS)

    Westbrook, John K.; Suh, Charles P.-C.; Yang, Chenghai; Lan, Yubin; Eyster, Ritchie S.

    2015-01-01

    Effective methods are needed for timely areawide detection of regrowth cotton plants because boll weevils (a quarantine pest) can feed and reproduce on these plants beyond the cotton production season. Airborne multispectral images of regrowth cotton plots were acquired on several dates after three shredding (i.e., stalk destruction) dates. Linear spectral unmixing (LSU) classification was applied to high-resolution airborne multispectral images of regrowth cotton plots to estimate the minimum detectable size and subsequent growth of plants. We found that regrowth cotton fields can be identified when the mean plant width is ˜0.2 m for an image resolution of 0.1 m. LSU estimates of canopy cover of regrowth cotton plots correlated well (r2=0.81) with the ratio of mean plant width to row spacing, a surrogate measure of plant canopy cover. The height and width of regrowth plants were both well correlated (r2=0.94) with accumulated degree-days after shredding. The results will help boll weevil eradication program managers use airborne multispectral images to detect and monitor the regrowth of cotton plants after stalk destruction, and identify fields that may require further inspection and mitigation of boll weevil infestations.

  20. Radiometric Characterization of IKONOS Multispectral Imagery

    NASA Technical Reports Server (NTRS)

    Pagnutti, Mary; Ryan, Robert E.; Kelly, Michelle; Holekamp, Kara; Zanoni, Vicki; Thome, Kurtis; Schiller, Stephen

    2002-01-01

    A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

  1. A comparison of real and simulated airborne multisensor imagery

    NASA Astrophysics Data System (ADS)

    Bloechl, Kevin; De Angelis, Chris; Gartley, Michael; Kerekes, John; Nance, C. Eric

    2014-06-01

    This paper presents a methodology and results for the comparison of simulated imagery to real imagery acquired with multiple sensors hosted on an airborne platform. The dataset includes aerial multi- and hyperspectral imagery with spatial resolutions of one meter or less. The multispectral imagery includes data from an airborne sensor with three-band visible color and calibrated radiance imagery in the long-, mid-, and short-wave infrared. The airborne hyperspectral imagery includes 360 bands of calibrated radiance and reflectance data spanning 400 to 2450 nm in wavelength. Collected in September 2012, the imagery is of a park in Avon, NY, and includes a dirt track and areas of grass, gravel, forest, and agricultural fields. A number of artificial targets were deployed in the scene prior to collection for purposes of target detection, subpixel detection, spectral unmixing, and 3D object recognition. A synthetic reconstruction of the collection site was created in DIRSIG, an image generation and modeling tool developed by the Rochester Institute of Technology, based on ground-measured reflectance data, ground photography, and previous airborne imagery. Simulated airborne images were generated using the scene model, time of observation, estimates of the atmospheric conditions, and approximations of the sensor characteristics. The paper provides a comparison between the empirical and simulated images, including a comparison of achieved performance for classification, detection and unmixing applications. It was found that several differences exist due to the way the image is generated, including finite sampling and incomplete knowledge of the scene, atmospheric conditions and sensor characteristics. The lessons learned from this effort can be used in constructing future simulated scenes and further comparisons between real and simulated imagery.

  2. Highly Protable Airborne Multispectral Imaging System

    NASA Technical Reports Server (NTRS)

    Lehnemann, Robert; Mcnamee, Todd

    2001-01-01

    A portable instrumentation system is described that includes and airborne and a ground-based subsytem. It can acquire multispectral image data over swaths of terrain ranging in width from about 1.5 to 1 km. The system was developed especially for use in coastal environments and is well suited for performing remote sensing and general environmental monitoring. It includes a small,munpilotaed, remotely controlled airplance that carries a forward-looking camera for navigation, three downward-looking monochrome video cameras for imaging terrain in three spectral bands, a video transmitter, and a Global Positioning System (GPS) reciever.

  3. Michigan experimental multispectral mapping system: A description of the M7 airborne sensor and its performance

    NASA Technical Reports Server (NTRS)

    Hasell, P. G., Jr.

    1974-01-01

    The development and characteristics of a multispectral band scanner for an airborne mapping system are discussed. The sensor operates in the ultraviolet, visual, and infrared frequencies. Any twelve of the bands may be selected for simultaneous, optically registered recording on a 14-track analog tape recorder. Multispectral imagery recorded on magnetic tape in the aircraft can be laboratory reproduced on film strips for visual analysis or optionally machine processed in analog and/or digital computers before display. The airborne system performance is analyzed.

  4. Airborne system for testing multispectral reconnaissance technologies

    NASA Astrophysics Data System (ADS)

    Schmitt, Dirk-Roger; Doergeloh, Heinrich; Keil, Heiko; Wetjen, Wilfried

    1999-07-01

    There is an increasing demand for future airborne reconnaissance systems to obtain aerial images for tactical or peacekeeping operations. Especially Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensor system and with real time jam resistant data transmission capabilities are of high interest. An airborne experimental platform has been developed as testbed to investigate different concepts of reconnaissance systems before their application in UAVs. It is based on a Dornier DO 228 aircraft, which is used as flying platform. Great care has been taken to achieve the possibility to test different kinds of multispectral sensors. Hence basically it is capable to be equipped with an IR sensor head, high resolution aerial cameras of the whole optical spectrum and radar systems. The onboard equipment further includes system for digital image processing, compression, coding, and storage. The data are RF transmitted to the ground station using technologies with high jam resistance. The images, after merging with enhanced vision components, are delivered to the observer who has an uplink data channel available to control flight and imaging parameters.

  5. A comparison of digital multi-spectral imagery versus conventional photography for mapping seagrass in Indian River Lagoon, Florida

    SciTech Connect

    Virnstein, R.; Tepera, M.; Beazley, L.

    1997-06-01

    A pilot study is very briefly summarized in the article. The study tested the potential of multi-spectral digital imagery for discrimination of seagrass densities and species, algae, and bottom types. Imagery was obtained with the Compact Airborne Spectral Imager (casi) and two flight lines flown with hyper-spectral mode. The photogrammetric method used allowed interpretation of the highest quality product, eliminating limitations caused by outdated or poor quality base maps and the errors associated with transfer of polygons. Initial image analysis indicates that the multi-spectral imagery has several advantages, including sophisticated spectral signature recognition and classification, ease of geo-referencing, and rapid mosaicking.

  6. Comparative performance between compressed and uncompressed airborne imagery

    NASA Astrophysics Data System (ADS)

    Phan, Chung; Rupp, Ronald; Agarwal, Sanjeev; Trang, Anh; Nair, Sumesh

    2008-04-01

    The US Army's RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division is evaluating the compressibility of airborne multi-spectral imagery for mine and minefield detection application. Of particular interest is to assess the highest image data compression rate that can be afforded without the loss of image quality for war fighters in the loop and performance of near real time mine detection algorithm. The JPEG-2000 compression standard is used to perform data compression. Both lossless and lossy compressions are considered. A multi-spectral anomaly detector such as RX (Reed & Xiaoli), which is widely used as a core algorithm baseline in airborne mine and minefield detection on different mine types, minefields, and terrains to identify potential individual targets, is used to compare the mine detection performance. This paper presents the compression scheme and compares detection performance results between compressed and uncompressed imagery for various level of compressions. The compression efficiency is evaluated and its dependence upon different backgrounds and other factors are documented and presented using multi-spectral data.

  7. Evaluating SPOT 5 Multispectral Imagery for Crop Yield Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery has the potential for mapping within-field variability in crop growth and yield. This study examined SPOT 5 multispectral imagery for estimating grain sorghum yield. A SPOT 5 image with 10-m spatial resolution and four spectral bands (green, red, near-infrared and m...

  8. Visualizing Airborne and Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Bierwirth, Victoria A.

    2011-01-01

    Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

  9. Study on airborne multispectral imaging fusion detection technology

    NASA Astrophysics Data System (ADS)

    Ding, Na; Gao, Jiaobo; Wang, Jun; Cheng, Juan; Gao, Meng; Gao, Fei; Fan, Zhe; Sun, Kefeng; Wu, Jun; Li, Junna; Gao, Zedong; Cheng, Gang

    2014-11-01

    The airborne multispectral imaging fusion detection technology is proposed in this paper. In this design scheme, the airborne multispectral imaging system consists of the multispectral camera, the image processing unit, and the stabilized platform. The multispectral camera can operate in the spectral region from visible to near infrared waveband (0.4-1.0um), it has four same and independent imaging channels, and sixteen different typical wavelengths to be selected based on the different typical targets and background. The related experiments were tested by the airborne multispectral imaging system. In particularly, the camouflage targets were fused and detected in the different complex environment, such as the land vegetation background, the desert hot background and underwater. In the spectral region from 0.4 um to 1.0um, the three different characteristic wave from sixteen typical spectral are selected and combined according to different backgrounds and targets. The spectral image corresponding to the three characteristic wavelengths is resisted and fused by the image processing technology in real time, and the fusion video with typical target property is outputted. In these fusion images, the contrast of target and background is greatly increased. Experimental results confirm that the airborne multispectral imaging fusion detection technology can acquire multispectral fusion image with high contrast in real time, and has the ability of detecting and identification camouflage objects from complex background to targets underwater.

  10. Airborne system for multispectral, multiangle polarimetric imaging.

    PubMed

    Bowles, Jeffrey H; Korwan, Daniel R; Montes, Marcos J; Gray, Deric J; Gillis, David B; Lamela, Gia M; Miller, W David

    2015-11-01

    In this paper, we describe the design, fabrication, calibration, and deployment of an airborne multispectral polarimetric imager. The motivation for the development of this instrument was to explore its ability to provide information about water constituents, such as particle size and type. The instrument is based on four 16 MP cameras and uses wire grid polarizers (aligned at 0°, 45°, 90°, and 135°) to provide the separation of the polarization states. A five-position filter wheel provides for four narrow-band spectral filters (435, 550, 625, and 750 nm) and one blocked position for dark-level measurements. When flown, the instrument is mounted on a programmable stage that provides control of the view angles. View angles that range to ±65° from the nadir have been used. Data processing provides a measure of the polarimetric signature as a function of both the view zenith and view azimuth angles. As a validation of our initial results, we compare our measurements, over water, with the output of a Monte Carlo code, both of which show neutral points off the principle plane. The locations of the calculated and measured neutral points are compared. The random error level in the measured degree of linear polarization (8% at 435) is shown to be better than 0.25%. PMID:26560615

  11. Multispectral Airborne Laser Scanning for Automated Map Updating

    NASA Astrophysics Data System (ADS)

    Matikainen, Leena; Hyyppä, Juha; Litkey, Paula

    2016-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.

  12. Mapping Waterhyacinth Infestations Using Airborne Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...

  13. High Resolution Airborne Digital Imagery for Precision Agriculture

    NASA Technical Reports Server (NTRS)

    Herwitz, Stanley R.

    1998-01-01

    The Environmental Research Aircraft and Sensor Technology (ERAST) program is a NASA initiative that seeks to demonstrate the application of cost-effective aircraft and sensor technology to private commercial ventures. In 1997-98, a series of flight-demonstrations and image acquisition efforts were conducted over the Hawaiian Islands using a remotely-piloted solar- powered platform (Pathfinder) and a fixed-wing piloted aircraft (Navajo) equipped with a Kodak DCS450 CIR (color infrared) digital camera. As an ERAST Science Team Member, I defined a set of flight lines over the largest coffee plantation in Hawaii: the Kauai Coffee Company's 4,000 acre Koloa Estate. Past studies have demonstrated the applications of airborne digital imaging to agricultural management. Few studies have examined the usefulness of high resolution airborne multispectral imagery with 10 cm pixel sizes. The Kodak digital camera integrated with ERAST's Airborne Real Time Imaging System (ARTIS) which generated multiband CCD images consisting of 6 x 106 pixel elements. At the designated flight altitude of 1,000 feet over the coffee plantation, pixel size was 10 cm. The study involved the analysis of imagery acquired on 5 March 1998 for the detection of anomalous reflectance values and for the definition of spectral signatures as indicators of tree vigor and treatment effectiveness (e.g., drip irrigation; fertilizer application).

  14. Joint spatio-spectral based edge detection for multispectral infrared imagery.

    SciTech Connect

    Krishna, Sanjay; Hayat, Majeed M.; Bender, Steven C.; Sharma, Yagya D.; Jang, Woo-Yong; Paskalva, Biliana S.

    2010-06-01

    Image segmentation is one of the most important and difficult tasks in digital image processing. It represents a key stage of automated image analysis and interpretation. Segmentation algorithms for gray-scale images utilize basic properties of intensity values such as discontinuity and similarity. However, it is possible to enhance edge-detection capability by means of using spectral information provided by multispectral (MS) or hyperspectral (HS) imagery. In this paper we consider image segmentation algorithms for multispectral images with particular emphasis on detection of multi-color or multispectral edges. More specifically, we report on an algorithm for joint spatio-spectral (JSS) edge detection. By joint we mean simultaneous utilization of spatial and spectral characteristics of a given MS or HS image. The JSS-based edge-detection approach, termed Spectral Ratio Contrast (SRC) edge-detection algorithm, utilizes the novel concept of matching edge signatures. The edge signature represents a combination of spectral ratios calculated using bands that enhance the spectral contrast between the two materials. In conjunction with a spatial mask, the edge signature give rise to a multispectral operator that can be viewed as a three-dimensional extension of the mask. In the extended mask, the third (spectral) dimension of each hyper-pixel can be chosen independently. The SRC is verified using MS and HS imagery from a quantum-dot in a well infrared (IR) focal plane array, and the Airborne Hyperspectral Imager.

  15. Estimating noise and information for multispectral imagery

    NASA Astrophysics Data System (ADS)

    Aiazzi, Bruno; Alparone, Luciano; Barducci, Alessandro; Baronti, Stefano; Pippi, Ivan

    2002-03-01

    We focus on reliably estimating the information conveyed to a user by multispectral image data. The goal is establishing the extent to which an increase in spectral resolution can increase the amount of usable information. As a matter of fact, a trade- off exists between spatial and spectral resolution, due to physical constraints of sensors imaging with a prefixed SNR. After describing some methods developed for automatically estimating the variance of the noise introduced by multispectral imagers, lossless data compression is exploited to measure the useful information content of the multispectral data. In fact, the bit rate achieved by the reversible compression process takes into account both the contribution of the 'observation' noise, i.e., information regarded as statistical uncertainty, whose relevance is null to a user, and the intrinsic information of hypothetically noise free multispectral data. An entropic model of the image source is defined and, once the standard deviation of the noise, assumed to be white and Gaussian, has been preliminarily estimated, such a model is inverted to yield an estimate of the information content of the noise-free source from the code rate. Results of both noise and information assessment are reported and discussed on synthetic noisy images and on Landsat thematic mapper (TM) data.

  16. Airborne Imagery Collections Barrow 2013

    DOE Data Explorer

    Cherry, Jessica; Crowder, Kerri

    2015-07-20

    The data here are orthomosaics, digital surface models (DSMs), and individual frames captured during low altitude airborne flights in 2013 at the Barrow Environmental Observatory. The orthomosaics, thermal IR mosaics, and DSMs were generated from the individual frames using Structure from Motion techniques.

  17. Citrus greening detection using airborne hyperspectral and multispectral imaging techniques

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging can provide unique spectral signatures for diseased vegetation. Airborne multispectral and hyperspectral imaging can be used to detect potentially infected trees over a large area for rapid detection of infected zones. This paper proposes a method to detect the citrus greening...

  18. The design and the development of a hyperspectral and multispectral airborne mapping system

    NASA Astrophysics Data System (ADS)

    Gorsevski, Pece V.; Gessler, Paul E.

    Flexible and cost-effective tools for rapid image acquisition and natural resource mapping are needed by land managers. This paper describes the hardware and software architecture of a low-cost system that can be deployed on a light aircraft for rapid data acquisition. The Hyperspectral and Multispectral Cameras for Airborne Mapping (HAMCAM) was designed and developed in the Geospatial Laboratory for Environmental Dynamics at the University of Idaho as a student-learning tool, and to enhance the existing curriculum currently offered. The system integrates a hyperspectral sensor with four multispectral cameras, an Inertial Navigation System (INS), a Wide Area Augmentation System (WAAS)-capable Global Positioning System (GPS), a data acquisition computer, and custom software for running the sensors in a variety of different modes. The outputs include very high resolution imagery obtained in four adjustable visible and near-infrared bands from the multispectral imager. The hyperspectral sensor acquires 240 spectral bands along 2.7 nm intervals within the 445-900 nm range. The INS provides aircraft pitch, roll and yaw information for rapid geo-registration of the imagery. This paper will discuss the challenges associated with the development of the system and the integration of components and software for implementation of this system for natural resource management applications. In addition, sample imagery acquired by the sensor will be presented.

  19. Airborne multispectral detecting system for marine mammals survey

    NASA Astrophysics Data System (ADS)

    Podobna, Yuliya; Sofianos, James; Schoonmaker, Jon; Medeiros, Dustin; Boucher, Cynthia; Oakley, Daniel; Saggese, Steve

    2010-04-01

    This work presents an electro-optical multispectral capability that detects and monitors marine mammals. It is a continuance of Whale Search Radar SBIR program funded by PMA-264 through NAVAIR. A lightweight, multispectral, turreted imaging system is designed for airborne and ship based platforms to detect and monitor marine mammals. The system tests were conducted over the Humpback whale breeding and calving area in Maui, Hawaii. The results of the tests and the system description are presented. The development of an automatic whale detection algorithm is discussed as well as methodology used to turn raw survey data into quantifiable data products.

  20. Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

    NASA Technical Reports Server (NTRS)

    Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

    2001-01-01

    Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative

  1. Sandia Multispectral Airborne Lidar for UAV Deployment

    SciTech Connect

    Daniels, J.W.; Hargis,Jr. P.J.; Henson, T.D.; Jordan, J.D.; Lang, A.R.; Schmitt, R.L.

    1998-10-23

    Sandia National Laboratories has initiated the development of an airborne system for W laser remote sensing measurements. System applications include the detection of effluents associated with the proliferation of weapons of mass destruction and the detection of biological weapon aerosols. This paper discusses the status of the conceptual design development and plans for both the airborne payload (pointing and tracking, laser transmitter, and telescope receiver) and the Altus unmanned aerospace vehicle platform. Hardware design constraints necessary to maintain system weight, power, and volume limitations of the flight platform are identified.

  2. Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

    USGS Publications Warehouse

    Su, H.; Karna, D.; Fraim, E.; Fitzgerald, M.; Dominguez, R.; Myers, J.S.; Coffland, B.; Handley, L.R.; Mace, T.

    2006-01-01

    Eelgrass (Zostera marina) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions. ?? 2006 American Society for Photogrammetry and Remote Sensing.

  3. An augmentative gaze directing framework for multi-spectral imagery

    NASA Astrophysics Data System (ADS)

    Hsiao, Libby

    Modern digital imaging techniques have made the task of imaging more prolic than ever and the volume of images and data available through multi-spectral imaging methods for exploitation is exceeding that which can be solely processed by human beings. The researchers proposed and developed a novel eye movement contingent framework and display system through adaption of the demonstrated technique of subtle gaze direction by presenting modulations within the displayed image. The system sought to augment visual search task performance of aerial imagery by incorporating multi-spectral image processing algorithms to determine potential regions of interest within an image. The exploratory work conducted was to study the feasibility of visual gaze direction with the specic intent of extending this application to geospatial image analysis without need for overt cueing to areas of potential interest and thereby maintaining the benefits of an undirected and unbiased search by an observer.

  4. Parallel evolution of image processing tools for multispectral imagery

    NASA Astrophysics Data System (ADS)

    Harvey, Neal R.; Brumby, Steven P.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Szymanski, John J.; Bloch, Jeffrey J.

    2000-11-01

    We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI , covering the recent Cerro Grande fire at Los Alamos, NM, USA.

  5. Developing a Method to Mask Trees in Commercial Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Becker, S. J.; Daughtry, C. S. T.; Jain, D.; Karlekar, S. S.

    2015-12-01

    The US Army has an increasing focus on using automated remote sensing techniques with commercial multispectral imagery (MSI) to map urban and peri-urban agricultural and vegetative features; however, similar spectral profiles between trees (i.e., forest canopy) and other vegetation result in confusion between these cover classes. Established vegetation indices, like the Normalized Difference Vegetation Index (NDVI), are typically not effective in reliably differentiating between trees and other vegetation. Previous research in tree mapping has included integration of hyperspectral imagery (HSI) and LiDAR for tree detection and species identification, as well as the use of MSI to distinguish tree crowns from non-vegetated features. This project developed a straightforward method to model and also mask out trees from eight-band WorldView-2 (1.85 meter x 1.85 meter resolution at nadir) satellite imagery at the Beltsville Agricultural Research Center in Beltsville, MD spanning 2012 - 2015. The study site included tree cover, a range of agricultural and vegetative cover types, and urban features. The modeling method exploits the product of the red and red edge bands and defines accurate thresholds between trees and other land covers. Results show this method outperforms established vegetation indices including the NDVI, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Simple Ratio, and Normalized Difference Red Edge Index in correctly masking trees while preserving the other information in the imagery. This method is useful when HSI and LiDAR collection are not possible or when using archived MSI.

  6. Evolving land cover classification algorithms for multispectral and multitemporal imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.

    2002-01-01

    The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.

  7. Spectra-view: A high performance, low-cost multispectral airborne imaging system

    SciTech Connect

    Helder, D.

    1996-11-01

    Although a variety of airborne platforms are available for collecting remote sensing data, a niche exists for a low cost, compact systemd capable of collecting accurate visible and infrared multispectral data in a digital format. To fill this void, an instrument known as Spectra-View was developed by Airborne Data Systems. Multispectral data is collected in the visible and near-infrared using an array of CCD cameras with appropriate spectral filtering. Infrared imaging is accomplished using commercially available cameras. Although the current system images in five spectral bands, a modular design approach allows various configurations for imaging in the visible and infrared regions with up to 10 or more channels. It was built entirely through integration of readily available commercial components, is compact enough to fly in an aircraft as small as a Cessna 172, and can record imagery at airspeeds in excess of 150 knots. A GPS-based navigation system provides a course deviation indicator for the pilot to follow and allows for georeferencing of the data. To maintain precise pointing knowledge, and at the same time keep system cost low, attitude sensors are mounted directly with the cameras rather than using a stabilized mounting system. Information is collect during camera firing of aircraft/camera attitude along the yaw, pitch, and roll axes. All data is collected in a digital format on a hard disk that is removable during flight so that virtually unlimited amounts of data may be recorded. Following collection, imagery is readily available for viewing and incorporation into computer-based systems for analysis and reduction. Ground processing software has been developed to perform radiometric calibration and georeference the imagery. Since June, 1995, the system has been collecting high-quality data in a variety of applications for numerous customers including applications in agriculture, forestry, and global change research. Several examples will be presented.

  8. Analysis Of Multispectral Imagery And Modeling Contaminant Transport

    NASA Astrophysics Data System (ADS)

    Irvine, J. M.; Becker, N. M.; Brumby, S.; David, N. A.

    2003-12-01

    A significant concern in the monitoring of hazardous waste is the potential for contaminants to migrate into locations where their presence poses greater environmental risks. The transport modeling performed in this study demonstrates the joint use of remotely sensed multispectral imagery and mathematical modeling to assess the surface migration of contaminants. KINEROS, an event-driven model of surface runoff and sediment transport, was used to assess uranium transport for various rain events. While our specific application was uranium transport, the methods apply to surface transport of any substance of concern. The model inputs include parameters related to the size and slope of watershed components, vegetation, and soil conditions. One distinct set of model inputs was derived from remotely sensed imagery data and another from site-specific knowledge. To derive the parameters of the KINEROS model from remotely sensed data, classification analysis was performed on IKONOS four-band multispectral imagery of the watershed. A system known as GENIE, developed by Los Alamos National Laboratory, employs genetics algorithms to evolve classifiers based on small, user-selected training samples. The classification analysis derived by employing GENIE provided insight into the correct KINEROS parameters for various sub-elements of the watershed. The model results offer valuable information about portions of the watershed that contributed the most to contaminant transport. These methods are applicable to numerous sites where possible transport of waste materials or other hazardous substances poses an environmental risk. Consequently, the approach presented here is relevant to homeland security and emergency response scenarios, as well as long-term environmental monitoring applications. Because the approach rests on the analysis of remote sensing data, the techniques can be used to monitor a range of sites and can reduce costs of data collection for model calibration.

  9. Comparison of hyperspectral imagery with aerial photography and multispectral imagery for mapping broom snakeweed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby] is one of the most widespread and abundant rangeland weeds in western North America. The objectives of this study were to evaluate airborne hyperspectral imagery and compare it with aerial color-infrared (CIR) photography and multispe...

  10. Developing unmanned airship onboard multispectral imagery system for quick-response to drinking water pollution

    NASA Astrophysics Data System (ADS)

    Liu, Zhigang; Wu, Jun; Yang, Haisheng; Li, Bo; Zhang, Yun; Yang, Shengtian

    2009-10-01

    Satellite multispectral imageries are usually limited in low space resolution, long revisit cycle or high cost. This paper presents our ongoing research on developing cost-effective unmanned airship on board Multispectral imagery system to acquire high-resolution multispectral imagery for quick-response to drinking water pollution issues. First, the overall architecture of developed system is described. After that, system integration including CCD cameras coupling, GPS/INS synchronization, stabilize platform control and wireless communication are discussed in detail. Next, system calibration is implemented in radiance and geometry respectively. An adaptive calibration method is developed to obtain absolute radiance and classic homography principle is employed to relate CCD cameras with each other geometrically. Finally, flight experiments are implemented to acquire high-resolution multispectral imageries along river and imageries are deliberately calibrated for the estimation of water quality. Conclusions are also conducted as well.

  11. Classification Metrics for Improved Atmospheric Correction of Multispectral VNIR Imagery

    PubMed Central

    Richter, Rudolf

    2008-01-01

    Multispectral visible/near-infrared (VNIR) earth observation satellites, e.g., Ikonos, Quickbird, ALOS AVNIR-2, and DMC, usually acquire imagery in a few (3 – 5) spectral bands. Atmospheric correction is a challenging task for these images because the standard methods require at least one shortwave infrared band (around 1.6 or 2.2 μm) or hyperspectral instruments to derive the aerosol optical thickness. New classification metrics for defining cloud, cloud over water, haze, water, and saturation are presented to achieve improvements for an automatic processing system. The background is an ESA contract for the development of a prototype atmospheric processor for the optical payload AVNIR-2 on the ALOS platform.

  12. Nonparametric classification of subpixel materials in multispectral imagery

    NASA Astrophysics Data System (ADS)

    Boudreau, Eric R.; Huguenin, Robert L.; Karaska, Mark A.

    1996-06-01

    An effective process for the automatic classification of subpixel materials in multispectral imagery has been developed. The applied analysis spectral analytical process (AASAP) isolates the contribution of specific materials of interest (MOI) within mixed pixels. AASAP consists of a suite of algorithms that perform environmental correction, signature derivation, and subpixel classification. Atmospheric and sun angle correction factors are extracted directly from imagery, allowing signatures produced from a given image to be applied to other images. AASAP signature derivation extracts a component of the pixel spectra that is most common to the training set to produce a signature spectrum and nonparametric feature space. The subpixel classifier applies a background estimation technique to a given pixel under test to produce a residual. A detection occurs when the residual falls within the signature feature space. AASAP was employed to detect stands of Loblolly Pine in a landsat TM scene that contained a variety of species of southern yellow pine. An independent field evaluation indicated that 85% of the detections contained over 20% Loblolly, and that 91% of the known Loblolly stands were detected. For another application, a crop signature derived from a scene in Texas detected occurrences of the same crop in scenes from Kansas and Mexico. AASAP has also been used to locate subpixel occurrences of soil contamination, wetlands species, and lines of communications.

  13. Rigorous Georeferencing of ALSAT-2A Panchromatic and Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Boukerch, I.; Hadeid, M.; Mahmoudi, R.; Takarli, B.; Hasni, K.

    2013-04-01

    The exploitation of the full geometric capabilities of the High-Resolution Satellite Imagery (HRSI), require the development of an appropriate sensor orientation model. Several authors studied this problem; generally we have two categories of geometric models: physical and empirical models. Based on the analysis of the metadata provided with ALSAT-2A, a rigorous pushbroom camera model can be developed. This model has been successfully applied to many very high resolution imagery systems. The relation between the image and ground coordinates by the time dependant collinearity involving many coordinates systems has been tested. The interior orientation parameters must be integrated in the model, the interior parameters can be estimated from the viewing angles corresponding to the pointing directions of any detector, these values are derived from cubic polynomials provided in the metadata. The developed model integrates all the necessary elements with 33 unknown. All the approximate values of the 33 unknowns parameters may be derived from the informations contained in the metadata files provided with the imagery technical specifications or they are simply fixed to zero, so the condition equation is linearized and solved using SVD in a least square sense in order to correct the initial values using a suitable number of well-distributed GCPs. Using Alsat-2A images over the town of Toulouse in the south west of France, three experiments are done. The first is about 2D accuracy analysis using several sets of parameters. The second is about GCPs number and distribution. The third experiment is about georeferencing multispectral image by applying the model calculated from panchromatic image.

  14. Application of High Resolution Multispectral Imagery for Levee Slide Detection and Monitoring

    NASA Technical Reports Server (NTRS)

    Hossain, A. K. M. Azad; Easson, Greg

    2007-01-01

    The objective is to develop methods to detect and monitor levee slides using commercially available high resolution multispectral imagery. High resolution multispectral imagery like IKONOS and QuickBird are suitable for detecting and monitoring levee slides. IKONOS is suitable for visual inspection, image classification and Tasseled Cap transform based slide detection. Tasseled Cap based model was found to be the best method for slide detection. QuickBird was suitable for visual inspection and image classification.

  15. Remote sensing of shorelines using data fusion of hyperspectral and multispectral imagery acquired from mobile and fixed platforms

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Frystacky, Heather

    2012-06-01

    An optimized data fusion methodology is presented and makes use of airborne and vessel mounted hyperspectral and multispectral imagery acquired at littoral zones in Florida and the northern Gulf of Mexico. The results demonstrate the use of hyperspectral-multispectral data fusion anomaly detection along shorelines and in surface and subsurface waters. Hyperspectral imagery utilized in the data fusion analysis was collected using a 64-1024 channel, 1376 pixel swath width; temperature stabilized sensing system; an integrated inertial motion unit; and differential GPS. The imaging system is calibrated using dual 18 inch calibration spheres, spectral line sources, and custom line targets. Simultaneously collected multispectral three band imagery used in the data fusion analysis was derived either a 12 inch focal length large format camera using 9 inch high speed AGFA color negative film, a 12.3 megapixel digital camera or dual high speed full definition video cameras. Pushbroom sensor imagery is corrected using Kalman filtering and smoothing in order to correct images for airborne platform motions or motions of a small vessel. Custom software developed for the hyperspectral system and the optimized data fusion process allows for post processing using atmospherically corrected and georeferenced reflectance imagery. The optimized data fusion approach allows for detecting spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using simulated embedded targets in actual imagery. The approach allows one to utilize spectral signature anomalies to identify features and targets that would otherwise not be possible. The optimized data fusion techniques and software has been developed in order to perform sensitivity analysis of the synthetic images in order to optimize the singular value decomposition model building process and the 2-D Butterworth cutoff frequency selection process, using the concept of user defined "feature

  16. High resolution multispectral photogrammetric imagery: enhancement, interpretation and evaluations

    NASA Astrophysics Data System (ADS)

    Roberts, Arthur; Haefele, Martin; Bostater, Charles; Becker, Thomas

    2007-10-01

    A variety of aerial mapping cameras were adapted and developed into simulated multiband digital photogrammetric mapping systems. Direct digital multispectral, two multiband cameras (IIS 4 band and Itek 9 band) and paired mapping and reconnaissance cameras were evaluated for digital spectral performance and photogrammetric mapping accuracy in an aquatic environment. Aerial films (24cm X 24cm format) tested were: Agfa color negative and extended red (visible and near infrared) panchromatic, and; Kodak color infrared and B&W (visible and near infrared) infrared. All films were negative processed to published standards and digitally converted at either 16 (color) or 10 (B&W) microns. Excellent precision in the digital conversions was obtained with scanning errors of less than one micron. Radiometric data conversion was undertaken using linear density conversion and centered 8 bit histogram exposure. This resulted in multiple 8 bit spectral image bands that were unaltered (not radiometrically enhanced) "optical count" conversions of film density. This provided the best film density conversion to a digital product while retaining the original film density characteristics. Data covering water depth, water quality, surface roughness, and bottom substrate were acquired using different measurement techniques as well as different techniques to locate sampling points on the imagery. Despite extensive efforts to obtain accurate ground truth data location errors, measurement errors, and variations in the correlation between water depth and remotely sensed signal persisted. These errors must be considered endemic and may not be removed through even the most elaborate sampling set up. Results indicate that multispectral photogrammetric systems offer improved feature mapping capability.

  17. Deriving Radiative Effects of Aerosol-Immersed Broken Cloud Fields from Multi-spectral Imagery

    NASA Astrophysics Data System (ADS)

    Schmidt, Sebastian

    2016-04-01

    Recently, significant progress has been made in the understanding of cloud inhomogeneity effects in shortwave passive remote sensing. Yet it has proven difficult to correct such effects on the pixel level using multi-spectral imagery alone, mainly because three-dimensional (3D) radiative transfer in cloud fields is a non-local phenomenon. As a result, estimates of irradiance - the fundamental climate variable - from space-or air-borne imagery continue to pose problems for complex cloud fields. The presence of aerosols in the vicinity of clouds exacerbates the prob- lem. I will show evidence from field experiments and 3D radiative transfer calculations that biases may exceed 40% at the pixel level at the MODIS spatial resolution, and that some of these effects "survive" spatial averaging. A new way to cope with this problem is the discovery that 3D effects manifest themselves as spectral perturba- tion in reflected radiances and in the associated irradiance fields throughout an inhomogeneous cloud domain. In parameterized form, these correlations between spatial cloud distribution and spectral signature can be used to de- rive first-order inhomogeneity corrections for irradiance fields - not on a pixel basis, but for populations of pixels within a cloud domain represented by probability density functions. I will present the first practical approach for using these new findings in a future proxy-3D algorithm for deriving irradiances below and above cloud-aerosol fields from multi-spectral imagers, and discuss the accuracy that can be expected from this simplified method to account for 3D effects in mixed aerosol-cloud scenes.

  18. JACIE Radiometric Assessment of QuickBird Multispectral Imagery

    NASA Technical Reports Server (NTRS)

    Pagnutti, Mary; Carver, David; Holekamp, Kara; Knowlton, Kelly; Ryan, Robert; Zanoni, Vicki; Thome, Kurtis; Aaron, David

    2004-01-01

    Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can place confidence in the imagery they use and can fully understand its properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, the NASA Stennis Space Center (SSC) Earth Science Applications (ESA) directorate,through the Joint Agency for Commercial Imagery Evaluation (JACIE) framework, established a commercial imaging satellite radiometric calibration team consisting of two groups: 1) NASA SSC ESA, supported by South Dakota State University, and 2) the University of Arizona Remote Sensing Group. The two groups determined the absolute radiometric calibration coefficients of the Digital Globe 4-band, 2.4-m QuickBird multispectral product covering the visible through near-infrared spectral region. For a 2-year period beginning in 2002, both groups employed some variant of a reflectance-based vicarious calibration approach, which required ground-based measurements coincident with QuickBird image acquisitions and radiative transfer calculations. The groups chose several study sites throughout the United States that covered nearly the entire dynamic range of the QuickBird sensor. QuickBird at-sensor radiance values were compared with those estimated by the two independent groups to determine the QuickBird sensor's radiometric accuracy. Approximately 20 at-sensor radiance estimates were vicariously determined each year. The estimates were combined to provide a high-precision radiometric gain calibration coefficient. The results of this evaluation provide the user community with an independent assessment of the QuickBird sensor's absolute calibration and stability over the 2-year period. While the techniques and method described reflect those developed at the NASA SSC, the results of both JACIE team groups are

  19. Spectral analysis algorithm for material detection from multispectral imagery

    NASA Astrophysics Data System (ADS)

    Racine, Joseph K.

    2011-06-01

    Material detection from multi-spectral imagery is critical to numerous geospatial applications. However, given the limited number of channels from various air and space-borne imaging sensors, coupled with varying illumination conditions, material-specific detection rules tend to generate large numbers of false positives. This paper will describe a novel approach that uses various band ratios (for example, [Blue + Green]/Red) to identify targets-of-interest, regardless of the illumination conditions and position of the sensor relative to the target. The approach uses a physics-based spectral model to estimate the observed channel-weighted radiance based on solar irradiance, atmospheric transmission, reflectivity of the target-of-interest and the spectral weighting functions of the sensor's channels. The observed channelweighted radiance is then converted to the expected channel pixel value by the channel-specific conversion factor. With each channel's pixel values estimated, the algorithm goes through a process to find which band ratio values show the least amount of variance, despite varying irradiance spectra and atmospheric absorption. The band ratios with the least amount of variance are then used to identify the target-of-interest in an image file. To determine the expected false alarm rate, the same band ratios are evaluated against a library of background materials using the same calculation method for determining the target-of-interest's channel pixel values. Testing of this approach against ground-truth imagery, with as few as four channels, has shown a high rate of success in identifying targets-of-interest, while maintaining low false alarm rates.

  20. ASPIS, A Flexible Multispectral System for Airborne Remote Sensing Environmental Applications

    PubMed Central

    Papale, Dario; Belli, Claudio; Gioli, Beniamino; Miglietta, Franco; Ronchi, Cesare; Vaccari, Francesco Primo; Valentini, Riccardo

    2008-01-01

    Airborne multispectral and hyperspectral remote sensing is a powerful tool for environmental monitoring applications. In this paper we describe a new system (ASPIS) composed by a 4-CCD spectral sensor, a thermal IR camera and a laser altimeter that is mounted on a flexible Sky-Arrow airplane. A test application of the multispectral sensor to estimate durum wheat quality is also presented.

  1. Evolving forest fire burn severity classification algorithms for multispectral imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Harvey, Neal R.; Bloch, Jeffrey J.; Theiler, James P.; Perkins, Simon J.; Young, Aaron C.; Szymanski, John J.

    2001-08-01

    Between May 6 and May 18, 2000, the Cerro Grande/Los Alamos wildfire burned approximately 43,000 acres (17,500 ha) and 235 residences in the town of Los Alamos, NM. Initial estimates of forest damage included 17,000 acres (6,900 ha) of 70-100% tree mortality. Restoration efforts following the fire were complicated by the large scale of the fire, and by the presence of extensive natural and man-made hazards. These conditions forced a reliance on remote sensing techniques for mapping and classifying the burn region. During and after the fire, remote-sensing data was acquired from a variety of aircraft-based and satellite-based sensors, including Landsat 7. We now report on the application of a machine learning technique, implemented in a software package called GENIE, to the classification of forest fire burn severity using Landsat 7 ETM+ multispectral imagery. The details of this automatic classification are compared to the manually produced burn classification, which was derived from field observations and manual interpretation of high-resolution aerial color/infrared photography.

  2. An Algorithm to Atmospherically Correct Visible and Thermal Airborne Imagery

    NASA Technical Reports Server (NTRS)

    Rickman, Doug L.; Luvall, Jeffrey C.; Schiller, Stephen; Arnold, James E. (Technical Monitor)

    2000-01-01

    The program Watts implements a system of physically based models developed by the authors, described elsewhere, for the removal of atmospheric effects in multispectral imagery. The band range we treat covers the visible, near IR and the thermal IR. Input to the program begins with atmospheric pal red models specifying transmittance and path radiance. The system also requires the sensor's spectral response curves and knowledge of the scanner's geometric definition. Radiometric characterization of the sensor during data acquisition is also necessary. While the authors contend that active calibration is critical for serious analytical efforts, we recognize that most remote sensing systems, either airborne or space borne, do not as yet attain that minimal level of sophistication. Therefore, Watts will also use semi-active calibration where necessary and available. All of the input is then reduced to common terms, in terms of the physical units. From this it Is then practical to convert raw sensor readings into geophysically meaningful units. There are a large number of intricate details necessary to bring an algorithm or this type to fruition and to even use the program. Further, at this stage of development the authors are uncertain as to the optimal presentation or minimal analytical techniques which users of this type of software must have. Therefore, Watts permits users to break out and analyze the input in various ways. Implemented in REXX under OS/2 the program is designed with attention to the probability that it will be ported to other systems and other languages. Further, as it is in REXX, it is relatively simple for anyone that is literate in any computer language to open the code and modify to meet their needs. The authors have employed Watts in their research addressing precision agriculture and urban heat island.

  3. Coastal and estuarine habitat mapping, using LIDAR height and intensity and multi-spectral imagery

    NASA Astrophysics Data System (ADS)

    Chust, Guillem; Galparsoro, Ibon; Borja, Ángel; Franco, Javier; Uriarte, Adolfo

    2008-07-01

    The airborne laser scanning LIDAR (LIght Detection And Ranging) provides high-resolution Digital Terrain Models (DTM) that have been applied recently to the characterization, quantification and monitoring of coastal environments. This study assesses the contribution of LIDAR altimetry and intensity data, topographically-derived features (slope and aspect), and multi-spectral imagery (three visible and a near-infrared band), to map coastal habitats in the Bidasoa estuary and its adjacent coastal area (Basque Country, northern Spain). The performance of high-resolution data sources was individually and jointly tested, with the maximum likelihood algorithm classifier in a rocky shore and a wetland zone; thus, including some of the most extended Cantabrian Sea littoral habitats, within the Bay of Biscay. The results show that reliability of coastal habitat classification was more enhanced with LIDAR-based DTM, compared with the other data sources: slope, aspect, intensity or near-infrared band. The addition of the DTM, to the three visible bands, produced gains of between 10% and 27% in the agreement measures, between the mapped and validation data (i.e. mean producer's and user's accuracy) for the two test sites. Raw LIDAR intensity images are only of limited value here, since they appeared heterogeneous and speckled. However, the enhanced Lee smoothing filter, applied to the LIDAR intensity, improved the overall accuracy measurements of the habitat classification, especially in the wetland zone; here, there were gains up to 7.9% in mean producer's and 11.6% in mean user's accuracy. This suggests that LIDAR can be useful for habitat mapping, when few data sources are available. The synergy between the LIDAR data, with multi-spectral bands, produced high accurate classifications (mean producer's accuracy: 92% for the 16 rocky habitats and 88% for the 11 wetland habitats). Fusion of the data enabled discrimination of intertidal communities, such as Corallina elongata

  4. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    NASA Astrophysics Data System (ADS)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  5. Restoration of the missing pixel information caused by contrails in multispectral remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Daxiang; Zhang, Chuanrong; Li, Weidong; Cromley, Robert; Hanink, Dean; Civco, Daniel; Travis, David

    2014-01-01

    Although removing the pixels covered by contrails and their shadows and restoring the missing information at the locations in remotely sensed imagery are important to understand contrails' effects on climate change, there are no such studies in the current literature. This study investigates the restoration of the missing information of the pixels caused by contrails in multispectral remotely sensed Landsat 5 TM imagery using a cokriging approach. Interpolation results and several validation methods show that it is practical to use the cokriging approach to restore the contrail-covered pixels in the multispectral remotely sensed imagery. Compared to ordinary kriging, the results are improved by taking advantage of both the spatial information in the original imagery and information from the secondary imagery.

  6. Multispectral thermal airborne TASI-600 data to study the Pompeii (IT) archaeological area

    NASA Astrophysics Data System (ADS)

    Palombo, Angelo; Pascucci, Simone; Pergola, Nicola; Pignatti, Stefano; Santini, Federico; Soldovieri, Francesco

    2016-04-01

    The management of archaeological areas refers to the conservation of the ruins/buildings and the eventual prospection of new areas having an archaeological potential. In this framework, airborne remote sensing is a well-developed geophysical tool for supporting the archaeological surveys of wide areas. The spectral regions applied in archaeological remote sensing spans from the VNIR to the TIR. In particular, the archaeological thermal imaging considers that materials absorb, emit, transmit, and reflect the thermal infrared radiation at different rate according to their composition, density and moisture content. Despite its potential, thermal imaging in archaeological applications are scarce. Among them, noteworthy are the ones related to the use of Landsat and ASTER [1] and airborne remote sensing [2, 3, 4 and 5]. In view of these potential in Cultural Heritage applications, the present study aims at analysing the usefulness of the high spatial resolution thermal imaging on the Pompeii archaeological park. To this purpose TASI-600 [6] airborne multispectral thermal imagery (32 channels from 8 to 11.5 nm with a spectral resolution of 100nm and a spatial resolution of 1m/pixel) was acquired on December the 7th, 2015. Airborne survey has been acquired to get useful information on the building materials (both ancient and of consolidation) characteristics and, whenever possible, to retrieve quick indicators on their conservation status. Thermal images will be, moreover, processed to have an insight of the critical environmental issues impacting the structures (e.g. moisture). The proposed study shows the preliminary results of the airborne deployments, the pre-processing of the multispectral thermal imagery and the retrieving of accurate land surface temperatures (LST). LST map will be analysed to describe the thermal pattern of the city of Pompeii and detect any thermal anomalies. As far as the ongoing TASI-600 sensors pre-processing, it will include: (a) radiometric

  7. The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

    NASA Technical Reports Server (NTRS)

    Stockton, J. G.; Bauer, M. E.; Blair, B. O.; Baumgardner, M. F.

    1975-01-01

    Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops.

  8. Evaluating Airborne Hyperspectral imagery for mapping waterhyacinth infestations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...

  9. Satellite imagery and airborne geophysics for geologic mapping of the Edembo area, Eastern Hoggar (Algerian Sahara)

    NASA Astrophysics Data System (ADS)

    Lamri, Takfarinas; Djemaï, Safouane; Hamoudi, Mohamed; Zoheir, Basem; Bendaoud, Abderrahmane; Ouzegane, Khadidja; Amara, Massinissa

    2016-03-01

    Satellite imagery combined with airborne geophysical data and field observations were employed for new geologic mapping of the Edembo area in the Eastern Hoggar (Tuareg Shield, Sahara). Multi-spectral band fusion, filtering, and transformation techniques, i.e., band combination, band-rationing and principal component analysis of ETM+ and ASTER data are used for better spectral discrimination of the different rocks units. A thematic map assessed by field data and available geologic information is compiled by supervised classification of satellite data with high overall accuracy (>90%). The automated extraction technique efficiently aided the detection of the structural lineaments, i.e., faults, shear zones, and joints. Airborne magnetic and Gamma-ray spectrometry data showed the pervasiveness of the large structures beneath the Paleozoic sedimentary cover and aeolian sands. The aeroradiometric K-range is used for discrimination of the high-K granitoids of Djanet from the peralumineous granites of Edembo, and to verify the Silurian sediments with their high K-bearing minerals. The new geological map is considered to be a high resolution improvement on all pre-existing maps of this hardly accessible area in the Tuareg Shield. Integration of the airborne geophysical and space-borne imagery data can hence provide a rapid means of geologically mapping areas hitherto poorly known or difficult to access.

  10. Multi-spectral tactical integrated scene generation capability using satellite imagery

    NASA Astrophysics Data System (ADS)

    Coker, Charles; Willis, Carla; Van, Tan; Smith, Brian; Destin, Phillip

    2010-04-01

    A multi-spectral tactical integrated scene generation capability using satellite terrain imagery is currently available using a synthetic predictive simulation code developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/RWGGS). This capability produces multi-spectral integrated scene imagery from the perspective of a sensor/seeker for an air-to-ground scenario using geo-referenced U.S. Geological Survey (USGS) Digital Terrain Elevation Data (DTED) and satellite terrain imagery. The produced imagery is spatially, spectrally, and temporally accurate. Using surveillance flight path and viewing angle, this capability has been interfaced with Microsoft Virtual Earth to extract terrain data of interest at the needed background resolution.

  11. Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

    NASA Astrophysics Data System (ADS)

    Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

    2016-06-01

    Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

  12. USING MULTISPECTRAL IMAGERY AND LINEAR SPECTRAL UNMIXING TECHNIQUES FOR ESTIMATING CROP YIELD VARIABILITY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation indices derived from multispectral imagery are commonly used to extract crop growth and yield information. Spectral unmixing techniques provide an alternative approach to quantifying crop canopy abundance within each image pixel and have the potential for mapping crop yield variability. T...

  13. Using multi-spectral imagery to detect and map stress induced by Russian wheat aphid

    NASA Astrophysics Data System (ADS)

    Backoulou, Georges Ferdinand

    Scope and Method of Study. The rationale of this study was to assess the stress in wheat field induced by the Russian wheat aphid using multispectral imagery. The study was conducted to (a) determine the relationship between RWA and edaphic and topographic factors; (b) identify and quantify the spatial pattern of RWA infestation within wheat fields; (c) differentiate the stress induced by RWA from other stress causing factors. Data used for the analysis included RWA population density from the wheat field in, Texas, Colorado, Wyoming, and Nebraska, Digital Elevation Model from the Unites States Geological Survey (USGS), soil data from the Soil Survey Geographic database (SSURGO), and multispectral imagery acquired in the panhandle of Oklahoma. Findings and Conclusions. The study revealed that the population density of the Russian wheat aphid was related to topographic and edaphic factors. Slope and sand were predictor variables that were positively related to the density of RWA at the field level. The study has also demonstrated that stress induced by the RWA has a specific spatial pattern that can be distinguished from other stress causing factors using a combination of landscape metrics and topographic and edaphic characteristics of wheat fields. Further field-based studies using multispectral imagery and spatial pattern analysis are suggested. The suggestions require acquiring biweekly multispectral imagery and collecting RWA, topographic and edaphic data at the sampling points during the phonological growth development of wheat plants. This is an approach that may pretend to have great potential for site specific technique for the integrated pest management.

  14. Estimation of cotton yield with varied irrigation and nitrogen treatments using aerial multispectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton yield varies spatially within a field. The variability can be caused by various production inputs such as soil properties, water management, and fertilizer application. Airborne multispectral imaging is capable of providing data and information to study effects of the inputs on yield qualitat...

  15. Range vegetation type mapping and above-ground green biomass estimations using multispectral imagery. [Wyoming

    NASA Technical Reports Server (NTRS)

    Houston, R. S. (Principal Investigator); Gordon, R. C.

    1974-01-01

    The author has identified the following significant results. Range vegetation types have been successfully mapped on a portion of the 68,000 acre study site located west of Baggs, Wyoming, using ERTS-1 imagery. These types have been ascertained from field transects over a five year period. Comparable studies will be made with EREP imagery. Above-ground biomass estimation studies are being conducted utilizing double sampling techniques on two similar study sites. Information obtained will be correlated with percent relative reflectance measurements obtained on the ground which will be related to image brightness levels. This will provide an estimate of above-ground green biomass with multispectral imagery.

  16. Skylab multispectral scanner /S-192/ - Optical design and operational imagery

    NASA Technical Reports Server (NTRS)

    Abel, I. R.; Reynolds, B. R.

    1974-01-01

    Description of the design and performance of a multispectral scanner that makes possible photographic reproductions of actual flight recordings at an 80-meter resolution for an altitude of 440 km. Maximum scan pattern stability and instrument compactness have been achieved in the design.

  17. Robust materials classification based on multispectral polarimetric BRDF imagery

    NASA Astrophysics Data System (ADS)

    Chen, Chao; Zhao, Yong-qiang; Luo, Li; Liu, Dan; Pan, Quan

    2009-07-01

    When light is reflected from object surface, its spectral characteristics will be affected by surface's elemental composition, while its polarimetric characteristics will be determined by the surface's orientation, roughness and conductance. Multispectral polarimetric imaging technique records both the spectral and polarimetric characteristics of the light, and adds dimensions to the spatial intensity typically acquired and it also could provide unique and discriminatory information which may argument material classification techniques. But for the sake of non-Lambert of object surface, the spectral and polarimetric characteristics will change along with the illumination angle and observation angle. If BRDF is ignored during the material classification, misclassification is inevitable. To get a feature that is robust material classification to non-Lambert surface, a new classification methods based on multispectral polarimetric BRDF characteristics is proposed in this paper. Support Vector Machine method is adopted to classify targets in clutter grass environments. The train sets are obtained in the sunny, while the test sets are got from three different weather and detected conditions, at last the classification results based on multispectral polarimetric BRDF features are compared with other two results based on spectral information, and multispectral polarimetric information under sunny, cloudy and dark conditions respectively. The experimental results present that the method based on multispectral polarimetric BRDF features performs the most robust, and the classification precision also surpasses the other two. When imaging objects under the dark weather, it's difficult to distinguish different materials using spectral features as the grays between backgrounds and targets in each different wavelength would be very close, but the method proposed in this paper would efficiently solve this problem.

  18. An airborne multispectral imaging system based on two consumer-grade cameras for agricultural remote sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS) sensor with 5616 × 3744 pixels. One came...

  19. Remote identification of potential boll weevil host plants: Airborne multispectral detection of regrowth cotton

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Regrowth cotton plants can serve as potential hosts for boll weevils during and beyond the production season. Effective methods for timely areawide detection of these host plants are critically needed to expedite eradication in south Texas. We acquired airborne multispectral images of experimental...

  20. Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

    PubMed Central

    Chaddad, Ahmad; Desrosiers, Christian; Bouridane, Ahmed; Toews, Matthew; Hassan, Lama; Tanougast, Camel

    2016-01-01

    Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials and Methods In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) and gray level co-occurrence matrices (GLCM). To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models. Results Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01). Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%. Conclusions These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images. PMID:26901134

  1. Mapping crop ground cover using airborne multispectral digital imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Empirical relationships between remotely sensed vegetation indices and density information, such as leaf area index or ground cover (GC), are commonly used to derive spatial information in many precision farming operations. In this study, we modified an existing methodology that does not depend on e...

  2. EVALUATION OF COTTON DEFOLIATION STRATEGIES USING AIRBORNE MULTISPECTRAL IMAGERY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Visual observations and ground measurements are commonly used to evaluate cotton (Gossypium hirsutum L.) harvest aids for defoliation, boll opening, and re-growth control. This paper presents a remote sensing-based method for evaluating the effectiveness of different defoliation treatments. Field ...

  3. Multispectral thermal airborne TASI-600 data to study the Pompeii (IT) archaeological area

    NASA Astrophysics Data System (ADS)

    Palombo, Angelo; Pascucci, Simone; Pergola, Nicola; Pignatti, Stefano; Santini, Federico; Soldovieri, Francesco

    2016-04-01

    The management of archaeological areas refers to the conservation of the ruins/buildings and the eventual prospection of new areas having an archaeological potential. In this framework, airborne remote sensing is a well-developed geophysical tool for supporting the archaeological surveys of wide areas. The spectral regions applied in archaeological remote sensing spans from the VNIR to the TIR. In particular, the archaeological thermal imaging considers that materials absorb, emit, transmit, and reflect the thermal infrared radiation at different rate according to their composition, density and moisture content. Despite its potential, thermal imaging in archaeological applications are scarce. Among them, noteworthy are the ones related to the use of Landsat and ASTER [1] and airborne remote sensing [2, 3, 4 and 5]. In view of these potential in Cultural Heritage applications, the present study aims at analysing the usefulness of the high spatial resolution thermal imaging on the Pompeii archaeological park. To this purpose TASI-600 [6] airborne multispectral thermal imagery (32 channels from 8 to 11.5 nm with a spectral resolution of 100nm and a spatial resolution of 1m/pixel) was acquired on December the 7th, 2015. Airborne survey has been acquired to get useful information on the building materials (both ancient and of consolidation) characteristics and, whenever possible, to retrieve quick indicators on their conservation status. Thermal images will be, moreover, processed to have an insight of the critical environmental issues impacting the structures (e.g. moisture). The proposed study shows the preliminary results of the airborne deployments, the pre-processing of the multispectral thermal imagery and the retrieving of accurate land surface temperatures (LST). LST map will be analysed to describe the thermal pattern of the city of Pompeii and detect any thermal anomalies. As far as the ongoing TASI-600 sensors pre-processing, it will include: (a) radiometric

  4. Scene segmentation from motion in multispectral imagery to aid automatic human gait recognition

    NASA Astrophysics Data System (ADS)

    Pearce, Daniel; Harvey, Christophe; Day, Simon; Goffredo, Michela

    2007-10-01

    Primarily focused at military and security environments where there is a need to identify humans covertly and remotely; this paper outlines how recovering human gait biometrics from a multi-spectral imaging system can overcome the failings of traditional biometrics to fulfil those needs. With the intention of aiding single camera human gait recognition, an algorithm was developed to accurately segment a walking human from multi-spectral imagery. 16-band imagery from the image replicating imaging spectrometer (IRIS) camera system is used to overcome some of the common problems associated with standard change detection techniques. Fusing the concepts of scene segmentation by spectral characterisation and background subtraction by image differencing gives a uniquely robust approach. This paper presents the results of real trials with human subjects and a prototype IRIS camera system, and compares performance to typical broadband camera systems.

  5. SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

    SciTech Connect

    Bradley, J.N.; Brislawn, C.M.

    1993-12-01

    The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multi-spectral imagery. The raw data used in this study is Landsat Thematic Mapper (TM) 7-channel imagery, with 8 bits of dynamic range per channel. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion at 50:1 compression and graceful degradation at higher compression ratios. Two TM images were processed in this experiment: a 1024 x 1024-pixel scene of the region surrounding the Chernobyl power plant, taken a few months before the reactor malfunction, and a 2048 x 2048 image of Moscow and surrounding countryside.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  7. Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

    NASA Technical Reports Server (NTRS)

    Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

    2015-01-01

    The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

  8. Using High Resolution SPOT 5 Multispectral Imagery for Crop Identification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery offers new opportunities for crop monitoring and assessment. A SPOT 5 image with four spectral bands (green, red, near-infrared, and mid-infrared) and 10-m pixel size covering intensively cropped areas in south Texas was evaluated for crop identification. Two images...

  9. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    DOE PAGESBeta

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-12-09

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

  10. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    SciTech Connect

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-12-09

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.

  11. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-01-01

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. Our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.

  12. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

    Lemeshewsky, G.P.

    2004-01-01

    Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

  13. EVOLUTIONARY COMPUTATION AND POST-WILDFIRE LAND-COVER MAPPING WITH MULTISPECTRAL IMAGERY.

    SciTech Connect

    Brumby, Steven P.; Koch, S. W.; Hansen, L. A.

    2001-01-01

    The Cerro Grande Los Alamos wildfire devastated approximately 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos. The need to monitor the continuing impact of the fire on the local environment has led to the application of a number of advanced remote sensing technologies. During and after the fire, remote-sensing data was acquired fiorn a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique io the automated classification of land cover using multispectral imagery. We apply a hybrid gertelic programminghupervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery fiom the Landsat 7 ETM+ instrument fiom before and after the wildfire. Using an existing land cover classification based on a Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, along with clouds and cloud shadows. The details of our evolved classification are compared to the manually produced land-cover classification. Keywords: Feature Extraction, Genetic programming, Supervised classification, Multi-spectral imagery, Land cover, Wildfire.

  14. Application of multispectral radar and LANDSAT imagery to geologic mapping in death valley

    NASA Technical Reports Server (NTRS)

    Daily, M.; Elachi, C.; Farr, T.; Stromberg, W.; Williams, S.; Schaber, G.

    1978-01-01

    Side-Looking Airborne Radar (SLAR) images, acquired by JPL and Strategic Air Command Systems, and visible and near-infrared LANDSAT imagery were applied to studies of the Quaternary alluvial and evaporite deposits in Death Valley, California. Unprocessed radar imagery revealed considerable variation in microwave backscatter, generally correlated with surface roughness. For Death Valley, LANDSAT imagery is of limited value in discriminating the Quaternary units except for alluvial units distinguishable by presence or absence of desert varnish or evaporite units whose extremely rough surfaces are strongly shadowed. In contrast, radar returns are most strongly dependent on surface roughness, a property more strongly correlated with surficial geology than is surface chemistry.

  15. Automated mesoscale winds derived from GOES multispectral imagery

    NASA Technical Reports Server (NTRS)

    Wilson, G. S.; Atkinson, R. J.

    1984-01-01

    An automated technique for extracting mesoscale winds from sequences of GOES VISSR image pairs was developed, tested and configured for quasi-real time/research applications on a computing system which gives mesoscale wind estimates at the highest spatial/temporal resolution possible from the VISSR imagery down to a wind vector separation of 10 km. Preprocessing of imagery using IR resampling, VIS edge preserving filtering, and reduced VIS resolution averaging improved height assignments and vector extraction for 10, 15, and 30 min imagery. An objective quality control system provides much greater than 99% accuracy in eliminating questionable wind estimates. Automated winds generally have better spatial coverage and density, and have random error estimates half as large as the manual winds. Dynamical analysis of cloud wind divergence revealed temporally consistent convergence centers on the meso beta scale that are highly correlated with on going and future developing convective storms. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than one hour.

  16. Using Airborne and Satellite Imagery to Distinguish and Map Black Mangrove

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper reports the results of studies evaluating color-infrared (CIR) aerial photography, CIR aerial true digital imagery, and high resolution QuickBird multispectral satellite imagery for distinguishing and mapping black mangrove [Avicennia germinans (L.) L.] populations along the lower Texas g...

  17. Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Fuell, Kevin K.; LaFontaine, Frank; McGrath, Kevin; Smith, Matt

    2013-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will

  18. Correlation of ERTS multispectral imagery with suspended matter and chlorophyll in lower Chesapeake Bay

    NASA Technical Reports Server (NTRS)

    Bowker, D. E.; Fleischer, P.; Gosink, T. A.; Hanna, W. J.; Ludwick, J. C.

    1973-01-01

    The feasibility of using multispectral satellite imagery to monitor the characteristics of estuarine waters is being investigated. Preliminary comparisons of MSS imagery with suspended matter concentrations, particle counts, chlorophyll, transmittance and bathymetry have been made. Some visual correlation of radiance with particulates and chlorophyll has been established. Effects of bathymetry are present, and their relation to transmittance and radiance is being investigated. Greatest detail in suspended matter is revealed by MSS band 5. Near-surface suspended sediment load and chlorophyll can be observed in bands 6 and 7. Images received to date have partially defined extent and location of high suspensate concentrations. Net quantity of suspended matter in the lower Bay has been decreasing since the inception of the study, and represents the diminution of turbid flood waters carried into the Bay in late September, 1972. The results so far point to the utility of MSS imagery in monitoring estuarine water character for the assessment of siltation, productivity, and water types.

  19. Analysis of aerial multispectral imagery to assess water quality parameters of Mississippi water bodies

    NASA Astrophysics Data System (ADS)

    Irvin, Shane Adison

    The goal of this study was to demonstrate the application of aerial imagery as a tool in detecting water quality indicators in a three mile segment of Tibbee Creek in, Clay County, Mississippi. Water samples from 10 transects were collected per sampling date over two periods in 2010 and 2011. Temperature and dissolved oxygen (DO) were measured at each point, and water samples were tested for turbidity and total suspended solids (TSS). Relative reflectance was extracted from high resolution (0.5 meter) multispectral aerial images. A regression model was developed for turbidity and TSS as a function of values for specific sampling dates. The best model was used to predict turbidity and TSS using datasets outside the original model date. The development of an appropriate predictive model for water quality assessment based on the relative reflectance of aerial imagery is affected by the quality of imagery and time of sampling.

  20. Citrus greening disease detection using airborne multispectral and hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging can provide unique spectral signatures for diseased vegetation. Airborne hyperspectral imaging can be used to detect potentially infected trees over a large area for rapid detection of infected zones. Ground inspection and management can be focused on these infected zones rath...

  1. A comparison between satellite and airborne multispectral data for the assessment of Mangrove areas in the eastern Caribbean

    SciTech Connect

    Green, E.P.; Edwards, A.J.; Mumby, P.J.

    1997-06-01

    Satellite (SPOT XS and Landsat TM) and airborne multispectral (CASI) imagery was acquired from the Turks and Caicos Islands, British West Indies. The descriptive resolution and accuracy of each image type is compared for two applications: mangrove habitat mapping and the measurement of mangrove canopy characteristics (leaf area index and canopy closure). Mangroves could be separated from non-mangrove vegetation to an accuracy of only 57% with SPOT XS data but better discrimination could be achieved with either Landsat TM or CASI (in both cases accuracy was >90%). CASI data permitted a more accurate classification of different mangrove habitats than was possible using Landsat TM. Nine mangrove habitats could be mapped to an accuracy of 85% with the high-resolution airborne data compared to 31% obtained with TM. A maximum of three mangrove habitats were separable with Landsat TM: the accuracy of this classification was 83%. Measurement of mangrove canopy characteristics is achieved more accurately with CASI than with either satellite sensor, but high costs probably make it a less cost-effective option. The cost-effectiveness of each sensor is discussed for each application.

  2. Calibrated and geocoded clutter from an airborne multispectral scanner

    NASA Astrophysics Data System (ADS)

    Heuer, Markus; Bruehlmann, Ralph; John, Marc-Andre; Schmid, Konrad J.; Hueppi, Rudolph; Koenig, Reto

    1999-07-01

    Robustness of automatic target recognition (ATR) to varying observation conditions and countermeasures is substantially increased by use of multispectral sensors. Assessment of such ATR systems is performed by captive flight tests and simulations (HWIL or complete modeling). Although the clutter components of a scene can be generated with specified statistics, clutter maps directly obtained from measurement are required for validation of a simulation. In addition, urban scenes have non-stationary characteristics and are difficult to simulate. The present paper describes a scanner, data acquisition and processing system used for the generation of realistic clutter maps incorporating infrared, passive and active millimeter wave channels. The sensors are mounted on a helicopter with coincident line-of-sight, enabling us to measure consistent clutter signatures under varying observation conditions. Position and attitude data from GPS and an inertial measurement unit, respectively, are used to geometrically correct the raw scanner data. After sensor calibration the original voltage signals are converted to physical units, i.e. temperatures and reflectivities, describing the clutter independently of the scanning sensor, thus allowing us the use of the clutter maps in tests of a priori unknown multispectral sensors. The data correction procedures are described and results are presented.

  3. Application of airborne thermal imagery to surveys of Pacific walrus

    USGS Publications Warehouse

    Burn, D.M.; Webber, M.A.; Udevitz, M.S.

    2006-01-01

    We conducted tests of airborne thermal imagery of Pacific walrus to determine if this technology can be used to detect walrus groups on sea ice and estimate the number of walruses present in each group. In April 2002 we collected thermal imagery of 37 walrus groups in the Bering Sea at spatial resolutions ranging from 1-4 m. We also collected high-resolution digital aerial photographs of the same groups. Walruses were considerably warmer than the background environment of ice, snow, and seawater and were easily detected in thermal imagery. We found a significant linear relation between walrus group size and the amount of heat measured by the thermal sensor at all 4 spatial resolutions tested. This relation can be used in a double-sampling framework to estimate total walrus numbers from a thermal survey of a sample of units within an area and photographs from a subsample of the thermally detected groups. Previous methods used in visual aerial surveys of Pacific walrus have sampled only a small percentage of available habitat, resulting in population estimates with low precision. Results of this study indicate that an aerial survey using a thermal sensor can cover as much as 4 times the area per hour of flight time with greater reliability than visual observation.

  4. FTIR-based airborne spectral imagery for target interrogation

    NASA Astrophysics Data System (ADS)

    Smithson, Tracy L.; St. Germain, Daniel; Nadeau, Denis

    2007-09-01

    DRDC Valcartier is continuing to developed infrared spectral imagery systems for a variety of military applications. Recently a hybrid airborne spectral imager / broadband imager system has been developed for ground target interrogation (AIRIS). This system employs a Fourier Transform Interferometer system coupled to two 8x8 element detector arrays to create spectral imagery in the region from 2.0 to 12 microns (830 to 5000 cm -1) at a spectral resolution of up to 1 cm -1. In addition, coupled to this sensor are three broadband imagers operating in the visible, mid-wave and long-wave infrared regions. AIRIS uses an on-board tracking capability to: dwell on a target, select multiple targets sequentially, or build a mosaic description of the environment around a specified target point. Currently AIRIS is being modified to include real-time spectral imagery calibration and application processing. In this paper the flexibility of the AIRIS system will be described, its concept of operation discussed and examples of measurements will be shown.

  5. Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping

    NASA Astrophysics Data System (ADS)

    Rapinel, Sébastien; Hubert-Moy, Laurence; Clément, Bernard

    2015-05-01

    Although wetlands play a key role in controlling flooding and nonpoint source pollution, sequestering carbon and providing an abundance of ecological services, the inventory and characterization of wetland habitats are most often limited to small areas. This explains why the understanding of their ecological functioning is still insufficient for a reliable functional assessment on areas larger than a few hectares. While LiDAR data and multispectral Earth Observation (EO) images are often used separately to map wetland habitats, their combined use is currently being assessed for different habitat types. The aim of this study is to evaluate the combination of multispectral and multiseasonal imagery and LiDAR data to precisely map the distribution of wetland habitats. The image classification was performed combining an object-based approach and decision-tree modeling. Four multispectral images with high (SPOT-5) and very high spatial resolution (Quickbird, KOMPSAT-2, aerial photographs) were classified separately. Another classification was then applied integrating summer and winter multispectral image data and three layers derived from LiDAR data: vegetation height, microtopography and intensity return. The comparison of classification results shows that some habitats are better identified on the winter image and others on the summer image (overall accuracies = 58.5 and 57.6%). They also point out that classification accuracy is highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectral images. Moreover, this study highlights the advantage of integrating vegetation height, microtopography and intensity parameters in the classification process. This article demonstrates that information provided by the synergetic use of multispectral images and LiDAR data can help in wetland functional assessment

  6. Evaluating airborne multispectral digital video to differentiate giant Salvinia from other features in northeast Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Giant salvinia is one of the world’s most noxious aquatic weeds. Researchers employed airborne digital video imagery and an unsupervised computer analysis to derive a map showing giant salvinia and other aquatic and terrestrial features within a study site located in northeast Texas. The map had a...

  7. Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

    2014-10-01

    Giant reed is an aggressive invasive plant of riparian ecosystems in many sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometric similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phenological variability of the invader. We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77%) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2 m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric

  8. Determining density of maize canopy. 2: Airborne multispectral scanner data

    NASA Technical Reports Server (NTRS)

    Stoner, E. R.; Baumgardner, M. F.; Cipra, J. E.

    1971-01-01

    Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density.

  9. Discriminating plant species across California's diverse ecosystems using airborne VSWIR and TIR imagery

    NASA Astrophysics Data System (ADS)

    Meerdink, S.; Roberts, D. A.; Roth, K. L.

    2015-12-01

    Accurate knowledge of the spatial distribution of plant species is required for many research and management agendas that track ecosystem health. Because of this, there is continuous development of research focused on remotely-sensed species classifications for many diverse ecosystems. While plant species have been mapped using airborne imaging spectroscopy, the geographic extent has been limited due to data availability and spectrally similar species continue to be difficult to separate. The proposed Hyperspectral Infrared Imager (HyspIRI) space-borne mission, which includes a visible near infrared/shortwave infrared (VSWIR) imaging spectrometer and thermal infrared (TIR) multi-spectral imager, would present an opportunity to improve species discrimination over a much broader scale. Here we evaluate: 1) the capability of VSWIR and/or TIR spectra to discriminate plant species; 2) the accuracy of species classifications within an ecosystem; and 3) the potential for discriminating among species across a range of ecosystems. Simulated HyspIRI imagery was acquired in spring/summer of 2013 spanning from Santa Barbara to Bakersfield, CA with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the MODIS/ASTER Airborne Simulator (MASTER) instruments. Three spectral libraries were created from these images: AVIRIS (224 bands from 0.4 - 2.5 µm), MASTER (8 bands from 7.5 - 12 µm), and AVIRIS + MASTER. We used canonical discriminant analysis (CDA) as a dimension reduction technique and then classified plant species using linear discriminant analysis (LDA). Our results show the inclusion of TIR spectra improved species discrimination, but only for plant species with emissivities departing from that of a gray body. Ecosystems with species that have high spectral contrast had higher classification accuracies. Mapping plant species across all ecosystems resulted in a classification with lower accuracies than a single ecosystem due to the complex nature of

  10. DEIMOS-2: cost-effective, very-high resolution multispectral imagery

    NASA Astrophysics Data System (ADS)

    Pirondini, Fabrizio; López, Julio; González, Enrique; González, José Antonio

    2014-10-01

    ELECNOR DEIMOS is a private Spanish company, part of the Elecnor industrial group, which owns and operates DEIMOS-1, the first Spanish Earth Observation satellite. DEIMOS-1, launched in 2009, is among the world leading sources of high resolution data. On June 19th, 2014 ELECNOR DEIMOS launched its second satellite, DEIMOS-2, which is a very-high resolution, agile satellite capable of providing 75-cm pan-sharpened imagery, with a 12kmwide swath. The DEIMOS-2 camera delivers multispectral imagery in 5 bands: Panchromatic, G, R, B and NIR. DEIMOS-2 is the first European satellite completely owned by private capital, which is capable of providing submetric multispectral imagery. The whole end-to-end DEIMOS-2 system is designed to provide a cost-effective, dependable and highly responsive service to cope with the increasing need of fast access to very-high resolution imagery. The same 24/7 commercial service which is now available for DEIMOS-1, including tasking, download, processing and delivery, will become available for DEIMOS-2 as well, as soon as the satellite enters into commercial operations, at the end of its in-orbit commissioning. The DEIMOS-2 satellite has been co-developed by ELECNOR DEIMOS and SATREC-I (South Korea), and it has been integrated and tested in the new ELECNOR DEIMOS Satellite Systems premises in Puertollano (Spain). The DEIMOS-2 ground segment, which includes four receiving/commanding ground stations in Spain, Sweden and Canada, has been completely developed in-house by ELECNOR DEIMOS, based on its Ground Segment for Earth Observation (gs4EO®) suite. In this paper we describe the main features of the DEIMOS-2 system, with emphasis on its initial operations and the quality of the initial imagery, and provide updated information on its mission status.

  11. Airborne imagery of a disintegrating Sargassum drift line

    NASA Astrophysics Data System (ADS)

    Marmorino, George O.; Miller, W. D.; Smith, Geoffrey B.; Bowles, Jeffrey H.

    2011-03-01

    Airborne hyperspectral and thermal infrared imagery collected over the Florida Current provide a view of the disintegration of a Sargassum drift line in 5 m s -1 winds. The drift line consists mostly of rafts 20-80 m 2 in size, though aggregations larger than 1000 m 2 also occur. Rafts tend to be elongated, curved in the upwind direction, and 0.1-0.5 °C warmer than the surrounding ocean surface. Long weed 'trails' extending upwind from the rafts are evidence of plants dropping out and being left behind more rapidly drifting rafts. The raft line may be a remnant of an earlier Sargassum frontal band, which is detectible as an upwind thermal front and areas of submerged weed. Issues are identified that require future field measurements.

  12. Error modeling based on geostatistics for uncertainty analysis in crop mapping using Gaofen-1 multispectral imagery

    NASA Astrophysics Data System (ADS)

    You, Jiong; Pei, Zhiyuan

    2015-01-01

    With the development of remote sensing technology, its applications in agriculture monitoring systems, crop mapping accuracy, and spatial distribution are more and more being explored by administrators and users. Uncertainty in crop mapping is profoundly affected by the spatial pattern of spectral reflectance values obtained from the applied remote sensing data. Errors in remotely sensed crop cover information and the propagation in derivative products need to be quantified and handled correctly. Therefore, this study discusses the methods of error modeling for uncertainty characterization in crop mapping using GF-1 multispectral imagery. An error modeling framework based on geostatistics is proposed, which introduced the sequential Gaussian simulation algorithm to explore the relationship between classification errors and the spectral signature from remote sensing data source. On this basis, a misclassification probability model to produce a spatially explicit classification error probability surface for the map of a crop is developed, which realizes the uncertainty characterization for crop mapping. In this process, trend surface analysis was carried out to generate a spatially varying mean response and the corresponding residual response with spatial variation for the spectral bands of GF-1 multispectral imagery. Variogram models were employed to measure the spatial dependence in the spectral bands and the derived misclassification probability surfaces. Simulated spectral data and classification results were quantitatively analyzed. Through experiments using data sets from a region in the low rolling country located at the Yangtze River valley, it was found that GF-1 multispectral imagery can be used for crop mapping with a good overall performance, the proposal error modeling framework can be used to quantify the uncertainty in crop mapping, and the misclassification probability model can summarize the spatial variation in map accuracy and is helpful for

  13. Using remotely-sensed multispectral imagery to build age models for alluvial fan surfaces

    NASA Astrophysics Data System (ADS)

    D'Arcy, Mitch; Mason, Philippa J.; Roda Boluda, Duna C.; Whittaker, Alexander C.; Lewis, James

    2016-04-01

    Accurate exposure age models are essential for much geomorphological field research, and generally depend on laboratory analyses such as radiocarbon, cosmogenic nuclide, or luminescence techniques. These approaches continue to revolutionise geomorphology, however they cannot be deployed remotely or in situ in the field. Therefore other methods are still needed for producing preliminary age models, performing relative dating of surfaces, or selecting sampling sites for the laboratory analyses above. With the widespread availability of detailed multispectral imagery, a promising approach is to use remotely-sensed data to discriminate surfaces with different ages. Here, we use new Landsat 8 Operational Land Imager (OLI) multispectral imagery to characterise the reflectance of 35 alluvial fan surfaces in the semi-arid Owens Valley, California. Alluvial fans are useful landforms to date, as they are widely used to study the effects of tectonics, climate and sediment transport processes on source-to-sink sedimentation. Our target fan surfaces have all been mapped in detail in the field, and have well-constrained exposure ages ranging from modern to ~ 125 ka measured using a high density of 10Be cosmogenic nuclide samples. Despite all having similar granitic compositions, the spectral properties of these surfaces vary systematically with their exposure ages. Older surfaces demonstrate a predictable shift in reflectance across the visible and short-wave infrared spectrum. Simple calculations, such as the brightness ratios of different wavelengths, generate sensitive power law relationships with exposure age that depend on post-depositional alteration processes affecting these surfaces. We investigate what these processes might be in this dryland location, and evaluate the potential for using remotely-sensed multispectral imagery for developing surface age models. The ability to remotely sense relative exposure ages has useful implications for preliminary mapping, selecting

  14. Effectiveness of airborne multispectral thermal data for karst groundwater resources recognition in coastal areas

    NASA Astrophysics Data System (ADS)

    Pignatti, Stefano; Fusilli, Lorenzo; Palombo, Angelo; Santini, Federico; Pascucci, Simone

    2013-04-01

    Currently the detection, use and management of groundwater in karst regions can be considered one of the most significant procedures for solving water scarcity problems during periods of low rainfall this because groundwater resources from karst aquifers play a key role in the water supply in karst areas worldwide [1]. In many countries of the Mediterranean area, where karst is widespread, groundwater resources are still underexploited, while surface waters are generally preferred [2]. Furthermore, carbonate aquifers constitute a crucial thermal water resource outside of volcanic areas, even if there is no detailed and reliable global assessment of thermal water resources. The composite hydrogeological characteristics of karst, particularly directions and zones of groundwater distribution, are not up till now adequately explained [3]. In view of the abovementioned reasons the present study aims at analyzing the detection capability of high spatial resolution thermal remote sensing of karst water resources in coastal areas in order to get useful information on the karst springs flow and on different characteristics of these environments. To this purpose MIVIS [4, 5] and TASI-600 [6] airborne multispectral thermal imagery (see sensors' characteristics in Table 1) acquired on two coastal areas of the Mediterranean area interested by karst activity, one located in Montenegro and one in Italy, were used. One study area is located in the Kotor Bay, a winding bay on the Adriatic Sea surrounded by high mountains in south-western Montenegro and characterized by many subaerial and submarine coastal springs related to deep karstic channels. The other study area is located in Santa Cesarea (Italy), encompassing coastal cold springs, the main local source of high quality water, and also a noticeable thermal groundwater outflow. The proposed study shows the preliminary results of the two airborne deployments on these areas. The preprocessing of the multispectral thermal imagery

  15. Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Palubinskas, G.

    2016-06-01

    Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods `better' satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald's protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property `better' should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

  16. Towards Automatic Single-Sensor Mapping by Multispectral Airborne Laser Scanning

    NASA Astrophysics Data System (ADS)

    Ahokas, E.; Hyyppä, J.; Yu, X.; Liang, X.; Matikainen, L.; Karila, K.; Litkey, P.; Kukko, A.; Jaakkola, A.; Kaartinen, H.; Holopainen, M.; Vastaranta, M.

    2016-06-01

    This paper describes the possibilities of the Optech Titan multispectral airborne laser scanner in the fields of mapping and forestry. Investigation was targeted to six land cover classes. Multispectral laser scanner data can be used to distinguish land cover classes of the ground surface, including the roads and separate road surface classes. For forest inventory using point cloud metrics and intensity features combined, total accuracy of 93.5% was achieved for classification of three main boreal tree species (pine, spruce and birch).When using intensity features - without point height metrics - a classification accuracy of 91% was achieved for these three tree species. It was also shown that deciduous trees can be further classified into more species. We propose that intensity-related features and waveform-type features are combined with point height metrics for forest attribute derivation in area-based prediction, which is an operatively applied forest inventory process in Scandinavia. It is expected that multispectral airborne laser scanning can provide highly valuable data for city and forest mapping and is a highly relevant data asset for national and local mapping agencies in the near future.

  17. Multispectral light scattering imaging and multivariate analysis of airborne particulates

    NASA Astrophysics Data System (ADS)

    Holler, Stephen; Skelsey, Charles R.; Fuerstenau, Stephen D.

    2005-05-01

    Light scattering patterns from non-spherical particles and aggregates exhibit complex structure that is only revealed when observing in two angular dimensions. However, due to the varied shape and packing of such aerosols, the rich structure in the two-dimensional angular optical scattering (TAOS) pattern varies from particle to particle. We examine two-dimensional light scattering patterns obtained at multiple wavelengths using a single CCD camera with minimal cross talk between channels. The integration of the approach with a single CCD camera assures that data is acquired within the same solid angle and orientation. Since the optical size of the scattering particle is inversely proportional to the illuminating wavelength, the spectrally resolved scattering information provides characteristic information about the airborne particles simultaneously in two different scaling regimes. The simultaneous acquisition of data from airborne particulate matter at two different wavelengths allows for additional degrees of freedom in the analysis and characterization of the aerosols. Whereas our previous multivariate analyses of aerosol particles has relied solely on spatial frequency components, our present approach attempts to incorporate the relative symmetry of the particledetector system while extracting information content from both spectral channels. In addition to single channel data, this current approach also examines relative metrics. Consequently, we have begun to employ multivariate techniques based on novel morphological descriptors in order to classify "unknown" particles within a database of TAOS patterns from known aerosols utilizing both spectral and spatial information acquired. A comparison is made among several different classification metrics, all of which show improved classification capabilities relative to our previous approaches.

  18. Urban land use monitoring from computer-implemented processing of airborne multispectral data

    NASA Technical Reports Server (NTRS)

    Todd, W. J.; Mausel, P. W.; Baumgardner, M. F.

    1976-01-01

    Machine processing techniques were applied to multispectral data obtained from airborne scanners at an elevation of 600 meters over central Indianapolis in August, 1972. Computer analysis of these spectral data indicate that roads (two types), roof tops (three types), dense grass (two types), sparse grass (two types), trees, bare soil, and water (two types) can be accurately identified. Using computers, it is possible to determine land uses from analysis of type, size, shape, and spatial associations of earth surface images identified from multispectral data. Land use data developed through machine processing techniques can be programmed to monitor land use changes, simulate land use conditions, and provide impact statistics that are required to analyze stresses placed on spatial systems.

  19. Tidal Front Characterization using Airborne Imagery and In-situ Hydrographic Data

    NASA Astrophysics Data System (ADS)

    Scott, N. V.; Hooper, B. A.; Anderson, S. P.

    2011-12-01

    Tidal flats are highly dynamic areas with strong horizontal and vertical density gradients and energetic currents capable of shaping bathymetry, as well as modulating the salinity, temperature, and sediment concentration of the surrounding waters. As part of the ONR Tidal Flat Dynamics program, Areté Associates' Airborne Remote Optical Spotlight System - Multispectral Polarimeter (AROSS-MSP) was flown over a tidal flat in Skagit Bay, Washington to characterize the spatial structure of the velocities and the sediment concentrations. Time-series imagery reveals a robust surface front generated during the flood to ebb tidal cycle. The front is characterized by different optical properties on either side of a foam line, and by horizontal streaks in water clarity perpendicular to the foam line in the muddier, fresher water (Figure 1). These streaks may be the result of shear instabilities which are given visibility by buoyant fine-grained suspensions. Temperature and salinity time series from data stations in the cross-shelf direction were analyzed via empirical orthogonal functions (EOF). Sudden changes in the trend of first temperature EOF at a place behind the tidal front where abundant fresh water channels meet very cool ocean waters associated with the flood tide suggest mixing. The possibility of cross-shelf variability in mixing is also suggested by the changes in the horizontal Richardson number. The horizontal Richardson number shows a minimum value at the same location as the first temperature EOF suggesting that turbulent shear is large enough to cause mixing.

  20. Land cover classification in multispectral satellite imagery using sparse approximations on learned dictionaries

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a modified Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using CoSA: unsupervised Clustering of Sparse Approximations. We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska (USA). Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g., soil moisture and inundation), and topographic/geomorphic characteristics. In this paper, we explore learning from both raw multispectral imagery, as well as normalized band difference indexes. We explore a quantitative metric to evaluate the spectral properties of the clusters, in order to potentially aid in assigning land cover categories to the cluster labels.

  1. Evolutionary computation and post-wildfire land-cover mapping with multispectral imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Koch, Steven; Hansen, Leslie A.

    2002-01-01

    The Cerro Grande/Los Alamos wildfire devastated approximately 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos. The need to monitor the continuing impact of the fire on the local environment has led to the application of a number of advanced remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multispectral imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before and after the wildfire. Using an existing land cover classification based on a Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, along with clouds and cloud shadows. The details of our evolved classification are compared to the manually produced land-cover classification.

  2. Detection of subpixel anomalies in multispectral infrared imagery using an adaptive Bayesian classifier

    SciTech Connect

    Ashton, E.A.

    1998-03-01

    The detection of subpixel targets with unknown spectral signatures and cluttered backgrounds in multispectral imagery is a topic of great interest for remote surveillance applications. Because no knowledge of the target is assumed, the only way to accomplish such a detection is through a search for anomalous pixels. Two approaches to this problem are examined in this paper. The first is to separate the image into a number of statistical clusters by using an extension of the well-known {kappa}-means algorithm. Each bin of resultant residual vectors is then decorrelated, and the results are thresholded to provide detection. The second approach requires the formation of a probabilistic background model by using an adaptive Bayesian classification algorithm. This allows the calculation of a probability for each pixel, with respect to the model. These probabilities are then thresholded to provide detection. Both algorithms are shown to provide significant improvement over current filtering techniques for anomaly detection in experiments using multispectral IR imagery with both simulated and actual subpixel targets.

  3. Effectiveness of airborne multispectral thermal data for karst groundwater resources recognition in coastal areas

    NASA Astrophysics Data System (ADS)

    Pignatti, Stefano; Fusilli, Lorenzo; Palombo, Angelo; Santini, Federico; Pascucci, Simone

    2013-04-01

    Currently the detection, use and management of groundwater in karst regions can be considered one of the most significant procedures for solving water scarcity problems during periods of low rainfall this because groundwater resources from karst aquifers play a key role in the water supply in karst areas worldwide [1]. In many countries of the Mediterranean area, where karst is widespread, groundwater resources are still underexploited, while surface waters are generally preferred [2]. Furthermore, carbonate aquifers constitute a crucial thermal water resource outside of volcanic areas, even if there is no detailed and reliable global assessment of thermal water resources. The composite hydrogeological characteristics of karst, particularly directions and zones of groundwater distribution, are not up till now adequately explained [3]. In view of the abovementioned reasons the present study aims at analyzing the detection capability of high spatial resolution thermal remote sensing of karst water resources in coastal areas in order to get useful information on the karst springs flow and on different characteristics of these environments. To this purpose MIVIS [4, 5] and TASI-600 [6] airborne multispectral thermal imagery (see sensors' characteristics in Table 1) acquired on two coastal areas of the Mediterranean area interested by karst activity, one located in Montenegro and one in Italy, were used. One study area is located in the Kotor Bay, a winding bay on the Adriatic Sea surrounded by high mountains in south-western Montenegro and characterized by many subaerial and submarine coastal springs related to deep karstic channels. The other study area is located in Santa Cesarea (Italy), encompassing coastal cold springs, the main local source of high quality water, and also a noticeable thermal groundwater outflow. The proposed study shows the preliminary results of the two airborne deployments on these areas. The preprocessing of the multispectral thermal imagery

  4. Novel round-robin tabu search algorithm for prostate cancer classification and diagnosis using multispectral imagery.

    PubMed

    Tahir, Muhammad Atif; Bouridane, Ahmed

    2006-10-01

    Quantitative cell imagery in cancer pathology has progressed greatly in the last 25 years. The application areas are mainly those in which the diagnosis is still critically reliant upon the analysis of biopsy samples, which remains the only conclusive method for making an accurate diagnosis of the disease. Biopsies are usually analyzed by a trained pathologist who, by analyzing the biopsies under a microscope, assesses the normality or malignancy of the samples submitted. Different grades of malignancy correspond to different structural patterns as well as to apparent textures. In the case of prostate cancer, four major groups have to be recognized: stroma, benign prostatic hyperplasia, prostatic intraepithelial neoplasia, and prostatic carcinoma. Recently, multispectral imagery has been used to solve this multiclass problem. Unlike conventional RGB color space, multispectral images allow the acquisition of a large number of spectral bands within the visible spectrum, resulting in a large feature vector size. For such a high dimensionality, pattern recognition techniques suffer from the well-known "curse-of-dimensionality" problem. This paper proposes a novel round-robin tabu search (RR-TS) algorithm to address the curse-of-dimensionality for this multiclass problem. The experiments have been carried out on a number of prostate cancer textured multispectral images, and the results obtained have been assessed and compared with previously reported works. The system achieved 98%-100% classification accuracy when testing on two datasets. It outperformed principal component/linear discriminant classifier (PCA-LDA), tabu search/nearest neighbor classifier (TS-1NN), and bagging/boosting with decision tree (C4.5) classifier. PMID:17044412

  5. Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

    NASA Astrophysics Data System (ADS)

    Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

    2015-03-01

    Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

  6. A system to geometrically rectify and map airborne scanner imagery and to estimate ground area. [by computer

    NASA Technical Reports Server (NTRS)

    Spencer, M. M.; Wolf, J. M.; Schall, M. A.

    1974-01-01

    A system of computer programs were developed which performs geometric rectification and line-by-line mapping of airborne multispectral scanner data to ground coordinates and estimates ground area. The system requires aircraft attitude and positional information furnished by ancillary aircraft equipment, as well as ground control points. The geometric correction and mapping procedure locates the scan lines, or the pixels on each line, in terms of map grid coordinates. The area estimation procedure gives ground area for each pixel or for a predesignated parcel specified in map grid coordinates. The results of exercising the system with simulated data showed the uncorrected video and corrected imagery and produced area estimates accurate to better than 99.7%.

  7. Evaluating airborne hyperspectral imagery for mapping saltcedar infestations in west Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Rio Grande of west Texas contains by far the largest infestation of saltcedar (Tamarix spp.) in Texas. The objective of this study was to evaluate airborne hyperspectral imagery and different classification techniques for mapping saltcedar infestations. Hyperspectral imagery with 102 usable band...

  8. Using airborne hyperspectral imagery for mapping saltcedar infestations in west Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Rio Grande of west Texas contains, by far, the largest infestation of saltcedar (Tamarix spp.) in Texas. The objective of this study was to evaluate airborne hyperspectral imagery and different classification techniques for mapping saltcedar infestations. Hyperspectral imagery with 102 usable ba...

  9. Spectral Unmixing of airborne hyperspectral imagery for mapping giant reed infestations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spectral unmixing techniques applied to hyperspectral imagery were examined for mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern United States and northern Mexico. Airborne hyperspectral imagery with 102...

  10. Multispectral airborne laser scanning - a new trend in the development of LiDAR technology

    NASA Astrophysics Data System (ADS)

    Bakuła, K.

    2015-12-01

    Airborne laser scanning (ALS) is the one of the most accurate remote sensing techniques for data acquisition where the terrain and its coverage is concerned. Modern scanners have been able to scan in two or more channels (frequencies of the laser) recently. This gives the rise to the possibility of obtaining diverse information about an area with the different spectral properties of objects. The paper presents an example of a multispectral ALS system - Titan by Optech - with the possibility of data including the analysis of digital elevation models accuracy and data density. As a result of the study, the high relative accuracy of LiDAR acquisition in three spectral bands was proven. The mean differences between digital terrain models (DTMs) were less than 0.03 m. The data density analysis showed the influence of the laser wavelength. The points clouds that were tested had average densities of 25, 23 and 20 points per square metre respectively for green (G), near-infrared (NIR) and shortwave-infrared (SWIR) lasers. In this paper, the possibility of the generation of colour composites using orthoimages of laser intensity reflectance and its classification capabilities using data from airborne multispectral laser scanning for land cover mapping are also discussed and compared with conventional photogrammetric techniques.

  11. Benchmarking High Density Image Matching for Oblique Airborne Imagery

    NASA Astrophysics Data System (ADS)

    Cavegn, S.; Haala, N.; Nebiker, S.; Rothermel, M.; Tutzauer, P.

    2014-08-01

    Both, improvements in camera technology and new pixel-wise matching approaches triggered the further development of software tools for image based 3D reconstruction. Meanwhile research groups as well as commercial vendors provide photogrammetric software to generate dense, reliable and accurate 3D point clouds and Digital Surface Models (DSM) from highly overlapping aerial images. In order to evaluate the potential of these algorithms in view of the ongoing software developments, a suitable test bed is provided by the ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. This paper discusses the proposed test scenario to investigate the potential of dense matching approaches for 3D data capture from oblique airborne imagery. For this purpose, an oblique aerial image block captured at a GSD of 6 cm in the west of Zürich by a Leica RCD30 Oblique Penta camera is used. Within this paper, the potential test scenario is demonstrated using matching results from two software packages, Agisoft PhotoScan and SURE from University of Stuttgart. As oblique images are frequently used for data capture at building facades, 3D point clouds are mainly investigated at such areas. Reference data from terrestrial laser scanning is used to evaluate data quality from dense image matching for several facade patches with respect to accuracy, density and reliability.

  12. An application of LANDSAT multispectral imagery for the classification of hydrobiological systems, Shark River Slough, Everglades National Park, Florida

    NASA Technical Reports Server (NTRS)

    Rose, P. W.; Rosendahl, P. C. (Principal Investigator)

    1979-01-01

    Multivariant hydrologic parameters over the Shark River Slough were investigated. Ground truth was established utilizing U-2 infrared photography and comprehensive field data to define a control network which represented all hydrobiological systems in the slough. These data were then applied to LANDSAT imagery utilizing an interactive multispectral processor which generated hydrographic maps through classification of the slough and defined the multispectral surface radiance characteristics of the wetlands areas in the park. The spectral response of each hydrobiological zone was determined and plotted to formulate multispectral relationships between the emittent energy from the slough in order to determine the best possible multispectral wavelength combinations to enhance classification results. The extent of each hydrobiological zone in slough was determined and flow vectors for water movement throughout the slough established.

  13. Testing of Land Cover Classification from Multispectral Airborne Laser Scanning Data

    NASA Astrophysics Data System (ADS)

    Bakuła, K.; Kupidura, P.; Jełowicki, Ł.

    2016-06-01

    Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud) acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images), spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and last return

  14. Fusion of remotely sensed data from airborne and ground-based sensors for cotton regrowth study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

  15. Mapping giant reed along the Rio Grande using airborne and satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Giant reed (Arundo donax L.) is a perennial invasive weed that presents a severe threat to agroecosystems and riparian areas in the Texas and Mexican portions of the Rio Grande Basin. The objective of this presentation is to give an overview on the use of aerial photography, airborne multispectral a...

  16. Combination of RGB and Multispectral Imagery for Discrimination of Cabernet Sauvignon Grapevine Elements

    PubMed Central

    Fernández, Roemi; Montes, Héctor; Salinas, Carlota; Sarria, Javier; Armada, Manuel

    2013-01-01

    This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting. PMID:23783736

  17. Watershed image segmentation and cloud classification from multispectral MSG-SEVIRI imagery

    NASA Astrophysics Data System (ADS)

    González, Albano; Pérez, Juan C.; Muñoz, Jonathan; Méndez, Zebensui; Armas, Montserrat

    2012-01-01

    In this work a technique for cloud detection and classification from MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infra-red Imager) imagery is presented. It is based on the segmentation of the multispectral images using order-invariant watershed algorithms, which are applied to the corresponding gradient images, computed by a multi-dimensional morphological operator. To reduce the over-segmentation produced by the watershed method, a RAG (Region Adjacency Graph) based region merging technique is applied, using region dissimilarity functions. Once the objects present in the image have been segmented, they are classified using a multi-threshold method based on physical considerations that takes into account the statistical parameters inside each region.

  18. Combination of RGB and multispectral imagery for discrimination of cabernet sauvignon grapevine elements.

    PubMed

    Fernández, Roemi; Montes, Héctor; Salinas, Carlota; Sarria, Javier; Armada, Manuel

    2013-01-01

    This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting. PMID:23783736

  19. Mineral Classification of the Martian Surface Using THEMIS Multi-Spectral Infrared Imagery

    NASA Astrophysics Data System (ADS)

    Osterloo, M. M.; Brumby, S. P.; Funsten, H. O.; Feldman, W. C.

    2004-12-01

    Recent advancements in multi-spectral imaging and image analysis techniques have greatly enhanced our ability to do planetary research. Much has been discovered about Mars through recent missions such as Mars Global Surveyor, 2001 Mars Odyssey, and the Mars Exploration Rovers. The Thermal Emission Spectrometer on board the Mars Global Surveyor has allowed the mapping of surface mineralogies on Mars at several kilometers scale through hyperspectral imaging [1]. Here, we use the high resolution multi-spectral imagery of THEMIS (THermal Emission Imaging System) on board the 2001 Mars Odyssey to identify different mineral classes at spatial scales of hundreds of meters. THEMIS contains two independent multi-spectral imaging systems: a 10-band thermal infrared imager (IR) with a resolution of 100m/pixel, and a 5-band visible imager with a resolution of 10m/pixel. Here we will use the IR data. The 9 IR bands are centered from 6.8 microns to 14 .9 microns [2]. Using Arizona State University's online spectral library[3], we have been investigating the extent to which we can differentiate between different mineral classes. By identifying certain mineral classes we can better understand the geologic processes which created them and detect areas of interest for further study. Linear mixing of minerals and dust is investigated to estimate ratios of minerals and their resulting spectra. We then compare these spectra to observations of several regions on Mars. We compare these results with TES data and previous mineralogical maps. [1] Christensen et al, (2001) JGR 106, E10; [2] Christensen et al, (2002) Space Science Reviews 110, 1; [3] Christensen et al, (2000) JGR 105, E4

  20. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    SciTech Connect

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  1. Focus-of-attention strategies for finding discrete objects in multispectral imagery

    NASA Astrophysics Data System (ADS)

    Harvey, Neal R.; Theiler, James

    2004-10-01

    Tools that perform pixel-by-pixel classification of multispectral imagery are useful in broad area mapping applications such as terrain categorization, but are less well-suited to the detection of discrete objects. Pixel-by-pixel classifiers, however, have many advantages: they are relatively simple to design, they can readily employ formal machine learning tools, and they are widely available on a variety of platforms. We describe an approach that enables pixel-by-pixel classifiers to be more effectively used in object-detection settings. This is achieved by optimizing a metric which does not attempt to precisely delineate every pixel comprising the objects of interest, but instead focusses the attention of the analyst to these objects without the distraction of many false alarms. The approach requires only minor modification of exisiting pixel-by-pixel classifiers, and produces substantially improved performance. We will describe algorithms that employ this approach and show how they work on a varitety of object detection problems using remotely-sensed multispectral data.

  2. Semi-supervised classification tool for DubaiSat-2 multispectral imagery

    NASA Astrophysics Data System (ADS)

    Al-Mansoori, Saeed

    2015-10-01

    This paper addresses a semi-supervised classification tool based on a pixel-based approach of the multi-spectral satellite imagery. There are not many studies demonstrating such algorithm for the multispectral images, especially when the image consists of 4 bands (Red, Green, Blue and Near Infrared) as in DubaiSat-2 satellite images. The proposed approach utilizes both unsupervised and supervised classification schemes sequentially to identify four classes in the image, namely, water bodies, vegetation, land (developed and undeveloped areas) and paved areas (i.e. roads). The unsupervised classification concept is applied to identify two classes; water bodies and vegetation, based on a well-known index that uses the distinct wavelengths of visible and near-infrared sunlight that is absorbed and reflected by the plants to identify the classes; this index parameter is called "Normalized Difference Vegetation Index (NDVI)". Afterward, the supervised classification is performed by selecting training homogenous samples for roads and land areas. Here, a precise selection of training samples plays a vital role in the classification accuracy. Post classification is finally performed to enhance the classification accuracy, where the classified image is sieved, clumped and filtered before producing final output. Overall, the supervised classification approach produced higher accuracy than the unsupervised method. This paper shows some current preliminary research results which point out the effectiveness of the proposed technique in a virtual perspective.

  3. Focus of attention strategies for finding discrete objects in multispectral imagery

    SciTech Connect

    Harvey, N. R.; Theiler, J. P.

    2004-01-01

    Tools that perform pixel-by-pixel classification of multispectral imagery are useful in broad area mapping applications such as terrain categorization, but are less well-suited to the detection of discrete objects. Pixel-by-pixel classifiers, however, have many advantages: they are relatively simple to design, they can readily employ formal machine learning tools, and they are widely available on a variety of platforms. We describe an approach that enables pixel-by-pixel classifiers to be more effectively used in object-detection settings. This is achieved by optimizing a metric which does not attempt to precisely delineate every pixel comprising the objects of interest, but instead focusses the attention of the analyst to these objects without the distraction of many false alarms. The approach requires only minor modification of exisiting pixel-by-pixel classifiers, and produces substantially improved performance. We will describe algorithms that employ this approach and show how they work on a varitety of object detection problems using remotely-sensed multispectral data.

  4. Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph; Berglund, Judith

    2000-01-01

    The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

  5. Roof heat loss detection using airborne thermal infrared imagery

    NASA Astrophysics Data System (ADS)

    Kern, K.; Bauer, C.; Sulzer, W.

    2012-12-01

    As part of the Austrian and European attempt to reduce energy consumption and greenhouse gas emissions, thermal rehabilitation and the improvement of the energy efficiency of buildings became an important topic in research as well as in building construction and refurbishment. Today, in-situ thermal infrared measurements are routinely used to determine energy loss through the building envelope. However, in-situ thermal surveys are expensive and time consuming, and in many cases the detection of the amount and location of waste heat leaving building through roofs is not possible with ground-based observations. For some years now, a new generation of high-resolution thermal infrared sensors makes it possible to survey heat-loss through roofs at a high level of detail and accuracy. However, to date, comparable studies have mainly been conducted on buildings with uniform roof covering and provided two-dimensional, qualitative information. This pilot study aims to survey the heat-loss through roofs of the buildings of the University of Graz (Austria) campus by using high-resolution airborne thermal infrared imagery (TABI 1800 - Thermal Airborne Broadband imager). TABI-1800 acquires data in a spectral range from 3.7 - 4.8 micron, a thermal resolution of 0.05 °C and a spatial resolution of 0.6 m. The remote sensing data is calibrated to different roof coverings (e.g. clay shingle, asphalt shingle, tin roof, glass) and combined with a roof surface model to determine the amount of waste heat leaving the building and to identify hot spots. The additional integration of information about the conditions underneath the roofs into the study allows a more detailed analysis of the upward heat flux and is a significant improvement of existing methods. The resulting data set provides useful information to the university facility service for infrastructure maintenance, especially in terms of attic and roof insulation improvements. Beyond that, the project is supposed to raise public

  6. A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters

    PubMed Central

    Li, Hanlun; Zhang, Aiwu; Hu, Shaoxing

    2015-01-01

    This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels. PMID:26205264

  7. Classifying Multiple Stages of Mountain Pine Beetle Disturbance Using Multispectral Aerial Imagery in North-Central Colorado

    NASA Astrophysics Data System (ADS)

    Meddens, A. J.; Hicke, J. A.; Vierling, L. A.

    2010-12-01

    Insect outbreaks are major forest disturbances, killing trees across millions of ha in the United States. These dead trees affect the condition of the ecosystems, leading to alterations of forest functioning and fuel arrangement, among other impacts. In this study, we evaluated methods for classifying 30-cm multispectral imagery including insect-caused tree mortality (both red and gray attack) classes and non-forest classes. We acquired 4-band imagery in lodgepole pine stands of central Colorado that were recently attacked by mountain pine beetle. The 30-cm resolution image facilitated delineation of field-observed trees, which were used for image classification. We employed the maximum likelihood classifier with the Normalized Difference Vegetation Index (NDVI), the Red-Green Index (RGI), and Green band (GREEN). Our initial classification used original spatial resolution imagery to identify green trees, red-attack, gray-attack, herbaceous, bare soil, and shadow classes. Although classification accuracies were good (overall accuracy of 85.95%, kappa = 0.826), we noted confusion between sunlit crowns of live (green) trees and herbaceous classes at this very fine spatial resolution, and confusion between sunlit crowns of gray- and red-attack trees and bare soil, and thus explored additional methods to reduce omission and commission errors. Classification confusion was overcome by aggregating the 30-cm multispectral imagery into a 2.4-m resolution image (matching very high resolution satellite imagery). Pixels in the 2.4-m resolution image included more shadow in the forested regions than the 30-cm resolution, thereby reducing forest canopy reflectance and improving the separability between the forest and non-forest classes that had caused previous errors. We conclude that operational mapping of insect-caused tree mortality with multispectral imagery has great potential for forest disturbance mapping, and that imagery with a spatial resolution about the crown width of

  8. Correlation and registration of ERTS multispectral imagery. [by a digital processing technique

    NASA Technical Reports Server (NTRS)

    Bonrud, L. O.; Henrikson, P. J.

    1974-01-01

    Examples of automatic digital processing demonstrate the feasibility of registering one ERTS multispectral scanner (MSS) image with another obtained on a subsequent orbit, and automatic matching, correlation, and registration of MSS imagery with aerial photography (multisensor correlation) is demonstrated. Excellent correlation was obtained with patch sizes exceeding 16 pixels square. Qualities which lead to effective control point selection are distinctive features, good contrast, and constant feature characteristics. Results of the study indicate that more than 300 degrees of freedom are required to register two standard ERTS-1 MSS frames covering 100 by 100 nautical miles to an accuracy of 0.6 pixel mean radial displacement error. An automatic strip processing technique demonstrates 600 to 1200 degrees of freedom over a quater frame of ERTS imagery. Registration accuracies in the range of 0.3 pixel to 0.5 pixel mean radial error were confirmed by independent error analysis. Accuracies in the range of 0.5 pixel to 1.4 pixel mean radial error were demonstrated by semi-automatic registration over small geographic areas.

  9. Techniques for automatic large scale change analysis of temporal multispectral imagery

    NASA Astrophysics Data System (ADS)

    Mercovich, Ryan A.

    Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring

  10. Fusion of remotely sensed data from airborne and ground-based sensors to enhance detection of cotton plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

  11. Reexamination of Faulting in the Tahoe Basin Using Airborne LiDAR Data and Seismic CHIRP Imagery

    NASA Astrophysics Data System (ADS)

    Schmauder, G. C.; Kent, G.; Smith, K. D.; Driscoll, N. W.; Maloney, J. M.

    2011-12-01

    Faulting across the Tahoe basin has been mapped using a combination of multibeam sonar, airborne Light Detection and Ranging (LiDAR), and high-resolution seismic CHIRP imagery. In August 2010, the Tahoe Regional Planning Agency (TRPA) collected 941 square kilometers of airborne LiDAR data in the Tahoe basin using a Leica ALS50 Phase II Laser system mounted on a Cessna Caravan 208B aircraft; our group was involved with data specification, selection of contractor and data QC. These data have a resolution of 11.82 points per square meter and a vertical accuracy of 3.5 centimeters. The high data resolution has allowed us to map with ease the many fault scarps associated with the three major active fault zones in the Tahoe basin, which include the West Tahoe-Dollar Point fault zone, the Stateline fault, and the Incline Village fault. By using the airborne LiDAR data, we were able to identify previously unmapped fault segments throughout the Tahoe basin. Future application of terrestrial LiDAR using an I-Site 4400 laser scanner at selected sites will provide better control and resolution of the fault scarp characteristics. This will allow us to not only ground truth the airborne LiDAR, but also look for subtle features that may be indicative of dextral motion on faults otherwise displaying predominantly normal displacement. Finally, to refine fault locations beneath Lake Tahoe, Fallen Leaf Lake and Cascade Lake, we collected additional CHIRP imagery using an Edgetech Subscan system, in some cases to groundtruth the new LiDAR fault data (i.e., Cascade Lake). By combining these images with the LiDAR, multibeam data and new multispectral imagery, we were able to link previously unknown segments of the faults and identify continuity in the individual fault systems. From our results, we have developed a much-improved model of the fault systems within the Lake Tahoe basin. Our model provides us with a better understanding of the tectonic environment of the basin and may help

  12. Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Klimesh, Matthew A.

    2009-01-01

    This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

  13. Land surface temperature retrieved from airborne multispectral scanner mid-infrared and thermal-infrared data.

    PubMed

    Qian, Yong-Gang; Wang, Ning; Ma, Ling-Ling; Liu, Yao-Kai; Wu, Hua; Tang, Bo-Hui; Tang, Ling-Li; Li, Chuan-Rong

    2016-01-25

    Land surface temperature (LST) is one of the key parameters in the physics of land surface processes at local/global scales. In this paper, a LST retrieval method was proposed from airborne multispectral scanner data comparing one mid-infrared (MIR) channel and one thermal infrared (TIR) channel with the land surface emissivity given as a priori knowledge. To remove the influence of the direct solar radiance efficiently, a relationship between the direct solar radiance and water vapor content and the view zenith angle and solar zenith angle was established. Then, LST could be retrieved with a split-window algorithm from MIR/TIR data. Finally, the proposed algorithm was applied to the actual airborne flight data and validated with in situ measurements of land surface types in the Baotou site in China on 17 October 2014. The results demonstrate that the difference between the retrieved and in situ LST was less than 1.5 K. The bais, RMSE, and standard deviation of the retrieved LST were 0.156 K, 0.883 K, and 0.869 K, respectively, for samples. PMID:26832579

  14. Airborne hyperspectral imagery for mapping crop yield variability

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information concerning the spatial variation in crop yield has become necessary for site-specific crop management. Traditional satellite imagery has long been used to monitor crop growing conditions and to estimate crop yields over large geographic areas. However, this type of imagery has limited us...

  15. Detecting new Buffel grass infestations in Australian arid lands: evaluation of methods using high-resolution multispectral imagery and aerial photography.

    PubMed

    Marshall, V M; Lewis, M M; Ostendorf, B

    2014-03-01

    We assess the feasibility of using airborne imagery for Buffel grass detection in Australian arid lands and evaluate four commonly used image classification techniques (visual estimate, manual digitisation, unsupervised classification and normalised difference vegetation index (NDVI) thresholding) for their suitability to this purpose. Colour digital aerial photography captured at approximately 5 cm of ground sample distance (GSD) and four-band (visible–near-infrared) multispectral imagery (25 cm GSD) were acquired (14 February 2012) across overlapping subsets of our study site. In the field, Buffel grass projected cover estimates were collected for quadrates (10 m diameter), which were subsequently used to evaluate the four image classification techniques. Buffel grass was found to be widespread throughout our study site; it was particularly prevalent in riparian land systems and alluvial plains. On hill slopes, Buffel grass was often present in depressions, valleys and crevices of rock outcrops, but the spread appeared to be dependent on soil type and vegetation communities. Visual cover estimates performed best (r 2 0.39), and pixel-based classifiers (unsupervised classification and NDVI thresholding) performed worst (r 2 0.21). Manual digitising consistently underrepresented Buffel grass cover compared with field- and image-based visual cover estimates; we did not find the labours of digitising rewarding. Our recommendation for regional documentation of new infestation of Buffel grass is to acquire ultra-high-resolution aerial photography and have a trained observer score cover against visual standards and use the scored sites to interpolate density across the region. PMID:24234223

  16. Distributed adaptive framework for multispectral/hyperspectral imagery and three-dimensional point cloud fusion

    NASA Astrophysics Data System (ADS)

    Rand, Robert S.; Khuon, Timothy; Truslow, Eric

    2016-07-01

    A proposed framework using spectral and spatial information is introduced for neural net multisensor data fusion. This consists of a set of independent-sensor neural nets, one for each sensor (type of data), coupled to a fusion net. The neural net of each sensor is trained from a representative data set of the particular sensor to map to a hypothesis space output. The decision outputs from the sensor nets are used to train the fusion net to an overall decision. During the initial processing, three-dimensional (3-D) point cloud data (PCD) are segmented using a multidimensional mean-shift algorithm into clustered objects. Concurrently, multiband spectral imagery data (multispectral or hyperspectral) are spectrally segmented by the stochastic expectation-maximization into a cluster map containing (spectral-based) pixel classes. For the proposed sensor fusion, spatial detections and spectral detections complement each other. They are fused into final detections by a cascaded neural network, which consists of two levels of neural nets. The success of the approach in utilizing sensor synergism for an enhanced classification is demonstrated for the specific case of classifying hyperspectral imagery and PCD extracted from LIDAR, obtained from an airborne data collection over the campus of University of Southern Mississippi, Gulfport, Mississippi.

  17. High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

    NASA Astrophysics Data System (ADS)

    Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

    2015-10-01

    The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

  18. Tracking stormwater discharge plumes and water quality of the Tijuana River with multispectral aerial imagery

    NASA Astrophysics Data System (ADS)

    Svejkovsky, Jan; Nezlin, Nikolay P.; Mustain, Neomi M.; Kum, Jamie B.

    2010-04-01

    Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline.

  19. Application of combined Landsat thematic mapper and airborne thermal infrared multispectral scanner data to lithologic mapping in Nevada

    USGS Publications Warehouse

    Podwysocki, M.H.; Ehmann, W.J.; Brickey, D.W.

    1987-01-01

    Future Landsat satellites are to include the Thematic Mapper (TM) and also may incorporate additional multispectral scanners. One such scanner being considered for geologic and other applications is a four-channel thermal-infrared multispectral scanner having 60-m spatial resolution. This paper discusses the results of studies using combined Landsat TM and airborne Thermal Infrared Multispectral Scanner (TIMS) digital data for lithologic discrimination, identification, and geologic mapping in two areas within the Basin and Range province of Nevada. Field and laboratory reflectance spectra in the visible and reflective-infrared and laboratory spectra in the thermal-infrared parts of the spectrum were used to verify distinctions made between rock types in the image data sets.

  20. Airborne multispectral and thermal remote sensing for detecting the onset of crop stress caused by multiple factors

    NASA Astrophysics Data System (ADS)

    Huang, Yanbo; Thomson, Steven J.

    2010-10-01

    Remote sensing technology has been developed and applied to provide spatiotemporal information on crop stress for precision management. A series of multispectral images over a field planted cotton, corn and soybean were obtained by a Geospatial Systems MS4100 camera mounted on an Air Tractor 402B airplane equipped with Camera Link in a Magma converter box triggered by Terraverde Dragonfly® flight navigation and imaging control software. The field crops were intentionally stressed by applying glyphosate herbicide via aircraft and allowing it to drift near-field. Aerial multispectral images in the visible and near-infrared bands were manipulated to produce vegetation indices, which were used to quantify the onset of herbicide induced crop stress. The vegetation indices normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) showed the ability to monitor crop response to herbicide-induced injury by revealing stress at different phenological stages. Two other fields were managed with irrigated versus nonirrigated treatments, and those fields were imaged with both the multispectral system and an Electrophysics PV-320T thermal imaging camera on board an Air Tractor 402B aircraft. Thermal imagery indicated water stress due to deficits in soil moisture, and a proposed method of determining crop cover percentage using thermal imagery was compared with a multispectral imaging method. Development of an image fusion scheme may be necessary to provide synergy and improve overall water stress detection ability.

  1. Retrieving TN and TP Concentration of Urban River From High Resolution IKONOS Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Liu, J.; Zhang, L.; Song, X.

    2014-12-01

    Total nitrogen (TN) and Total phosphorus (TP) are widely known as two important indexes to measure China urban rivers, and the technique of remote sensing plays an important role in quantitatively monitoring the dynamic change and timely grasping the status of urban rivers. Taking Wen-rui Tang River as examples, this paper develops both multiple regressions (MR) model and artificial neural networks (ANN) model to estimate TN and TP concentration from high resolution IKONOS image data and in situ water samples collected concurrently with satellite overpass. By analyzing determination coefficients (R2) and relative root mean square error (RMSE), it is found that the measured and estimated values of both MR and ANN models are in good agreement (R2>0.85 and RMSE<2.50), and the estimated accuracy using ANN model is better (R2>0.86 and RMSE<0.89). The results also present the potential of high resolution IKONOS multispectral imagery to apply to urban rivers. The spatial distribution maps of TP and TN concentration generated by ANN model present apparent spatial variations and inform the decision makers of water quality variations in Wen-rui Tang River. The approach developed in this study proves to be effective and has the potential to be applied over urban rivers for water quality monitoring.

  2. Use of multispectral Ikonos imagery for discriminating between conventional and conservation agricultural tillage practices

    USGS Publications Warehouse

    Vina, Andres; Peters, Albert J.; Ji, Lei

    2003-01-01

    There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.

  3. A review and analysis of neural networks for classification of remotely sensed multispectral imagery

    NASA Technical Reports Server (NTRS)

    Paola, Justin D.; Schowengerdt, Robert A.

    1993-01-01

    A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

  4. Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil hyperspectral reflectance imagery was obtained from an airborne imaging spectrometer (400 to 2450 nm with ~10 nm resolution, 2.5 m spatial resolution) flown over six tilled (bare soil) agricultural fields on the Eastern Shore of the Chesapeake Bay (Queen Anne’s county, MD). Surface soil samples...

  5. Applying linear spectral unmixing to airborne hyperspectral imagery for mapping crop yield variability.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study evaluated linear spectral unmixing techniques for mapping the variation in crop yield. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery recorded from one grain sorghum field and a cotton field. A pair of plant and soil spect...

  6. On-Orbit Calibration of a Multi-Spectral Satellite Satellite Sensor Using a High Altitude Airborne Imaging Spectrometer

    NASA Technical Reports Server (NTRS)

    Green, R. O.; Shimada, M.

    1996-01-01

    Earth-looking satellites must be calibrated in order to quantitatively measure and monitor components of land, water and atmosphere of the Earth system. The inevitable change in performance due to the stress of satellite launch requires that the calibration of a satellite sensor be established and validated on-orbit. A new approach to on-orbit satellite sensor calibration has been developed using the flight of a high altitude calibrated airborne imaging spectrometer below a multi-spectral satellite sensor.

  7. Use of Airborne Thermal Imagery to Detect and Monitor Inshore Oil Spill Residues During Darkness Hours.

    PubMed

    GRIERSON

    1998-11-01

    / Trials were conducted using an airborne video system operating in the visible, near-infrared, and thermal wavelengths to detect two known oil spill releases during darkness at a distance of 10 nautical miles from the shore in St. Vincent's Gulf, South Australia. The oil spills consisted of two 20-liter samples released at 2-h intervals, one sample consisted of paraffinic neutral material and the other of automotive diesel oil. A tracking buoy was sent overboard in conjunction with the release of sample 1, and its movement monitored by satellite relay. Both oil residues were overflown by a light aircraft equipped with thermal, visible, and infrared imagers at a period of approximately 1 h after the release of the second oil residue. Trajectories of the oil residue releases were also modeled and the results compared to those obtained by the airborne video and the tracking buoy. Airborne imagery in the thermal wavelengths successfully located and mapped both oil residue samples during nighttime conditions. Results from the trial suggest that the most advantageous technique would be the combined use of the tracking beacon to obtain an approximate location of the oil spill and the airborne imagery to ascertain its extent and characteristics.KEY WORDS: Airborne video; Thermal imagery; Global positioning; Oil-spill monitoring; Tracking beacon PMID:9732519

  8. Mapping of hydrothermally altered rocks using airborne multispectral scanner data, Marysvale, Utah, mining district

    USGS Publications Warehouse

    Podwysocki, M.H.; Segal, D.B.; Jones, O.D.

    1983-01-01

    Multispectral data covering an area near Marysvale, Utah, collected with the airborne National Aeronautics and Space Administration (NASA) 24-channel Bendix multispectral scanner, were analyzed to detect areas of hydrothermally altered, potentially mineralized rocks. Spectral bands were selected for analysis that approximate those of the Landsat 4 Thematic Mapper and which are diagnostic of the presence of hydrothermally derived products. Hydrothermally altered rocks, particularly volcanic rocks affected by solutions rich in sulfuric acid, are commonly characterized by concentrations of argillic minerals such as alunite and kaolinite. These minerals are important for identifying hydrothermally altered rocks in multispectral images because they have intense absorption bands centered near a wavelength of 2.2 ??m. Unaltered volcanic rocks commonly do not contain these minerals and hence do not have the absorption bands. A color-composite image was constructed using the following spectral band ratios: 1.6??m/2.2??m, 1.6??m/0.48??m, and 0.67??m/1.0??m. The particular bands were chosen to emphasize the spectral contrasts that exist for argillic versus non-argillic rocks, limonitic versus nonlimonitic rocks, and rocks versus vegetation, respectively. The color-ratio composite successfully distinguished most types of altered rocks from unaltered rocks. Some previously unrecognized areas of hydrothermal alteration were mapped. The altered rocks included those having high alunite and/or kaolinite content, siliceous rocks containing some kaolinite, and ash-fall tuffs containing zeolitic minerals. The color-ratio-composite image allowed further division of these rocks into limonitic and nonlimonitic phases. The image did not allow separation of highly siliceous or hematitically altered rocks containing no clays or alunite from unaltered rocks. A color-coded density slice image of the 1.6??m/2.2??m band ratio allowed further discrimination among the altered units. Areas

  9. High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.; Arnold, James E. (Technical Monitor)

    2000-01-01

    We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used

  10. Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

    NASA Technical Reports Server (NTRS)

    Krohn, M. Dennis

    1986-01-01

    The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

  11. Usefulness of Skylab color photography and ERTS-1 multispectral imagery for mapping range vegetation types in southwestern Wyoming

    NASA Technical Reports Server (NTRS)

    Gordon, R. C. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. Aerial photography at scales of 1:43,400 and 1:104,500 was used to evaluate the usefulness of Skylab color photography (scales of 1:477,979 and 1:712,917) and ERTS-1 multispectral imagery (scale 1:1,000,000) for mapping range vegetation types. The project was successful in producing a range vegetation map of the 68,000 acres of salt desert shrub type in southwestern Wyoming. Techniques for estimation of above-ground green biomass have not yet been confirmed due to the mechanical failure of the photometer used in obtaining relative reflectance measurement. However, graphs of log transmittance versus above-ground green biomass indicate that production estimates may be made for some vegetation types from ERTS imagery. Other vegetation types not suitable for direct ERTS estimation of green biomass may possibly be related to those vegetation types whose production has been estimated from the multispectral imagery.

  12. Reconstructing Holocene Glacier Changes in West Greenland From Multispectral ASTER Imagery

    NASA Astrophysics Data System (ADS)

    Huh, K.; Csatho, B.; van der Veen, C. J.; Ahn, Y.

    2006-12-01

    To understand the mass balance of the Greenland Ice Sheet and to identify mechanisms controlling that balance and Greenland's contribution to future changes in global sea level, it is crucial to construct longer temporal records, reaching back to the Little Ice Age (LIA) or beyond. The primary objectives of this project are to develop procedures for mapping glacial trimlines, marking maximum glacier extent during the LIA, and terminal moraines indicating earlier advanced terminus positions, in central west Greenland using multispectral ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. The motivation for using satellite imagery for mapping glacial-geological features is the greater spatial coverage that can be achieved, as opposed to the traditional method of field mapping in restricted areas. ASTER imagery provides spectral bands spanning from the visible to the thermal infrared bands, including two stereo bands, enabling us to map the spectral properties of the Earth's surface as well as to obtain surface topography. This poster presents examples of mapping the 3D shapes of glacial geomorphological features using supervised classification, visual interpretation and advanced pattern recognition methods, and results of the volume change computation and interpretation, focusing on the Jakobshavn drainage basin. For trimline mapping, a Digital Elevation Model (DEM) was generated from the stereo bands of the same data set, followed by orthorectification using Ground Control Points (GCPs) and checkpoints extracted from stereo aerial photographs and digital maps. Surface reflectance was estimated from the raw DN values by applying the Empirical Line Correction model for atmospheric effects. Maximum likelihood classification, in supervised mode, was applied to distinguish different land cover types. Classification of the ASTER image with nine non-thermal bands provides a good discrimination between the exposed fresh rock surfaces, moraines of

  13. Semi-automated based ground-truthing GUI for airborne imagery

    NASA Astrophysics Data System (ADS)

    Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan

    2005-06-01

    Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.

  14. Optimal design of neural networks for land-cover classification from multispectral imagery

    NASA Astrophysics Data System (ADS)

    Silvan-Cardenas, Jose L.

    2004-02-01

    It has long been shown the effectiveness of artificial neural networks to solve highly non-linear problems such as land-cover classification based on multispectral imagery. However, due to the large amount of data that is processed within this kind of applications, it is desirable to design networks with the lowest number of neurons that are capable to separate all of the given classes. At present, there are several methods intended to determine this optimal network. Most of them involve adjoining or pruning hidden neurons followed by further training in iterative fashion, which is generally a very slow process. As an alternative, the approach described in this paper is based on the computation of centroids of relevant clusters for each class samples through the well known clustering method ISODATA. A proper tessellation of the ISODATA centroids allows first the determination of the minimum number of neurons in the first hidden layer that are required to effectively separate all of the classes; and secondly, to compute weight and bias parameters for such neurons. Then, the minimum network required to perform the logic function that combines the halfspaces generated by the first layer into class-discriminant surfaces is determined via a logic function reduction method. This approach is much faster than that of current methods because it allows to determine the optimum network size and compute weight and bias parameters without further iterative adjustments. The procedure was tested with landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. Results indicated that (1) the network exhibits good generalization behavior and (2) classification accuracies do not depend on the class boundary complexity but only on the class overlapping extent.

  15. Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

    NASA Astrophysics Data System (ADS)

    Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

    2005-10-01

    Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

  16. Processing Of Multispectral Data For Identification Of Rocks

    NASA Technical Reports Server (NTRS)

    Evans, Diane L.

    1990-01-01

    Linear discriminant analysis and supervised classification evaluated. Report discusses processing of multispectral remote-sensing imagery to identify kinds of sedimentary rocks by spectral signatures in geological and geographical contexts. Raw image data are spectra of picture elements in images of seven sedimentary rock units exposed on margin of Wind River Basin in Wyoming. Data acquired by Landsat Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and NASA/JPL airborne synthetic-aperture radar (SAR).

  17. Use of remote sensing techniques for geological hazard surveys in vegetated urban regions. [multispectral imagery for lithological mapping

    NASA Technical Reports Server (NTRS)

    Stow, S. H.; Price, R. C.; Hoehner, F.; Wielchowsky, C.

    1976-01-01

    The feasibility of using aerial photography for lithologic differentiation in a heavily vegetated region is investigated using multispectral imagery obtained from LANDSAT satellite and aircraft-borne photography. Delineating and mapping of localized vegetal zones can be accomplished by the use of remote sensing because a difference in morphology and physiology results in different natural reflectances or signatures. An investigation was made to show that these local plant zones are affected by altitude, topography, weathering, and gullying; but are controlled by lithology. Therefore, maps outlining local plant zones were used as a basis for lithologic map construction.

  18. Stress indicators based on airborne thermal imagery for field phenotyping a heterogeneous tree population for response to water constraints

    PubMed Central

    Virlet, Nicolas; Lebourgeois, Valentine; Martinez, Sébastien; Costes, Evelyne; Labbé, Sylvain; Regnard, Jean-Luc

    2014-01-01

    As field phenotyping of plant response to water constraints constitutes a bottleneck for breeding programmes, airborne thermal imagery can contribute to assessing the water status of a wide range of individuals simultaneously. However, the presence of mixed soil–plant pixels in heterogeneous plant cover complicates the interpretation of canopy temperature. Moran’s Water Deficit Index (WDI = 1–ETact/ETmax), which was designed to overcome this difficulty, was compared with surface minus air temperature (T s–T a) as a water stress indicator. As parameterization of the theoretical equations for WDI computation is difficult, particularly when applied to genotypes with large architectural variability, a simplified procedure based on quantile regression was proposed to delineate the Vegetation Index–Temperature (VIT) scatterplot. The sensitivity of WDI to variations in wet and dry references was assessed by applying more or less stringent quantile levels. The different stress indicators tested on a series of airborne multispectral images (RGB, near-infrared, and thermal infrared) of a population of 122 apple hybrids, under two irrigation regimes, significantly discriminated the tree water statuses. For each acquisition date, the statistical method efficiently delineated the VIT scatterplot, while the limits obtained using the theoretical approach overlapped it, leading to inconsistent WDI values. Once water constraint was established, the different stress indicators were linearly correlated to the stem water potential among a tree subset. T s–T a showed a strong sensitivity to evaporative demand, which limited its relevancy for temporal comparisons. Finally, the statistical approach of WDI appeared the most suitable for high-throughput phenotyping. PMID:25080086

  19. Stress indicators based on airborne thermal imagery for field phenotyping a heterogeneous tree population for response to water constraints.

    PubMed

    Virlet, Nicolas; Lebourgeois, Valentine; Martinez, Sébastien; Costes, Evelyne; Labbé, Sylvain; Regnard, Jean-Luc

    2014-10-01

    As field phenotyping of plant response to water constraints constitutes a bottleneck for breeding programmes, airborne thermal imagery can contribute to assessing the water status of a wide range of individuals simultaneously. However, the presence of mixed soil-plant pixels in heterogeneous plant cover complicates the interpretation of canopy temperature. Moran's Water Deficit Index (WDI = 1-ETact/ETmax), which was designed to overcome this difficulty, was compared with surface minus air temperature (T s-T a) as a water stress indicator. As parameterization of the theoretical equations for WDI computation is difficult, particularly when applied to genotypes with large architectural variability, a simplified procedure based on quantile regression was proposed to delineate the Vegetation Index-Temperature (VIT) scatterplot. The sensitivity of WDI to variations in wet and dry references was assessed by applying more or less stringent quantile levels. The different stress indicators tested on a series of airborne multispectral images (RGB, near-infrared, and thermal infrared) of a population of 122 apple hybrids, under two irrigation regimes, significantly discriminated the tree water statuses. For each acquisition date, the statistical method efficiently delineated the VIT scatterplot, while the limits obtained using the theoretical approach overlapped it, leading to inconsistent WDI values. Once water constraint was established, the different stress indicators were linearly correlated to the stem water potential among a tree subset. T s-T a showed a strong sensitivity to evaporative demand, which limited its relevancy for temporal comparisons. Finally, the statistical approach of WDI appeared the most suitable for high-throughput phenotyping. PMID:25080086

  20. Biooptical variability in the Greenland Sea observed with the Multispectral Airborne Radiometer System (MARS)

    NASA Technical Reports Server (NTRS)

    Mueller, James L.; Trees, Charles C.

    1989-01-01

    A site-specific ocean color remote sensing algorithm was developed and used to convert Multispectral Airborne Radiometer System (MARS) spectral radiance measurements to chlorophyll-a concentration profiles along aircraft tracklines in the Greenland Sea. The analysis is described and the results given in graphical or tabular form. Section 2 describes the salient characteristics and history of development of the MARS instrument. Section 3 describes the analyses of MARS flight segments over consolidated sea ice, resulting in a set of altitude dependent ratios used (over water) to estimate radiance reflected by the surface and atmosphere from total radiance measured. Section 4 presents optically weighted pigment concentrations calculated from profile data, and spectral reflectances measured in situ from the top meter of the water column; this data was analyzed to develop an algorithm relating chlorophyll-a concentrations to the ratio of radiance reflectances at 441 and 550 nm (with a selection of coefficients dependent upon whether significant gelvin presence is implied by a low ratio of reflectances at 410 and 550 nm). Section 5 describes the scaling adjustments which were derived to reconcile the MARS upwelled radiance ratios at 410:550 nm and 441:550 nm to in situ reflectance ratios measured simultaneously on the surface. Section 6 graphically presents the locations of MARS data tracklines and positions of the surface monitoring R/V. Section 7 presents stick-plots of MARS tracklines selected to illustrate two-dimensional spatial variability within the box covered by each day's flight. Section 8 presents curves of chlorophyll-a concentration profiles derived from MARS data along survey tracklines. Significant results are summarized in Section 1.

  1. A new method of building footprints detection using airborne laser scanning data and multispectral image

    NASA Astrophysics Data System (ADS)

    Luo, Yiping; Jiang, Ting; Gao, Shengli; Wang, Xin

    2010-10-01

    It presents a new approach for detecting building footprints in a combination of registered aerial image with multispectral bands and airborne laser scanning data synchronously obtained by Leica-Geosystems ALS40 and Applanix DACS-301 on the same platform. A two-step method for building detection was presented consisting of selecting 'building' candidate points and then classifying candidate points. A digital surface model(DSM) derived from last pulse laser scanning data was first filtered and the laser points were classified into classes 'ground' and 'building or tree' based on mathematic morphological filter. Then, 'ground' points were resample into digital elevation model(DEM), and a Normalized DSM(nDSM) was generated from DEM and DSM. The candidate points were selected from 'building or tree' points by height value and area threshold in nDSM. The candidate points were further classified into building points and tree points by using the support vector machines(SVM) classification method. Two classification tests were carried out using features only from laser scanning data and associated features from two input data sources. The features included height, height finite difference, RGB bands value, and so on. The RGB value of points was acquired by matching laser scanning data and image using collinear equation. The features of training points were presented as input data for SVM classification method, and cross validation was used to select best classification parameters. The determinant function could be constructed by the classification parameters and the class of candidate points was determined by determinant function. The result showed that associated features from two input data sources were superior to features only from laser scanning data. The accuracy of more than 90% was achieved for buildings in first kind of features.

  2. Water turbidity estimation from airborne hyperspectral imagery and full waveform bathymetric LiDAR

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Glennie, C. L.; Fernandez-Diaz, J. C.

    2015-12-01

    The spatial and temporal variations in water turbidity are of great interest for the study of fluvial and coastal environments; and for predicting the performance of remote sensing systems that are used to map these. Conventional water turbidity estimates from remote sensing observations have normally been derived using near infrared reflectance. We have investigated the potential of determining water turbidity from additional remote sensing sources, namely airborne hyperspectral imagery and single wavelength bathymetric LiDAR (Light Detection and Ranging). The confluence area of the Blue and Colorado River, CO was utilized as a study area to investigate the capabilities of both airborne bathymetric LiDAR and hyperspectral imagery for water turbidity estimation. Discrete and full waveform bathymetric data were collected using Optech's Gemini (1064 nm) and Aquarius (532 nm) LiDAR sensors. Hyperspectral imagery (1.2 m pixel resolution and 72 spectral bands) was acquired using an ITRES CASI-1500 imaging system. As an independent reference, measurements of turbidity were collected concurrent with the airborne remote sensing acquisitions, using a WET Labs EcoTriplet deployed from a kayak and turbidity was then derived from the measured backscatter. The bathymetric full waveform dataset contains a discretized sample of the full backscatter of water column and benthic layer. Therefore, the full waveform records encapsulate the water column characteristics of turbidity. A nonparametric support vector regression method is utilized to estimate water turbidity from both hyperspectral imagery and voxelized full waveform LiDAR returns, both individually and as a fused dataset. Results of all the evaluations will be presented, showing an initial turbidity prediction accuracy of approximately 1.0 NTU. We will also discuss our future strategy for enhanced fusion of the full waveform LiDAR and hyperspectral imagery for improved turbidity estimation.

  3. Multispectral microwave imaging radar for remote sensing applications

    NASA Technical Reports Server (NTRS)

    Larson, R. W.; Rawson, R.; Ausherman, D.; Bryan, L.; Porcello, L.

    1974-01-01

    A multispectral airborne microwave radar imaging system, capable of obtaining four images simultaneously is described. The system has been successfully demonstrated in several experiments and one example of results obtained, fresh water ice, is given. Consideration of the digitization of the imagery is given and an image digitizing system described briefly. Preliminary results of digitization experiments are included.

  4. Assessing canopy PRI from airborne imagery to map water stress in maize

    NASA Astrophysics Data System (ADS)

    Rossini, M.; Fava, F.; Cogliati, S.; Meroni, M.; Marchesi, A.; Panigada, C.; Giardino, C.; Busetto, L.; Migliavacca, M.; Amaducci, S.; Colombo, R.

    2013-12-01

    This paper presents a method for mapping water stress in a maize field using hyperspectral remote sensing imagery. An airborne survey using AISA (Specim, Finland) was performed in July 2008 over an experimental farm in Italy. Hyperspectral data were acquired over a maize field with three different irrigation regimes. An intensive field campaign was also conducted concurrently with imagery acquisition to measure relative leaf water content (RWC), active chlorophyll fluorescence (ΔF/Fm‧), leaf temperature (Tl) and Leaf Area Index (LAI). The analysis of the field data showed that at the time of the airborne overpass the maize plots with irrigation deficits were experiencing a moderate water stress, affecting the plant physiological status (ΔF/Fm‧, difference between Tl and air temperature (Tair), and RWC) but not the canopy structure (LAI). Among the different Vegetation Indices (VIs) computed from the airborne imagery the Photochemical Reflectance Index computed using the reflectance at 570 nm as the reference band (PRI570) showed the strongest relationships with ΔF/Fm‧ (r2 = 0.76), Tl - Tair (r2 = 0.82) and RWC (r2 = 0.64) and the red-edge Chlorophyll Index (CIred-edge) with LAI (r2 = 0.64). Thus PRI has been proven to be related to water stress at early stages, before structural changes occurred.

  5. Feature Line Based Building Detection and Reconstruction from Oblique Airborne Imagery

    NASA Astrophysics Data System (ADS)

    Zhu, Q.; Jiang, W.; Zhang, J.

    2015-05-01

    In this paper, a feature line based method for building detection and reconstruction from oblique airborne imagery is presented. With the development of Multi-View Stereo technology, increasing photogrammetric softwares are provided to generate textured meshes from oblique airborne imagery. However, errors in image matching and mesh segmentation lead to the low geometrical accuracy of building models, especially at building boundaries. To simplify massive meshes and construct accurate 3D building models, we integrate multi-view images and meshes by using feature lines, in which contour lines are used for building detection and straight skeleton for building reconstruction. Firstly, through the contour clustering method, buildings can be quickly and robustly detected from meshes. Then, a feature preserving mesh segmentation method is applied to accurately extract 3D straight skeleton from meshes. Finally, straight feature lines derived from multi-view images are used to rectify inaccurate parts of 3D straight skeleton of buildings. Therefore, low quality model can be refined by the accuracy improvement of mesh feature lines and rectification with feature lines of multi-view images. The test dataset in Zürich is provided by ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. The experiments reveal that the proposed method can obtain convincing and high quality 3D building models from oblique airborne imagery.

  6. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Fuell, Kevin K.; Knaff, John; Lee, Thomas

    2012-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross

  7. Use of airborne thermal imagery to detect and monitor inshore oil spill residues during darkness hours

    SciTech Connect

    Grierson, I.T.

    1998-11-01

    Trials were conducted using an airborne video system operating in the visible, near-infrared, and thermal wavelengths to detect two known oil spill releases during darkness at a distance of 10 nautical miles from the shore in St. Vincent`s Gulf, South Australia. The oil spills consisted of two 20-liter samples released at 2-h intervals, one sample consisted of paraffinic neutral material and the other of automotive diesel oil. A tracking buoy was sent overboard in conjunction with the release of sample 1, and its movement monitored by satellite relay. Both oil residues were overflown by a light aircraft equipped with thermal, visible, and infrared imagers at a period of approximately 1 h after the release of the second oil residue. Trajectories of the oil residue releases were also modeled and the results compared to those obtained by the airborne video and the tracking buoy. Airborne imagery in the thermal wavelengths successfully located and mapped both oil residue samples during nighttime conditions. Results from the trial suggest that the most advantageous technique would be the combined use of the tracking beacon to obtain an approximate location of the oil spill and the airborne imagery to ascertain its extent and characteristics.

  8. Testing different classification methods in airborne hyperspectral imagery processing.

    PubMed

    Kozoderov, Vladimir V; Dmitriev, Egor V

    2016-05-16

    To enhance the efficiency of machine-learning algorithms of optical remote sensing imagery processing, optimization techniques are evolved of the land surface objects pattern recognition. Different methods of supervised classification are considered for these purposes, including the metrical classifier operating with Euclidean distance between any points of the multi-dimensional feature space given by registered spectra, the K-nearest neighbors classifier based on a majority vote for neighboring pixels of the recognized objects, the Bayesian classifier of statistical decision making, the Support Vector Machine classifier dealing with stable solutions of the mini-max optimization problem and their different modifications. We describe the related techniques applied for selected test regions to compare the listed classifiers. PMID:27409968

  9. Multisensor airborne imagery collection and processing onboard small unmanned systems

    NASA Astrophysics Data System (ADS)

    Linne von Berg, Dale; Anderson, Scott A.; Bird, Alan; Holt, Niel; Kruer, Melvin; Walls, Thomas J.; Wilson, Michael L.

    2010-04-01

    FEATHAR (Fusion, Exploitation, Algorithms, and Targeting for High-Altitude Reconnaissance) is an ONR funded effort to develop and test new tactical sensor systems specifically designed for small manned and unmanned platforms (payload weight < 50 lbs). This program is being directed and executed by the Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL). FEATHAR has developed and integrated EyePod, a combined long-wave infrared (LWIR) and visible to near infrared (VNIR) optical survey & inspection system, with NuSAR, a combined dual band synthetic aperture radar (SAR) system. These sensors are being tested in conjunction with other ground and airborne sensor systems to demonstrate intelligent real-time cross-sensor cueing and in-air data fusion. Results from test flights of the EyePod and NuSAR sensors will be presented.

  10. A Synergistic Approach to Atmospheric Compensation of Neon's Airborne Hyperspectral Imagery Utilizing an Airborne Solar Spectral Irradiance Radiometer

    NASA Astrophysics Data System (ADS)

    Wright, L.; Karpowicz, B. M.; Kindel, B. C.; Schmidt, S.; Leisso, N.; Kampe, T. U.; Pilewskie, P.

    2014-12-01

    A wide variety of critical information regarding bioclimate, biodiversity, and biogeochemistry is embedded in airborne hyperspectral imagery. Most, if not all of the primary signal relies upon first deriving the surface reflectance of land cover and vegetation from measured hyperspectral radiance. This places stringent requirements on terrain, and atmospheric compensation algorithms to accurately derive surface reflectance properties. An observatory designed to measure bioclimate, biodiversity, and biogeochemistry variables from surface reflectance must take great care in developing an approach which chooses algorithms with the highest accuracy, along with providing those algorithms with data necessary to describe the physical mechanisms that affect the measured at sensor radiance. The Airborne Observation Platform (AOP) part of the National Ecological Observatory Network (NEON) is developing such an approach. NEON is a continental-scale ecological observation platform designed to collect and disseminate data to enable the understanding and forecasting of the impacts of climate change, land use change, and invasive species on ecology. The instrumentation package used by the AOP includes a visible and shortwave infrared hyperspectral imager, waveform LiDAR, and high resolution (RGB) digital camera. In addition to airborne measurements, ground-based CIMEL sun photometers will be used to help characterize atmospheric aerosol loading, and ground validation measurements with field spectrometers will be made at select NEON sites. While the core instrumentation package provides critical information to derive surface reflectance of land surfaces and vegetation, the addition of a Solar Spectral Irradiance Radiometer (SSIR) is being investigated as an additional source of data to help identify and characterize atmospheric aerosol, and cloud contributions contributions to the radiance measured by the hyperspectral imager. The addition of the SSIR provides the opportunity to

  11. Integration of airborne optical and thermal imagery for archaeological subsurface structures detection: the Arpi case study (Italy)

    NASA Astrophysics Data System (ADS)

    Bassani, C.; Cavalli, R. M.; Fasulli, L.; Palombo, A.; Pascucci, S.; Santini, F.; Pignatti, S.

    2009-04-01

    The application of Remote Sensing data for detecting subsurface structures is becoming a remarkable tool for the archaeological observations to be combined with the near surface geophysics [1, 2]. As matter of fact, different satellite and airborne sensors have been used for archaeological applications, such as the identification of spectral anomalies (i.e. marks) related to the buried remnants within archaeological sites, and the management and protection of archaeological sites [3, 5]. The dominant factors that affect the spectral detectability of marks related to manmade archaeological structures are: (1) the spectral contrast between the target and background materials, (2) the proportion of the target on the surface (relative to the background), (3) the imaging system characteristics being used (i.e. bands, instrument noise and pixel size), and (4) the conditions under which the surface is being imaged (i.e. illumination and atmospheric conditions) [4]. In this context, just few airborne hyperspectral sensors were applied for cultural heritage studies, among them the AVIRIS (Airborne Visible/Infrared Imaging Spectrometer), the CASI (Compact Airborne Spectrographic Imager), the HyMAP (Hyperspectral MAPping) and the MIVIS (Multispectral Infrared and Visible Imaging Spectrometer). Therefore, the application of high spatial/spectral resolution imagery arise the question on which is the trade off between high spectral and spatial resolution imagery for archaeological applications and which spectral region is optimal for the detection of subsurface structures. This paper points out the most suitable spectral information useful to evaluate the image capability in terms of spectral anomaly detection of subsurface archaeological structures in different land cover contexts. In this study, we assess the capability of MIVIS and CASI reflectances and of ATM and MIVIS emissivities (Table 1) for subsurface archaeological prospection in different sites of the Arpi

  12. Edge-Based Registration for Airborne Imagery and LIDAR Data

    NASA Astrophysics Data System (ADS)

    Chen, L. C.; Lo, C. Y.

    2012-07-01

    Aerial imagery and LIDAR points are two important data sources for building reconstruction in a geospatial area. Aerial imagery implies building contours with planimetric features; LIDAR data explicitly represent building geometries using three-dimensional discrete point clouds. Data integration may take advantage of merits from two data sources in building reconstruction and change detection. However, heterogeneous data may contain a relative displacement because of different sensors and the capture time. To reduce this displacement, data registration should be an essential step. Therefore, this investigation proposes an edge-based approach to register these two data sets in three parts: (1) data preprocessing; (2) feature detection; and (3) data registration. The first step rasterizes laser point clouds into a pseudo-grid digital surface model (PDSM), which describes the relief with the original elevation information. The second step implements topological analyses to detect image edges and three-dimensional structure lines from the aerial image and PDSM. These detected features provide the initial positions of building shapes for registration. The third part registers these two data sets in Hough space to compensate for the displacement. Because each building may have prominent geometric structures, the proposed scheme transforms these two groups of edges, and estimates the correspondence by the Hough distribution. The following procedure then iteratively compares two groups of Hough patterns, which are from an aerial image and LIDAR data. This iterative procedure stops when the displacement is within a threshold. The test area is located in Taipei City, Taiwan. DMC system captured the aerial image with 18-cm spatial resolution. The LIDAR data were scanned with a 10-point density per square meter using the Leica ALS50 system. This study proposed a 50 cm spatial resolution of PDSM, which is slightly larger than the point spacing. The experiment selected two

  13. Airborne target identification from low-crossrange-resolution ISAR imagery

    NASA Astrophysics Data System (ADS)

    Hauss, Bruce I.; Agravante, Hiroshi H.; Eberhard, C. D.; Luebkemann, Karen M.; Samec, Thomas K.; Wagner, Thomas M.; Rihaczek, August W.; Hershkowitz, Stephen J.; Mitchell, R. L.; Perahia, E.; Arnush, Donald; Lakshmanan, Sridhar

    1996-11-01

    In a target-rich battlefield environment, a shipboard or an airborne radar must maintain situational awareness while tracking and identifying targets. Often the opportunity to dwell on each target long enough for confident identification via high resolution SAR/ISAR imaging will not exist, especially for those engagement geometries where the relative translational motion of the aircraft does not result in large rotation rates. Inadvertent aircraft tactical dither often generates enough target rotational during a brief imaging interval to allow the formation of an ISAR image with low crossrange resolution. We have developed an automated identification procedure that utilizes this resolution, along with high range resolution, to produce confident target identification. The advanced signal processing algorithms employed extract feature measurements from the complex ISAR image. including accurate measurements of the two-dimensional positions, amplitudes and range extents of the dominant target scatterers. A deformable template matching procedure is used to correlate these 'measured features' with those predicted for each candidate aircraft in a database generated from readily available diagrams, photographs and CAD models. After obtaining the optimal fit between the measured and predicted features for each candidate aircraft, the 'most likely' candidate is selected using a conventional Bayes classifier.

  14. Reconciling In Situ Foliar Nitrogen and Vegetation Structure Measurements with Airborne Imagery Across Ecosystems

    NASA Astrophysics Data System (ADS)

    Flagg, C.

    2015-12-01

    Over the next 30 years the National Ecological Observatory Network (NEON) will monitor environmental and ecological change throughout North America. NEON will provide a suite of standardized data from several ecological topics of interest, including net primary productivity and nutrient cycling, from 60+ sites across 20 eco-climatic domains when fully operational in 2017. The breadth of sampling includes ground-based measurements of foliar nitrogen and vegetation structure, ground-based spectroscopy, airborne LIDAR, and airborne hyperspectral surveys occurring within narrow overlapping time intervals once every five years. While many advancements have been made in linking and scaling in situ data with airborne imagery, establishing these relationships across dozens of highly variable sites poses significant challenges to understanding continental-wide processes. Here we study the relationship between foliar nitrogen content and airborne hyperspectral imagery at different study sites. NEON collected foliar samples from three sites in 2014 as part of a prototype study: Ordway Swisher Biological Station (pine-oak savannah, with active fire management), Jones Ecological Research Center (pine-oak savannah), and San Joaquin Experimental Range (grass-pine oak woodland). Leaf samples and canopy heights of dominant and co-dominant species were collected from trees located within 40 x 40 meter sampling plots within two weeks of aerial LIDAR and hyperspectral surveys. Foliar canopy samples were analyzed for leaf mass per area (LMA), stable isotopes of C and N, C/N content. We also examine agreement and uncertainty between ground based canopy height and airborne LIDAR derived digital surface models (DSM) for each site. Site-scale maps of canopy nitrogen and canopy height will also be presented.

  15. Airborne Multispectral LIDAR Data for Land-Cover Classification and Land/water Mapping Using Different Spectral Indexes

    NASA Astrophysics Data System (ADS)

    Morsy, S.; Shaker, A.; El-Rabbany, A.; LaRocque, P. E.

    2016-06-01

    Airborne Light Detection And Ranging (LiDAR) data is widely used in remote sensing applications, such as topographic and landwater mapping. Recently, airborne multispectral LiDAR sensors, which acquire data at different wavelengths, are available, thus allows recording a diversity of intensity values from different land features. In this study, three normalized difference feature indexes (NDFI), for vegetation, water, and built-up area mapping, were evaluated. The NDFIs namely, NDFIG-NIR, NDFIG-MIR, and NDFINIR-MIR were calculated using data collected at three wavelengths; green: 532 nm, near-infrared (NIR): 1064 nm, and mid-infrared (MIR): 1550 nm by the world's first airborne multispectral LiDAR sensor "Optech Titan". The Jenks natural breaks optimization method was used to determine the threshold values for each NDFI, in order to cluster the 3D point data into two classes (water and land or vegetation and built-up area). Two sites at Scarborough, Ontario, Canada were tested to evaluate the performance of the NDFIs for land-water, vegetation, and built-up area mapping. The use of the three NDFIs succeeded to discriminate vegetation from built-up areas with an overall accuracy of 92.51%. Based on the classification results, it is suggested to use NDFIG-MIR and NDFINIR-MIR for vegetation and built-up areas extraction, respectively. The clustering results show that the direct use of NDFIs for land-water mapping has low performance. Therefore, the clustered classes, based on the NDFIs, are constrained by the recorded number of returns from different wavelengths, thus the overall accuracy is improved to 96.98%.

  16. Measurement of the earth resources technology satellite /ERTS-1/ multi-spectral scanner OTF from operational imagery. [Optical Transfer Function

    NASA Technical Reports Server (NTRS)

    Schowengerdt, R. A.; Antos, R. L.; Slater, P. N.

    1974-01-01

    The optical transfer function (OTF) of some typical ERTS-1 multispectral imagery was obtained by comparison of matched sets of aircraft underflight and ERTS photographic and digital images. One-dimensional OTF analysis consisted in obtaining U-2 and ERTS microdensitometer scans followed by density to transmission conversion, microdensitometer aperture correction, exposure calibration, scan correlation scale optimization, OTF calculation, obtaining a form weighted average of the OTFs, transformation of the OTFs back to the spatial domain (giving the line spread function or LSF), and application of a window function to the LSF resulting in a smoothed OTF. Date-to-date comparison of ERTS OTFs showed a drop in quality on April 4, 1973, compared with January 4, 1973.

  17. A geologic analysis of the Side-Looking Airborne Radar imagery of southern New England

    USGS Publications Warehouse

    Banks, Paul T.

    1975-01-01

    Analysis of the side looking airborn radar imagery of Massachusetts, Connecticut and Rhode Island indicates that radar shows the topography in great detail. Since bedrock geologic features are frequently expressed in the topography the radar lends itself to geologic interpretation. The radar was studied by comparisons with field mapped geologic data first at a scale of approximately 1:125,000 and then at a scale of 1:500,000. The larger scale comparison revealed that faults, minor faults, joint sets, bedding and foliation attitudes, lithology and lithologic contacts all have a topographic expression interpretable on the imagery. Surficial geologic features were far less visible on the imagery over most of the area studied. The smaller scale comparisons revealed a pervasive, near orthogonal fracture set cutting all types and ages of rock and trending roughly N40?E and N30?W. In certain places the strike of bedding and foliation attitudes and some lithologic Contacts were visible in addition to the fractures. Fracturing in southern New England is apparently far more important than has been previously recognized. This new information, together with the visibility of many bedding and foliation attitudes and lithologic contacts, indicates the importance of radar imagery in improving the geologic interpretation of an area.

  18. Detection algorithm for cracks on the surface of tomatoes using Multispectral Vis/NIR Reflectance Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Tomatoes, an important agricultural product in fresh-cut markets, are sometimes a source of foodborne illness, mainly Salmonella spp. Growth cracks on tomatoes can be a pathway for bacteria, so its detection prior to consumption is important for public health. In this study, multispectral Visible/Ne...

  19. Deriving a flow coherent surface for runoff simulation in urban areas using light detection and ranging data and multispectral imagery

    NASA Astrophysics Data System (ADS)

    de Almeida Pereira, Gabriel Henrique; Centeno, Jorge Antonio Silva

    2014-01-01

    This work addresses the topic of flow direction and flow accumulation simulations in urban areas over digital surface models derived from light detection and ranging (LiDAR) data and multispectral high-resolution imagery. LiDAR data are very dense point clouds that include many objects that, in a 2 1/2-dimensional model, may become false obstacles for runoff, such as power lines or treetops. The presence of such obstacles is a problem for the flow paths simulation, especially in urban areas. We describe a methodology to produce a surface model more suitable for runoff modeling, by filtering objects that are above the surface and should not influence the flow paths. In a first step, thin obstacles are suppressed by applying mathematical morphology to a raster surface model. In a second step, satellite multispectral data and LiDAR data are classified using a support vector machine to identify trees, which are also removed from the digital model, and produce a more coherent surface model for runoff simulation. To simulate and evaluate the results, the flow-routing algorithm Dinfinity was used. The results show that the filtering is necessary to achieve a better characterization of runoff paths and allows identifying places where runoff may accumulate, causing floods or other problems.

  20. Extraction, modelling, and use of linear features for restitution of airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Lee, Changno; Bethel, James S.

    This paper presents an approach for the restitution of airborne hyperspectral imagery with linear features. The approach consisted of semi-automatic line extraction and mathematical modelling of the linear features. First, the line was approximately determined manually and refined using dynamic programming. The extracted lines could then be used as control data with the ground information of the lines, or as constraints with simple assumption for the ground information of the line. The experimental results are presented numerically in tables of RMS residuals of check points as well as visually in ortho-rectified images.

  1. GIS Meets Airborne MSS: Geospatial Applications of High-Resolution Multispectral Data

    SciTech Connect

    Albert Guber

    1999-07-27

    Bechtel Nevada operates and flies Daedalus multispectral scanners for funded project tasks at the Department of Energy's Remote Sensing Laboratory. Historically, processing and analysis of multispectral data has afforded scientists the opportunity to see natural phenomena not visible to the naked eye. However, only recently has a system, more specifically a Geometric Correction System, existed to automatically geo-reference these data directly into a Geographic Information (GIS) database. Now, analyses, performed previously in a nongeospatial environment, are integrated directly into an Arc/Info GIS. This technology is of direct benefit to environmental and emergency response applications.

  2. Use and Assessment of Multi-Spectral Satellite Imagery in NWS Operational Forecasting Environments

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew; Fuell, Kevin; Stano, Geoffrey; McGrath, Kevin; Schultz, Lori; LeRoy, Anita

    2015-01-01

    NOAA's Satellite Proving Grounds have established partnerships between product developers and NWS WFOs for the evaluation of new capabilities from the GOES-R and JPSS satellite systems. SPoRT has partnered with various WFOs to evaluate multispectral (RGB) products from MODIS, VIIRS and Himawari/AHI to prepare for GOES-R/ABI. Assisted through partnerships with GINA, UW/CIMSS, NOAA, and NASA Direct Broadcast capabilities.

  3. TACMSI: a novel multi-look multispectral imager for maritime mine detection

    NASA Astrophysics Data System (ADS)

    Leonard, Carrie L.; Chan, Chong Wai; Cottis, Tamara; DeWeert, Michael; Dichner, Michael; Farm, Brian; Kokubun, Dan; Louchard, Eric; Noguchi, Reid; Topping, Miles; Wong, Timothy; Yoon, Dugan

    2008-04-01

    Airborne EO imagery, including wideband, hyperspectral, and multispectral modalities, has greatly enhanced the ability of the ISR community to detect and classify various targets of interest from long standoff distances and with large area coverage rates. The surf zone is a dynamic environment that presents physical and operational challenges to effective remote sensing with optical systems. In response to these challenges, BAE Systems has developed the Tactical Multi-spectral (TACMSI) system. The system includes a VNIR six-band multispectral sensor and all other hardware that is used to acquire, store and process imagery, navigation, and supporting metadata on the airborne platform. In conjunction with the hardware, BAE Systems has innovative data processing methods that exploit the inherent capabilities of multi-look framing imagery to essentially remove the overlying clutter or obscuration to enable EO visualization of the objects of interest.

  4. Detection of a buoyant coastal wastewater discharge using airborne hyperspectral and infrared imagery

    NASA Astrophysics Data System (ADS)

    Marmorino, George O.; Smith, Geoffrey B.; Miller, W. D.; Bowles, Jeffrey H.

    2010-01-01

    Municipal wastewater discharged into the ocean through a submerged pipe, or outfall, can rise buoyantly to the sea surface, resulting in a near-field mixing zone and, in the presence of an ambient ocean current, an extended surface plume. In this paper, data from a CASI (Compact Airborne Spectrographic Imager) and an airborne infrared (IR) camera are shown to detect a municipal wastewater discharge off the southeast coast of Florida, U.S.A., through its elevated levels of chromophoric dissolved organic matter plus detrital material (CDOM) and cooler sea surface temperatures. CDOM levels within a ~15-m-diameter surface 'boil' are found to be about twice those in the ambient shelf water, and surface temperatures near the boil are lower by ~0.4°C, comparable to the vertical temperature difference across the ambient water column. The CASI and IR imagery show a nearly identically shaped buoyant plume, consistent with a fully surfacing discharge, but the IR data more accurately delineate the area of most rapid dilution as compared with previous in-situ measurements. The imagery also allows identification of ambient oceanographic processes that affect dispersion and transport in the far field. This includes an alongshore front, which limits offshore dispersion of the discharge, and shoreward-propagating nonlinear internal waves, which may be responsible for an enhanced onshore transport of the discharge.

  5. Active and passive multispectral scanner for earth resources applications: An advanced applications flight experiment

    NASA Technical Reports Server (NTRS)

    Hasell, P. G., Jr.; Peterson, L. M.; Thomson, F. J.; Work, E. A.; Kriegler, F. J.

    1977-01-01

    The development of an experimental airborne multispectral scanner to provide both active (laser illuminated) and passive (solar illuminated) data from a commonly registered surface scene is discussed. The system was constructed according to specifications derived in an initial programs design study. The system was installed in an aircraft and test flown to produce illustrative active and passive multi-spectral imagery. However, data was not collected nor analyzed for any specific application.

  6. An algorithm for the estimation of water temperatures from thermal multispectral airborne remotely sensed data

    NASA Technical Reports Server (NTRS)

    Jaggi, S.; Quattrochi, D.; Baskin, R.

    1992-01-01

    A method for water temperature estimation on the basis of thermal data is presented and tested against NASA's Thermal IR Multispectral Scanner. Using realistic bounds on emissivities, temperature bounds are calculated and refined to estimate a tighter bound on the emissivity of the source. The method is useful only when a realistic set of bounds can be obtained for the emissivities of the data.

  7. GeoEarthScope Airborne LiDAR and Satellite InSAR Imagery

    NASA Astrophysics Data System (ADS)

    Phillips, D. A.; Jackson, M. E.; Meertens, C.

    2008-12-01

    UNAVCO has successfully acquired a significant volume of aerial and satellite geodetic imagery as part of GeoEarthScope, a component of the EarthScope Facility project funded by the National Science Foundation. All GeoEarthScope acquisition activities are now complete. Airborne LiDAR data acquisitions took place in 2007 and 2008 and cover a total area of more than 5000 square kilometers. The primary LiDAR survey regions cover features in Northern California, Southern/Eastern California, the Pacific Northwest, the Intermountain Seismic Belt (including the Wasatch and Teton faults and Yellowstone), and Alaska. We have ordered and archived more than 28,000 scenes (more than 81,000 frames) of synthetic aperture radar (SAR) data suitable for interferometric analyses covering most of the western U.S. and parts of Alaska and Hawaii from several satellite platforms, including ERS-1/2, ENVISAT and RADARSAT. In addition to ordering data from existing archives, we also tasked the ESA ENVISAT satellite to acquire new SAR data in 2007 and 2008. GeoEarthScope activities were led by UNAVCO, guided by the community and conducted in partnership with the USGS and NASA. Processed imagery products, in addition to formats intended for use in standard research software, can also be viewed using general purpose tools such as Google Earth. We present a summary of these vast geodetic imagery datasets, totaling tens of terabytes, which are freely available to the community.

  8. Ortho-Rectification of Narrow Band Multi-Spectral Imagery Assisted by Dslr RGB Imagery Acquired by a Fixed-Wing Uas

    NASA Astrophysics Data System (ADS)

    Rau, J.-Y.; Jhan, J.-P.; Huang, C.-Y.

    2015-08-01

    Miniature Multiple Camera Array (MiniMCA-12) is a frame-based multilens/multispectral sensor composed of 12 lenses with narrow band filters. Due to its small size and light weight, it is suitable to mount on an Unmanned Aerial System (UAS) for acquiring high spectral, spatial and temporal resolution imagery used in various remote sensing applications. However, due to its wavelength range is only 10 nm that results in low image resolution and signal-to-noise ratio which are not suitable for image matching and digital surface model (DSM) generation. In the meantime, the spectral correlation among all 12 bands of MiniMCA images are low, it is difficult to perform tie-point matching and aerial triangulation at the same time. In this study, we thus propose the use of a DSLR camera to assist automatic aerial triangulation of MiniMCA-12 imagery and to produce higher spatial resolution DSM for MiniMCA12 ortho-image generation. Depending on the maximum payload weight of the used UAS, these two kinds of sensors could be collected at the same time or individually. In this study, we adopt a fixed-wing UAS to carry a Canon EOS 5D Mark2 DSLR camera and a MiniMCA-12 multi-spectral camera. For the purpose to perform automatic aerial triangulation between a DSLR camera and the MiniMCA-12, we choose one master band from MiniMCA-12 whose spectral range has overlap with the DSLR camera. However, all lenses of MiniMCA-12 have different perspective centers and viewing angles, the original 12 channels have significant band misregistration effect. Thus, the first issue encountered is to reduce the band misregistration effect. Due to all 12 MiniMCA lenses being frame-based, their spatial offsets are smaller than 15 cm and all images are almost 98% overlapped, we thus propose a modified projective transformation (MPT) method together with two systematic error correction procedures to register all 12 bands of imagery on the same image space. It means that those 12 bands of images acquired at

  9. Fusion of information from optical, thermal, multispectral imagery and geologic/topographic products to detect underground detonations (video). Audio-Visual (Final)

    SciTech Connect

    Not Available

    1992-04-01

    The video documents the results of a Small Business Innovative Research (SBIR-Phase II) project conducted for DARPA focusing on the use of all-source overhead remote sensor imagery for monitoring underground nuclear tests and related activities. The documentation includes: (1) the main unclassified body of the report; (2) a separate ground truth Annex; and (3) a separate classified Annex. Autometric's approach was to investigate the exploitation potential of the various sensors, especially the fusion of products from them in combination with each other and other available collateral data. This approach featured empirical analyses of multisensor/multispectral imagery and collateral data collected before, during, and after an actual underground nuclear test (named 'BEXAR'). Advanced softcopy digital image processing and hardcopy image interpretation techniques were investigated for the research. These included multispectral (Landsat, SPOT), hyperspectral, and subpixel analyses; stereoscopic and monoscopic information extraction; multisensor fusion processes; end-to-end exploitation workstation concept development; and innovative change detection methodologies.

  10. Estimating ground cover of field crops using medium-resolution multispectral satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is useful for estimating plant canopy characteristics, such as leaf area index (LAI) and ground cover (GC). When the source of remote sensing data is medium-resolution satellite imagery, plant canopy characteristics can be estimated for numerous fields within an agricultural region. I...

  11. Estimating ground cover of field crops using medium resolution multispectral satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is useful for estimating plant canopy characteristics, such as leaf area index (LAI) and ground cover (GC). When the source of remote sensing data is medium-resolution satellite imagery, plant canopy characteristics can be estimated for numerous fields within an agricultural region. I...

  12. Applying linear spectral unmixing to airborne hyperspectral imagery for mapping yield variability in grain sorghum and cotton fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study examined linear spectral unmixing techniques for mapping the variation in crop yield for precision agriculture. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery collected from a grain sorghum field and a cotton field. A pair...

  13. Detection of European Corn Borer Infestation in Iowa Corn Plots using Spectral Vegetation Indices Derived from Airborne Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing technology was used to distinguish corn infested with European corn borers, Ostrinia nubilalis, from corn that was not infested. In 2004 and 2005, eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery. Manual inocu...

  14. Shallow sea-floor reflectance and water depth derived by unmixing multispectral imagery

    SciTech Connect

    Bierwirth, P.N.; Lee, T.J.; Burne, R.V. Michigan Environmental Research Inst., Ann Arbor )

    1993-03-01

    A major problem for mapping shallow water zones by the analysis of remotely sensed data is that contrast effects due to water depth obscure and distort the special nature of the substrate. This paper outlines a new method which unmixes the exponential influence of depth in each pixel by employing a mathematical constraint. This leaves a multispectral residual which represents relative substrate reflectance. Input to the process are the raw multispectral data and water attenuation coefficients derived by the co-analysis of known bathymetry and remotely sensed data. Outputs are substrate-reflectance images corresponding to the input bands and a greyscale depth image. The method has been applied in the analysis of Landsat TM data at Hamelin Pool in Shark Bay, Western Australia. Algorithm derived substrate reflectance images for Landsat TM bands 1, 2, and 3 combined in color represent the optimum enhancement for mapping or classifying substrate types. As a result, this color image successfully delineated features, which were obscured in the raw data, such as the distributions of sea-grasses, microbial mats, and sandy area. 19 refs.

  15. A preliminary report of multispectral scanner data from the Cleveland harbor study

    NASA Technical Reports Server (NTRS)

    Shook, D.; Raquet, C.; Svehla, R.; Wachter, D.; Salzman, J.; Coney, T.; Gedney, D.

    1975-01-01

    Imagery obtained from an airborne multispectral scanner is presented. A synoptic view of the entire study area is shown for a number of time periods and for a number of spectral bands. Using several bands, sediment distributions, thermal plumes, and Rhodamine B dye distributions are shown.

  16. [Cross-comparison between ASTER and Landsat-7 ETM+ multispectral imagery].

    PubMed

    Li, Chun-hua; Xu, Han-qiu; Chen, Li-cong

    2010-09-01

    Up to present, no study has been published with respect to the cross-comparison between ASTER and Landsat-7 ETM+ imagery. Therefore, the present paper has implemented the complementary study on the images between these two sensors. The study firstly conducted the sensors characteristics comparison, including orbit characteristic, sensor scanning mode and imagery spectral characteristic. Further comparison was implemented to get the relation equations between corresponding VNIR and SWIR bands of these two sensors based on the apparent reflectance of the three pairs of synchronization images and large common ground regions. The validation has been done to verify the effectiveness of the proposed corresponding bands relation equations and matching coefficients. The result shows that the provided relation equations have high accuracy. PMID:21105431

  17. Mapping cotton root rot infestations over a 10-year interval with airborne multispectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot, caused by the pathogen Phymatotrichopsis omnivora, is a very serious and destructive disease of cotton grown in the southwestern and south central U.S. Accurate information regarding temporal changes of cotton root rot infestations within fields is important for the management and c...

  18. Estimating hourly crop ET using a two-source energy balance model and multispectral airborne imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Efficient water use through improved irrigation scheduling is expected to moderate fast declining groundwater levels and improve sustainability of the Ogallala Aquifer. Thus, an accurate estimation of spatial actual evapotranspiration (ET) is needed for this purpose. Therefore, during 2007, the Bush...

  19. Comparison of airborne multispectral and hyperspectral imagery for mapping cotton root rot

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot, caused by the soilborne fungus, Phymatotrichum omnivorum, is a major cotton disease affecting cotton production in the southwestern and south central U.S. Accurate delineation of root rot infestations is necessary for cost-effective management of the disease. The objective of this s...

  20. Change detection of cotton root rot infection over a 10-year interval using airborne multispectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot is a very serious and destructive disease of cotton grown in the southwestern and south central United States. Accurate information regarding the spatial and temporal infections of the disease within fields is important for effective management and control of the disease. The objecti...

  1. Mapping ET at high resolution in an advective semi-arid environment with airborne multispectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Periodic and accurate estimates of spatially distributed evapotranspiration (ET) are essential for managing water in irrigated regions and in hydrologic modeling. In this study, METRIC (Mapping ET at high Resolution with Internalized Calibration), an energy balance algorithm originally developed for...

  2. Evaluating spectral measures derived from airborne multispectral imagery for detecting cotton root rot

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is one of the most destructive plant diseases occurring throughout the southwestern United States. This disease has plagued the cotton industry for more than 100 years, but effective practices for its control are still lacki...

  3. ET mapping with METRIC algorithm using airborne high resolution multispectral remote sensing imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Routine and accurate estimates of spatially distributed evapotranspiration (ET) are essential for managing water resources particularly in irrigated regions such as the U.S. Southern High Plains. For instance, ET maps would assist in the improvement of the Ogallala Aquifer ground water management. M...

  4. Monitoring cotton root rot progression within a growing season using airborne multispectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot, caused by the fungus Phymatotrichopsis omnivora, is a serious and destructive disease affecting cotton production in the southwestern United States. Accurate delineation of cotton root rot infections is important for cost-effective management of the disease. The objective of this st...

  5. Comparison of airborne multispectral and hyperspectral imagery for mapping cotton root rot

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot caused by the soilborne fungus, Phymatotrichum omnivorum, is a major cotton disease affecting cotton production in the southwestern and south central U.S. Accurate delineation of root rot infestations is necessary for cost-effective management of the disease. The objective of this st...

  6. Use of Airborne Multi-Spectral Imagery in Pest Management Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Scientists and researchers have been developing, integrating, and evaluating multiple strategies and technologies into a systems approach for management of field crop insect pests. Remote sensing along with Global Positioning Systems, Geographic Information Systems, and variable rate technology are...

  7. Road Network Extraction from High Resolution Multispectral Satellite Imagery Based on Object Oriented Techniques

    NASA Astrophysics Data System (ADS)

    Kumar, M.; Singh, R. K.; Raju, P. L. N.; Krishnamurthy, Y. V. N.

    2014-11-01

    High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resolution space imagery. The proposed approach begins with segmentation of the scene with Multi-resolution Object Oriented segmentation. This step focuses on exploiting both spatial and spectral information for the target feature extraction. The road regions are automatically identified using a soft fuzzy classifier based on a set of predefined membership functions. A number of shape descriptors are computed to reduce the misclassifications between road and other spectrally similar objects. The detected road segments are further refined using morphological operations to form final road network, which is then evaluated for its completeness, correctness and quality. The experiments were carried out of fused IKONOS 2 , Quick bird ,Worldview 2 Products with fused resolution's ranging from 0.5m to 1 m. Results indicate that the proposed methodology is effective in extracting accurate road networks from high resolution imagery.

  8. Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm

    NASA Technical Reports Server (NTRS)

    Shapiro, Jerome M.; Martucci, Stephen A.; Czigler, Martin

    1994-01-01

    The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.

  9. An analysis task comparison of uncorrected vs. geo-registered airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sun, Yihang; Kerekes, John

    2015-05-01

    Geo-registration is the task of assigning geospatial coordinates to the pixels of an image and placing them in a geographic coordinate system. However, the process of geo-registration can impair the quality of the image. This paper studies this topic by applying a comparison methodology to uncorrected and geo-registered airborne hyperspectral images obtained from the RIT SHARE 2012 data set. The uncorrected image was analyzed directly as collected by the sensor without being treated, while the geo-registered image was corrected using the nearest neighbor resampling approach. A comparison of performance was done for the analysis tasks of spectral unmixing and subpixel target detection, which can represent a measure of utility. The comparison demonstrates that the geo-registration process can affect the utility of hyperspectral imagery to a limited extent.

  10. Classification of the forest cover of Tver oblast using hyperspectral airborne imagery

    NASA Astrophysics Data System (ADS)

    Dmitriev, E. V.

    2014-12-01

    Recent research efforts have been focused on building a system of hyperspectral aerial sounding of forest vegetation on regional scales. The components of this system are developed using data obtained in the course of measurement campaigns in Tver forestry test sites. Hyperspectral airborne surveys are conducted using a Russian video spectrometer produced by the NPO Lepton company. The technique for recognizing ground-based objects is based on Bayesian classification principles with the feature space optimization. The choice of the most informative spectral channels is based on the step-up method. We propose an approach allowing the choice of channels to be more stable. We compare the classification of timber stands on the basis of hyperspectral imagery with ground-based data to demonstrate the consistency of the system developed.

  11. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    NASA Astrophysics Data System (ADS)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  12. Vehicle tracking in wide area motion imagery from an airborne platform

    NASA Astrophysics Data System (ADS)

    van Eekeren, Adam W. M.; van Huis, Jasper R.; Eendebak, Pieter T.; Baan, Jan

    2015-10-01

    Airborne platforms, such as UAV's, with Wide Area Motion Imagery (WAMI) sensors can cover multiple square kilometers and produce large amounts of video data. Analyzing all data for information need purposes becomes increasingly labor-intensive for an image analyst. Furthermore, the capacity of the datalink in operational areas may be inadequate to transfer all data to the ground station. Automatic detection and tracking of people and vehicles enables to send only the most relevant footage to the ground station and assists the image analysts in effective data searches. In this paper, we propose a method for detecting and tracking vehicles in high-resolution WAMI images from a moving airborne platform. For the vehicle detection we use a cascaded set of classifiers, using an Adaboost training algorithm on Haar features. This detector works on individual images and therefore does not depend on image motion stabilization. For the vehicle tracking we use a local template matching algorithm. This approach has two advantages. In the first place, it does not depend on image motion stabilization and it counters the inaccuracy of the GPS data that is embedded in the video data. In the second place, it can find matches when the vehicle detector would miss a certain detection. This results in long tracks even when the imagery is of low frame-rate. In order to minimize false detections, we also integrate height information from a 3D reconstruction that is created from the same images. By using the locations of buildings and roads, we are able to filter out false detections and increase the performance of the tracker. In this paper we show that the vehicle tracks can also be used to detect more complex events, such as traffic jams and fast moving vehicles. This enables the image analyst to do a faster and more effective search of the data.

  13. Use of High-Resolution Multispectral Imagery to Estimate Chlorophyll and Plant Nitrogen in Oats (Avena sativa)

    NASA Astrophysics Data System (ADS)

    ELarab, M.; Ticlavilca, A. M.; Torres-Rua, A. F.; Maslova, I.; McKee, M.

    2013-12-01

    Precision agriculture requires high spatial resolution in the application of the inputs to agricultural production. This requires that actionable information about crop and field status be acquired at the same high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high-resolution imagery was obtained through the use of a small, unmanned aerial vehicle, called AggieAirTM, that provides spatial resolution as fine as 6 cm. Simultaneously with AggieAir flights, intensive ground sampling was conducted at precisely determined locations for plant chlorophyll, plant nitrogen, and other parameters. This study investigated the spectral signature of a crop of oats (Avena sativa) and formulated machine learning regression models of reflectance response between the multi-spectral bands available from AggieAir (red, green, blue, near infrared, and thermal), plant chlorophyll and plant nitrogen. We tested two, separate relevance vector machines (RVM) and a single multivariate relevance vector machine (MVRVM) to develop the linkages between the remotely sensed data and plant chlorophyll and nitrogen at approximately 15-cm resolution. The results of this study are presented, including a statistical evaluation of the performance of the different models and a comparison of the RVM modeling methods against more traditional approaches that have been used for estimation of plant chlorophyll and nitrogen.

  14. Use of High-Resolution Multispectral Imagery to Estimate Soil and Plant Nitrogen in Oats (Avena sativa)

    NASA Astrophysics Data System (ADS)

    ELarab, M.; Ticlavilca, A. M.; Torres-Rua, A. F.; McKee, M.

    2014-12-01

    Precision agriculture requires high spatial resolution in the application of the inputs to agricultural production. This requires that actionable information about crop and field status be acquired at the same high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high-resolution imagery was obtained through the use of a small, unmanned aerial vehicle, called AggieAirTM, which provides spatial resolution as fine as 15 cm. Simultaneously with AggieAir flights, intensive ground sampling was conducted at precisely determined locations for plant and soil nitrogen among other parameters. This study investigated the spectral signature of oats and formulated a machine learning regression model of reflectance response between the multi-spectral bands available from AggieAir (red, green, blue, near infrared, and thermal), plant nitrogen and soil nitrogen. A multivariate relevance vector machine (MVRVM) was used to develop the linkages between the remotely sensed data and plant and soil nitrogen at approximately 15-cm resolution. The results of this study are presented, including a statistical evaluation of the performance of the model.

  15. Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

    USGS Publications Warehouse

    Hively, W. Dean; McCarty, Gregory W.; Reeves, James B., III; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

    2011-01-01

    Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

  16. Detection of Extreme Climate Event Impacts to Terrestrial Productivity From Airborne Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Desai, A. R.; DuBois, S.; Singh, A.; Serbin, S.; Goulden, M.; Baldocchi, D. D.; Oechel, W. C.; Kruger, E. L.; Townsend, P. A.

    2015-12-01

    Changes in drought frequency and intensity are likely to be some of the largest climate anomalies to influence the net productivity of ecosystems, especially in already water-limited regions. However, the physiological mechanisms that drive this response are limited by primarily infrequent and small-scale leaf-level measurements. Here, we integrated eddy covariance flux tower estimates of gross primary productivity (GPP) across an elevation-gradient in California with airborne imagery from the NASA HyspIRI Preparatory campaign to evaluate the potential of hyperspectral imagery to detect responses of GPP to prolonged drought. We observed a number of spectral features in the visible, infrared, and shortwave infrared regions that yielded stronger linkages than traditional broadband indices with space and time variation in GPP across a range of ecosystems in California experiencing water stress in the past three years. Further, partial least squares regression (PLSR) modeling offers the ability to generate predictive models of GPP from narrowband hyperspectral remote sensing that directly links plant chemistry and spectral properties to productivity, and could serve as a significant advance over broadband remote sensing of GPP anomalies.

  17. Urban Building Collapse Detection Using Very High Resolution Imagery and Airborne LIDAR Data

    NASA Astrophysics Data System (ADS)

    Wang, X.; Li, P.

    2013-07-01

    The increasing availability of very high resolution (VHR) remotely sensed images makes it possible to detect and assess urban building damages in the aftermath of earthquake disasters by using these data. However, the accuracy obtained using spectral features from VHR data alone is comparatively low, since both undamaged and collapsed buildings are spectrally similar. The height information provided by airborne LiDAR (Light Detection And Ranging) data is complementary to VHR imagery. Thus, combination of these two datasets will be beneficial to the automatic and accurate extraction of building collapse. In this study, a hierarchical multi-level method of building collapse detection using bi-temporal (pre- and post-earthquake) VHR images and postevent airborne LiDAR data was proposed. First, buildings, bare ground, vegetation and shadows were extracted using post-event image and LiDAR data and masked out. Then building collapse was extracted using the bi-temporal VHR images of the remaining area with a one-class classifier. The proposed method was evaluated using bi-temporal VHR images and LiDAR data of Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010. The method was also compared with some existing methods. The results showed that the method proposed in this study significantly outperformed the existing methods, with improvement range of 47.6% in kappa coefficient. The proposed method provided a fast and reliable way of detecting urban building collapse, which can also be applied to relevant applications.

  18. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

    USGS Publications Warehouse

    Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

    2009-01-01

    In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared

  19. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

    NASA Astrophysics Data System (ADS)

    Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

    2009-10-01

    In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus ( Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 × 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each tile. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal

  20. Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

    NASA Astrophysics Data System (ADS)

    Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

    2016-06-01

    Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

  1. Bayesian classifier applications of airborne hyperspectral imagery processing for forested areas

    NASA Astrophysics Data System (ADS)

    Kozoderov, Vladimir; Kondranin, Timofei; Dmitriev, Egor; Kamentsev, Vladimir

    2015-06-01

    Pattern recognition problem is outlined in the context of textural and spectral analysis of remote sensing imagery processing. Main attention is paid to Bayesian classifier that can be used to realize the processing procedures based on parallel machine-learning algorithms and high-productive computers. We consider the maximum of the posterior probability principle and the formalism of Markov random fields for the neighborhood description of the pixels for the related classes of objects with the emphasis on forests of different species and ages. The energy category of the selected classes serves to account for the likelihood measure between the registered radiances and the theoretical distribution functions approximating remotely sensed data. Optimization procedures are undertaken to solve the pattern recognition problem of the texture description for the forest classes together with finding thin nuances of their spectral distribution in the feature space. As a result, possible redundancy of the channels for imaging spectrometer due to their correlations is removed. Difficulties are revealed due to different sampling data while separating pixels, which characterize the sunlit tops, shaded space and intermediate cases of the Sun illumination conditions on the hyperspectral images. Such separation of pixels for the forest classes is maintained to enhance the recognition accuracy, but learning ensembles of data need to be agreed for these categories of pixels. We present some results of the Bayesian classifier applicability for recognizing airborne hyperspectral images using the relevant improvements in separating such pixels for the forest classes on a test area of the 4 × 10 km size encompassed by 13 airborne tracks, each forming the images by 500 pixels across the track and from 10,000 to 14,000 pixels along the track. The spatial resolution of each image is near to 1 m from the altitude near to 2 km above the ground level. The results of the hyperspectral imagery

  2. Recent advances in airborne terrestrial remote sensing with the NASA airborne visible/infrared imaging spectrometer (AVIRIS), airborne synthetic aperture radar (SAR), and thermal infrared multispectral scanner (TIMS)

    NASA Technical Reports Server (NTRS)

    Vane, Gregg; Evans, Diane L.; Kahle, Anne B.

    1989-01-01

    Significant progress in terrestrial remote sensing from the air has been made with three NASA-developed sensors that collectively cover the solar-reflected, thermal infrared, and microwave regions of the electromagnetic spectrum. These sensors are the airborne visible/infrared imaging spectrometer (AVIRIS), the thermal infrared mapping spectrometer (TIMS) and the airborne synthetic aperture radar (SAR), respectively. AVIRIS and SAR underwent extensive in-flight engineering testing in 1987 and 1988 and are scheduled to become operational in 1989. TIMS has been in operation for several years. These sensors are described.

  3. Detection of turbidity dynamics in Tampa Bay, Florida using multispectral imagery from ERTS-1

    NASA Technical Reports Server (NTRS)

    Coker, A. E.; Higer, A. L.; Goodwin, C. R.

    1973-01-01

    In 1970, Congress authorized the deepening of the Tampa Bay channel (Rivers and Harbors Act of 1970) from 34 to 44 feet. In order to determine the effects of this deepening on circulation, water quality, and biota, during and after the construction, the U.S. Geological Survey, in cooperation with the Tampa Port Authority, has collected data and developed a digital simulation model of the bay. In addition to data collected using conventional tools, use is being made of data collected from ERTS-1. Return beam vidicon (RBV) multispectral data were collected, while a shell dredging barge was operating in the bay, and used for turbidity recognition and unique spectral signatures representative of type and amount of material in suspension. A three-dimensional concept of the dynamics of the plume was achieved by superimposing the parts of the plume recognized in each RBV band. This provides a background for automatic computer processing of ERTS data and three-dimensional modeling of turbidity plumes.

  4. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    PubMed

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

  5. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    PubMed Central

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

  6. Active/passive scanning. [airborne multispectral laser scanners for agricultural and water resources applications

    NASA Technical Reports Server (NTRS)

    Woodfill, J. R.; Thomson, F. J.

    1979-01-01

    The paper deals with the design, construction, and applications of an active/passive multispectral scanner combining lasers with conventional passive remote sensors. An application investigation was first undertaken to identify remote sensing applications where active/passive scanners (APS) would provide improvement over current means. Calibration techniques and instrument sensitivity are evaluated to provide predictions of the APS's capability to meet user needs. A preliminary instrument design was developed from the initial conceptual scheme. A design review settled the issues of worthwhile applications, calibration approach, hardware design, and laser complement. Next, a detailed mechanical design was drafted and construction of the APS commenced. The completed APS was tested and calibrated in the laboratory, then installed in a C-47 aircraft and ground tested. Several flight tests completed the test program.

  7. Detection of neolithic settlements in thessaly (Greece) through multispectral and hyperspectral satellite imagery.

    PubMed

    Alexakis, Dimitrios; Sarris, Apostolos; Astaras, Theodoros; Albanakis, Konstantinos

    2009-01-01

    Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 - 3,000 BC). Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution. PMID:22399961

  8. Detection of Neolithic Settlements in Thessaly (Greece) Through Multispectral and Hyperspectral Satellite Imagery

    PubMed Central

    Alexakis, Dimitrios; Sarris, Apostolos; Astaras, Theodoros; Albanakis, Konstantinos

    2009-01-01

    Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 – 3,000 BC). Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution. PMID:22399961

  9. New, Flexible Applications with the Multi-Spectral Titan Airborne Lidar

    NASA Astrophysics Data System (ADS)

    Swirski, A.; LaRocque, D. P.; Shaker, A.; Smith, B.

    2015-12-01

    Traditional lidar designs have been restricted to using a single laser channel operating at one particular wavelength. Single-channel systems excel at collecting high-precision spatial (XYZ) data, with accuracies down to a few centimeters. However, target classification is difficult with spatial data alone, and single-wavelength systems are limited to the strengths and weaknesses of the wavelength they use. To resolve these limitations in lidar design, Teledyne Optech developed the Titan, the world's first multispectral lidar system, which uses three independent laser channels operating at 532, 1064, and 1550 nm. Since Titan collects 12 bit intensity returns for each wavelength separately, users can compare how strongly targets in the survey area reflect each wavelength. Materials such as soil, rock and foliage all reflect the wavelengths differently, enabling post-processing algorithms to identify the material of targets easily and automatically. Based on field tests in Canada, automated classification algorithms have combined this with elevation data to classify targets into six basic types with 78% accuracy. Even greater accuracy is possible with further algorithm enhancement and the use of an in-sensor passive imager such as a thermal, multispectral, CIR or RGB camera. Titan therefore presents an important new tool for applications such as land-cover classification and environmental modeling while maintaining lidar's traditional strengths: high 3D accuracy and day/night operation. Multispectral channels also enable a single lidar to handle both topographic and bathymetric surveying efficiently, which previously required separate specialized lidar systems operating at different wavelengths. On land, Titan can survey efficiently from 2000 m AGL with a 900 kHz PRF (300 kHz per channel), or up to 2500 m if only the infrared 1064 and 1550 nm channels are used. Over water, the 532 nm green channel penetrates water to collect seafloor returns while the infrared

  10. Segmenting clouds from space : a hybrid multispectral classification algorithm for satellite imagery.

    SciTech Connect

    Post, Brian Nelson; Wilson, Mark P.; Smith, Jody Lynn; Wehlburg, Joseph Cornelius; Nandy, Prabal

    2005-07-01

    This paper reports on a novel approach to atmospheric cloud segmentation from a space based multi-spectral pushbroom satellite system. The satellite collects 15 spectral bands ranging from visible, 0.45 um, to long wave infra-red (IR), 10.7um. The images are radiometrically calibrated and have ground sample distances (GSD) of 5 meters for visible to very near IR bands and a GSD of 20 meters for near IR to long wave IR. The algorithm consists of a hybrid-classification system in the sense that supervised and unsupervised networks are used in conjunction. For performance evaluation, a series of numerical comparisons to human derived cloud borders were performed. A set of 33 scenes were selected to represent various climate zones with different land cover from around the world. The algorithm consisted of the following. Band separation was performed to find the band combinations which form significant separation between cloud and background classes. The potential bands are fed into a K-Means clustering algorithm in order to identify areas in the image which have similar centroids. Each cluster is then compared to the cloud and background prototypes using the Jeffries-Matusita distance. A minimum distance is found and each unknown cluster is assigned to their appropriate prototype. A classification rate of 88% was found when using one short wave IR band and one mid-wave IR band. Past investigators have reported segmentation accuracies ranging from 67% to 80%, many of which require human intervention. A sensitivity of 75% and specificity of 90% were reported as well.

  11. Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of European corn borer infestation in Iowa corn plots

    EPA Science Inventory

    Eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery and evaluated in 2004 and 2005 for their ability to detect experimental plots of corn manually inoculated with Ostrinia nubilalis (Hübner) neonate larvae. ...

  12. Assessing the application of an airborne intensified multispectral video camera to measure chlorophyll a in three Florida estuaries

    SciTech Connect

    Dierberg, F.E.; Zaitzeff, J.

    1997-08-01

    After absolute and spectral calibration, an airborne intensified, multispectral video camera was field tested for water quality assessments over three Florida estuaries (Tampa Bay, Indian River Lagoon, and the St. Lucie River Estuary). Univariate regression analysis of upwelling spectral energy vs. ground-truthed uncorrected chlorophyll a (Chl a) for each estuary yielded lower coefficients of determination (R{sup 2}) with increasing concentrations of Gelbstoff within an estuary. More predictive relationships were established by adding true color as a second independent variable in a bivariate linear regression model. These regressions successfully explained most of the variation in upwelling light energy (R{sup 2}=0.94, 0.82 and 0.74 for the Tampa Bay, Indian River Lagoon, and St. Lucie estuaries, respectively). Ratioed wavelength bands within the 625-710 nm range produced the highest correlations with ground-truthed uncorrected Chl a, and were similar to those reported as being the most predictive for Chl a in Tennessee reservoirs. However, the ratioed wavebands producing the best predictive algorithms for Chl a differed among the three estuaries due to the effects of varying concentrations of Gelbstoff on upwelling spectral signatures, which precluded combining the data into a common data set for analysis.

  13. Mapping beech ( Fagus sylvatica L.) forest structure with airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Cho, Moses Azong; Skidmore, Andrew K.; Sobhan, Istiak

    2009-06-01

    Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast height (DBH), mean tree height and tree density of a closed canopy beech forest ( Fagus sylvatica L.). Airborne HyMap images and data on forest structural attributes were collected from the Majella National Park, Italy in July 2004. The predictive performances of vegetation indices (VI) derived from all possible two-band combinations (VI ( i, j) = ( Ri - Rj)/( Ri + Rj), where Ri and Rj = reflectance in any two bands) were evaluated using calibration ( n = 33) and test ( n = 20) data sets. The potential of partial least squares (PLS) regression, a multivariate technique involving several bands was also assessed. New VIs based on the contrast between reflectance in the red-edge shoulder (756-820 nm) and the water absorption feature centred at 1200 nm (1172-1320 nm) were found to show higher correlations with the forest structural parameters than standard VIs derived from NIR and visible reflectance (i.e. the normalised difference vegetation index, NDVI). PLS regression showed a slight improvement in estimating the beech forest structural attributes (prediction errors of 27.6%, 32.6% and 46.4% for mean DBH, height and tree density, respectively) compared to VIs using linear regression models (prediction errors of 27.8%, 35.8% and 48.3% for mean DBH, height and tree density, respectively). Mean DBH was the best predicted variable among the stand parameters (calibration R2 = 0.62 for an exponential model fit and standard error of prediction = 5.12 cm, i.e. 25% of the mean). The predicted map of mean DBH revealed high heterogeneity in the beech forest structure in the study area. The spatial variability of mean DBH occurs at less than 450 m. The DBH

  14. D Land Cover Classification Based on Multispectral LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  15. Multispectral processing of combined visible and x-ray fluorescence imagery in the Archimedes palimpsest

    NASA Astrophysics Data System (ADS)

    Walvoord, Derek; Bright, Allison; Easton, Roger L., Jr.

    2008-02-01

    The Archimedes palimpsest is one of the most significant early texts in the history of science that has survived to the present day. It includes the oldest known copies of text from seven treatises by Archimedes, along with pages from other important historical writings. In the 13th century, the original texts were erased and overwritten by a Christian prayer book, which was used in religious services probably into the 19th century. Since 2001, much of the text from treatises of Archimedes has been transcribed from images taken in reflected visible light and visible fluorescence generated by exposure of the parchment to ultraviolet light. However, these techniques do not work well on all pages of the manuscript, including the badly stained colophon, four pages of the manuscript obscured by icons painted during the first half of the 20th century, and some pages of non-Archimedes texts. Much of the text on the colophon and overpainted pages has been recovered from X-ray fluorescence (XRF) imagery. In this work, the XRF images of one of the other pages were combined with the bands of optical images to create hyperspectral image cubes and processed using standard statistical classification techniques developed for environmental remote sensing to test if this improved the recovery of the original text.

  16. Towards 3D Matching of Point Clouds Derived from Oblique and Nadir Airborne Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Ming

    Because of the low-expense high-efficient image collection process and the rich 3D and texture information presented in the images, a combined use of 2D airborne nadir and oblique images to reconstruct 3D geometric scene has a promising market for future commercial usage like urban planning or first responders. The methodology introduced in this thesis provides a feasible way towards fully automated 3D city modeling from oblique and nadir airborne imagery. In this thesis, the difficulty of matching 2D images with large disparity is avoided by grouping the images first and applying the 3D registration afterward. The procedure starts with the extraction of point clouds using a modified version of the RIT 3D Extraction Workflow. Then the point clouds are refined by noise removal and surface smoothing processes. Since the point clouds extracted from different image groups use independent coordinate systems, there are translation, rotation and scale differences existing. To figure out these differences, 3D keypoints and their features are extracted. For each pair of point clouds, an initial alignment and a more accurate registration are applied in succession. The final transform matrix presents the parameters describing the translation, rotation and scale requirements. The methodology presented in the thesis has been shown to behave well for test data. The robustness of this method is discussed by adding artificial noise to the test data. For Pictometry oblique aerial imagery, the initial alignment provides a rough alignment result, which contains a larger offset compared to that of test data because of the low quality of the point clouds themselves, but it can be further refined through the final optimization. The accuracy of the final registration result is evaluated by comparing it to the result obtained from manual selection of matched points. Using the method introduced, point clouds extracted from different image groups could be combined with each other to build a

  17. Potential of Multi-Temporal Oblique Airborne Imagery for Structural Damage Assessment

    NASA Astrophysics Data System (ADS)

    Vetrivel, A.; Duarte, D.; Nex, F.; Gerke, M.; Kerle, N.; Vosselman, G.

    2016-06-01

    Quick post-disaster actions demand automated, rapid and detailed building damage assessment. Among the available technologies, post-event oblique airborne images have already shown their potential for this task. However, existing methods usually compensate the lack of pre-event information with aprioristic assumptions of building shapes and textures that can lead to uncertainties and misdetections. However, oblique images have been already captured over many cities of the world, and the exploitation of pre- and post-event data as inputs to damage assessment is readily feasible in urban areas. In this paper, we investigate the potential of multi-temporal oblique imagery for detailed damage assessment focusing on two methodologies: the first method aims at detecting severe structural damages related to geometrical deformation by combining the complementary information provided by photogrammetric point clouds and oblique images. The developed method detected 87% of damaged elements. The failed detections are due to varying noise levels within the point cloud which hindered the recognition of some structural elements. We observed, in general that the façade regions are very noisy in point clouds. To address this, we propose our second method which aims to detect damages to building façades using the oriented oblique images. The results show that the proposed methodology can effectively differentiate among the three proposed categories: collapsed/highly damaged, lower levels of damage and undamaged buildings, using a computationally light-weight approach. We describe the implementations of the above mentioned methods in detail and present the promising results achieved using multi-temporal oblique imagery over the city of L'Aquila (Italy).

  18. Mapping Active Fault Zones in Southern California Using Master Multispectral Imagery Data

    NASA Astrophysics Data System (ADS)

    Harvey, J. C.; Peltzer, G. F.; Hook, S. J.; Alley, R.; Myers, J.; Coffland, B.; Dominguez, R.; Fitzgerald, M.

    2004-12-01

    Recent studies of active fault zones using the GPS and InSAR techniques have revealed slip rates that often differ from the slip rates determined from geological observations. This discrepancy is principally due to the different time windows over which surface movements are integrated in both approaches. If surface velocities near faults vary over cycles of several hundreds of years, it becomes important to document the slip history along faults over various time scales as it has been recorded in the Quaternary deposits along the fault. To this endeavor, we have acquired sets of images of the major active faults in Southern California using the MODIS/ASTER airborne simulator (MASTER) instrument. The lines are flown at low altitude above the ground to provide 4 to 5 m spatial resolution in the 50 spectral bands (0.5 to 13 microns) of the instrument. A preliminary set of data was acquired in the summer 2003 over the Garlock and the Blackwater faults in the Mojave. A more extensive campaign carried out in September 2004 covered more than 1000 km of fault lines from the central section of the San Andreas fault to the Salton Sea area. The data are being processed to extract reflectance and emissivity information. Preliminary analysis of the 2003 data confirmed the strong potential of the MASTER thermal bands to identify changes in surface emissivity due to subtle variations of the mineral composition of the deposits. Additional information on the near surface structure of the fault zones can be obtained by combining day and night surface temperature maps, as buried sections of faults are revealed by thermal capacity contrasts between the two sides of a given fault. The paper will present the data set acquired during the 2003 and 2004 campaigns and the status of the raw data processing into geo-referenced emissivity and reflectivity maps of the fault zones.

  19. Assessing plantation canopy condition from airborne imagery using spectral mixture analysis and fractional abundances

    NASA Astrophysics Data System (ADS)

    Goodwin, Nicholas; Coops, Nicholas C.; Stone, Christine

    2005-05-01

    Pine plantations in Australia are subject to a range of abiotic and biotic damaging agents that affect tree health and productivity. In order to optimise management decisions, plantation managers require regular intelligence relating to the status and trends in the health and condition of trees within individual compartments. Remote sensing technology offers an alternative to traditional ground-based assessment of these plantations. Automated estimation of foliar crown health, especially in degraded crowns, can be difficult due to mixed pixels when there is low or fragmented vegetation cover. In this study we apply a linear spectral unmixing approach to high spatial resolution (50 cm) multispectral imagery to quantify the fractional abundances of the key image endmembers: sunlit canopy, shadow, and soil. A number of Pinus radiata tree crown attributes were modelled using multiple linear regression and endmember fraction images. We found high levels of significance ( r2 = 0.80) for the overall crown colour and colour of the crown leader ( r2 = 0.79) in tree crowns affected by the fungal pathogen Sphaeropsis sapinea, which produces both needle necrosis and chlorosis. Results for stands associated with defoliation and chlorosis through infestation by the aphid Essigella californica were lower with an r2 = 0.33 for crown transparency and r2 = 0.31 for proportion of crown affected. Similar analysis of data from a nitrogen deficient site produced an outcome somewhat in between the other two damaging agents. Overall the sunlit canopy image fraction has been the most important variable used in the modelling of forest condition for all damaging agents.

  20. Capturing the Green River -- Multispectral airborne videography to evaluate the environmental impacts of hydropower operations

    SciTech Connect

    Snider, M.A.; Hayse, J.W.; Hlohowskyj, I.; LaGory, K.E.

    1996-02-01

    The 500-mile long Green River is the largest tributary of the Colorado River. From its origin in the Wind River Range mountains of western Wyoming to its confluence with the Colorado River in southeastern Utah, the Green River is vital to the arid region through which it flows. Large portions of the area remain near-wilderness with the river providing a source of recreation in the form of fishing and rafting, irrigation for farming and ranching, and hydroelectric power. In the late 1950`s and early 1960`s hydroelectric facilities were built on the river. One of these, Flaming Gorge Dam, is located just south of the Utah-Wyoming border near the town of Dutch John, Utah. Hydropower operations result in hourly and daily fluctuations in the releases of water from the dam that alter the natural stream flow below the dam and affect natural resources in and along the river corridor. In the present study, the authors were interested in evaluating the potential impacts of hydropower operations at Flaming Gorge Dam on the downstream natural resources. Considering the size of the area affected by the daily pattern of water release at the dam as well as the difficult terrain and limited accessibility of many reaches of the river, evaluating these impacts using standard field study methods was virtually impossible. Instead an approach was developed that used multispectral aerial videography to determine changes in the affected parameters at different flows, hydrologic modeling to predict flow conditions for various hydropower operating scenarios, and ecological information on the biological resources of concern to assign impacts.

  1. Airborne multispectral and hyperspectral remote sensing: Examples of applications to the study of environmental and engineering problems

    SciTech Connect

    Bianchi, R.; Marino, C.M.

    1997-10-01

    The availability of a new aerial survey capability carried out by the CNR/LARA (National Research Council - Airborne Laboratory for the Environmental Research) by a new spectroradiometer AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) on board a CASA 212/200 aircraft, enable the scientists to obtain innovative data sets, for different approach to the definitions and the understanding of a variety of environmental and engineering problems. The 102 MIVIS channels spectral bandwidths are chosen to meet the needs of scientific research for advanced applications of remote sensing data. In such configuration MIVIS can offer significant contributions to problem solving in wide sectors such as geologic exploration, agricultural crop studies, forestry, land use mapping, idrogeology, oceanography and others. LARA in 1994-96 has been active over different test-sites in joint-venture with JPL, Pasadena, different European Institutions and Italian University and Research Institutes. These aerial surveys allow the national and international scientific community to approach the use of Hyperspectral Remote Sensing in environmental problems of very large interest. The sites surveyed in Italy, France and Germany include a variety of targets such as quarries, landfills, karst cavities areas, landslides, coastlines, geothermal areas, etc. The deployments gathered up to now more than 300 GBytes of MIVIS data in more than 30 hours of VLDS data recording. The purpose of this work is to present and to comment the procedures and the results at research and at operational level of the past campaigns with special reference to the study of environmental and engineering problems.

  2. Multispectral Terrain Background Simulation Techniques For Use In Airborne Sensor Evaluation

    NASA Astrophysics Data System (ADS)

    Weinberg, Michael; Wohlers, Ronald; Conant, John; Powers, Edward

    1988-08-01

    A background simulation code developed at Aerodyne Research, Inc., called AERIE is designed to reflect the major sources of clutter that are of concern to staring and scanning sensors of the type being considered for various airborne threat warning (both aircraft and missiles) sensors. The code is a first principles model that could be used to produce a consistent image of the terrain for various spectral bands, i.e., provide the proper scene correlation both spectrally and spatially. The code utilizes both topographic and cultural features to model terrain, typically from DMA data, with a statistical overlay of the critical underlying surface properties (reflectance, emittance, and thermal factors) to simulate the resulting texture in the scene. Strong solar scattering from water surfaces is included with allowance for wind driven surface roughness. Clouds can be superimposed on the scene using physical cloud models and an analytical representation of the reflectivity obtained from scattering off spherical particles. The scene generator is augmented by collateral codes that allow for the generation of images at finer resolution. These codes provide interpolation of the basic DMA databases using fractal procedures that preserve the high frequency power spectral density behavior of the original scene. Scenes are presented illustrating variations in altitude, radiance, resolution, material, thermal factors, and emissivities. The basic models utilized for simulation of the various scene components and various "engineering level" approximations are incorporated to reduce the computational complexity of the simulation.

  3. Estimating Leaf Water Potential of Giant Sequoia Trees from Airborne Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Francis, E. J.; Asner, G. P.

    2015-12-01

    Recent drought-induced forest dieback events have motivated research on the mechanisms of tree survival and mortality during drought. Leaf water potential, a measure of the force exerted by the evaporation of water from the leaf surface, is an indicator of plant water stress and can help predict tree mortality in response to drought. Scientists have traditionally measured water potentials on a tree-by-tree basis, but have not been able to produce maps of tree water potential at the scale of a whole forest, leaving forest managers unaware of forest drought stress patterns and their ecosystem-level consequences. Imaging spectroscopy, a technique for remote measurement of chemical properties, has been used to successfully estimate leaf water potentials in wheat and maize crops and pinyon-pine and juniper trees, but these estimates have never been scaled to the canopy level. We used hyperspectral reflectance data collected by the Carnegie Airborne Observatory (CAO) to map leaf water potentials of giant sequoia trees (Sequoiadendron giganteum) in an 800-hectare grove in Sequoia National Park. During the current severe drought in California, we measured predawn and midday leaf water potentials of 48 giant sequoia trees, using the pressure bomb method on treetop foliage samples collected with tree-climbing techniques. The CAO collected hyperspectral reflectance data at 1-meter resolution from the same grove within 1-2 weeks of the tree-level measurements. A partial least squares regression was used to correlate reflectance data extracted from the 48 focal trees with their water potentials, producing a model that predicts water potential of giant sequoia trees. Results show that giant sequoia trees can be mapped in the imagery with a classification accuracy of 0.94, and we predicted the water potential of the mapped trees to assess 1) similarities and differences between a leaf water potential map and a canopy water content map produced from airborne hyperspectral data, 2

  4. Daily evapotranspiration estimates from extrapolating instantaneous airborne remote sensing ET values

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study, six extrapolation methods have been compared for their ability to estimate daily crop evapotranspiration (ETd) from instantaneous latent heat flux estimates derived from digital airborne multispectral remote sensing imagery. Data used in this study were collected during an experiment...

  5. Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

    NASA Astrophysics Data System (ADS)

    Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

    2014-10-01

    Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

  6. Do Additional Bands (coastal, NIR-2, Red-Edge and Yellow) in WORLDVIEW-2 Multispectral Imagery Improve Discrimination of AN Invasive Tussock, Buffel Grass (cenchrus Ciliaris)?

    NASA Astrophysics Data System (ADS)

    Marshall, V.; Lewis, M.; Ostendorf, B.

    2012-07-01

    Our goals is to determine if Worldview-2 8-band multispectral imagery can be used to discriminate an invasive grass species namely, Buffel grass (Cenchrus ciliaris) in the subtropical arid parts of central Australia and whether it offers a tangible improvement on 4-band (visible and near infra red) multispectral imagery. A Worldview-2 scene was acquired for a 10*10km area just west of Alice Springs in central Australia following heavy rains of early Summer. Mixture Tuned Matched Filtering was used to classify the image. Target and background spectra were selected in the field and extracted from the image. Linear discriminate analysis (LDA) was used to examine the spectral separability of each group of the target/ background spectra. The importance of the additional spectral bands on the image classification was assessed by running LDA for both 8 and 4 bands (red, green, blue and NIR). LDA did not indicate improved separability between groups when additional spectral bands were applied. Preliminary classification results indicate that Buffel grass (Cenchrus ciliaris) is detected with an omission error 44%, commission error of 11.8% and overall accuracy of 59.5%. We were surprised that the additional spectral bands did not improve spectral separability and in part attribute this to the high degree of variance we observed within groups of spectra, which was particularly observable in the NIR2 and Yellow bands. The analyses may be significantly improved by acquiring imagery following the first big rains at the end of the dry season. At this time, phonological differences between our focal species and the surrounding native vegetation should be maximised. We suspect that Worldview-2 will offer even greater potential for the discrimination of Buffel grass under these conditions, being able to fully utilise the yellow-band in particular.

  7. Ground-based multispectral measurements for airborne data verification in non-operating open pit mine "Kremikovtsi"

    NASA Astrophysics Data System (ADS)

    Borisova, Denitsa; Nikolov, Hristo; Petkov, Doyno

    2013-10-01

    The impact of mining industry and metal production on the environment is presented all over the world. In our research we set focus on the impact of already non-operating ferrous "Kremikovtsi"open pit mine and related waste dumps and tailings which we consider to be the major factor responsible for pollution of one densely populated region in Bulgaria. The approach adopted is based on correct estimation of the distribution of the iron oxides inside open pit mines and the neighboring regions those considered in this case to be the key issue for the ecological state assessment of soils, vegetation and water. For this study the foremost source of data are those of airborne origin and those combined with ground-based in-situ and laboratory acquired data were used for verification of the environmental variables and thus in process of assessment of the present environmental status influenced by previous mining activities. The percentage of iron content was selected as main indicator for presence of metal pollution since it could be reliably identified by multispectral data used in this study and also because the iron compounds are widely spread in the most of the minerals, rocks and soils. In our research the number of samples from every source (air, field, lab) was taken in the way to be statistically sound and confident. In order to establish relationship between the degree of pollution of the soil and mulspectral data 40 soil samples were collected during a field campaign in the study area together with GPS measurements for two types of laboratory measurements: the first one, chemical and mineralogical analysis and the second one, non-destructive spectroscopy. In this work for environmental variables verification over large areas mulspectral satellite data from Landsat instruments TM/ETM+ and from ALI/OLI (Operational Land Imager) were used. Ground-based (laboratory and in-situ) spectrometric measurements were performed using the designed and constructed in Remote

  8. Client-Side Data Processing and Training for Multispectral Imagery Applications in the GOES-R Era

    NASA Technical Reports Server (NTRS)

    Fuell, Kevin; Gravelle, Chad; Burks, Jason; Berndt, Emily; Schultz, Lori; Molthan, Andrew; Leroy, Anita

    2016-01-01

    RGB imagery can be created locally (i.e. client-side) from single band imagery already on the system with little impact given recommended change to texture cache in AWIPS II. Training/Reference material accessible to forecasters within their operational display system improves RGB interpretation and application as demonstrated at OPG. Application examples from experienced forecasters are needed to support the larger community use of RGB imagery and these can be integrated into the user's display system.

  9. Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture

    NASA Astrophysics Data System (ADS)

    Elarab, Manal; Ticlavilca, Andres M.; Torres-Rua, Alfonso F.; Maslova, Inga; McKee, Mac

    2015-12-01

    Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS-NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm-2, efficiency of 0.76, and 9 relevance vectors.

  10. Evaluation of SPOT imagery data

    SciTech Connect

    Berger, Z.; Brovey, R.L.; Merembeck, B.F.; Hopkins, H.R.

    1988-01-01

    SPOT, the French satellite imaging system that became operational in April 1986, provides two major advances in satellite imagery technology: (1) a significant increase in spatial resolution of the data to 20 m multispectral and 10 m panchromatic, and (2) stereoscopic capabilities. The structural and stratigraphic mapping capabilities of SPOT data and compare favorably with those of other available space and airborne remote sensing data. In the Rhine graben and Jura Mountains, strike and dip of folded strata can be determined using SPOT stereoscopic imagery, greatly improving the ability to analyze structures in complex areas. The increased spatial resolution also allows many features to be mapped that are not visible on thematic mapper (TM) imagery. In the San Rafael swell, Utah, TM spectral data were combined with SPOT spatial data to map lithostratigraphic units of the exposed Jurassic and Cretaceous rocks. SPOT imagery provides information on attitude, geometry, and geomorphic expressions of key marker beds that is not available on TM imagery. Over the Central Basin platform, west Texas, SPOT imagery, compared to TM imagery, provided more precise information on the configuration of outcropping beds and drainage patterns that reflect the subtle surface expression of buried structures.

  11. Reflectance Data Processing of High Resolution Multispectral Data Acquired with an Autonomous Unmanned Aerial Vehicle AggieairTM

    NASA Astrophysics Data System (ADS)

    Zaman, B.; Jensen, A.; McKee, M.

    2012-12-01

    In this study, the performance and accuracy of a method for converting airborne multispectral data to reflectance data are characterized. Spectral reflectance is the ratio of reflected to incident radiant flux and it may have values only in the interval 0-1, inclusive. Reflectance is a key physical property of a surface and is empirically derived from on-ground observations. The paper presents a method for processing multispectral data acquired by an unmanned aerial vehicle (UAV) platform, called AggieAirTM, and a process for converting raw digital numbers to calibrated reflectance values. Imagery is acquired by two identical sets of cameras. One set is aboard the UAV and the other is over a barium sulfate reference panel. The cameras have identical settings. The major steps for producing the reflectance data involve the calibration of the reference panel, calibration of the multispectral UAV cameras, zenith angle calculations and image processing. The method converts airborne multispectral data by calculating the ratio of linearly-interpolated reference values from the pre- and post-flight reference panel readings. The flight interval is typically approximately 30 minutes and the imagery is acquired around local solar noon. The UAV is typically flown at low altitudes to reduce atmospheric effects to a negligible level. Data acquired over wetlands near Great Salt Lake, Utah is used to illustrate ground data and processed imagery. The spectral resolution of the multispectral data is 25 cms. The paper discusses the accuracy issues and errors associated with the proposed method.

  12. Part task investigation of multispectral image fusion using gray scale and synthetic color night-vision sensor imagery for helicopter pilotage

    NASA Astrophysics Data System (ADS)

    Steele, Paul M.; Perconti, Philip

    1997-06-01

    Today, night vision sensor and display systems used in the pilotage or navigation of military helicopters are either long wave IR thermal sensors (8 - 12 microns) or image intensified, visible and near IR (0.6 - 0.9 microns), sensors. The sensor imagery is displayed using a monochrome phosphor on a Cathode Ray Tube or night vision goggle. Currently, there is no fielded capability to combine the best attributes of the emissive radiation sensed by the thermal sensor and the reflected radiation sensed by the image intensified sensor into a single fused image. However, recent advances in signal processing have permitted the real time image fusion and display of multispectral sensors in either monochrome or synthetic chromatic form. The merits of such signal processing is explored. A part task simulation using a desktop computer, video playback unit, and a biocular head mounted display was conducted. Response time and accuracy measures of test subject responses to visual perception tasks were taken. Subjective ratings were collected to determine levels of pilot acceptance. In general, fusion based formats resulted in better subject performance. The benefits of integrating synthetic color to fused imagery, however, is dependent on the color algorithm used, the visual task performed, and scene content.

  13. [Soil Salinity Estimation Based on Near-Ground Multispectral Imagery in Typical Area of the Yellow River Delta].

    PubMed

    Zhang, Tong-rui; Zhao, Geng-xing; Gao, Ming-xiu; Wang, Zhuo-ran; Jia, Ji-chao; Li, Ping; An, De-yu

    2016-01-01

    This study chooses the core demonstration area of 'Bohai Barn' project as the study area, which is located in Wudi, Shandong Province. We first collected near-ground and multispectral images and surface soil salinity data using ADC portable multispectral camera and EC110 portable salinometer. Then three vegetation indices, namely NDVI, SAVI and GNDVI, were used to build 18 models respectively with the actual measured soil salinity. These models include linear function, exponential function, logarithmic function, exponentiation function, quadratic function and cubic function, from which the best estimation model for soil salinity estimation was selected and used for inverting and analyzing soil salinity status of the study area. Results indicated that all models mentioned above could effectively estimate soil salinity and models using SAVI as the dependent variable were more effective than the others. Among SAVI models, the linear model (Y = -0.524x + 0.663, n = 70) is the best, under which the test value of F is the highest as 141.347 at significance test level, estimated R2 0.797 with a 93.36% accuracy. Soil salinity of the study area is mainly around 2.5 per thousand - 3.5 per thousand, which gradually increases from southwest to northeast. The study has probed into soil salinity estimation methods based on near-ground and multispectral data, and will provide a quick and effective technical soil salinity estimation approach for coastal saline soil of the study area and the whole Yellow River Delta. PMID:27228776

  14. Russian multispectral-hyperspectral airborne scanner for geological and environmental investigations - {open_quotes}Vesuvius-EC{close_quotes}

    SciTech Connect

    Yassinsky, G.I.; Shilin, B.V.

    1996-07-01

    Small variations of spectral characteristics in 0,3-14 microns band are of great significance in geological and environmental investigations. Multipurpose multispectral digital scanner with narrow field of view, high spectral resolution and radiometric calibration designed in Russia. Changeable modules permit to obtain parameters of the device for practical using.

  15. Airborne Multispectral and Thermal Remote Sensing for Detecting the Onset of Crop Stress Caused by Multiple Factors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing technology has been developed and applied to provide spatiotemporal information on crop stress for precision management. A series of multispectral images over a field planted cotton, corn and soybean were obtained by a Geospatial Systems MS4100 camera mounted on an Air Tractor 402B ai...

  16. Mapping tree health using airborne full-waveform laser scans and hyperspectral imagery: a case study for floodplain eucalypt forest

    NASA Astrophysics Data System (ADS)

    Shendryk, I.; Tulbure, M. G.; Broich, M.

    2014-12-01

    Barmah-Millewa Forest (BMF), the largest River Red Gum forest in the world, located in south-eastern Australia is suffering from severe dieback, thus diminishing its ecological and economical value. Previous research showed that dieback is a good predictor of the forest health and stressed the need for BMF health mapping and change monitoring. In this respect, airborne laser scanning and hyperspectral imaging offer extensive spatial and spectral coverage of measurements and represent an ideal tool for forest health mapping at individual tree scale. The aim of this project is to quantify the health of individual, structurally complex floodplain eucalypt trees by integrating airborne hyperspectral imagery, full-waveform laser scans and field measurements. An aerial survey, conducted in May 2014, was designed to provide a representative sample of BMF tree health. The positioning of 17 flight lines aimed to capture the heterogeneity of the forest health and flood frequency. Preliminary analysis of the aerial remote sensing data with regards to chlorophyll concentrations, dieback levels and canopy densities allowed us to target our field campaign (conducted in June 2014). Field measurements included accurate position measurements, LAI, visual assessment, spectral measurement and mensuration of individual trees in 30 m2 plots. For detection of individual tree trunks from airborne laser scans we used a novel approach based on Euclidean distance clustering, taking advantage of the intensity and pulse width difference between woody and leaf tree compartments. The detected trunks were used to seed a minimum cut algorithm for tree crown delineation. In situ measurements confirmed the high structural diversity of the forest and allowed the calibration of the tree detection algorithm. An overall accuracy of the tree detection of 54% and 67% was achieved for trees with circumference over 40 cm and over 100 cm respectively. As a further step, 3D point clusters representing

  17. Estimating Carbon STOCK Changes of Mangrove Forests Using Satellite Imagery and Airborne LiDAR Data in the South Sumatra State, Indonesia

    NASA Astrophysics Data System (ADS)

    Maeda, Y.; Fukushima, A.; Imai, Y.; Tanahashi, Y.; Nakama, E.; Ohta, S.; Kawazoe, K.; Akune, N.

    2016-06-01

    The purposes of this study were 1) to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2) to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1) Classification of types of tree species using Satellite imagery in the study area, (2) Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3) Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.

  18. On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Kingfield, D.; de Beurs, K.

    2014-12-01

    It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

  19. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression

    NASA Astrophysics Data System (ADS)

    Cho, Moses Azong; Skidmore, Andrew; Corsi, Fabio; van Wieren, Sipke E.; Sobhan, Istiak

    2007-12-01

    The main objective was to determine whether partial least squares (PLS) regression improves grass/herb biomass estimation when compared with hyperspectral indices, that is normalised difference vegetation index (NDVI) and red-edge position (REP). To achieve this objective, fresh green grass/herb biomass and airborne images (HyMap) were collected in the Majella National Park, Italy in the summer of 2005. The predictive performances of hyperspectral indices and PLS regression models were then determined and compared using calibration ( n = 30) and test ( n = 12) data sets. The regression model derived from NDVI computed from bands at 740 and 771 nm produced a lower standard error of prediction (SEP = 264 g m -2) on the test data compared with the standard NDVI involving bands at 665 and 801 nm (SEP = 331 g m -2), but comparable results with REPs determined by various methods (SEP = 261 to 295 g m -2). PLS regression models based on original, derivative and continuum-removed spectra produced lower prediction errors (SEP = 149 to 256 g m -2) compared with NDVI and REP models. The lowest prediction error (SEP = 149 g m -2, 19% of mean) was obtained with PLS regression involving continuum-removed bands. In conclusion, PLS regression based on airborne hyperspectral imagery provides a better alternative to univariate regression involving hyperspectral indices for grass/herb biomass estimation in the Majella National Park.

  20. Detection of tropical landslides using airborne lidar data and multi imagery: A case study in genting highland, pahang

    NASA Astrophysics Data System (ADS)

    Khamsin, I.; Zulkarnain, M.; Razak, K. A.; Rizal, S.

    2014-02-01

    The landslide geomorphological system in a tropical region is complex, and its understanding often depends on the completeness and correctness of landslide inventorization. In mountainous regions, landslides pose a significant impact and are known as an important geomorphic process in shaping major landscape in the tropics. A modern remote sensing based approach has revolutionized the landslide investigation in a forested terrain. Optical satellite imagery, aerial photographs and synthetic aperture radar images are less effective to create reliable tropical DTMs for landslide recognition, and even so in the forested equatorial regions. Airborne laser scanning (ALS) data have been used to construct the digital terrain model (DTM) under dense vegetation, but its reliability for landslide recognition in the tropics remains surprisingly unknown. The present study aims at providing better insight into the use of airborne laser scanning (ALS) data. For the bare-earth extraction, several prominent filtering algorithms and surface interpolation methods, i.e. progressive TIN densitification, morphological, and command prompt from Lastool are evaluated in a qualitative analysis, aiming at removing non-ground points while preserving important landslide features. As a result, a large landslide can be detected using OOA. Small landslides remain unrecognized. Three out of five landslides can be detected, with a 60 percent overall accuracy.

  1. Airborne hyperspectral imagery and linear spectral unmixing for mapping variation in crop yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation indices derived from remotely sensed imagery are commonly used to estimate crop yields. Spectral unmixing techniques provide an alternative approach to quantifying crop canopy abundance within each pixel of an image and have the potential for mapping crop yield variability. The objective ...

  2. Prediction of senescent rangeland canopy structural attributes with airborne hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Canopy structural and chemical data are needed for senescent, mixed-grass prairie landscapes in autumn, yet models driven by image data are lacking for rangelands dominated by non-photosynthetically active vegetation (NPV). Here, we report how aerial hyperspectral imagery might be modeled to predic...

  3. Mapping freshwater deltaic wetlands and aquatic habitats at multiple scales with high-resolution multispectral WorldView-2 imagery and Indicator Species Analysis

    NASA Astrophysics Data System (ADS)

    Lane, C.; Liu, H.; Anenkhonov, O.; Autrey, B.; Chepinoga, V.

    2012-12-01

    Remote sensing technology has long been used in wetland inventory and monitoring though derived wetland maps were limited in applicability and often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. The advent of high-resolution multispectral satellite systems presents new and exciting capabilities in mapping wetland systems with unprecedented accuracy and spatial detail. This research explores and evaluates the use of high-resolution WorldView-2 (WV2) multispectral imagery in identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta, a Ramsar Wetland of International Importance that drains into Lake Baikal, Russia - a United Nations World Heritage site. A hybrid approach was designed and applied for WV2 image classification consisting of initial unsupervised classification, training data acquisition and analysis, indicator species analysis, and final supervised classification. A hierarchical scheme was defined and adopted for classifying aquatic habitats and wetland vegetation at genus and community levels at a fine scale, while at a coarser scale representing wetland systems as broad substrate and vegetation classes for regional comparisons under various existing wetland classification systems. Rigorous radiometric correction of WV2 images and orthorectification based on GPS-derived ground control points and an ASTER global digital elevation model resulted in 2- to 3-m positional accuracy. We achieved overall classification accuracy of 86.5% for 22 classes of wetland and aquatic habitats at the finest scale and >91% accuracy for broad vegetation and aquatic classes at more generalized scales. At the finest scale, the addition of four new WV2 spectral bands contributed to a classification accuracy increase of 3.5%. The coastal band of WV2 was found to increase the separation between different open water and aquatic habitats, while yellow, red-edge, and

  4. Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study, the SEBAL was evaluated for its ability to derive aerodynamic components and surface energy fluxes from high resolution airborne remote sensing data acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2008 in Texas, USA. Issues related to hot and...

  5. Using mosaicked airborne imagery to assess cotton root rot infection on a regional basis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot is a serious and destructive disease in many of the cotton production areas in Texas. Since 2012, many cotton growers in Texas have used the Topguard fungicide to control this disease in their fields under Section 18 emergency exemptions. Airborne images have been used to monitor the...

  6. A general framework of TOPSIS method for integration of airborne geophysics, satellite imagery, geochemical and geological data

    NASA Astrophysics Data System (ADS)

    Abedi, Maysam; Norouzi, Gholam-Hossain

    2016-04-01

    This work presents the promising application of three variants of TOPSIS method (namely the conventional, adjusted and modified versions) as a straightforward knowledge-driven technique in multi criteria decision making processes for data fusion of a broad exploratory geo-dataset in mineral potential/prospectivity mapping. The method is implemented to airborne geophysical data (e.g. potassium radiometry, aeromagnetic and frequency domain electromagnetic data), surface geological layers (fault and host rock zones), extracted alteration layers from remote sensing satellite imagery data, and five evidential attributes from stream sediment geochemical data. The central Iranian volcanic-sedimentary belt in Kerman province at the SE of Iran that is embedded in the Urumieh-Dokhtar Magmatic Assemblage arc (UDMA) is chosen to integrate broad evidential layers in the region of prospect. The studied area has high potential of ore mineral occurrences especially porphyry copper/molybdenum and the generated mineral potential maps aim to outline new prospect zones for further investigation in future. Two evidential layers of the downward continued aeromagnetic data and its analytic signal filter are prepared to be incorporated in fusion process as geophysical plausible footprints of the porphyry type mineralization. The low values of the apparent resistivity layer calculated from the airborne frequency domain electromagnetic data are also used as an electrical criterion in this investigation. Four remote sensing evidential layers of argillic, phyllic, propylitic and hydroxyl alterations were extracted from ASTER images in order to map the altered areas associated with porphyry type deposits, whilst the ETM+ satellite imagery data were used as well to map iron oxide layer. Since potassium alteration is generally the mainstay of porphyry ore mineralization, the airborne potassium radiometry data was used. The geochemical layers of Cu/B/Pb/Zn elements and the first component of PCA

  7. Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Yang, Ping; Arnold, G. Thomas; Gray, Mark A.; Riedi, Jerome C.; Ackerman, Steven A.; Liou, Kuo-Nan

    2003-01-01

    A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

  8. Geologic analyses of LANDSAT-1 multispectral imagery of a possible power plant site employing digital and analog image processing. [in Pennsylvania

    NASA Technical Reports Server (NTRS)

    Lovegreen, J. R.; Prosser, W. J.; Millet, R. A.

    1975-01-01

    A site in the Great Valley subsection of the Valley and Ridge physiographic province in eastern Pennsylvania was studied to evaluate the use of digital and analog image processing for geologic investigations. Ground truth at the site was obtained by a field mapping program, a subsurface exploration investigation and a review of available published and unpublished literature. Remote sensing data were analyzed using standard manual techniques. LANDSAT-1 imagery was analyzed using digital image processing employing the multispectral Image 100 system and using analog color processing employing the VP-8 image analyzer. This study deals primarily with linears identified employing image processing and correlation of these linears with known structural features and with linears identified manual interpretation; and the identification of rock outcrops in areas of extensive vegetative cover employing image processing. The results of this study indicate that image processing can be a cost-effective tool for evaluating geologic and linear features for regional studies encompassing large areas such as for power plant siting. Digital image processing can be an effective tool for identifying rock outcrops in areas of heavy vegetative cover.

  9. Using airborne multispectral imagery to monitor cotton root rot progression in fungicide-treated and non-treated cotton fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton root rot has affected cotton production in the southwestern and south central U.S for over 100 years. A fungicide, flutriafol, has shown considerable promise for controlling this disease in field studies in the last few years. With the temporary authorization for use of the fungicide to contr...

  10. Mapping quaternary landforms and deposits in the Midwest and Great Plains by means of ERTS-1 multispectral imagery

    NASA Technical Reports Server (NTRS)

    Morrison, R. B.

    1973-01-01

    ERTS-1 multispectral images are proving effective for differentiating many kinds of Quaternary surficial deposits and landforms units in Illinois, Iowa, Missouri, Kansas, Nebraska, and South Dakota. Examples of features that have been distinguished are: (1) the more prominent end moraines of the last glaciation; (2) certain possible palimpsests of older moraines mantled by younger deposits; (3) various abandoned river valleys, including suspected ones deeply filled by deposits; (4) river terraces; and (5) some known faults and a few previously unmapped lineaments that may be faults. The ERTS images are being used for systematic mapping of Quaternary landforms and deposits in about 20 potential study areas. Some study areas, already well mapped, provide checks on the reliability of mapping from the images. For other study areas, previously mapped only partly or not at all, our maps will be the first comprehensive, synoptic ones, and should be useful for regional land-use planning and ground-water, engineering-geology, and other environmental applications.

  11. Use of reflectance spectra of native plant species for interpreting airborne multispectral scanner data in the East Tintic Mountains, Utah.

    USGS Publications Warehouse

    Milton, N.M.

    1983-01-01

    Analysis of in situ reflectance spectra of native vegetation was used to interpret airborne MSS data. Representative spectra from three plant species in the E Tintic Mountains, Utah, were used to interpret the color components on a color ratio composite image made from MSS data in the visible and near-infrared regions. A map of plant communities was made from the color ratio composite image and field checked. -from Author

  12. Estimation of Evapotraspiration of Tamarisk using Energy Balance Models with High Resolution Airborne Imagery and LIDAR Data

    NASA Astrophysics Data System (ADS)

    Geli, H. M.; Taghvaeian, S.; Neale, C. M.; Pack, R.; Watts, D. R.; Osterberg, J.

    2010-12-01

    The wide uncontrolled spread of the invasive species of Tamarisk (Salt Cedar) in the riparian areas of the southwest of the United States has become a source of concern to the water resource management community. This tree which was imported for ornamental purposes and to control bank erosion during the 1800’s later became problematic and unwanted due to its biophysical properties: Its vigorous growth out-competes native species for moisture, lowering water tables, increasing the soil salinity and hence becomes the dominant riparian vegetation especially over arid to semi-arid floodplain environments. Most importantly they consume large amounts of water leading to reduction of river flows and lowering the groundwater table. We implemented this study in an effort to provide reliable estimates of the amount of water consumed or “lost” by such species through evapotranspiration (ET) as well as to a better understand of the related land surface and near atmosphere interactions. The recent advances in remote sensing techniques and the related data quality made it possible to provide spatio-temporal estimates of ET at a considerably higher resolution and reliable accuracy over a wide range of surface heterogeneity. We tested two different soil-vegetation atmosphere transfer models (SVAT) that are based on thermal remote sensing namely: the two source model (TSM) of Norman et al. (1995) with its recent modifications and the Surface Energy balance algorithm (SEBAL) of Bastiaanssen et al. (1998) to estimate the different surface energy balance components and the evapotranspiration (ET) spatially. We used high resolution (1.0 meter pixel size) shortwave reflectance and longwave thermal airborne imagery acquired by the research aircraft at the Remote Sensing Services Lab at Utah State University (USU) and land use map classified from these images as well as a detailed vegetation height image acquired by the LASSI Lidar also developed at USU. We also compared estimates

  13. Quality Assessment of Building Textures Extracted from Oblique Airborne Thermal Imagery

    NASA Astrophysics Data System (ADS)

    Iwaszczuk, D.; Stilla, U.

    2016-06-01

    Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.

  14. Using airborne thermal infrared imagery and helicopter EM conductivity to locate mine pools and discharges in the Kettle Creek watershed, north-central Pennsylvania

    SciTech Connect

    Love, E.; Hammack, R.; Harbert, W.; Sams, J.; Veloski, G.; Ackman, T.

    2005-12-01

    The Kettle Creek watershed contains 50-100-year-old surface and underground coal mines that are a continuing source of acid mine drainage (AMD). To characterize the mining-altered hydrology of this watershed, an airborne reconnaissance was conducted in 2002 using airborne thermal infrared imagery (TIR) and helicopter-mounted electromagnetic (HEM) surveys. TIR uses the temperature differential between surface water and groundwater to locate areas where groundwater emerges at the surface. TIR anomalies located in the survey included seeps and springs, as well as mine discharges. In a follow-up ground investigation, hand-held GPS units were used to locate 103 of the TIR anomalies. Of the sites investigated, 26 correlated with known mine discharges, whereas 27 were previously unknown. Seven known mine discharges previously obscured from TIR imagery were documented. HEM surveys were used to delineate the groundwater table and also to locate mine pools, mine discharges, and groundwater recharge zones. These surveys located 12 source regions and flow paths for acidic, metal-containing (conductive) mine drainage; areas containing acid-generating mine spoil; and areas of groundwater recharge and discharge, as well as identifying potential mine discharges previously obscured from TIR imagery by nondeciduous vegetation. Follow-up ground-based electromagnetic surveys verified the results of the HEM survey. Our study suggests that airborne reconnaissance can make the remediation of large watersheds more efficient by focusing expensive ground surveys on small target areas.

  15. Using airborne thermal infrared imagery and helicopter EM conductivity to locate mine pools and discharges in the Kettle Creek watershed, north-central Pennsylvania

    SciTech Connect

    Love, E.; Hammack, R.W.; Harbert, W.P.; Sams, J.I.; Veloski, G.A.; Ackman, T.E.

    2005-11-01

    The Kettle Creek watershed contains 50–100-year-old surface and underground coal mines that are a continuing source of acid mine drainage (AMD). To characterize the mining-altered hydrology of this watershed, an airborne reconnaissance was conducted in 2002 using airborne thermal infrared imagery (TIR) and helicopter-mounted electromagnetic (HEM) surveys. TIR uses the temperature differential between surface water and groundwater to locate areas where groundwater emerges at the surface. TIR anomalies located in the survey included seeps and springs, as well as mine discharges. In a follow-up ground investigation, hand-held GPS units were used to locate 103 of the TIR anomalies. Of the sites investigated, 26 correlated with known mine discharges, whereas 27 were previously unknown. Seven known mine discharges previously obscured from TIR imagery were documented. HEM surveys were used to delineate the groundwater table and also to locate mine pools, mine discharges, and groundwater recharge zones. These surveys located 12 source regions and flow paths for acidic, metal-containing (conductive) mine drainage; areas containing acid-generating mine spoil; and areas of groundwater recharge and discharge, as well as identifying potential mine discharges previously obscured from TIR imagery by nondeciduous vegetation. Follow-up ground-based electromagnetic surveys verified the results of the HEM survey. Our study suggests that airborne reconnaissance can make the remediation of large watersheds more efficient by focusing expensive ground surveys on small target areas.

  16. A multispectral scanner survey of the Tonopah Test Range, Nevada. Date of survey: August 1993

    SciTech Connect

    Brewster, S.B. Jr.; Howard, M.E.; Shines, J.E.

    1994-08-01

    The Multispectral Remote Sensing Department of the Remote Sensing Laboratory conducted an airborne multispectral scanner survey of a portion of the Tonopah Test Range, Nevada. The survey was conducted on August 21 and 22, 1993, using a Daedalus AADS1268 scanner and coincident aerial color photography. Flight altitudes were 5,000 feet (1,524 meters) above ground level for systematic coverage and 1,000 feet (304 meters) for selected areas of special interest. The multispectral scanner survey was initiated as part of an interim and limited investigation conducted to gather preliminary information regarding historical hazardous material release sites which could have environmental impacts. The overall investigation also includes an inventory of environmental restoration sites, a ground-based geophysical survey, and an aerial radiological survey. The multispectral scanner imagery and coincident aerial photography were analyzed for the detection, identification, and mapping of man-made soil disturbances. Several standard image enhancement techniques were applied to the data to assist image interpretation. A geologic ratio enhancement and a color composite consisting of AADS1268 channels 10, 7, and 9 (mid-infrared, red, and near-infrared spectral bands) proved most useful for detecting soil disturbances. A total of 358 disturbance sites were identified on the imagery and mapped using a geographic information system. Of these sites, 326 were located within the Tonopah Test Range while the remaining sites were present on the imagery but outside the site boundary. The mapped site locations are being used to support ongoing field investigations.

  17. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew; Fuell, Kevin; Knaff, John; Lee, Thomas

    2012-01-01

    What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

  18. Bundle block adjustment of airborne three-line array imagery based on rotation angles.

    PubMed

    Zhang, Yongjun; Zheng, Maoteng; Huang, Xu; Xiong, Jinxin

    2014-01-01

    In the midst of the rapid developments in electronic instruments and remote sensing technologies, airborne three-line array sensors and their applications are being widely promoted and plentiful research related to data processing and high precision geo-referencing technologies is under way. The exterior orientation parameters (EOPs), which are measured by the integrated positioning and orientation system (POS) of airborne three-line sensors, however, have inevitable systematic errors, so the level of precision of direct geo-referencing is not sufficiently accurate for surveying and mapping applications. Consequently, a few ground control points are necessary to refine the exterior orientation parameters, and this paper will discuss bundle block adjustment models based on the systematic error compensation and the orientation image, considering the principle of an image sensor and the characteristics of the integrated POS. Unlike the models available in the literature, which mainly use a quaternion to represent the rotation matrix of exterior orientation, three rotation angles are directly used in order to effectively model and eliminate the systematic errors of the POS observations. Very good experimental results have been achieved with several real datasets that verify the correctness and effectiveness of the proposed adjustment models. PMID:24811075

  19. Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

    NASA Astrophysics Data System (ADS)

    Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

    2015-12-01

    Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

  20. Quantification of gully volume using very high resolution DSM generated through 3D reconstruction from airborne and field digital imagery

    NASA Astrophysics Data System (ADS)

    Castillo, Carlos; Zarco-Tejada, Pablo; Laredo, Mario; Gómez, Jose Alfonso

    2013-04-01

    Major advances have been made recently in automatic 3D photo-reconstruction techniques using uncalibrated and non-metric cameras (James and Robson, 2012). However, its application on soil conservation studies and landscape feature identification is currently at the outset. The aim of this work is to compare the performance of a remote sensing technique using a digital camera mounted on an airborne platform, with 3D photo-reconstruction, a method already validated for gully erosion assessment purposes (Castillo et al., 2012). A field survey was conducted in November 2012 in a 250 m-long gully located in field crops on a Vertisol in Cordoba (Spain). The airborne campaign was conducted with a 4000x3000 digital camera installed onboard an aircraft flying at 300 m above ground level to acquire 6 cm resolution imagery. A total of 990 images were acquired over the area ensuring a large overlap in the across- and along-track direction of the aircraft. An ortho-mosaic and the digital surface model (DSM) were obtained through automatic aerial triangulation and camera calibration methods. For the field-level photo-reconstruction technique, the gully was divided in several reaches to allow appropriate reconstruction (about 150 pictures taken per reach) and, finally, the resulting point clouds were merged into a unique mesh. A centimetric-accuracy GPS provided a benchmark dataset for gully perimeter and distinguishable reference points in order to allow the assessment of measurement errors of the airborne technique and the georeferenciation of the photo-reconstruction 3D model. The uncertainty on the gully limits definition was explicitly addressed by comparison of several criteria obtained by 3D models (slope and second derivative) with the outer perimeter obtained by the GPS operator identifying visually the change in slope at the top of the gully walls. In this study we discussed the magnitude of planimetric and altimetric errors and the differences observed between the

  1. Effective Key Parameter Determination for an Automatic Approach to Land Cover Classification Based on Multispectral Remote Sensing Imagery

    PubMed Central

    Wang, Yong; Jiang, Dong; Zhuang, Dafang; Huang, Yaohuan; Wang, Wei; Yu, Xinfang

    2013-01-01

    The classification of land cover based on satellite data is important for many areas of scientific research. Unfortunately, some traditional land cover classification methods (e.g. known as supervised classification) are very labor-intensive and subjective because of the required human involvement. Jiang et al. proposed a simple but robust method for land cover classification using a prior classification map and a current multispectral remote sensing image. This new method has proven to be a suitable classification method; however, its drawback is that it is a semi-automatic method because the key parameters cannot be selected automatically. In this study, we propose an approach in which the two key parameters are chosen automatically. The proposed method consists primarily of the following three interdependent parts: the selection procedure for the pure-pixel training-sample dataset, the method to determine the key parameters, and the optimal combination model. In this study, the proposed approach employs both overall accuracy and their Kappa Coefficients (KC), and Time-Consumings (TC, unit: second) in order to select the two key parameters automatically instead of using a test-decision, which avoids subjective bias. A case study of Weichang District of Hebei Province, China, using Landsat-5/TM data of 2010 with 30 m spatial resolution and prior classification map of 2005 recognised as relatively precise data, was conducted to test the performance of this method. The experimental results show that the methodology determining the key parameters uses the portfolio optimisation model and increases the degree of automation of Jiang et al.'s classification method, which may have a wide scope of scientific application. PMID:24204582

  2. Detection of spatio-temporal changes of Norway spruce forest stands in Ore Mountains using airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Misurec, J.; Kopačková, V.; Lhotáková, Z.; Albrechtova, J.; Campbell, P. K. E.

    2015-12-01

    The Ore Mountains are an example of the region that suffered from severe environmental pollution caused by long-term coal mining and heavy industry leading to massive dieback of the local Norway spruce forests between the 1970's and 1990's. The situation became getting better at the end of 1990's after pollution loads significantly decreased. In 1998 and 2013, airborne hyperspectral data (with sensor ASAS and APEX, respectively) were used to study recovery of the originally damaged forest stands and compared them with those that have been less affected by environmental pollution. The field campaign (needle biochemical analysis, tree defoliation etc.) accompanied hyperspectral imagery acquisition. An analysis was conducted assessing a set of 16 vegetation indices providing complex information on foliage, biochemistry and canopy biophysics and structure. Five of them (NDVI, NDVI705, VOG1, MSR and TCARI/OSAVI) showing the best results were employed to study spatial gradients as well as temporal changes. The detected gradients are in accordance with ground truth data on representative trees. The obtained results indicate that the original significant differences between the damaged and undamaged stands have been generally levelled until 2013, although it is still possible to detect signs of the previous damages in several cases.

  3. Assessment of EOS Aqua AMSR-E Arctic Sea Ice Concentrations using Landsat-7 and Airborne Microwave Imagery

    NASA Technical Reports Server (NTRS)

    Cavalieri, Donald J.; Markus, Thorsten; Hall, Dorothy K.; Gasiewski, Albin J.; Klein, Marian; Ivanoff, Alvaro

    2006-01-01

    An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (approx. 1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (approx. 10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points.

  4. Cloud-shadow suppression technique for enhancement of Airborne Thematic Mapper imagery

    SciTech Connect

    Guo, L.J.; Moore, J.M. )

    1993-08-01

    Airborne Thematic Mapper (ATM) data are often degraded by the shadows from clouds above the aircraft during the flight. The spectral information in cloud-shadowed areas is reduced but not totally lost because the reflected energy of diffuse illumination (sky light) reaches the sensors from the shadowed ground despite obstruction of direct solar radiation. The thermal band image is almost unaffected by the temporary change of radiation caused by clouds. An enhancement technique for cloud-shadow suppression has been developed based on differencing, RGB-HSI-RGB transformation, and thermal band modulation. The method suppresses cloud shadows with topographic shading retained; spectral information is retrieved and enhanced. The result is a nearly normal color composite with full topographic expression but without cloud shadows. Such a color composite is easy to interpret for geological structures and lithologies. 6 refs.

  5. Analysis of testbed airborne multispectral scanner data from Superflux II. [Chesapeake Bay plume and James Shelf data

    NASA Technical Reports Server (NTRS)

    Bowker, D. E.; Hardesty, C. A.; Jobson, D. J.; Bahn, G. S.

    1981-01-01

    A test bed aircraft multispectral scanner (TBAMS) was flown during the James Shelf, Plume Scan, and Chesapeake Bay missions as part of the Superflux 2 experiment. Excellent correlations were obtained between water sample measurements of chlorophyll and sediment and TBAMS radiance data. The three-band algorithms used were insensitive to aircraft altitude and varying atmospheric conditions. This was particularly fortunate due to the hazy conditions during most of the experiments. A contour map of sediment, and also chlorophyll, was derived for the Chesapeake Bay plume along the southern Virginia-Carolina coastline. A sediment maximum occurs about 5 nautical miles off the Virginia Beach coast with a chlorophyll maximum slightly shoreward of this. During the James Shelf mission, a thermal anomaly (or front) was encountered about 50 miles from the coast. There was a minor variation in chlorophyll and sediment across the boundary. During the Chesapeake Bay mission, the Sun elevation increased from 50 degrees to over 70 degrees, interfering with the generation of data products.

  6. The Multispectral Imaging Science Working Group. Volume 3: Appendices

    NASA Technical Reports Server (NTRS)

    Cox, S. C. (Editor)

    1982-01-01

    The status and technology requirements for using multispectral sensor imagery in geographic, hydrologic, and geologic applications are examined. Critical issues in image and information science are identified.

  7. Design and modeling of spectral-thermal unmixing targets for airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Clare, Phil

    2006-05-01

    Techniques to determine the proportions of constituent materials within a single pixel spectrum are well documented in the reflective (0.4-2.5μm) domain. The same capability is also desirable for the thermal (7-14μm) domain, but is complicated by the thermal contributions to the measured spectral radiance. Atmospheric compensation schemes for the thermal domain have been described along with methods for estimating the spectral emissivity from a spectral radiance measurement and hence the next stage to be tackled is the unmixing of thermal spectral signatures. In order to pursue this goal it is necessary to collect data of well-calibrated targets which will expose the limits of the available techniques and enable more robust methods to be designed. This paper describes the design of a set of ground targets for an airborne hyperspectral imager, which will test the effectiveness of available methods. The set of targets include panels to explore a number of difficult scenarios such as isothermal (different materials at identical temperature), isochromal (identical materials, but at differing temperatures), thermal adjacency and thermal point sources. Practical fabrication issues for heated targets and selection of appropriate materials are described. Mathematical modelling of the experiments has enabled prediction of at-sensor measured radiances which are used to assess the design parameters. Finally, a number of useful lessons learned during the fielding of these actual targets are presented to assist those planning future trials of thermal hyperspectral sensors.

  8. FireMapper 2.0: a multispectral uncooled infrared imaging system for airborne wildfire mapping and remote sensing

    NASA Astrophysics Data System (ADS)

    Hoffman, James W.; Riggan, Philip J.; Griffin, Stephanie A.; Grush, Ronald C.; Grush, William H.; Pena, James

    2003-11-01

    FireMapper®2.0 is a second-generation airborne system developed specifically for wildfire mapping and remote sensing. Its design is based on lessons learned from two years of flight-testing of a research FireMapper® system by the Pacific uthwest Research Station of the USDA Forest Service. The new, operational design features greater coverage and improved performance with a rugged sensor that is less than one third the size and weight of the original research sensor. The sensor obtains thermal infrared images in two narrow spectral bands and one wide spectral band with the use of a single uncooled microbolometer detector array. The dynamic range of the sensor is designed to accurately measure scene temperatures from normal backgrounds, for remote sensing and disaster management applications, up to flaming fronts without saturating. All three channels are extremely linear and are calibrated in-flight with a highly accurate absolute calibration system. Airborne testing of the research system has led to improved displays and simplified operator interfaces. These features facilitate the operational use of the FireMapper®2.0 system on both fixed wing aircraft and helicopters with minimal operator inputs. The operating system features custom software to display and zoom in on the images in realtime as they are obtained. Selected images can also be saved and recalled for detailed study. All images are tagged with GPS date, time, latitude, longitude, altitude, and heading and can be recorded on a portable USB hard drive upon operator command. The operating system can also be used to replay previously recorded image sequences. The FireMapper® 2.0 was designed and fabricated by Space Instruments, Inc. as part of a Research Joint Venture with the USDA Forest Service.

  9. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    NASA Technical Reports Server (NTRS)

    Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2001-01-01

    Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

  10. Mapping of macro and micro nutrients of mixed pastures using airborne AisaFENIX hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Pullanagari, R. R.; Kereszturi, Gábor; Yule, I. J.

    2016-07-01

    On-farm assessment of mixed pasture nutrient concentrations is important for animal production and pasture management. Hyperspectral imaging is recognized as a potential tool to quantify the nutrient content of vegetation. However, it is a great challenge to estimate macro and micro nutrients in heterogeneous mixed pastures. In this study, canopy reflectance data was measured by using a high resolution airborne visible-to-shortwave infrared (Vis-SWIR) imaging spectrometer measuring in the wavelength region 380-2500 nm to predict nutrient concentrations, nitrogen (N) phosphorus (P), potassium (K), sulfur (S), zinc (Zn), sodium (Na), manganese (Mn) copper (Cu) and magnesium (Mg) in heterogeneous mixed pastures across a sheep and beef farm in hill country, within New Zealand. Prediction models were developed using four different methods which are included partial least squares regression (PLSR), kernel PLSR, support vector regression (SVR), random forest regression (RFR) algorithms and their performance compared using the test data. The results from the study revealed that RFR produced highest accuracy (0.55 ⩽ R2CV ⩽ 0.78; 6.68% ⩽ nRMSECV ⩽ 26.47%) compared to all other algorithms for the majority of nutrients (N, P, K, Zn, Na, Cu and Mg) described, and the remaining nutrients (S and Mn) were predicted with high accuracy (0.68 ⩽ R2CV ⩽ 0.86; 13.00% ⩽ nRMSECV ⩽ 14.64%) using SVR. The best training models were used to extrapolate over the whole farm with the purpose of predicting those pasture nutrients and expressed through pixel based spatial maps. These spatially registered nutrient maps demonstrate the range and geographical location of often large differences in pasture nutrient values which are normally not measured and therefore not included in decision making when considering more effective ways to utilized pasture.

  11. Airborne multispectral remote sensing data to estimate several oenological parameters in vineyard production. A case study of application of remote sensing data to precision viticulture in central Italy.

    NASA Astrophysics Data System (ADS)

    Tramontana, Gianluca; Girard, Filippo; Belli, Claudio; Comandini, Maria Cristina; Pietromarchi, Paolo; Tiberi, Domenico; Papale, Dario

    2010-05-01

    It is widely recognized that environmental differences within the vineyard, with respect to soils, microclimate, and topography, can influence grape characteristics and crop yields. Besides, the central Italy landscape is characterized by a high level of fragmentation and heterogeneity It requires stringent Remote sensing technical features in terms of spectral, geometric and temporal resolution to aimed at supporting applications for precision viticulture. In response to the needs of the Italian grape and wine industry for an evaluation of precision viticulture technologies, the DISAFRI (University of Tuscia) and the Agricultural Research Council - Oenological research unit (ENC-CRA) jointly carried out an experimental study during the year 2008. The study was carried out on 2 areas located in the town of Velletri, near Rome; for each area, two varieties (red and white grape) were studied: Nero d'Avola and Sauvignon blanc in first area , Merlot and Sauvignon blanc in second. Remote sensing data were acquired in different periods using a low cost multisensor Airborne remote sensing platform developed by DISAFRI (ASPIS-2 Advanced Spectroscopic Imager System). ASPIS-2, an evolution of the ASPIS sensor (Papale et al 2008, Sensors), is a multispectral sensor based on 4 CCD and 3 interferential filters per CCD. The filters are user selectable during the flight and in this way Aspis is able to acquire data in 12 bands in the visible and near infrared regions with a bandwidth of 10 or 20 nm. To the purposes of this study 7 spectral band were acquired and 15 vegetation indices calculated. During the ripeness period several vegetative and oenochemical parameters were monitored. Anova test shown that several oenochemical variables, such as sugars, total acidity, polyphenols and anthocyanins differ according to the variety taken into consideration. In order to evaluate the time autocorrelation of several oenological parameters value, a simple linear regression between

  12. An algorithm for the estimation of bounds on the emissivity and temperatures from thermal multispectral airborne remotely sensed data

    NASA Technical Reports Server (NTRS)

    Jaggi, S.; Quattrochi, D.; Baskin, R.

    1992-01-01

    The effective flux incident upon the detectors of a thermal sensor, after it has been corrected for atmospheric effects, is a function of a non-linear combination of the emissivity of the target for that channel and the temperature of the target. The sensor system cannot separate the contribution from the emissivity and the temperature that constitute the flux value. A method that estimates the bounds on these temperatures and emissivities from thermal data is described. This method is then tested with remotely sensed data obtained from NASA's Thermal Infrared Multispectral Scanner (TIMS) - a 6 channel thermal sensor. Since this is an under-determined set of equations i.e. there are 7 unknowns (6 emissivities and 1 temperature) and 6 equations (corresponding to the 6 channel fluxes), there exist theoretically an infinite combination of values of emissivities and temperature that can satisfy these equations. Using some realistic bounds on the emissivities, bounds on the temperature are calculated. These bounds on the temperature are refined to estimate a tighter bound on the emissivity of the source. An error analysis is also carried out to quantitatively determine the extent of uncertainty introduced in the estimate of these parameters. This method is useful only when a realistic set of bounds can be obtained for the emissivities of the data. In the case of water the lower and upper bounds were set at 0.97 and 1.00 respectively. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected with the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. Ground truth temperatures using thermometers and radiometers were also obtained over an area of the reservoir. The results of two independent runs of the radiometer data averaged

  13. Forest Inventory Attribute Estimation Using Airborne Laser Scanning, Aerial Stereo Imagery, Radargrammetry and Interferometry-Finnish Experiences of the 3d Techniques

    NASA Astrophysics Data System (ADS)

    Holopainen, M.; Vastaranta, M.; Karjalainen, M.; Karila, K.; Kaasalainen, S.; Honkavaara, E.; Hyyppä, J.

    2015-03-01

    Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry and interferometry. Airborne stereo imagery can be used in deriving photogrammetric point clouds, as very-high-resolution synthetic aperture radar (SAR) data are used in radargrammetry and interferometry. ALS is capable of mapping both the terrain and tree heights in mixed forest conditions, which is an advantage over aerial images or SAR data. However, in many jurisdictions, a detailed ALS-based digital terrain model is already available, and that enables linking photogrammetric or SAR-derived heights to heights above the ground. In other words, in forest conditions, the height of single trees, height of the canopy and/or density of the canopy can be measured and used in estimation of forest inventory attributes. In this paper, first we review experiences of the use of digital stereo imagery and spaceborne SAR in estimation of forest inventory attributes in Finland, and we compare techniques to ALS. In addition, we aim to present new implications based on our experiences.

  14. A comparison of airborne GEMS/SAR with satellite-borne Seasat/SAR radar imagery - The value of archived multiple data sets

    NASA Technical Reports Server (NTRS)

    Hanson, Bradford C.; Dellwig, Louis F.

    1988-01-01

    In a study concerning the value of using radar imagery from systems with diverse parameters, X-band images of the Northern Louisiana Salt dome area generated by the airborne Goodyear electronic mapping system (GEMS) are analyzed in conjunction with imagery generated by the satelliteborne Seasat/SAR. The GEMS operated with an incidence angle of 75 to 85 deg and a resolution of 12 m, whereas the Seasat/SAR operated with an incidence angle of 23 deg and a resolution of 25 m. It is found that otherwise unattainable data on land management activities, improved delineation of the drainage net, better definition of surface roughness in cleared areas, and swamp identification, became accessible when adjustments for the time lapse between the two missions were made and supporting ground data concerning the physical and vegetative characteristics of the terrain were acquired.

  15. Multispectral observations of the surf zone

    NASA Astrophysics Data System (ADS)

    Schoonmaker, Jon S.; Dirbas, Joseph; Gilbert, Gary

    2003-09-01

    Airborne multispectral imagery was collected over various targets on the beach and in the water in an attempt to characterize the surf zone environment with respect to electro-optical system capabilities and to assess the utility of very low cost, small multispectral systems in mine counter measures (MCM) and intelligence, surveillance and reconnaissance applications. The data was collected by PAR Government Systems Corporation (PGSC) at the Army Corps of Engineers Field Research Facility at Duck North Carolina and on the beaches of Camp Pendleton Marine Corps Base in Southern California. PGSC flew the first two of its MANTIS (Mission Adaptable Narrowband Tunable Imaging Sensor) systems. Both MANTIS systems were flown in an IR - red - green - blue (700, 600, 550, 480 nm) configuration from altitudes ranging from 200 to 700 meters. Data collected has been lightly analyzed and a surf zone index (SZI) defined and calculated. This index allows mine hunting system performance measurements in the surf zone to be normalized by environmental conditions. The SZI takes into account water clarity, wave energy, and foam persistence.

  16. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    NASA Astrophysics Data System (ADS)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  17. Forest fuel treatment detection using multi-temporal airborne Lidar data and high resolution aerial imagery ---- A case study at Sierra Nevada, California

    NASA Astrophysics Data System (ADS)

    Su, Y.; Guo, Q.; Collins, B.; Fry, D.; Kelly, M.

    2014-12-01

    Forest fuel treatments (FFT) are often employed in Sierra Nevada forest (located in California, US) to enhance forest health, regulate stand density, and reduce wildfire risk. However, there have been concerns that FFTs may have negative impacts on certain protected wildlife species. Due to the constraints and protection of resources (e.g., perennial streams, cultural resources, wildlife habitat, etc.), the actual FFT extents are usually different from planned extents. Identifying the actual extent of treated areas is of primary importance to understand the environmental influence of FFTs. Light detection and ranging (Lidar) is a powerful remote sensing technique that can provide accurate forest structure measurements, which provides great potential to monitor forest changes. This study used canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne Lidar data to detect FFTs by an approach combining a pixel-wise thresholding method and a object-of-interest segmentation method. We also investigated forest change following the implementation of landscape-scale FFT projects through the use of normalized difference vegetation index (NDVI) and standardized principle component analysis (PCA) from multi-temporal high resolution aerial imagery. The same FFT detection routine was applied on the Lidar data and aerial imagery for the purpose of comparing the capability of Lidar data and aerial imagery on FFT detection. Our results demonstrated that the FFT detection using Lidar derived CC products produced both the highest total accuracy and kappa coefficient, and was more robust at identifying areas with light FFTs. The accuracy using Lidar derived CHM products was significantly lower than that of the result using Lidar derived CC, but was still slightly higher than using aerial imagery. FFT detection results using NDVI and standardized PCA using multi-temporal aerial imagery produced almost identical total accuracy and kappa coefficient

  18. Evolution of a highly dilatant fault zone in the grabens of Canyonlands National Park, Utah, USA - integrating fieldwork, ground-penetrating radar and airborne imagery analysis

    NASA Astrophysics Data System (ADS)

    Kettermann, M.; Grützner, C.; van Gent, H. W.; Urai, J. L.; Reicherter, K.; Mertens, J.

    2015-07-01

    The grabens of Canyonlands National Park are a young and active system of sub-parallel, arcuate grabens, whose evolution is the result of salt movement in the subsurface and a slight regional tilt of the faulted strata. We present results of ground-penetrating radar (GPR) surveys in combination with field observations and analysis of high-resolution airborne imagery. GPR data show intense faulting of the Quaternary sediments at the flat graben floors, implying a more complex fault structure than visible at the surface. Direct measurements of heave and throw at several locations to infer fault dips at depth, combined with observations of primary joint surfaces in the upper 100 m, suggest a highly dilatant fault geometry. Sinkholes observed in the field as well as in airborne imagery give insights in local dilatancy and show where water and sediments are transported underground. Based on correlations of paleosols observed in outcrops and GPR profiles, we argue that either the grabens in Canyonlands National Park are older than previously assumed or that sedimentation rates were much higher in the Pleistocene.

  19. Michigan experimental multispectral scanner system

    NASA Technical Reports Server (NTRS)

    Hasell, P. G., Jr.

    1972-01-01

    A functional description of a multispectral airborne scanner system that provides spectral bands along a single optical line of sight is reported. The airborne scanner consists of an optical telescope for scanning plane perpendicular to the longitudinal axis of the aircraft and radiation detectors for converting radiation to electrical signals. The system makes a linear transformation of input radiation to voltage recorded on analog magnetic tape.

  20. Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Brook, Anna; Wittenberg, Lea

    2015-04-01

    promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.

  1. Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

    PubMed Central

    de Castro, Ana-Isabel; Jurado-Expósito, Montserrat; Gómez-Casero, María-Teresa; López-Granados, Francisca

    2012-01-01

    In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops. PMID:22629171

  2. Improved capabilities of the Multispectral Atmospheric Mapping Sensor (MAMS)

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Batson, K. Bryan; Atkinson, Robert J.; Moeller, Chris C.; Menzel, W. Paul; James, Mark W.

    1989-01-01

    The Multispectral Atmospheric Mapping Sensor (MAMS) is an airborne instrument being investigated as part of NASA's high altitude research program. Findings from work on this and other instruments have been important as the scientific justification of new instrumentation for the Earth Observing System (EOS). This report discusses changes to the instrument which have led to new capabilities, improved data quality, and more accurate calibration methods. In order to provide a summary of the data collected with MAMS, a complete list of flight dates and locations is provided. For many applications, registration of MAMS imagery with landmarks is required. The navigation of this data on the Man-computer Interactive Data Access System (McIDAS) is discussed. Finally, research applications of the data are discussed and specific examples are presented to show the applicability of these measurements to NASA's Earth System Science (ESS) objectives.

  3. An approach to optimal hyperspectral and multispectral signature and image fusion for detecting hidden targets on shorelines

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.

    2015-10-01

    Hyperspectral and multispectral imagery of shorelines collected from airborne and shipborne platforms are used following pushbroom imagery corrections using inertial motion motions units and augmented global positioning data and Kalman filtering. Corrected radiance or reflectance images are then used to optimize synthetic high spatial resolution spectral signatures resulting from an optimized data fusion process. The process demonstrated utilizes littoral zone features from imagery acquired in the Gulf of Mexico region. Shoreline imagery along the Banana River, Florida, is presented that utilizes a technique that makes use of numerically embedded targets in both higher spatial resolution multispectral images and lower spatial resolution hyperspectral imagery. The fusion process developed utilizes optimization procedures that include random selection of regions and pixels in the imagery, and minimizing the difference between the synthetic signatures and observed signatures. The optimized data fusion approach allows detection of spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using numerically embedded line targets within actual imagery. The approach allows one to test spectral signature anomaly detection and to identify features and targets. The optimized data fusion techniques and software allows one to perform sensitivity analysis and optimization in the singular value decomposition model building process and the 2-D Butterworth cutoff frequency and order numerical selection process. The data fusion "synthetic imagery" forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within "spectral anomaly areas". Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K

  4. Remote distinction of a noxious weed (musk thistle: Carduus nutans) using airborne hyperspectral imagery and the support vector machine classifier

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote detection of invasive plant species using geospatial imagery may significantly improve monitoring, planning, and management practices by eliminating shortfalls such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion ex...

  5. Challenges in collecting hyperspectral imagery of coastal waters using Unmanned Aerial Vehicles (UAVs)

    NASA Astrophysics Data System (ADS)

    English, D. C.; Herwitz, S.; Hu, C.; Carlson, P. R., Jr.; Muller-Karger, F. E.; Yates, K. K.; Ramsewak, D.

    2013-12-01

    Airborne multi-band remote sensing is an important tool for many aquatic applications; and the increased spectral information from hyperspectral sensors may increase the utility of coastal surveys. Recent technological advances allow Unmanned Aerial Vehicles (UAVs) to be used as alternatives or complements to manned aircraft or in situ observing platforms, and promise significant advantages for field studies. These include the ability to conduct programmed flight plans, prolonged and coordinated surveys, and agile flight operations under difficult conditions such as measurements made at low altitudes. Hyperspectral imagery collected from UAVs should allow the increased differentiation of water column or shallow benthic communities at relatively small spatial scales. However, the analysis of hyperspectral imagery from airborne platforms over shallow coastal waters differs from that used for terrestrial or oligotrophic ocean color imagery, and the operational constraints and considerations for the collection of such imagery from autonomous platforms also differ from terrestrial surveys using manned aircraft. Multispectral and hyperspectral imagery of shallow seagrass and coral environments in the Florida Keys were collected with various sensor systems mounted on manned and unmanned aircrafts in May 2012, October 2012, and May 2013. The imaging systems deployed on UAVs included NovaSol's Selectable Hyperspectral Airborne Remote-sensing Kit (SHARK), a Tetracam multispectral imaging system, and the Sunflower hyperspectal imager from Galileo Group, Inc. The UAVs carrying these systems were Xtreme Aerial Concepts' Vision-II Rotorcraft UAV, MLB Company's Bat-4 UAV, and NASA's SIERRA UAV, respectively. Additionally, the Galileo Group's manned aircraft also surveyed the areas with their AISA Eagle hyperspectral imaging system. For both manned and autonomous flights, cloud cover and sun glint (solar and viewing angles) were dominant constraints on retrieval of quantitatively

  6. The use of ERTS/LANDSAT imagery in relation to airborne remote sensing for terrain analysis in Western Queensland, Australia

    NASA Technical Reports Server (NTRS)

    Cole, M. M. (Principal Investigator); Owen-Jones, E. S.

    1976-01-01

    The author has identified the following significant results. LANDSAT 1 and 2 imagery contrast the geology of the Cloncurry-Dobbyn and the Gregory River-Mt. Isa areas very clearly. Known major structural features and lithological units are clearly displayed while, hitherto unknown lineaments were revealed. Throughout this area, similar rock types produce similar spectral signatures, e.g. quartzites produce light signatures, iron rich rocks produce dark signatures. More geological data are discernible at the 1:50,000 scale than on the 1:250,000 scale. Ore horizons may be identified at the 1:50,000 scale, particularly where they are associated with iron rich rocks. On the level plains north of Cloncurry, distinctive spectral signatures produced by the combined reflectances of plant cover, soils, and geology, distinguish different types of superficial deposits. Existing and former channels of the Cloncurry and Williams Rivers are distinguished at the 1:50,000 scale on both the LANDSAT 1 and 2 imagery. On the Cloncurry Plains, fence lines are discernible on the 1:50,000 LANDSAT 2 imagery.

  7. Automatic Extraction of Optimal Endmembers from Airborne Hyperspectral Imagery Using Iterative Error Analysis (IEA) and Spectral Discrimination Measurements

    PubMed Central

    Song, Ahram; Chang, Anjin; Choi, Jaewan; Choi, Seokkeun; Kim, Yongil

    2015-01-01

    Pure surface materials denoted by endmembers play an important role in hyperspectral processing in various fields. Many endmember extraction algorithms (EEAs) have been proposed to find appropriate endmember sets. Most studies involving the automatic extraction of appropriate endmembers without a priori information have focused on N-FINDR. Although there are many different versions of N-FINDR algorithms, computational complexity issues still remain and these algorithms cannot consider the case where spectrally mixed materials are extracted as final endmembers. A sequential endmember extraction-based algorithm may be more effective when the number of endmembers to be extracted is unknown. In this study, we propose a simple but accurate method to automatically determine the optimal endmembers using such a method. The proposed method consists of three steps for determining the proper number of endmembers and for removing endmembers that are repeated or contain mixed signatures using the Root Mean Square Error (RMSE) images obtained from Iterative Error Analysis (IEA) and spectral discrimination measurements. A synthetic hyperpsectral image and two different airborne images such as Airborne Imaging Spectrometer for Application (AISA) and Compact Airborne Spectrographic Imager (CASI) data were tested using the proposed method, and our experimental results indicate that the final endmember set contained all of the distinct signatures without redundant endmembers and errors from mixed materials. PMID:25625907

  8. Mapping variations in weight percent silica measured from multispectral thermal infrared imagery - Examples from the Hiller Mountains, Nevada, USA and Tres Virgenes-La Reforma, Baja California Sur, Mexico

    USGS Publications Warehouse

    Hook, S.J.; Dmochowski, J.E.; Howard, K.A.; Rowan, L.C.; Karlstrom, K.E.; Stock, J.M.

    2005-01-01

    Remotely sensed multispectral thermal infrared (8-13 ??m) images are increasingly being used to map variations in surface silicate mineralogy. These studies utilize the shift to longer wavelengths in the main spectral feature in minerals in this wavelength region (reststrahlen band) as the mineralogy changes from felsic to mafic. An approach is described for determining the amount of this shift and then using the shift with a reference curve, derived from laboratory data, to remotely determine the weight percent SiO2 of the surface. The approach has broad applicability to many study areas and can also be fine-tuned to give greater accuracy in a particular study area if field samples are available. The approach was assessed using airborne multispectral thermal infrared images from the Hiller Mountains, Nevada, USA and the Tres Virgenes-La Reforma, Baja California Sur, Mexico. Results indicate the general approach slightly overestimates the weight percent SiO2 of low silica rocks (e.g. basalt) and underestimates the weight percent SiO2 of high silica rocks (e.g. granite). Fine tuning the general approach with measurements from field samples provided good results for both areas with errors in the recovered weight percent SiO2 of a few percent. The map units identified by these techniques and traditional mapping at the Hiller Mountains demonstrate the continuity of the crystalline rocks from the Hiller Mountains southward to the White Hills supporting the idea that these ranges represent an essentially continuous footwall block below a regional detachment. Results from the Baja California data verify the most recent volcanism to be basaltic-andesite. ?? 2005 Elsevier Inc. All rights reserved.

  9. Undercomplete learned dictionaries for land cover classification in multispectral imagery of Arctic landscapes using CoSA: clustering of sparse approximations

    NASA Astrophysics Data System (ADS)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Gangodagamage, Chandana

    2013-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a Hebbian learning rule to build undercomplete spectral-textural dictionaries that are adapted to the data. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using our CoSA algorithm: unsupervised Clustering of Sparse Approximations. We demonstrate our method using multispectral Worldview-2 data from three Arctic study areas: Barrow, Alaska; the Selawik River, Alaska; and a watershed near the Mackenzie River delta in northwest Canada. Our goal is to develop a robust classification methodology that will allow for the automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and geomorphic characteristics. To interpret and assign land cover categories to the clusters we both evaluate the spectral properties of the clusters and compare the clusters to both field- and remote sensing-derived classifications of landscape attributes. Our work suggests that neuroscience-based models are a promising approach to practical pattern recognition problems in remote sensing.

  10. An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

    NASA Technical Reports Server (NTRS)

    Jaggi, S.

    1993-01-01

    A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

  11. General pattern of the turbid water in the Seto-inland sea extracted from multispectral imageries by the LANDSAT-1 and 2

    NASA Technical Reports Server (NTRS)

    Maruyasu, T. (Principal Investigator); Watanabe, K.

    1976-01-01

    The author has identified the following significant results. Each distribution pattern of turbid water changes with the time in accordance with daily tides, seasonal variation of tides, and occasional rainfall. Two cases of successfully repeated LANDSAT observations for the same sea regions suggested a general pattern of turbid water could be extracted for each region. Photographic and digital processes were used to extract patterns of turbid water separately from the cloud and smog-layer in MSS 4, 5, and 7 imageries. A mosaic of image-masked imageries displays a general pattern of turbid water for almost the entire Seto Inland Sea. No such pattern was extracted for the Aki-Nada south of Hiroshima City where the water is fairly polluted, nor for the Iyo-Nada where the water is generally clearer than in other regions of the Seto Inland Sea.

  12. Developing a semi/automated protocol to post-process large volume, High-resolution airborne thermal infrared (TIR) imagery for urban waste heat mapping

    NASA Astrophysics Data System (ADS)

    Rahman, Mir Mustafizur

    In collaboration with The City of Calgary 2011 Sustainability Direction and as part of the HEAT (Heat Energy Assessment Technologies) project, the focus of this research is to develop a semi/automated 'protocol' to post-process large volumes of high-resolution (H-res) airborne thermal infrared (TIR) imagery to enable accurate urban waste heat mapping. HEAT is a free GeoWeb service, designed to help Calgary residents improve their home energy efficiency by visualizing the amount and location of waste heat leaving their homes and communities, as easily as clicking on their house in Google Maps. HEAT metrics are derived from 43 flight lines of TABI-1800 (Thermal Airborne Broadband Imager) data acquired on May 13--14, 2012 at night (11:00 pm--5:00 am) over The City of Calgary, Alberta (˜825 km 2) at a 50 cm spatial resolution and 0.05°C thermal resolution. At present, the only way to generate a large area, high-spatial resolution TIR scene is to acquire separate airborne flight lines and mosaic them together. However, the ambient sensed temperature within, and between flight lines naturally changes during acquisition (due to varying atmospheric and local micro-climate conditions), resulting in mosaicked images with different temperatures for the same scene components (e.g. roads, buildings), and mosaic join-lines arbitrarily bisect many thousands of homes. In combination these effects result in reduced utility and classification accuracy including, poorly defined HEAT Metrics, inaccurate hotspot detection and raw imagery that are difficult to interpret. In an effort to minimize these effects, three new semi/automated post-processing algorithms (the protocol) are described, which are then used to generate a 43 flight line mosaic of TABI-1800 data from which accurate Calgary waste heat maps and HEAT metrics can be generated. These algorithms (presented as four peer-reviewed papers)---are: (a) Thermal Urban Road Normalization (TURN)---used to mitigate the microclimatic

  13. Band-to-band registration and ortho-rectification of multilens/multispectral imagery: A case study of MiniMCA-12 acquired by a fixed-wing UAS

    NASA Astrophysics Data System (ADS)

    Jhan, Jyun-Ping; Rau, Jiann-Yeou; Huang, Cho-Ying

    2016-04-01

    MiniMCA (Miniature Multiple Camera Array) is a lightweight, frame-based, and multilens composed multispectral sensor, which is suitable to mount on an unmanned aerial systems (UAS) to acquire high spatial and temporal resolution imagery for various remote sensing applications. Since MiniMCA has significant band misregistration effect, an automatic and precise band-to-band registration (BBR) method is proposed in this study. Based on the principle of sensor plane-to-plane projection, a modified projective transformation (MPT) model is developed. It is to estimate all coefficients of MPT from indoor camera calibration, together with two systematic errors correction. Therefore, we can transfer all bands into the same image space. Quantitative error analysis shows that the proposed BBR scheme is scene independent and can achieve 0.33 pixels of accuracy, which demonstrating the proposed method is accurate and reliable. Meanwhile, it is difficult to mark ground control points (GCPs) on the MiniMCA images, as its spatial resolution is low when the flight height is higher than 400 m. In this study, a higher resolution RGB camera is adopted to produce digital surface model (DSM) and assist MiniMCA ortho-image generation. After precise BBR, only one reference band of MiniMCA image is necessary for aerial triangulation because all bands have same exterior and interior orientation parameters. It means that all the MiniMCA imagery can be ortho-rectified through the same exterior and interior orientation parameters of the reference band. The result of the proposed ortho-rectification procedure shows the co-registration errors between MiniMCA reference band and the RGB ortho-images is less than 0.6 pixels.

  14. Analyses of the cloud contents of multispectral imagery from LANDSAT 2: Mesoscale assessments of cloud and rainfall over the British Isles

    NASA Technical Reports Server (NTRS)

    Barrett, E. C.; Grant, C. K. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total cloud amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, cloud shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the cloud itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of clouds in summer revealed marked differences between the reflectance characteristics of cloud fields in the visible/near infrared region of the spectrum.

  15. Airborne imaging sensors for environmental monitoring & surveillance in support of oil spills & recovery efforts

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Jones, James; Frystacky, Heather; Coppin, Gaelle; Leavaux, Florian; Neyt, Xavier

    2011-11-01

    Collection of pushbroom sensor imagery from a mobile platform requires corrections using inertial measurement units (IMU's) and DGPS in order to create useable imagery for environmental monitoring and surveillance of shorelines in freshwater systems, coastal littoral zones and harbor areas. This paper describes a suite of imaging systems used during collection of hyperspectral imagery in northern Florida panhandle and Gulf of Mexico airborne missions to detect weathered oil in coastal littoral zones. Underlying concepts of pushbroom imagery, the needed corrections for directional changes using DGPS and corrections for platform yaw, pitch, and roll using IMU data is described as well as the development and application of optimal band and spectral regions associated with weathered oil. Pushbroom sensor and frame camera data collected in response to the recent Gulf of Mexico oil spill disaster is presented as the scenario documenting environmental monitoring and surveillance techniques using mobile sensing platforms. Data was acquired during the months of February, March, April and May of 2011. The low altitude airborne systems include a temperature stabilized hyperspectral imaging system capable of up to 1024 spectral channels and 1376 spatial across track pixels flown from 3,000 to 4,500 feet altitudes. The hyperspectral imaging system is collocated with a full resolution high definition video recorder for simultaneous HD video imagery, a 12.3 megapixel digital, a mapping camera using 9 inch film types that yields scanned aerial imagery with approximately 22,200 by 22,200 pixel multispectral imagery (~255 megapixel RGB multispectral images in order to conduct for spectral-spatial sharpening of fused multispectral, hyperspectral imagery. Two high spectral (252 channels) and radiometric sensitivity solid state spectrographs are used for collecting upwelling radiance (sub-meter pixels) with downwelling irradiance fiber optic attachment. These sensors are utilized for

  16. Multispectral data compression through transform coding and block quantization

    NASA Technical Reports Server (NTRS)

    Ready, P. J.; Wintz, P. A.

    1972-01-01

    Transform coding and block quantization techniques are applied to multispectral aircraft scanner data, and digitized satellite imagery. The multispectral source is defined and an appropriate mathematical model proposed. The Karhunen-Loeve, Fourier, and Hadamard encoders are considered and are compared to the rate distortion function for the equivalent Gaussian source and to the performance of the single sample PCM encoder.

  17. a Comparison of LIDAR Reflectance and Radiometrically Calibrated Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Roncat, A.; Briese, C.; Pfeifer, N.

    2016-06-01

    In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a "single-wavelength reflectometer" to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

  18. The use of ERTS/LANDSAT imagery in relation to airborne remote sensing for terrain analysis in western Queensland, Australia

    NASA Technical Reports Server (NTRS)

    Cole, M. M. (Principal Investigator); Owen-Jones, S.

    1976-01-01

    The author has identified the following significant results. Distinctive spectral signatures were found associated with areas of near surface bedrock with covered ground east of Dugald River and along the Thorntonia River valley west of Lady Annie. Linears identified in the Dugald River area on LANDSAT 2 imagery taken in March and July 1975 over the Cloncurry-Dobbyn area, displayed preferred orientation. A linear group with NE-SW orientation was identified in the Lady Annie area. In this area, the copper mineralization in the Mt. Kelly area occurs along a well marked linear with NNW/SSE direction apparent on images for March, September, and November 1975. Geobotanical anomalies provided surface expression of the copper deposits in Mt. Kelley.

  19. Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of European corn borer infestation in Iowa corn plots.

    PubMed

    Carroll, Matthew W; Glaser, John A; Hellmich, Richard L; Hunt, Thomas E; Sappington, Thomas W; Calvin, Dennis; Copenhaver, Ken; Fridgen, John

    2008-10-01

    Eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery and evaluated in 2004 and 2005 for their ability to detect experimental plots of corn manually inoculated with Ostrinia nubilalis (Hübner) neonate larvae. Manual inoculations were timed to simulate infestation of corn, Zea mays L., by first and second flights of adult O. nubilalis. The ability of spectral vegetation indices to detect O. nubilalis-inoculated plots improved as the growing season progressed, with multiple spectral vegetation indices able to identify infested plots in late August and early September. Our findings also indicate that for detecting O. nubilalis-related plant stress in corn, spectral vegetation indices targeting carotenoid and anthocyanin pigments are not as effective as those targeting chlorophyll. Analysis of image data suggests that feeding and stem boring by O. nubilalis larvae may increase the rate of plant senescence causing detectable differences in plant biomass and vigor when compared with control plots. Further, we identified an approximate time frame of 5-6 wk postinoculation, when spectral differences of manually inoculated "second" generation O. nubilalis plots seem to peak. PMID:18950044

  20. Inversion study of rainfall intensity field at all time during Mei-Yu period by using MTSAT multi-spectral imagery

    NASA Astrophysics Data System (ADS)

    Wang, Chenxi; Yu, Fan; Zhao, Yongjing

    2008-12-01

    The retrieval of MTSAT multi-spectral satellite image rainfall intensity field was studied, with which the "Unit-Feature Spatial Classification (UFSC) method" was proposed to become the foremost basis of the possibility of continuous observation of real-time precipitation from geostationary satellite. In this method, MTSAT multi-spectral satellite measured value and measured precipitation rate from high density ground stations of plum rain season in east china (Jiangsu Province, Zhejiang Province and Anhui Province) in 2007 are combined to conduct the cooperative analysis, and therefore the distribution features of the level of each precipitation probability and each precipitation intensity are well established on different two-dimensional and three-dimensional spectral feature spaces. On the basis, the discrimination matrices, correspondingly, are established for precipitation probability and precipitation intensity of different spectral combinations. Different spectral combinations are used for the construction of the discrimination matrices of the day and the night, respectively. For the day, IR1 (11µm), IR3 (6.7μm), VIS (0.7m), IR12 (TIR2-IR1) and IR13 (TIR3-IR1) are available, among which IR1, VIS and IR3 (or IR13) are mainly used ; for the night, IR1, IR3, IR4 (3.7μm), IR12, IR13, IR14 (TIR4-IR1)and IR24 (TIR4-IR2) are available and IR1, IR3 and IR24 (or IR14) are mainly used. The contrast test between the observed data of precipitation and the retrieval results based on precipitation data from basic stations and reference stations in China in 2007 shows that, 30% precipitation probability can ideally distinguish precipitation area from non-precipitation area; and the analysis of precipitation intensity category also matches well with the fact. It is well known that the observation of satellite is instantaneous one time per hour while the rain gauge observation is an accumulative process during an hour. The error study further suggests that the

  1. Mapping of lithologic and structural units using multispectral imagery. [Afar-Triangle/Ethiopia and adjacent areas (Ethiopian Plateau, Somali Plateau, and parts of Yemen and Saudi Arabia)

    NASA Technical Reports Server (NTRS)

    Kronberg, P. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. ERTS-1 MSS imagery covering the Afar-Triangle/Ethiopia and adjacent regions (Ethiopian Plateau, Somali Plateau, and parts of Yemen and Saudi Arabi) was applied to the mapping of lithologic and structural units of the test area at a scale 1:1,000,000. Results of the geological evaluation of the ERTS-1 imagery of the Afar have proven the usefullness of this type of satellite data for regional geological mapping. Evaluation of the ERTS images also resulted in new aspects of the structural setting and tectonic development of the Afar-Triangle, where three large rift systems, the oceanic rifts of the Red Sea and Gulf of Aden and the continental East African rift system, seem to meet each other. Surface structures mapped by ERTS do not indicate that the oceanic rift of the Gulf of Aden (Sheba Ridge) continues into the area of continental crust west of the Gulf of Tadjura. ERTS data show that the Wonji fault belt of the African rift system does not enter or cut through the central Afar. The Aysha-Horst is not a Horst but an autochthonous spur of the Somali Plateau.

  2. Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

    PubMed

    Diaz-Varela, R A; Zarco-Tejada, P J; Angileri, V; Loudjani, P

    2014-02-15

    Agricultural terraces are features that provide a number of ecosystem services. As a result, their maintenance is supported by measures established by the European Common Agricultural Policy (CAP). In the framework of CAP implementation and monitoring, there is a current and future need for the development of robust, repeatable and cost-effective methodologies for the automatic identification and monitoring of these features at farm scale. This is a complex task, particularly when terraces are associated to complex vegetation cover patterns, as happens with permanent crops (e.g. olive trees). In this study we present a novel methodology for automatic and cost-efficient identification of terraces using only imagery from commercial off-the-shelf (COTS) cameras on board unmanned aerial vehicles (UAVs). Using state-of-the-art computer vision techniques, we generated orthoimagery and digital surface models (DSMs) at 11 cm spatial resolution with low user intervention. In a second stage, these data were used to identify terraces using a multi-scale object-oriented classification method. Results show the potential of this method even in highly complex agricultural areas, both regarding DSM reconstruction and image classification. The UAV-derived DSM had a root mean square error (RMSE) lower than 0.5 m when the height of the terraces was assessed against field GPS data. The subsequent automated terrace classification yielded an overall accuracy of 90% based exclusively on spectral and elevation data derived from the UAV imagery. PMID:24473345

  3. Mapping tree health using airborne laser scans and hyperspectral imagery: a case study for a floodplain eucalypt forest

    NASA Astrophysics Data System (ADS)

    Shendryk, Iurii; Tulbure, Mirela; Broich, Mark; McGrath, Andrew; Alexandrov, Sergey; Keith, David

    2016-04-01

    Airborne laser scanning (ALS) and hyperspectral imaging (HSI) are two complementary remote sensing technologies that provide comprehensive structural and spectral characteristics of forests over large areas. In this study we developed two algorithms: one for individual tree delineation utilizing ALS and the other utilizing ALS and HSI to characterize health of delineated trees in a structurally complex floodplain eucalypt forest. We conducted experiments in the largest eucalypt, river red gum forest in the world, located in the south-east of Australia that experienced severe dieback over the past six decades. For detection of individual trees from ALS we developed a novel bottom-up approach based on Euclidean distance clustering to detect tree trunks and random walks segmentation to further delineate tree crowns. Overall, our algorithm was able to detect 67% of tree trunks with diameter larger than 13 cm. We assessed the accuracy of tree delineations in terms of crown height and width, with correct delineation of 68% of tree crowns. The increase in ALS point density from ~12 to ~24 points/m2 resulted in tree trunk detection and crown delineation increase of 11% and 13%, respectively. Trees with incorrectly delineated crowns were generally attributed to areas with high tree density along water courses. The accurate delineation of trees allowed us to classify the health of this forest using machine learning and field-measured tree crown dieback and transparency ratios, which were good predictors of tree health in this forest. ALS and HSI derived indices were used as predictor variables to train and test object-oriented random forest classifier. Returned pulse width, intensity and density related ALS indices were the most important predictors in the tree health classifications. At the forest level in terms of tree crown dieback, 77% of trees were classified as healthy, 14% as declining and 9% as dying or dead with 81% mapping accuracy. Similarly, in terms of tree

  4. An historical empirical line method for the retrieval of surface reflectance factor from multi-temporal SPOT HRV, HRVIR and HRG multispectral satellite imagery

    NASA Astrophysics Data System (ADS)

    Clark, Barnaby; Suomalainen, Juha; Pellikka, Petri

    2011-04-01

    SPOT satellites have been imaging Earth's surface since SPOT 1 was launched in 1986. It is argued that absolute atmospheric correction is a prerequisite for quantitative remote sensing. Areas where land cover changes are occurring rapidly are also often areas most lacking in situ data which would allow full use of radiative transfer models for reflectance factor retrieval (RFR). Consequently, this study details the proposed historical empirical line method (HELM) for RFR from multi-temporal SPOT imagery. HELM is designed for use in landscape level studies in circumstances where no detailed overpass concurrent atmospheric or meteorological data are available, but where there is field access to the research site(s) and a goniometer or spectrometer is available. SPOT data are complicated by the ±27° off-nadir cross track viewing. Calibration to nadir only surface reflectance factor ( ρs) is denoted as HELM-1, whilst calibration to ρs modelling imagery illumination and view geometries is termed HELM-2. Comparisons of field measured ρs with those derived from HELM corrected SPOT imagery, covering Helsinki, Finland, and Taita Hills, Kenya, indicated HELM-1 RFR absolute accuracy was ±0.02 ρs in the visible and near infrared (VIS/NIR) bands and ±0.03 ρs in the shortwave infrared (SWIR), whilst HELM-2 performance was ±0.03 ρs in the VIS/NIR and ±0.04 ρs in the SWIR. This represented band specific relative errors of 10-15%. HELM-1 and HELM-2 RFR were significantly better than at-satellite reflectance ( ρSAT), indicating HELM was effective in reducing atmospheric effects. However, neither HELM approach reduced variability in mean ρs between multi-temporal images, compared to ρSAT. HELM-1 calibration error is dependent on surface characteristics and scene illumination and view geometry. Based on multiangular ρs measurements of vegetation-free ground targets, calibration error was negligible in the forward scattering direction, even at maximum off-nadir view

  5. On the integration of Airborne full-waveform laser scanning and optical imagery for Site Detection and Mapping: Monteserico study case

    NASA Astrophysics Data System (ADS)

    Coluzzi, R.; Guariglia, A.; Lacovara, B.; Lasaponara, R.; Masini, N.

    2009-04-01

    This paper analyses the capability of airborne LiDAR derived data in the recognition of archaeological marks. It also evaluates the benefits to integrate them with aerial photos and very high resolution satellite imagery. The selected test site is Monteserico, a medieval village located on a pastureland hill in the North East of Basilicata (Southern Italy). The site, attested by documentary sources beginning from the 12th century, was discovered by aerial survey in 1996 [1] and investigated in 2005 by using QuickBird imagery [2]. The only architectural evidence is a castle, built on the western top of the hill; whereas on the southern side, earthenware, pottery and crumbling building materials, related to the medieval settlement, could be observed. From a geological point of view, the stratigraphic sequence is composed of Subappennine Clays, Monte Marano sands and Irsina conglomerates. Sporadic herbaceous plants grow over the investigated area. For the purpose of this study, a full-waveform laser scanning with a 240.000 Hz frequency was used. The average point density value of dataset is about 30 points/m2. The final product is a 0.30 m Digital Surface Models (DSMs) accurately modelled. To derive the DSM the point cloud of the ALS was filtered and then classified by applying appropriate algorithms. In this way surface relief and archaeological features were surveyed with great detail. The DSM was compared with other remote sensing data source such as oblique and nadiral aerial photos and QuickBird imagery, acquired in different time. In this way it was possible to evaluate, compare each other and overlay the archaeological features recorded from each data source (aerial, satellite and lidar). Lidar data showed some interesting results. In particular, they allowed for identifying and recording differences in height on the ground produced by surface and shallow archaeological remains (the so-called shadow marks). Most of these features are visible also by the optical

  6. Chernobyl doses. Volume 1. Analysis of forest canopy radiation response from multispectral imagery and the relationship to doses. Technical report, 29 July 1987-30 September 1993

    SciTech Connect

    McClennan, G.E.; Anno, G.H.; Whicker, F.W.

    1994-09-01

    This volume of the report Chernobyl Doses presents details of a new, quantitative method for remotely sensing ionizing radiation dose to vegetation. Analysis of Landsat imagery of the area within a few kilometers of the Chernobyl nuclear reactor station provides maps of radiation dose to pine forest canopy resulting from the accident of April 26, 1986. Detection of the first date of significant, persistent deviation from normal of the spectral reflectance signature of pine foliage produces contours of radiation dose in the 20 to 80 Gy range extending up to 4 km from the site of the reactor explosion. The effective duration of exposure for the pine foliage is about 3 weeks. For this exposure time, the LD50 of Pinus sylvestris (Scotch pine) is about 23 Gy. The practical lower dose limit for the remote detection of radiation dose to pine foliage with the Landsat Thematic Mapper is about 5 Gy or 1/4 of the LD50.

  7. Applications of multispectral imagery to water resources development planning in the lower Mekong Basin (Khmer Republic, Laos, Thailand and Viet-Nam)

    NASA Technical Reports Server (NTRS)

    Vankiere, W. J.

    1973-01-01

    The use of ERTS imagery for water resources planning in the lower Mekong Basin relates to three major issues: (1) it complements data from areas, which have been inaccessible in the past because of security; this concerns mainly forest cover of the watersheds, and geological features, (2) it refines ground surveys; this concerns mainly land forms, and soils of existing and planned irrigation perimeters, and (3) it provides new information, which would be almost or entirely impossible to detect with ground surveys or conventional photography; this concerns the mechanism of flooding and drainage of the delta; siltation of the Great Lake and mapping of acidity, possibly also of salinity, in the lower delta; sedimentation and fisheries in the Mekong Delta estuarine areas.

  8. A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions

    USGS Publications Warehouse

    Selkowitz, David J.; Green, Gordon; Peterson, Birgit; Wylie, Bruce

    2012-01-01

    Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting

  9. Multispectral Photography

    NASA Technical Reports Server (NTRS)

    1982-01-01

    Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

  10. Extrapolation of in situ data from 1-km squares to adjacent squares using remote sensed imagery and airborne lidar data for the assessment of habitat diversity and extent.

    PubMed

    Lang, M; Vain, A; Bunce, R G H; Jongman, R H G; Raet, J; Sepp, K; Kuusemets, V; Kikas, T; Liba, N

    2015-03-01

    Habitat surveillance and subsequent monitoring at a national level is usually carried out by recording data from in situ sample sites located according to predefined strata. This paper describes the application of remote sensing to the extension of such field data recorded in 1-km squares to adjacent squares, in order to increase sample number without further field visits. Habitats were mapped in eight central squares in northeast Estonia in 2010 using a standardized recording procedure. Around one of the squares, a special study site was established which consisted of the central square and eight surrounding squares. A Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image was used for correlation with in situ data. An airborne light detection and ranging (lidar) vegetation height map was also included in the classification. A series of tests were carried out by including the lidar data and contrasting analytical techniques, which are described in detail in the paper. Training accuracy in the central square varied from 75 to 100 %. In the extrapolation procedure to the surrounding squares, accuracy varied from 53.1 to 63.1 %, which improved by 10 % with the inclusion of lidar data. The reasons for this relatively low classification accuracy were mainly inherent variability in the spectral signatures of habitats but also differences between the dates of imagery acquisition and field sampling. Improvements could therefore be made by better synchronization of the field survey and image acquisition as well as by dividing general habitat categories (GHCs) into units which are more likely to have similar spectral signatures. However, the increase in the number of sample kilometre squares compensates for the loss of accuracy in the measurements of individual squares. The methodology can be applied in other studies as the procedures used are readily available. PMID:25648761

  11. Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa

    NASA Astrophysics Data System (ADS)

    Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad

    2013-05-01

    Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicollinearity limit the successful application of the technology. The aim of this study was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n = 230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user's and producer's accuracies ranging from 50% to 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n = 78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user's and producer's accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.

  12. Investigation of a rift zone in the western Fimbulisen by means of airborne radio echo sounding, satellite imagery, and ice flow modelling

    NASA Astrophysics Data System (ADS)

    Humbert, Angelika; Steinhage, Daniel

    2010-05-01

    The Fimbulisen, an ice shelf located roughly between 3°W-8°E at the coast of Dronning Maud Land, East Antarctica, consists of the fast flowing extension of Jutulstraumen and slower moving parts west and east of it. The largely rifted western part of the Fimbulisen is the subject of this study, which combines observations and modelling. Airborne radio echo sounding performed by the Alfred Wegener Institute between 1996 and 2008 with a frequency of 150 MHz and pulse length of 60 ns, respectively 600 ns, is analysed in order to study the internal structure of the ice in parts of the rift zone and to estimate the ice thickness in this area precisely. High-resolution radar imagery acquired by the TerraSAR-X in 2008 and 2009 is used to evaluate principal deformation axis at characteristic locations, to detect crack modes as well as to classify zones of similar structural characteristics. These zones were incorporated in a 2D diagnostic ice flow model as sub-domains with variable stress enhancement factor and thus treated as zones of different damage related stiffness. The temperature-dependent stiffness is calculated by applying the solution of a validated 3D temperature model of the ice shelf and thus the simulations focus on the softening effect caused by cracks. Extensive parameter studies show the effect of the stress enhancement factor on the principal deformation rates and axis. Comparison with the estimated deformation pattern aims to confine the softening effect for each zone separately.

  13. Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

    USGS Publications Warehouse

    Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

    2010-01-01

    This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a

  14. Multispectral-image fusion using neural networks

    NASA Astrophysics Data System (ADS)

    Kagel, Joseph H.; Platt, C. A.; Donaven, T. W.; Samstad, Eric A.

    1990-08-01

    A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard a circuit card assembly and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations results and a description of the prototype system are presented. 1.

  15. Multispectral image fusion using neural networks

    NASA Technical Reports Server (NTRS)

    Kagel, J. H.; Platt, C. A.; Donaven, T. W.; Samstad, E. A.

    1990-01-01

    A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard, a circuit card assembly, and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations, results, and a description of the prototype system are presented.

  16. Combining Landsat TM multispectral satellite imagery and different modelling approaches for mapping post-fire erosion changes in a Mediterranean site

    NASA Astrophysics Data System (ADS)

    Petropoulos, George P.; Kairis, Orestis; Karamesouti, Mina; Papanikolaou, Ioannis D.; Kosmas, Constantinos

    2013-04-01

    South European countries are naturally vulnerable to wildfires. Their natural resources such as soil, vegetation and water may be severely affected by wildfires, causing an imminent environmental deterioration due to the complex interdependence among biophysical components. Soil surface water erosion is a natural process essential for soil formation that is affected by such interdependences. Accelerated erosion due to wildfires, constitutes a major restrictive factor for ecosystem sustainability. In 2007, South European countries were severely affected by wildfires, with more than 500,000 hectares of land burnt in that year alone, well above the average of the last 30 years. The present work examines the changes in spatial variability of soil erosion rates as a result of a wildfire event that took place in Greece in 2007, one of the most devastating years in terms of wildfire hazards. Regional estimates of soil erosion rates before and after the fire outbreak were derived from the Revised Universal Soil Loss Equation (RUSLE, Renard et al. 1991) and the Pan-European Soil Erosion Risk Assessment model (PESERA, Kirkby, 1999; Kirkby et al., 2000). Inputs for both models included climatic, land-use, soil type, topography and land use management data. Where appropriate, both models were also fed with input data derived from the analysis of LANDSAT TM satellite imagery available in our study area, acquired before and shortly after the fire suppression. Our study was compiled and performed in a GIS environment. In overall, the loss of vegetation from the fire outbreak caused a substantial increase of soil erosion rates in the affected area, particularly towards the steep slopes. Both tested models were compared to each other and noticeable differences were observed in the soil erosion predictions before and after the fire event. These are attributed to the different parameterization requirements of the 2 models. This quantification of sediment supply through the river

  17. Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery

    NASA Astrophysics Data System (ADS)

    Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.

    2015-04-01

    Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively

  18. Quantifying the Availability of Tidewater Glacial Ice as Habitat for Harbor Seals in a Tidewater Glacial Fjord in Alaska Using Object-Based Image Analysis of Airborne Visible Imagery

    NASA Astrophysics Data System (ADS)

    Prakash, A.; Haselwimmer, C. E.; Gens, R.; Womble, J. N.; Ver Hoef, J.

    2013-12-01

    Tidewater glaciers are prominent landscape features that play a significant role in landscape and ecosystem processes along the southeastern and southcentral coasts of Alaska. Tidewater glaciers calve large icebergs that serve as an important substrate for harbor seals (Phoca vitulina richardii) for resting, pupping, nursing young, molting, and avoiding predators. Many of the tidewater glaciers in Alaska are retreating, which may influence harbor seal populations. Our objectives are to investigate the relationship between ice conditions and harbor seal distributions, which are poorly understood, in John's Hopkins Inlet, Glacier Bay National Park, Alaska, using a combination of airborne remote sensing and statistical modeling techniques. We present an overview of some results from Object-Based Image Analysis (OBIA) for classification of a time series of very high spatial resolution (4 cm pixels) airborne imagery acquired over John's Hopkins Inlet during the harbor seal pupping season in June and during the molting season in August from 2007 - 2012. Using OBIA we have developed a workflow to automate processing of the large volumes (~1250 images/survey) of airborne visible imagery for 1) classification of ice products (e.g. percent ice cover, percent brash ice, percent ice bergs) at a range of scales, and 2) quantitative determination of ice morphological properties such as iceberg size, roundness, and texture that are not found in traditional per-pixel classification approaches. These ice classifications and morphological variables are then used in statistical models to assess relationships with harbor seal abundance and distribution. Ultimately, understanding these relationships may provide novel perspectives on the spatial and temporal variation of harbor seals in tidewater glacial fjords.

  19. Commercial Applications Multispectral Sensor System

    NASA Technical Reports Server (NTRS)

    Birk, Ronald J.; Spiering, Bruce

    1993-01-01

    NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information. The ATLAS system will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal infrared wavelengths, variable spatial resolution from 2-25 meters; high geometric and geo-location accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight. ATLAS is scheduled to be available in 3rd quarter 1992 for acquisition of data for applications such as environmental monitoring, facilities management, geographic information systems data base development, and mineral exploration.

  20. Detection of Verticillium wilt of olive trees and downy mildew of opium poppy using hyperspectral and thermal UAV imagery

    NASA Astrophysics Data System (ADS)

    Calderón Madrid, Rocío; Navas Cortés, Juan Antonio; Montes Borrego, Miguel; Landa del Castillo, Blanca Beatriz; Lucena León, Carlos; Jesús Zarco Tejada, Pablo

    2014-05-01

    The present study explored the use of high-resolution thermal, multispectral and hyperspectral imagery as indicators of the infections caused by Verticillium wilt (VW) in olive trees and downy mildew (DM) in opium poppy fields. VW, caused by the soil-borne fungus Verticillium dahliae, and DM, caused by the biotrophic obligate oomycete Peronospora arborescens, are the most economically limiting diseases of olive trees and opium poppy, respectively, worldwide. V. dahliae infects the plant by the roots and colonizes its vascular system, blocking water flow and eventually inducing water stress. P. arborescens colonizes the mesophyll, appearing the first symptoms as small chlorotic leaf lesions, which can evolve to curled and thickened tissues and systemic infections that become deformed and necrotic as the disease develops. The work conducted to detect VW and DM infection consisted on the acquisition of time series of airborne thermal, multispectral and hyperspectral imagery using 2-m and 5-m wingspan electric Unmanned Aerial Vehicles (UAVs) in spring and summer of three consecutive years (2009 to 2011) for VW detection and on three dates in spring of 2009 for DM detection. Two 7-ha commercial olive orchards naturally infected with V. dahliae and two opium poppy field plots artificially infected by P. arborescens were flown. Concurrently to the airborne campaigns, olive orchards and opium poppy fields were assessed "in situ" to assess actual VW severity and DM incidence. Furthermore, field measurements were conducted at leaf and crown level. The field results related to VW detection showed a significant increase in crown temperature (Tc) minus air temperature (Ta) and a decrease in leaf stomatal conductance (G) as VW severity increased. This reduction in G was associated with a significant increase in the Photochemical Reflectance Index (PRI570) and a decrease in chlorophyll fluorescence. DM asymptomatic leaves showed significantly higher NDVI and lower green/red index

  1. Semi-automated DIRSIG scene modeling from three-dimensional lidar and passive imagery

    NASA Astrophysics Data System (ADS)

    Lach, Stephen R.

    include multiple-return point information provided by an Optech lidar linescanning sensor, multispectral frame array imagery from the Wildfire Airborne Sensor Program (WASP) and WASP-lite sensors, and hyperspectral data from the Modular Imaging Spectrometer Instrument (MISI) and the COMPact Airborne Spectral Sensor (COMPASS). Information from these image sources was fused and processed using the semi-automated approach to provide the DIRSIG input files used to define a synthetic scene. When compared to the standard manual process for creating these files, we achieved approximately a tenfold increase in speed, as well as a significant increase in geometric accuracy.

  2. Fast Lossless Compression of Multispectral-Image Data

    NASA Technical Reports Server (NTRS)

    Klimesh, Matthew

    2006-01-01

    An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive-filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

  3. Scene/object classification using multispectral data fusion algorithms

    NASA Astrophysics Data System (ADS)

    Kuzma, Thomas J.; Lazofson, Laurence E.; Choe, Howard C.; Chovan, John D.

    1994-06-01

    Near-simultaneous, multispectral, coregistered imagery of ground target and background signatures were collected over a full diurnal cycle in visible, infrared, and ultraviolet spectrally filtered wavebands using Battelle's portable sensor suite. The imagery data were processed using classical statistical algorithms, artificial neural networks and data clustering techniques to classify objects in the imaged scenes. Imagery collected at different times throughout the day were employed to verify algorithm robustness with respect to temporal variations of spectral signatures. In addition, several multispectral sensor fusion medical imaging applications were explored including imaging of subcutaneous vasculature, retinal angiography, and endoscopic cholecystectomy. Work is also being performed to advance the state of the art using differential absorption lidar as an active remote sensing technique for spectrally detecting, identifying, and tracking hazardous emissions. These investigations support a wide variety of multispectral signature discrimination applications including the concepts of automated target search, landing zone detection, enhanced medical imaging, and chemical/biological agent tracking.

  4. From HYSOMA to ENSOMAP - A new open source tool for quantitative soil properties mapping based on hyperspectral imagery from airborne to spaceborne applications

    NASA Astrophysics Data System (ADS)

    Chabrillat, Sabine; Guillaso, Stephane; Rabe, Andreas; Foerster, Saskia; Guanter, Luis

    2016-04-01

    Soil spectroscopy from the visible-near infrared to the short wave infrared has been shown to be a proven method for the quantitative prediction of key soil surface properties in the laboratory, field, and up to airborne studies for exposed soils in appropriate surface conditions. With the upcoming launch of the next generation of spaceborne hyperspectral sensors within the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. This potential can be achieved only if adequate software tools are available, as shown by the increasing demand for the availability/accessibility of hyperspectral soil products from the geoscience community that have neither the capacity nor the expertise to deliver these soil products. In this context, recently many international efforts were tuned toward the development of robust and easy-to-access soil algorithms to allow non-remote sensing experts to obtain geoscience information based on non-expensive software packages where repeatability of the results is an important prerequisite. In particular, several algorithms for geological and mineral mapping were recently released such as the U.S. Geological Survey Processing Routines in IDL for Spectroscopic Measurements (PRISM) software, or the GFZ EnMAP Geological Mapper. For quantitative soil mapping and monitoring, the HYSOMA (Hyperspectral Soil Mapper) software interface was developed at GFZ under the EUFAR (www.eufar.net) and the EnMAP (www.enmap.org) programs. HYSOMA was specifically oriented toward digital soil mapping applications and has been distributed since 2012 for free as IDL plug-ins under the IDL-virtual machine at www.gfz-potsdam.de/hysoma under a close source license. The HYSOMA interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. With more than 100 users around the world

  5. Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery

    NASA Astrophysics Data System (ADS)

    Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.

    2015-04-01

    Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively

  6. Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Kurt, Thome; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

    2009-01-01

    The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

  7. Radiometric characterization of hyperspectral imagers using multispectral sensors

    NASA Astrophysics Data System (ADS)

    McCorkel, Joel; Thome, Kurt; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

    2009-08-01

    The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of MODIS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most bands as well as similar agreement between results that employ the different MODIS sensors as a reference.

  8. A multispectral automatic target recognition application for maritime surveillance, search, and rescue

    NASA Astrophysics Data System (ADS)

    Schoonmaker, Jon; Reed, Scott; Podobna, Yuliya; Vazquez, Jose; Boucher, Cynthia

    2010-04-01

    Due to increased security concerns, the commitment to monitor and maintain security in the maritime environment is increasingly a priority. A country's coast is the most vulnerable area for the incursion of illegal immigrants, terrorists and contraband. This work illustrates the ability of a low-cost, light-weight, multi-spectral, multi-channel imaging system to handle the environment and see under difficult marine conditions. The system and its implemented detecting and tracking technologies should be organic to the maritime homeland security community for search and rescue, fisheries, defense, and law enforcement. It is tailored for airborne and ship based platforms to detect, track and monitor suspected objects (such as semi-submerged targets like marine mammals, vessels in distress, and drug smugglers). In this system, automated detection and tracking technology is used to detect, classify and localize potential threats or objects of interest within the imagery provided by the multi-spectral system. These algorithms process the sensor data in real time, thereby providing immediate feedback when features of interest have been detected. A supervised detection system based on Haar features and Cascade Classifiers is presented and results are provided on real data. The system is shown to be extendable and reusable for a variety of different applications.

  9. Land cover/use classification of Cairns, Queensland, Australia: A remote sensing study involving the conjunctive use of the airborne imaging spectrometer, the large format camera and the thematic mapper simulator

    NASA Technical Reports Server (NTRS)

    Heric, Matthew; Cox, William; Gordon, Daniel K.

    1987-01-01

    In an attempt to improve the land cover/use classification accuracy obtainable from remotely sensed multispectral imagery, Airborne Imaging Spectrometer-1 (AIS-1) images were analyzed in conjunction with Thematic Mapper Simulator (NS001) Large Format Camera color infrared photography and black and white aerial photography. Specific portions of the combined data set were registered and used for classification. Following this procedure, the resulting derived data was tested using an overall accuracy assessment method. Precise photogrammetric 2D-3D-2D geometric modeling techniques is not the basis for this study. Instead, the discussion exposes resultant spectral findings from the image-to-image registrations. Problems associated with the AIS-1 TMS integration are considered, and useful applications of the imagery combination are presented. More advanced methodologies for imagery integration are needed if multisystem data sets are to be utilized fully. Nevertheless, research, described herein, provides a formulation for future Earth Observation Station related multisensor studies.

  10. An airborne thematic thermal infrared and electro-optical imaging system

    NASA Astrophysics Data System (ADS)

    Sun, Xiuhong; Shu, Peter

    2011-08-01

    This paper describes an advanced Airborne Thematic Thermal InfraRed and Electro-Optical Imaging System (ATTIREOIS) and its potential applications. ATTIREOIS sensor payload consists of two sets of advanced Focal Plane Arrays (FPAs) - a broadband Thermal InfraRed Sensor (TIRS) and a four (4) band Multispectral Electro-Optical Sensor (MEOS) to approximate Landsat ETM+ bands 1,2,3,4, and 6, and LDCM bands 2,3,4,5, and 10+11. The airborne TIRS is 3-axis stabilized payload capable of providing 3D photogrammetric images with a 1,850 pixel swathwidth via pushbroom operation. MEOS has a total of 116 million simultaneous sensor counts capable of providing 3 cm spatial resolution multispectral orthophotos for continuous airborne mapping. ATTIREOIS is a complete standalone and easy-to-use portable imaging instrument for light aerial vehicle deployment. Its miniaturized backend data system operates all ATTIREOIS imaging sensor components, an INS/GPS, and an e-Gimbal™ Control Electronic Unit (ECU) with a data throughput of 300 Megabytes/sec. The backend provides advanced onboard processing, performing autonomous raw sensor imagery development, TIRS image track-recovery reconstruction, LWIR/VNIR multi-band co-registration, and photogrammetric image processing. With geometric optics and boresight calibrations, the ATTIREOIS data products are directly georeferenced with an accuracy of approximately one meter. A prototype ATTIREOIS has been configured. Its sample LWIR/EO image data will be presented. Potential applications of ATTIREOIS include: 1) Providing timely and cost-effective, precisely and directly georeferenced surface emissive and solar reflective LWIR/VNIR multispectral images via a private Google Earth Globe to enhance NASA's Earth science research capabilities; and 2) Underflight satellites to support satellite measurement calibration and validation observations.

  11. Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial multispectral images are a good source of crop, soil, and ground coverage information. Spectral reflectance indices provide a useful tool for monitoring crop growing status. A series of aerial images were acquired by an airborne MS4100 multispectral imaging system on the cotton and soybean f...

  12. Advanced Image Processing of Aerial Imagery

    NASA Technical Reports Server (NTRS)

    Woodell, Glenn; Jobson, Daniel J.; Rahman, Zia-ur; Hines, Glenn

    2006-01-01

    Aerial imagery of the Earth is an invaluable tool for the assessment of ground features, especially during times of disaster. Researchers at the NASA Langley Research Center have developed techniques which have proven to be useful for such imagery. Aerial imagery from various sources, including Langley's Boeing 757 Aries aircraft, has been studied extensively. This paper discusses these studies and demonstrates that better-than-observer imagery can be obtained even when visibility is severely compromised. A real-time, multi-spectral experimental system will be described and numerous examples will be shown.

  13. Application of ERTS-1 Imagery to Flood Inundation Mapping

    NASA Technical Reports Server (NTRS)

    Hallberg, G. R.; Hoyer, B. E.; Rango, A.

    1973-01-01

    Ground data and a variety of low-altitude multispectral imagery were acquired for the East Nishnabotna River on September 14 and 15. This successful effort concluded that a near-visible infrared sensor could map inundated areas in late summer for at least three days after flood recession. ERTS-1 multispectral scanner subsystem (MSS) imagery of the area was obtained on September 18 and 19. Analysis of MSS imagery by IGSRSL, USGS, and NASA reinforced the conclusions of the low-altitude study while increasing the time period critical for imagery acquisition to at least 7 days following flood recession. The capability of satellite imagery to map late summer flooding at a scale of 1:250,000 is exhibited by the agreement of interpreted flood boundaries obtained from ERTS-1 imagery to boundaries mapped by low-altitude imagery and ground methods.

  14. A color prediction model for imagery analysis

    NASA Technical Reports Server (NTRS)

    Skaley, J. E.; Fisher, J. R.; Hardy, E. E.

    1977-01-01

    A simple model has been devised to selectively construct several points within a scene using multispectral imagery. The model correlates black-and-white density values to color components of diazo film so as to maximize the color contrast of two or three points per composite. The CIE (Commission Internationale de l'Eclairage) color coordinate system is used as a quantitative reference to locate these points in color space. Superimposed on this quantitative reference is a perceptional framework which functionally contrasts color values in a psychophysical sense. This methodology permits a more quantitative approach to the manual interpretation of multispectral imagery while resulting in improved accuracy and lower costs.

  15. Integrating optical satellite data and airborne laser scanning in habitat classification for wildlife management

    NASA Astrophysics Data System (ADS)

    Nijland, W.; Coops, N. C.; Nielsen, S. E.; Stenhouse, G.

    2015-06-01

    Wildlife habitat selection is determined by a wide range of factors including food availability, shelter, security and landscape heterogeneity all of which are closely related to the more readily mapped landcover types and disturbance regimes. Regional wildlife habitat studies often used moderate resolution multispectral satellite imagery for wall to wall mapping, because it offers a favourable mix of availability, cost and resolution. However, certain habitat characteristics such as canopy structure and topographic factors are not well discriminated with these passive, optical datasets. Airborne laser scanning (ALS) provides highly accurate three dimensional data on canopy structure and the underlying terrain, thereby offers significant enhancements to wildlife habitat mapping. In this paper, we introduce an approach to integrate ALS data and multispectral images to develop a new heuristic wildlife habitat classifier for western Alberta. Our method combines ALS direct measures of canopy height, and cover with optical estimates of species (conifer vs. deciduous) composition into a decision tree classifier for habitat - or landcover types. We believe this new approach is highly versatile and transferable, because class rules can be easily adapted for other species or functional groups. We discuss the implications of increased ALS availability for habitat mapping and wildlife management and provide recommendations for integrating multispectral and ALS data into wildlife management.

  16. Road Asphalt Pavements Analyzed by Airborne Thermal Remote Sensing: Preliminary Results of the Venice Highway

    PubMed Central

    Pascucci, Simone; Bassani, Cristiana; Palombo, Angelo; Poscolieri, Maurizio; Cavalli, Rosa

    2008-01-01

    This paper describes a fast procedure for evaluating asphalt pavement surface defects using airborne emissivity data. To develop this procedure, we used airborne multispectral emissivity data covering an urban test area close to Venice (Italy).For this study, we first identify and select the roads' asphalt pavements on Multispectral Infrared Visible Imaging Spectrometer (MIVIS) imagery using a segmentation procedure. Next, since in asphalt pavements the surface defects are strictly related to the decrease of oily components that cause an increase of the abundance of surfacing limestone, the diagnostic absorption emissivity peak at 11.2μm of the limestone was used for retrieving from MIVIS emissivity data the areas exhibiting defects on asphalt pavements surface.The results showed that MIVIS emissivity allows establishing a threshold that points out those asphalt road sites on which a check for a maintenance intervention is required. Therefore, this technique can supply local government authorities an efficient, rapid and repeatable road mapping procedure providing the location of the asphalt pavements to be checked.

  17. Multispectral observations of marine mammals

    NASA Astrophysics Data System (ADS)

    Schoonmaker, Jon; Dirbas, Joseph; Podobna, Yuliya; Wells, Tami; Boucher, Cynthia; Oakley, Daniel

    2008-10-01

    Multispectral visible and infrared observations of various species of whales were made in the St. Lawrence Seaway near Quebec, Canada and Papawai Point in Maui, Hawaii. The Multi-mission Adaptable Narrowband Imaging System (MANTIS) was deployed in two configurations: airborne looking down, and bluff mounted looking at low-grazing angles. An Infrared (IR) sensor was also deployed in the bluff mounted configuration. Detections of marine mammals were made with these systems of submerged mammals and surface mammals at ranges up to 8 miles. Automatic detection algorithms are being explored to detect, track and monitor the behavior of individuals and pods of whales. This effort is part of a United States Navy effort to insure that marine mammals are not injured during the testing of the US Navy's acoustic Anti-submarine Warfare (ASW) systems.

  18. Leica ADS40 Sensor for Coastal Multispectral Imaging

    NASA Technical Reports Server (NTRS)

    Craig, John C.

    2007-01-01

    The Leica ADS40 Sensor as it is used for coastal multispectral imaging is presented. The contents include: 1) Project Area Overview; 2) Leica ADS40 Sensor; 3) Focal Plate Arrangements; 4) Trichroid Filter; 5) Gradient Correction; 6) Image Acquisition; 7) Remote Sensing and ADS40; 8) Band comparisons of Satellite and Airborne Sensors; 9) Impervious Surface Extraction; and 10) Impervious Surface Details.

  19. Mapping Giant Salvinia with Satellite Imagery and Image Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands)...

  20. BOREAS RSS-2 Extracted Reflectance Factors Derived from ASAS Imagery

    NASA Technical Reports Server (NTRS)

    Russell, C.; Hall, Forrest G. (Editor); Nickerson, Jaime (Editor); Dabney, P.; Kovalick, W.; Graham, D.; Bur, Michael; Irons, James R.; Tierney, M.

    2000-01-01

    The BOREAS RSS-2 team derived atmospherically corrected bidirectional reflectance factor means from multispectral, multiangle ASAS imagery for small homogeneous areas near several BOREAS sites. The ASAS imagery was acquired from the C-130 aircraft platform in 1994 and 1996. The data are stored in tabular ASCII files.

  1. Multispectral imaging using a single bucket detector

    PubMed Central

    Bian, Liheng; Suo, Jinli; Situ, Guohai; Li, Ziwei; Fan, Jingtao; Chen, Feng; Dai, Qionghai

    2016-01-01

    Existing multispectral imagers mostly use available array sensors to separately measure 2D data slices in a 3D spatial-spectral data cube. Thus they suffer from low photon efficiency, limited spectrum range and high cost. To address these issues, we propose to conduct multispectral imaging using a single bucket detector, to take full advantage of its high sensitivity, wide spectrum range, low cost, small size and light weight. Technically, utilizing the detector’s fast response, a scene’s 3D spatial-spectral information is multiplexed into a dense 1D measurement sequence and then demultiplexed computationally under the single pixel imaging scheme. A proof-of-concept setup is built to capture multispectral data of 64 pixels × 64 pixels × 10 wavelength bands ranging from 450 nm to 650 nm, with the acquisition time being 1 minute. The imaging scheme holds great potentials for various low light and airborne applications, and can be easily manufactured as production-volume portable multispectral imagers. PMID:27103168

  2. Multispectral imaging using a single bucket detector.

    PubMed

    Bian, Liheng; Suo, Jinli; Situ, Guohai; Li, Ziwei; Fan, Jingtao; Chen, Feng; Dai, Qionghai

    2016-01-01

    Existing multispectral imagers mostly use available array sensors to separately measure 2D data slices in a 3D spatial-spectral data cube. Thus they suffer from low photon efficiency, limited spectrum range and high cost. To address these issues, we propose to conduct multispectral imaging using a single bucket detector, to take full advantage of its high sensitivity, wide spectrum range, low cost, small size and light weight. Technically, utilizing the detector's fast response, a scene's 3D spatial-spectral information is multiplexed into a dense 1D measurement sequence and then demultiplexed computationally under the single pixel imaging scheme. A proof-of-concept setup is built to capture multispectral data of 64 pixels × 64 pixels × 10 wavelength bands ranging from 450 nm to 650 nm, with the acquisition time being 1 minute. The imaging scheme holds great potentials for various low light and airborne applications, and can be easily manufactured as production-volume portable multispectral imagers. PMID:27103168

  3. Multispectral multisensor image fusion using wavelet transforms

    USGS Publications Warehouse

    Lemeshewsky, George P.

    1999-01-01

    Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

  4. Investigation of Satellite Imagery for Regional Planning

    NASA Technical Reports Server (NTRS)

    Harting, W. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Satellite multispectral imagery was found to be useful in regional planning for depicting general developed land patterns, wooded areas, and newly constructed highways by using visual photointerpretation methods. Other characteristics, such as residential and nonresidential development, street patterns, development density, and some vacant land components cannot be adequately detected using these standard methods.

  5. Spatial patterns of vegetation biomass and soil organic carbon acquired from airborne lidar and hyperspectral imagery at Reynolds Creek Critical Zone Observatory

    NASA Astrophysics Data System (ADS)

    Will, R. M.; Li, A.; Glenn, N. F.; Benner, S. G.; Spaete, L.; Ilangakoon, N. T.

    2015-12-01

    Soil organic carbon distribution and the factors influencing this distribution are important for understanding carbon stores, vegetation dynamics, and the overall carbon cycle. Linking soil organic carbon (SOC) with aboveground vegetation biomass may provide a method to better understand SOC distribution in semiarid ecosystems. The Reynolds Creek Critical Zone Observatory (RC CZO) in Idaho, USA, is approximately 240 square kilometers and is situated in the semiarid Great Basin of the sagebrush-steppe ecosystem. Full waveform airborne lidar data and Next-Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-ng) collected in 2014 across the RC CZO are used to map vegetation biomass and SOC and then explore the relationships between them. Vegetation biomass is estimated by identifying vegetation species, and quantifying distribution and structure with lidar and integrating the field-measured biomass. Spectral data from AVIRIS-ng are used to differentiate non-photosynthetic vegetation (NPV) and soil, which are commonly confused in semiarid ecosystems. The information from lidar and AVIRIS-ng are then used to predict SOC by partial least squares regression (PLSR). An uncertainty analysis is provided, demonstrating the applicability of these approaches to improving our understanding of the distribution and patterns of SOC across the landscape.

  6. Practical example for use of the supervised vicarious calibration (SVC) method on multisource hyperspectral imagery data - ValCalHyp airborne hyperspectral campaign under the EUFAR framework

    NASA Astrophysics Data System (ADS)

    Brook, A.; Ben Dor, E.

    2014-09-01

    A novel approach for radiometric calibration and atmospheric correction of airborne hyperspectral (HRS) data, termed supervised vicarious calibration (SVC) was proposed by Brook and Ben-Dor in 2010. The present study was aimed at validating this SVC approach by simultaneously using several different airborne HSR sensors that acquired HSR data over several selected sites at the same time. The general goal of this study was to apply a cross-calibration approach to examine the capability and stability of the SVC method and to examine its validity. This paper reports the result of the multi sensors campaign took place over Salon de Provenance, France on behalf of the ValCalHyp project took place in 2011. The SVC method enabled the rectification of the radiometric drift of each sensor and improves their performance significantly. The flight direction of the SVC targets was found to be a critical issue for such correction and recommendations have been set for future utilization of this novel method. The results of the SVC method were examined by comparing ground-truth spectra of several selected validation targets with the image spectra as well as by comparing the classified water quality images generated from all sensors over selected water bodies.

  7. Imagery Integration Team

    NASA Technical Reports Server (NTRS)

    Calhoun, Tracy; Melendrez, Dave

    2014-01-01

    The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one

  8. Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response

    NASA Astrophysics Data System (ADS)

    Kruse, F. A.; Kim, A. M.; Runyon, S. C.; Carlisle, Sarah C.; Clasen, C. C.; Esterline, C. H.; Jalobeanu, A.; Metcalf, J. P.; Basgall, P. L.; Trask, D. M.; Olsen, R. C.

    2014-06-01

    The Naval Postgraduate School (NPS) Remote Sensing Center (RSC) and research partners have completed a remote sensing pilot project in support of California post-earthquake-event emergency response. The project goals were to dovetail emergency management requirements with remote sensing capabilities to develop prototype map products for improved earthquake response. NPS coordinated with emergency management services and first responders to compile information about essential elements of information (EEI) requirements. A wide variety of remote sensing datasets including multispectral imagery (MSI), hyperspectral imagery (HSI), and LiDAR were assembled by NPS for the purpose of building imagery baseline data; and to demonstrate the use of remote sensing to derive ground surface information for use in planning, conducting, and monitoring post-earthquake emergency response. Worldview-2 data were converted to reflectance, orthorectified, and mosaicked for most of Monterey County; CA. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired at two spatial resolutions were atmospherically corrected and analyzed in conjunction with the MSI data. LiDAR data at point densities from 1.4 pts/m2 to over 40 points/ m2 were analyzed to determine digital surface models. The multimodal data were then used to develop change detection approaches and products and other supporting information. Analysis results from these data along with other geographic information were used to identify and generate multi-tiered products tied to the level of post-event communications infrastructure (internet access + cell, cell only, no internet/cell). Technology transfer of these capabilities to local and state emergency response organizations gives emergency responders new tools in support of post-disaster operational scenarios.

  9. DTM generation in forest regions from satellite stereo imagery

    NASA Astrophysics Data System (ADS)

    Tian, J.; Krauss, T.; Reinartz, P.

    2014-11-01

    Satellite stereo imagery is becoming a popular data source for derivation of height information. Many new Digital Surface Model (DSM) generation and evaluation methods have been proposed based on these data. A novel Digital Terrain Model (DTM) extraction method based on the DSM from satellite stereo imagery is proposed in this paper. Instead of directly filtering the DSM, firstly a single channel based classification method is proposed. In this step, no multi-spectral information is used, because for some stereo sensors, like Cartosat-1, only panchromatic channels are available. The proposed classification method adopts the random forests method to get initial probability maps of the four main classes in forest regions (high-forest, low-forest, ground, and buildings). To cover the pepper and salt effect of this pixel based classification method, the probability maps are further filtered based on the adaptive Wiener filtering. Then a cube-based greedy strategy is applied in generating the final classification map from these refined probability maps. Secondly, the height distances between neighboring regions are calculated along the boundary regions. These height distances can be used to estimate the relative region heights. Thirdly, the DTM is extracted by subtracting these relative region heights from the DSM in the order of: buildings - low forest - high forest. In the end, the extracted DTM is further smoothed using median filter. The proposed DTM extraction method is finally tested on satellite stereo imagery captured by Cartosat-1. Quality evaluation is performed by comparing the extracted DTMs to a reference DTM, which is generated from the last return airborne laser scanning point cloud.

  10. Development of the second generation Hyperspectral Airborne Terrestrial Imager (HATI): HATI - 2500

    NASA Astrophysics Data System (ADS)

    Sandor-Leahy, S.; Thordarson, S.; Baldauf, B.; Figueroa, M.; Helmlinger, M.; Miller, H.; Reynolds, T.; Shepanski, J.

    2010-08-01

    Northrop Grumman Aerospace Systems (NGAS) has a long legacy developing and fielding hyperspectral sensors, including airborne and space based systems covering the visible through Long Wave Infrared (LWIR) wavelength ranges. Most recently NGAS has developed the Hyperspectral Airborne Terrestrial Instrument (HATI) family of hyperspectral sensors, which are compact airborne hyperspectral imagers designed to fly on a variety of platforms and be integrated with other sensors in NGAS's instrument suite. The current sensor under development is the HATI-2500, a full range Visible Near Infrared (VNIR) through Short Wave Infrared (SWIR) instrument covering the 0.4 - 2.5 micron wavelength range with high spectral resolution (3nm). The system includes a framing camera integrated with a GPS/INS to provide high-resolution multispectral imagery and precision geolocation. Its compact size and flexible acquisition parameters allow HATI-2500 to be integrated on a large variety of aerial platforms. This paper describes the HATI-2500 sensor and subsystems and its expected performance specifications.

  11. Remote Multispectral Imaging of Wildland Fires (Invited)

    NASA Astrophysics Data System (ADS)

    Vodacek, A.; Kremens, R.

    2010-12-01

    Wildland fires produce a variety of signal phenomenology that are remotely observable. These signals span a large portion of the electromagnetic spectrum and can be related to a variety of properties of wildland fires as they propagate. The deployment of multispectral sensors from aircraft provides a unique perspective on the fire and its interactions in the environment by repeated imaging over time. We describe a set of airborne imaging experiments, image processing methodologies and a workflow system for near real-time extraction of information on the fire and the immediate environment.

  12. Multispectral image analysis for object recognition and classification

    NASA Astrophysics Data System (ADS)

    Viau, C. R.; Payeur, P.; Cretu, A.-M.

    2016-05-01

    Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

  13. Regional prediction of soil organic carbon content over temperate croplands using visible near-infrared airborne hyperspectral imagery and synchronous field spectra

    NASA Astrophysics Data System (ADS)

    Vaudour, E.; Gilliot, J. M.; Bel, L.; Lefevre, J.; Chehdi, K.

    2016-07-01

    This study aimed at identifying the potential of Vis-NIR airborne hyperspectral AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with both contrasted soils and SOC contents, located in the western region of Paris, France. Soil types comprised haplic luvisols, calcaric cambisols and colluvic cambisols. Airborne AISA-Eagle data (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks. Tracks were atmospherically corrected then mosaicked at a 2 m-resolution using a set of 24 synchronous field spectra of bare soils, black and white targets and impervious surfaces. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then calculation and thresholding of NDVI from an atmospherically corrected SPOT image acquired the same day enabled to map agricultural fields with bare soil. A total of 101 sites sampled either in 2013 or in the 3 previous years and in 2015 were identified as bare by means of this map. Predictions were made from the mosaic AISA spectra which were related to topsoil SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples, considering 74 sites outside cloud shadows only, and different sampling strategies for selecting calibration samples. Validation root-mean-square errors (RMSE) were comprised between 3.73 and 4.49 g Kg-1 and were ∼4 g Kg-1 in median. The most performing models in terms of coefficient of determination (R2) and Residual Prediction Deviation (RPD) values were the calibration models derived either from Kennard-Stone or conditioned Latin Hypercube sampling on smoothed spectra. The most generalizable model leading to lowest RMSE value of 3.73 g Kg-1 at the regional scale and 1.44 g Kg-1 at the within-field scale and low bias was the cross-validated leave

  14. Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models

    NASA Astrophysics Data System (ADS)

    Darvishzadeh, Roshanak; Atzberger, Clement; Skidmore, Andrew; Schlerf, Martin

    2011-11-01

    Statistical and physical models have seldom been compared in studying grasslands. In this paper, both modeling approaches are investigated for mapping leaf area index (LAI) in a Mediterranean grassland (Majella National Park, Italy) using HyMap airborne hyperspectral images. We compared inversion of the PROSAIL radiative transfer model with narrow band vegetation indices (NDVI-like and SAVI2-like) and partial least squares regression (PLS). To assess the performance of the investigated models, the normalized RMSE (nRMSE) and R2 between in situ measurements of leaf area index and estimated parameter values are reported. The results of the study demonstrate that LAI can be estimated through PROSAIL inversion with accuracies comparable to those of statistical approaches ( R2 = 0.89, nRMSE = 0.22). The accuracy of the radiative transfer model inversion was further increased by using only a spectral subset of the data ( R2 = 0.91, nRMSE = 0.18). For the feature selection wavebands not well simulated by PROSAIL were sequentially discarded until all bands fulfilled the imposed accuracy requirements.

  15. Galileo multispectral imaging of Earth.

    PubMed

    Geissler, P; Thompson, W R; Greenberg, R; Moersch, J; McEwen, A; Sagan, C

    1995-08-25

    Nearly 6000 multispectral images of Earth were acquired by the Galileo spacecraft during its two flybys. The Galileo images offer a unique perspective on our home planet through the spectral capability made possible by four narrowband near-infrared filters, intended for observations of methane in Jupiter's atmosphere, which are not incorporated in any of the currently operating Earth orbital remote sensing systems. Spectral variations due to mineralogy, vegetative cover, and condensed water are effectively mapped by the visible and near-infrared multispectral imagery, showing a wide variety of biological, meteorological, and geological phenomena. Global tectonic and volcanic processes are clearly illustrated by these images, providing a useful basis for comparative planetary geology. Differences between plant species are detected through the narrowband IR filters on Galileo, allowing regional measurements of variation in the "red edge" of chlorophyll and the depth of the 1-micrometer water band, which is diagnostic of leaf moisture content. Although evidence of life is widespread in the Galileo data set, only a single image (at approximately 2 km/pixel) shows geometrization plausibly attributable to our technical civilization. Water vapor can be uniquely imaged in the Galileo 0.73-micrometer band, permitting spectral discrimination of moist and dry clouds with otherwise similar albedo. Surface snow and ice can be readily distinguished from cloud cover by narrowband imaging within the sensitivity range of Galileo's silicon CCD camera. Ice grain size variations can be mapped using the weak H2O absorption at 1 micrometer, a technique which may find important applications in the exploration of the moons of Jupiter. The Galileo images have the potential to make unique contributions to Earth science in the areas of geological, meteorological and biological remote sensing, due to the inclusion of previously untried narrowband IR filters. The vast scale and near global

  16. DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING AIRBORNE LWIR HYPERSPECTRAL IMAGING

    EPA Science Inventory

    Airborne longwave infrared LWIR) hyperspectral imagery was utilized to detect and identify gaseous chemical release plumes at sites in sourthern Texzas. The Airborne Hysperspectral Imager (AHI), developed by the University of Hawaii was flown over a petrochemical facility and a ...

  17. Gully erosion and land degradation in the Souss Basin, southern Morocco - application of airborne and terrestrial imagery and SfM procedures

    NASA Astrophysics Data System (ADS)

    Kaiser, Andreas; Peter, Klaus Daniel; Brings, Christine; Iserloh, Thomas; Seeger, Manuel; Ghafrani, Hassan; d'Oleire-Oltmanns, Sebastian; Marzolff, Irene; Ait Hssaine, Ali; Ries, Johannes B.

    2014-05-01

    Gully erosion is one major issue in soil erosion and land degradation. This major soil degradation process has affected the Souss Basin, located between the High and the Anti-Atlas, historically, and is increasing nowadays again. Since the 16th century, related to the production of sugar cane, gullies have been incising into the sedimentary fans and alluvial terraces. Today, the intensification of agro-industrial production of citrus fruit and vegetables has led to severe changes in surface geomorphology, and thus again to an increase of gully formation. For the understanding of the dynamics and formation of gullies, a combination of methods is needed, such as characterization of the precipitation patterns and quantification of infiltration and runoff generation dynamics as well as soil erosion rates within the gully catchments. In addition, the continuous and short-term monitoring of the gully morphology is essential in order to quantify the soil loss by gully erosion. Due to the complex 3-dimensional shapes of gullies, with overhangs and bank-cuttings, their assessment is a challenge. This paper aims at presenting a combination of terrestrial and airborne methods for quantifying the gully growth related to intensive agricultural productions in the Souss Basin (southern Morocco). Systematic series of images taken by a fixed-wing UAS are combined with detailed terrestrial images. Images were taken in different short-term to medium-term intervals of 11 months to 8 years, and 3D models were generated by means of structure from motion (SfM) algorithms. From these, gully growth volume and gully erosion rates could be quantified. In addition, the 3D visualization of the gully models - in contrast to more traditional 2.5D models common in GIS environments - allows new insights into the complex forms with undercuts, piping outlets etc and into the processes involved in their evolution.

  18. Synergy of airborne LiDAR and Worldview-2 satellite imagery for land cover and habitat mapping: A BIO_SOS-EODHaM case study for the Netherlands

    NASA Astrophysics Data System (ADS)

    Mücher, C. A.; Roupioz, L.; Kramer, H.; Bogers, M. M. B.; Jongman, R. H. G.; Lucas, R. M.; Kosmidou, V. E.; Petrou, Z.; Manakos, I.; Padoa-Schioppa, E.; Adamo, M.; Blonda, P.

    2015-05-01

    A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of

  19. Characteristic variogram for land use in Multispectral Images

    NASA Astrophysics Data System (ADS)

    Mera, E.; Condal, A.; Rios, C.; Da Silva, L.

    2016-05-01

    In remote sensing is the concept of spectral signature in multispectral imagery to recognize different land uses in the area; This study proposes the existence of a characteristic variogram for land use in multispectral images. To test this idea we proceeded to work with a sector of a scene image of multispectral Landsat 7 ETM +, in 6 of their bands (1- 450nm to 520nm, 2 - 520nm to 600nm, 3 - 630nm to 690nm, 4 - 760nm to 900nm 5 - over 1550nm to 1.750nm and 7 - 2.080nm to 2.350nm), corresponding to two uses of urban land and agricultural, the omnidirectional variogram for each band was analyzed and modal variogram for each land use was established in the stripe set. Of the analyzed claims data for each land use is a model characteristic and modal cross variogram how their wavelengths.

  20. An Approach to Application of Multispectral Sensors, using AVIRIS Data

    NASA Technical Reports Server (NTRS)

    Warner, Amanda; Blonski, Slawomir; Gasser, Gerald; Ryan, Robert; Zanoni, Vicki

    2001-01-01

    High spatial resolution multispectral/hyperspectral sensors are being developed by private industry with science/research customers as end users. With an increasingly wide range of sensor choices, it is important for the remote sensing science community and commercial community alike to understand the trade-offs between ground sample distance (GSD), spectral resolution, and signal-to-noise ratio (SNR) in selecting a sensor that will best meet their needs. High spatial resolution hyperspectral imagery and super resolution multispectral charge-coupled device imagery can be used to develop prototypes of proposed data acquisition systems without building new systems or collecting large sets of additional data. By using these datasets to emulate proposed and existing systems, imaging systems may be optimized to meet customer needs in a virtual environment. This approach also enables one to determine, a priori, whether an existing dataset will be useful for a given application.

  1. Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: a case study from the Greek wildland fires of 2007

    NASA Astrophysics Data System (ADS)

    Petropoulos, G. P.; Knorr, W.; Scholze, M.; Boschetti, L.; Karantounias, G.

    2010-02-01

    Remote sensing is increasingly being used as a cost-effective and practical solution for the rapid evaluation of impacts from wildland fires. The present study investigates the use of the support vector machine (SVM) classification method with multispectral data from the Advanced Spectral Emission and Reflection Radiometer (ASTER) for obtaining a rapid and cost effective post-fire assessment in a Mediterranean setting. A further objective is to perform a detailed intercomparison of available burnt area datasets for one of the most catastrophic forest fire events that occurred near the Greek capital during the summer of 2007. For this purpose, two ASTER scenes were acquired, one before and one closely after the fire episode. Cartography of the burnt area was obtained by classifying each multi-band ASTER image into a number of discrete classes using the SVM classifier supported by land use/cover information from the CORINE 2000 land nomenclature. Overall verification of the derived thematic maps based on the classification statistics yielded results with a mean overall accuracy of 94.6% and a mean Kappa coefficient of 0.93. In addition, the burnt area estimate derived from the post-fire ASTER image was found to have an average difference of 9.63% from those reported by other operationally-offered burnt area datasets available for the test region.

  2. An Approach to Application Validation of Multispectral Sensors Using AVIRIS

    NASA Technical Reports Server (NTRS)

    Warner, Amanda; Blonski, Slawomir; Gasser, Gerald; Ryan, Robert; Zanoni, Vicki

    2001-01-01

    High-resolution multispectral data are becoming widely available for commercial and scientific use. For specific applications, such as agriculture studies, there is a need to quantify the performance of such systems. In many cases, parameters such as GSD and SNR can be optimized. Data sets with varying GSD's for the Landsat ETM+ bands were produced to evaluate the effects of GSD on various algorithms and transformations, such as NDVI, principal component analysis, unsupervised classification, and mixture analysis. By showing that AVIRIS data can be used to simulate spaceborne and airborne multispectral platforms over a wide range of GSD, this research can be used to assist in band selection and spatial resolution specifications for new sensors and in optimization of acquisition strategies for existing multispectral systems.

  3. A multispectral scanner survey of the Rocky Flats Environmental Technology Site and surrounding area, Golden, Colorado

    SciTech Connect

    Brewster, S.B. Jr.; Brickey, D.W.; Ross, S.L.; Shines, J.E.

    1997-04-01

    Aerial multispectral scanner imagery was collected of the Rocky Flats Environmental Technology Site in Golden, Colorado, on June 3, 5, 6, and 7, 1994, using a Daedalus AADS1268 multispectral scanner and coincident aerial color and color infrared photography. Flight altitudes were 4,500 feet (1372 meters) above ground level to match prior 1989 survey data; 2,000 feet (609 meters) above ground level for sitewide vegetation mapping; and 1,000 feet (304 meters) above ground level for selected areas of special interest. A multispectral survey was initiated to improve the existing vegetation classification map, to identify seeps and springs, and to generate ARC/INFO Geographic Information System compatible coverages of the vegetation and wetlands for the entire site including the buffer zone. The multispectral scanner imagery and coincident aerial photography were analyzed for the detection, identification, and mapping of vegetation and wetlands. The multispectral scanner data were processed digitally while the color and color infrared photography were manually photo-interpreted to define vegetation and wetlands. Several standard image enhancement techniques were applied to the multispectral scanner data to assist image interpretation. A seep enhancement was applied and a color composite consisting of multispectral scanner channels 11, 7, and 5 (thermal infrared, mid-infrared, and red bands, respectively) proved most useful for detecting seeps, seep zones, and springs. The predawn thermal infrared data were also useful in identifying and locating seeps. The remote sensing data, mapped wetlands, and ancillary Geographic Information System compatible data sets were spatially analyzed for seeps.

  4. Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

    2015-12-01

    Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

  5. Land use classification utilizing remote multispectral scanner data and computer analysis techniques

    NASA Technical Reports Server (NTRS)

    Leblanc, P. N.; Johannsen, C. J.; Yanner, J. E.

    1973-01-01

    An airborne multispectral scanner was used to collect the visible and reflective infrared data. A small subdivision near Lafayette, Indiana was selected as the test site for the urban land use study. Multispectral scanner data were collected over the subdivision on May 1, 1970 from an altitude of 915 meters. The data were collected in twelve wavelength bands from 0.40 to 1.00 micrometers by the scanner. The results indicated that computer analysis of multispectral data can be very accurate in classifying and estimating the natural and man-made materials that characterize land uses in an urban scene.

  6. Multispectral photography for earth resources

    NASA Technical Reports Server (NTRS)

    Wenderoth, S.; Yost, E.; Kalia, R.; Anderson, R.

    1972-01-01

    A guide for producing accurate multispectral results for earth resource applications is presented along with theoretical and analytical concepts of color and multispectral photography. Topics discussed include: capabilities and limitations of color and color infrared films; image color measurements; methods of relating ground phenomena to film density and color measurement; sensitometry; considerations in the selection of multispectral cameras and components; and mission planning.

  7. Multispectral imaging probe

    SciTech Connect

    Sandison, David R.; Platzbecker, Mark R.; Descour, Michael R.; Armour, David L.; Craig, Marcus J.; Richards-Kortum, Rebecca

    1999-01-01

    A multispectral imaging probe delivers a range of wavelengths of excitation light to a target and collects a range of expressed light wavelengths. The multispectral imaging probe is adapted for mobile use and use in confined spaces, and is sealed against the effects of hostile environments. The multispectral imaging probe comprises a housing that defines a sealed volume that is substantially sealed from the surrounding environment. A beam splitting device mounts within the sealed volume. Excitation light is directed to the beam splitting device, which directs the excitation light to a target. Expressed light from the target reaches the beam splitting device along a path coaxial with the path traveled by the excitation light from the beam splitting device to the target. The beam splitting device directs expressed light to a collection subsystem for delivery to a detector.

  8. Multispectral imaging probe

    DOEpatents

    Sandison, D.R.; Platzbecker, M.R.; Descour, M.R.; Armour, D.L.; Craig, M.J.; Richards-Kortum, R.

    1999-07-27

    A multispectral imaging probe delivers a range of wavelengths of excitation light to a target and collects a range of expressed light wavelengths. The multispectral imaging probe is adapted for mobile use and use in confined spaces, and is sealed against the effects of hostile environments. The multispectral imaging probe comprises a housing that defines a sealed volume that is substantially sealed from the surrounding environment. A beam splitting device mounts within the sealed volume. Excitation light is directed to the beam splitting device, which directs the excitation light to a target. Expressed light from the target reaches the beam splitting device along a path coaxial with the path traveled by the excitation light from the beam splitting device to the target. The beam splitting device directs expressed light to a collection subsystem for delivery to a detector. 8 figs.

  9. A neural network approach for enhancing information extraction from multispectral image data

    USGS Publications Warehouse

    Liu, J.; Shao, G.; Zhu, H.; Liu, S.

    2005-01-01

    A back-propagation artificial neural network (ANN) was applied to classify multispectral remote sensing imagery data. The classification procedure included four steps: (i) noisy training that adds minor random variations to the sampling data to make the data more representative and to reduce the training sample size; (ii) iterative or multi-tier classification that reclassifies the unclassified pixels by making a subset of training samples from the original training set, which means the neural model can focus on fewer classes; (iii) spectral channel selection based on neural network weights that can distinguish the relative importance of each channel in the classification process to simplify the ANN model; and (iv) voting rules that adjust the accuracy of classification and produce outputs of different confidence levels. The Purdue Forest, located west of Purdue University, West Lafayette, Indiana, was chosen as the test site. The 1992 Landsat thematic mapper imagery was used as the input data. High-quality airborne photographs of the same Lime period were used for the ground truth. A total of 11 land use and land cover classes were defined, including water, broadleaved forest, coniferous forest, young forest, urban and road, and six types of cropland-grassland. The experiment, indicated that the back-propagation neural network application was satisfactory in distinguishing different land cover types at US Geological Survey levels II-III. The single-tier classification reached an overall accuracy of 85%. and the multi-tier classification an overall accuracy of 95%. For the whole test, region, the final output of this study reached an overall accuracy of 87%. ?? 2005 CASI.

  10. Vector statistics of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R., Jr.; Underwood, D.

    1977-01-01

    A digitized multispectral image, such as LANDSAT data, is composed of numerous four dimensional vectors, which quantitatively describe the ground scene from which the data are acquired. The statistics of unique vectors that occur in LANDSAT imagery are studied to determine if that information can provide some guidance on reducing image processing costs. A second purpose of this report is to investigate how the vector statistics are changed by various types of image processing techniques and determine if that information can be useful in choosing one processing approach over another.

  11. A new computer approach to map mixed forest features and postprocess multispectral data

    NASA Technical Reports Server (NTRS)

    Kan, E. P.

    1976-01-01

    A computer technique for mapping mixed softwood and hardwood stands in multispectral satellite imagery of forest regions is described. The purpose of the technique is to obtain smoother resource maps useful in timber harvesting operations. The computer program relies on an algorithm which assesses the size and similarity of adjacent sections on satellite imagery (Landsat-1 data is used) and constructs, through an iteration of the basic algorithm, a more general map of timber mixtures, eliminating the mottled appearance of the raw imagery. Despite difficulties in the experimental analysis of a Texas forest, apparently due to relatively low resolution of the Landsat data, the computer classification approach outlined is suggested as a generally applicable method of creating serviceable maps from multispectral imagery.

  12. Multispectral imaging for digital painting analysis: a Gauguin case study

    NASA Astrophysics Data System (ADS)

    Cornelis, Bruno; Dooms, Ann; Leen, Frederik; Munteanu, Adrian; Schelkens, Peter

    2010-08-01

    This paper is an introduction into the analysis of multispectral recordings of paintings. First, we will give an overview of the advantages of multispectral image analysis over more traditional techniques: first of all, the bands residing in the visible domain provide an accurate measurement of the color information which can be used for analysis but also for conservational and archival purposes (i.e. preserving the art patrimonial by making a digital library). Secondly, inspection of the multispectral imagery by art experts and art conservators has shown that combining the information present in the spectral bands residing in- and outside the visible domain can lead to a richer analysis of paintings. In the remainder of the paper, practical applications of multispectral analysis are demonstrated, where we consider the acquisition of thirteen different, high resolution spectral bands. Nine of these reside in the visible domain, one in the near ultraviolet and three in the infrared. The paper will illustrate the promising future of multispectral analysis as a non-invasive tool for acquiring data which cannot be acquired by visual inspection alone and which is highly relevant to art preservation, authentication and restoration. The demonstrated applications include detection of restored areas and detection of aging cracks.

  13. Analysis of Coincident HICO and Airborne Hyperspectral Images Over Lake Erie Western Basin HABs

    NASA Astrophysics Data System (ADS)

    Cline, M., Jr.; Becker, R.; Lekki, J.; Bridgeman, T. B.; Tokars, R. P.; Anderson, R. C.

    2015-12-01

    Harmful algal blooms (HABs) produce waterborne toxins that pose a significant threat to people, livestock, and wildlife. 40 million people in both Canada and the U.S. depend on Great Lakes water. In the summer of 2014, in the Lake Erie Western Basin, an HAB of the cyanobacteria Microsystis was so severe that a water-use ban was in effect for the greater Toledo area, Ohio. This shut off the water supply to over 400,000 people from a single water intake. We investigated bloom intensity, composition, and spatial variability by comparing hyperspectral data from NASA's HICO, multispectral data from MODIS spaceborne imagers and NASA GRC's HSI imagers to on-lake ASD radiometer measurements using in situ water quality testing as ground reference data, all acquired on a single day during the bloom in 2014. HICO imagery acquired on Aug 15, 2014 was spatially georeferenced and atmospherically corrected using empirical line method utilizing on-lake ASD spectra. HSI imagery were processed in a similar way. Cyanobacteria Index (CI) images were created from processed images using the Wynne (2010) algorithm, previously used for MODIS and MERIS imagery. This algorithm-generated CI images provide reliable results for both ground level (R²=0.7784), and satellite imagery (R²=0.7794) for seven sampling points in Lake Erie's western basin. Spatial variability in the bloom was high, and was not completely characterized by the lower spatial resolution MODIS data. The ability to robustly atmospherically correct and generate useful CI maps from airborne and satellite sensors can provide a time- and cost-effective method for HABs analysis. Timely processing of these high spatial and spectral resolution remote sensing data can aid in management of water intake resources.

  14. Evaluating high resolution SPOT 5 satellite imagery for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery has the potential for mapping within-field variability in crop growth and yield. This study examined SPOT 5 multispectral imagery for estimating grain sorghum yield. A SPOT 5 image with 10-m spatial resolution and four spectral bands (green, red, near-infrared, and ...

  15. Comparison of QuickBird and SPOT 5 Satellite Imagery for Mapping Giant Reed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    QuickBird (2.4 m resolution) and SPOT 5 (10 m resolution) multi-spectral satellite imagery were compared for mapping the invasive grass, giant reed (Arundo donax L.), along the Rio Grande in southwest Texas. The imagery had three bands (green, red, and near-infrared). Three subsets from both the Q...

  16. Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imagery, which contains hundreds of spectral bands, has the potential to better describe the biological and chemical attributes on the plants than multispectral imagery and has been evaluated in this paper for the purpose of crop yield estimation. The spectrum of each pixel in a hypers...

  17. Mapping a Riparian Weed with SPOT 5 Imagery and Image Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    SPOT 5 (10 m resolution) multi-spectral satellite imagery was evaluated for mapping infestations of the invasive grass giant reed (Arundo donax L.) along the Rio Grande in southwest Texas. The imagery had three bands (green, red, and near-infrared). Three subsets from the SPOT 5 image were extract...

  18. EXPERIMENTS IN LITHOGRAPHY FROM REMOTE SENSOR IMAGERY.

    USGS Publications Warehouse

    Kidwell, R. H.; McSweeney, J.; Warren, A.; Zang, E.; Vickers, E.

    1983-01-01

    Imagery from remote sensing systems such as the Landsat multispectral scanner and return beam vidicon, as well as synthetic aperture radar and conventional optical camera systems, contains information at resolutions far in excess of that which can be reproduced by the lithographic printing process. The data often require special handling to produce both standard and special map products. Some conclusions have been drawn regarding processing techniques, procedures for production, and printing limitations.

  19. IMAGE 100: The interactive multispectral image processing system

    NASA Technical Reports Server (NTRS)

    Schaller, E. S.; Towles, R. W.

    1975-01-01

    The need for rapid, cost-effective extraction of useful information from vast quantities of multispectral imagery available from aircraft or spacecraft has resulted in the design, implementation and application of a state-of-the-art processing system known as IMAGE 100. Operating on the general principle that all objects or materials possess unique spectral characteristics or signatures, the system uses this signature uniqueness to identify similar features in an image by simultaneously analyzing signatures in multiple frequency bands. Pseudo-colors, or themes, are assigned to features having identical spectral characteristics. These themes are displayed on a color CRT, and may be recorded on tape, film, or other media. The system was designed to incorporate key features such as interactive operation, user-oriented displays and controls, and rapid-response machine processing. Owing to these features, the user can readily control and/or modify the analysis process based on his knowledge of the input imagery. Effective use can be made of conventional photographic interpretation skills and state-of-the-art machine analysis techniques in the extraction of useful information from multispectral imagery. This approach results in highly accurate multitheme classification of imagery in seconds or minutes rather than the hours often involved in processing using other means.

  20. Automated Data Production for a Novel Airborne Multiangle Spectropolarimetric Imager (airmspi)

    NASA Astrophysics Data System (ADS)

    Jovanovic, V. M.; Bull, M.; Diner, D. J.; Geier, S.; Rheingans, B.

    2012-07-01

    A novel polarimetric imaging technique making use of rapid retardance modulation has been developed by JPL as a part of NASA's Instrument Incubator Program. It has been built into the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) under NASA's Airborne Instrument Technology Transition Program, and is aimed primarily at remote sensing of the amounts and microphysical properties of aerosols and clouds. AirMSPI includes an 8-band (355, 380, 445, 470, 555, 660, 865, 935 nm) pushbroom camera that measures polarization in a subset of the bands (470, 660, and 865 nm). The camera is mounted on a gimbal and acquires imagery in a configurable set of along-track viewing angles ranging between +67° and -67° relative to nadir. As a result, near simultaneous multi-angle, multi-spectral, and polarimetric measurements of the targeted areas at a spatial resolution ranging from 7 m to 20 m (depending on the viewing angle) can be derived. An automated data production system is being built to support high data acquisition rate in concert with co-registration and orthorectified mapping requirements. To date, a number of successful engineering checkout flights were conducted in October 2010, August-September 2011, and January 2012. Data products resulting from these flights will be presented.

  1. Automated Data Production For A Novel Airborne Multiangle Spectropolarimetric Imager (AIRMSPI)

    NASA Technical Reports Server (NTRS)

    Jovanovic, V .M.; Bull, M.; Diner, D. J.; Geier, S.; Rheingans, B.

    2012-01-01

    A novel polarimetric imaging technique making use of rapid retardance modulation has been developed by JPL as a part of NASA's Instrument Incubator Program. It has been built into the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) under NASA's Airborne Instrument Technology Transition Program, and is aimed primarily at remote sensing of the amounts and microphysical properties of aerosols and clouds. AirMSPI includes an 8-band (355, 380, 445, 470, 555, 660, 865, 935 nm) pushbroom camera that measures polarization in a subset of the bands (470, 660, and 865 nm). The camera is mounted on a gimbal and acquires imagery in a configurable set of along-track viewing angles ranging between +67 deg and -67 deg relative to nadir. As a result, near simultaneous multi-angle, multi-spectral, and polarimetric measurements of the targeted areas at a spatial resolution ranging from 7 m to 20 m (depending on the viewing angle) can be derived. An automated data production system is being built to support high data acquisition rate in concert with co-registration and orthorectified mapping requirements. To date, a number of successful engineering checkout flights were conducted in October 2010, August-September 2011, and January 2012. Data products resulting from these flights will be presented.

  2. Actual evapotranspiration estimation by means of airborne and satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Ciraolo, Giuseppe; D'Urso, Guido; Minacapilli, Mario

    2006-09-01

    During the last the two decades, the scientific community developed detailed mathematical models for simulating land surface energy fluxes and crop evapotranspiration rates by means of a energy balance approach. These models can be applied in large areas and with a spatial distributed approach using surface brightness temperature and some ancillary data retrieved from satellite/airborne remote sensed imagery. In this paper a district scale application in combination with multispectral (LandaSat 7 TM data) and hyperspectral airborne MIVIS data has been carried out to test the potentialities of two different energy balance models to estimate evapotranspiration fluxes from a set of typical Mediterranean crops (wine, olive, citrus). The impact of different spatial and radiometric resolutions of MIVIS (3m x 3m) and LandSat (60m x 60m) on models-derived fluxes has been investigated to understand the roles and the main conceptual differences between the two models which respectively use a "single-layer" (SEBAL) and a "two-layer" (TS) schematisation.

  3. Use of ERTS-1 imagery in forest inventory

    NASA Technical Reports Server (NTRS)

    Rennie, J. C.; Birth, E. E.

    1974-01-01

    The utility of ERTS-1 imagery when combined with field observations and with aircraft imagery and field observations is evaluated. Satellite imagery consisted of 9-1/2 inch black and white negatives of four multispectral scanner bands taken over Polk County, Tennessee. Aircraft imagery was obtained by a C-130 flying at 23,000 ft over the same area and provided the basis for locating ground plots for field observations. Correspondence between aircraft and satellite imagery was somewhat inaccurate due to seasonal differences in observations and lack of good photogrammetry with the data processing system used. Better correspondence was found between satellite imagery and ground observations. Ways to obtain more accurate data are discussed, and comparisons between aircraft and satellite observations are tabulated.

  4. Suomi NPP VIIRS Imagery evaluation

    NASA Astrophysics Data System (ADS)

    Hillger, Donald; Seaman, Curtis; Liang, Calvin; Miller, Steven; Lindsey, Daniel; Kopp, Thomas

    2014-06-01

    The Visible Infrared Imaging Radiometer Suite (VIIRS) combines the best aspects of both civilian and military heritage instrumentation. VIIRS has improved capabilities over its predecessors: a wider swath width and much higher spatial resolution at swath edge. The VIIRS day-night band (DNB) is sensitive to very low levels of visible light and is capable of detecting low clouds, land surface features, and sea ice at night, in addition to light emissions from both man-made and natural sources. Imagery from the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite has been in the checkout process since its launch on 28 October 2011. The ongoing evaluation of VIIRS Imagery helped resolve several imagery-related issues, including missing radiance measurements. In particular, near-constant contrast imagery, derived from the DNB, had a large number of issues to overcome, including numerous missing or blank-fill images and a stray light leakage problem that was only recently resolved via software fixes. In spite of various sensor issues, the VIIRS DNB has added tremendous operational and research value to Suomi NPP. Remarkably, it has been discovered to be sensitive enough to identify clouds even in very low light new moon conditions, using reflected light from the Earth's airglow layer. Impressive examples of the multispectral imaging capabilities are shown to demonstrate its applications for a wide range of operational users. Future members of the Joint Polar Satellite System constellation will also carry and extend the use of VIIRS. Imagery evaluation will continue with these satellites to ensure the quality of imagery for end users.

  5. A Comparison of Local Variance, Fractal Dimension, and Moran's I as Aids to Multispectral Image Classification

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.; Sig-NganLam, Nina; Quattrochi, Dale A.

    2004-01-01

    The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.

  6. An airborne system for collecting polarization imagery

    NASA Technical Reports Server (NTRS)

    Hildum, Edward A.; Spinhirne, James D.

    1992-01-01

    This paper describes a recently completed electrooptical camera flying onboard the NASA ER-2 high altitude aircraft. The device includes a six-position filter wheel which can be fitted with a combination of polarizing and/or spectral filters. An alternate configuration will include a polarizing filter which can be rotated to any angle under computer control. The camera mount in the nose of the ER-2 can tilt forward or aft up to 40 degrees, both for bidirectional reflectance studies and for image motion compensation (the aircraft moves 34 meters between frame acquisitions). The ground resolution is nominally 5 meters from and altitude of 20 km. Spectral responsivity is that of the silicon imaging array (Kodak KAF-1400). Initial data sets were acquired in support of the International Satellite Cloud Climatology Program Regional Experiment of November, 1991, and will be used to study cirrus cloud properties.

  7. Mapping invasive weeds using airborne hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Invasive plant species present a serious problem to the natural environment and have adverse ecological and economic impacts on both terrestrial and aquatic ecosystems they invade. This article provides a brief overview on the use of remote sensing for mapping invasive plant species in both terrestr...

  8. Mapping riparian and wetland weeds with high resolution satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquatic and wetland weeds are a serious management problem in many freshwater ecosystems of the world. This paper presents an overview on the application of using high resolution QuickBird multi-spectral satellite imagery for detecting weeds in waterways and wetlands in Texas. Unsupervised image a...

  9. Mapping Invasive Aquatic and Wetland Weeds with Quickbird Satellite Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquatic and wetland weeds are a serious management problem in many freshwater ecosystems of the world. This paper presents an overview on the application of using high resolution QuickBird multi-spectral satellite imagery for detecting weeds in waterways and wetlands in Texas. Unsupervised image a...

  10. Multispectral metamaterial absorber.

    PubMed

    Grant, J; McCrindle, I J H; Li, C; Cumming, D R S

    2014-03-01

    We present the simulation, implementation, and measurement of a multispectral metamaterial absorber (MSMMA) and show that we can realize a simple absorber structure that operates in the mid-IR and terahertz (THz) bands. By embedding an IR metamaterial absorber layer into a standard THz metamaterial absorber stack, a narrowband resonance is induced at a wavelength of 4.3 μm. This resonance is in addition to the THz metamaterial absorption resonance at 109 μm (2.75 THz). We demonstrate the inherent scalability and versatility of our MSMMA by describing a second device whereby the MM-induced IR absorption peak frequency is tuned by varying the IR absorber geometry. Such a MSMMA could be coupled with a suitable sensor and formed into a focal plane array, enabling multispectral imaging. PMID:24690713

  11. Multispectral Image Feature Points

    PubMed Central

    Aguilera, Cristhian; Barrera, Fernando; Lumbreras, Felipe; Sappa, Angel D.; Toledo, Ricardo

    2012-01-01

    This paper presents a novel feature point descriptor for the multispectral image case Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  12. Polarimetric Multispectral Imaging Technology

    NASA Technical Reports Server (NTRS)

    Cheng, L.-J.; Chao, T.-H.; Dowdy, M.; Mahoney, C.; Reyes, G.

    1993-01-01

    The Jet Propulsion Laboratory is developing a remote sensing technology on which a new generation of compact, lightweight, high-resolution, low-power, reliable, versatile, programmable scientific polarimetric multispectral imaging instruments can be built to meet the challenge of future planetary exploration missions. The instrument is based on the fast programmable acousto-optic tunable filter (AOTF) of tellurium dioxide (TeO2) that operates in the wavelength range of 0.4-5 microns. Basically, the AOTF multispectral imaging instrument measures incoming light intensity as a function of spatial coordinates, wavelength, and polarization. Its operation can be in either sequential, random access, or multiwavelength mode as required. This provides observation flexibility, allowing real-time alternation among desired observations, collecting needed data only, minimizing data transmission, and permitting implementation of new experiments. These will result in optimization of the mission performance with minimal resources. Recently we completed a polarimetric multispectral imaging prototype instrument and performed outdoor field experiments for evaluating application potentials of the technology. We also investigated potential improvements on AOTF performance to strengthen technology readiness for applications. This paper will give a status report on the technology and a prospect toward future planetary exploration.

  13. Wetlands mapping with spot multispectral scanner data

    SciTech Connect

    Mackey, H.E. Jr. ); Jensen, J.R. . Dept. of Geography)

    1989-01-01

    Government facilities such as the US Department of Energy's Savannah River Plant (SRP) near Aiken, South Carolina, often use remote sensing data to assist in environmental management. Airborne multispectral scanner (MSS) data have been acquired at SRP since 1981. Various types of remote sensing data have been used to map and characterize wetlands. Regional Landsat MSS and TM satellite data have been used for wetlands mapping by various government agencies and private organizations. Furthermore, SPOT MSS data are becoming available and provide opportunities for increased spacial resolution and temporal coverage for wetlands mapping. This paper summarizes the initial results from using five dates of SPOT MSS data from April through October, 1987, as a means to monitor seasonal wetland changes in freshwater wetlands of the SRP. 11 refs., 4 figs.

  14. Aerial multispectral imaging for cotton yield estimation under different irrigation and nitrogen treatments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton yield varied spatially within a field. The variability can be caused by various production inputs such as soil property, water management, and fertilizer application. Airborne multispectral imaging is capable of providing data and information to study effects of the inputs on the yield qualit...

  15. Use of multispectral scanner images for assessment of hydrothermal alteration in the Marysvale, Utah, mining area.

    USGS Publications Warehouse

    Podwysocki, M.H.; Segal, D.B.; Abrams, M.J.

    1983-01-01

    Airborne multispectral scanner. A color composite image was constructed using the following spectral band ratios: 1.6/2.2 mu m, 1.6/0.48 mu m, and 0.67/1.0 mu m. The color ratio composite successfully distinguished most types of altered rocks from unaltered rocks; further division of altered rocks into ferric oxide-rich and -poor types.

  16. Multispectral imaging with type II superlattice detectors

    NASA Astrophysics Data System (ADS)

    Ariyawansa, Gamini; Duran, Joshua M.; Grupen, Matt; Scheihing, John E.; Nelson, Thomas R.; Eismann, Michael T.

    2012-06-01

    Infrared (IR) focal plane arrays (FPAs) with multispectral detector elements promise significant advantages for airborne threat warning, surveillance, and targeting applications. At present, the use of type II superlattice (T2SL) structures based on the 6.1Å-family materials (InAs, GaSb, and AlSb) has become an area of interest for developing IR detectors and their FPAs. The ability to vary the bandgap in the IR range, suppression of Auger processes, prospective reduction of Shockley-Read-Hall centers by improved material growth capabilities, and the material stability are a few reasons for the predicted dominance of the T2SL technology over presently leading HgCdTe and quantum well technologies. The focus of the work reported here is on the development of T2SL based dual-band IR detectors and their applicability for multispectral imaging. A new NpBPN detector designed for the detection of IR in the 3-5 and 8-12 μm atmospheric windows is presented; comparing its advantages over other T2SL based approaches. One of the key challenges of the T2SL dual-band detectors is the spectral crosstalk associated with the LWIR band. The properties of the state-of-the-art T2SLs (i.e., absorption coefficient, minority carrier lifetime and mobility, etc.) and the present growth limitations that impact spectral crosstalk are discussed.

  17. Environmental studies of Iceland with ERTS-1 imagery

    NASA Technical Reports Server (NTRS)

    Williams, R. S., Jr.; Boovarsson, A.; Frioriksson, S.; Thorsteinsson, I.; Palmason, G.; Rist, S.; Saemundsson, K.; Sigtryggsson, H.; Thorarinsson, S.

    1974-01-01

    Imagery from the ERTS-1 satellite can be used to study geological and geophysical phenomena which are important in relation to Iceland's natural resources. Multispectral scanner (MSS) imagery can be used to map areas of altered ground, intense thermal emission, fallout from volcanic eruptions, lava flows, volcanic geomorphology, erosion or build-up of land, snow cover, the areal extent of glaciers and ice caps, etc. At least five distinct vegetation types and barren areas can be mapped using MSS false-color composites. Stereoscopic coverage of iceland by side-lapping ERTS imagery permits precise analysis of various natural phenomena.

  18. Improved Prediction of Momentum and Scalar Fluxes Using MODIS Imagery

    NASA Technical Reports Server (NTRS)

    Crago, Richard D.; Jasinski, Michael F.

    2003-01-01

    There are remote sensing and science objectives. The remote sensing objectives are: To develop and test a theoretical method for estimating local momentum aerodynamic roughness length, z(sub 0m), using satellite multispectral imagery. To adapt the method to the MODIS imagery. To develop a high-resolution (approx. 1km) gridded dataset of local momentum roughness for the continental United States and southern Canada, using MODIS imagery and other MODIS derived products. The science objective is: To determine the sensitivity of improved satellite-derived (MODIS-) estimates of surface roughness on the momentum and scalar fluxes, within the context of 3-D atmospheric modeling.

  19. User interface development for semiautomated imagery exploitation

    NASA Astrophysics Data System (ADS)

    O'Connor, R. P.; Bohling, Edward H.

    1991-08-01

    Operational reconnaissance technical organizations are burdened by greatly increasing workloads due to expanding capabilities for collection and delivery of large-volume near-real- time multisensor/multispectral softcopy imagery. Related to the tasking of reconnaissance platforms to provide the imagery are more stringent timelines for exploiting the imagery in response to the rapidly changing threat environment being monitored. The development of a semi-automated softcopy multisensor image exploitation capability is a critical step toward integrating existing advanced image processing techniques in conjunction with appropriate intelligence and cartographic data for next-generation image exploitation systems. This paper discusses the results of a recent effort to develop computer-assisted aids for the image analyst (IA) in order to rapidly and accurately exploit multispectral/multisensor imagery in combination with intelligence support data and cartographic information for the purpose of target detection and identification. A key challenge of the effort was to design and implement an effective human-computer interface that would satisfy any generic IA task and readily accommodate the needs of a broad range of IAs.

  20. MULTISPECTRAL THERMAL IMAGER - OVERVIEW

    SciTech Connect

    P. WEBER

    2001-03-01

    The Multispectral Thermal Imager satellite fills a new and important role in advancing the state of the art in remote sensing sciences. Initial results with the full calibration system operating indicate that the system was already close to achieving the very ambitious goals which we laid out in 1993, and we are confident of reaching all of these goals as we continue our research and improve our analyses. In addition to the DOE interests, the satellite is tasked about one-third of the time with requests from other users supporting research ranging from volcanology to atmospheric sciences.

  1. Multispectral thermal imaging

    SciTech Connect

    Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W.; Garrett, A.; Pendergast, M.M.; Kay, R.R.

    1998-12-01

    Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

  2. An airborne four-camera imaging system for agricultural applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper describes the design and testing of an airborne multispectral digital imaging system for remote sensing applications. The system consists of four high resolution charge coupled device (CCD) digital cameras and a ruggedized PC equipped with a frame grabber and image acquisition software. T...

  3. Development of an airborne remote sensing system for aerial applicators

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An airborne remote sensing system was developed and tested for recording aerial images of field crops, which were analyzed for variations of crop health or pest infestation. The multicomponent system consists of a multi-spectral camera system, a camera control system, and a radiometer for normalizi...

  4. [In-flight absolute radiometric calibration of UAV multispectral sensor].

    PubMed

    Chen, Wei; Yan, Lei; Gou, Zhi-Yang; Zhao, Hong-Ying; Liu, Da-Ping; Duan, Yi-Ni

    2012-12-01

    Based on the data of the scientific experiment in Urad Front Banner for UAV Remote Sensing Load Calibration Field project, with the help of 6 hyperspectral radiometric targets with good Lambertian property, the wide-view multispectral camera in UAV was calibrated adopting reflectance-based method. The result reveals that for green, red and infrared channel, whose images were successfully captured, the linear correlation coefficients between the DN and radiance are all larger than 99%. In final analysis, the comprehensive error is no more than 6%. The calibration results demonstrate that the hyperspectral targets equipped by the calibration field are well suitable for air-borne multispectral load in-flight calibration. The calibration result is reliable and could be used in the retrieval of geophysical parameters. PMID:23427528

  5. New Tools for Viewing Spectrally and Temporally-Rich Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Bradley, E. S.; Toomey, M. P.; Roberts, D. A.; Still, C. J.

    2010-12-01

    High frequency, temporally extensive remote sensing datasets (GOES: 30 minutes, Santa Cruz Island webcam: nearly 5 years at every 10 min.) and airborne imaging spectrometry (AVIRIS with 224 spectral bands), present exciting opportunities for education, synthesis, and analysis. However, the large file volume / size can make holistic review and exploration difficult. In this research, we explore two options for visualization (1) a web-based portal for time-series analysis, PanOpt, and (2) Google Earth-based timestamped image overlays. PanOpt is an interactive website (http://zulu.geog.ucsb.edu/panopt/), which integrates high frequency (GOES) and multispectral (MODIS) satellite imagery with webcam ground-based repeat photography. Side-by-side comparison of satellite imagery with webcam images supports analysis of atmospheric and environmental phenomena. In this proof of concept, we have integrated four years of imagery for a multi-view FogCam on Santa Cruz Island off the coast of Southern California with two years of GOES-11 and four years of MODIS Aqua imagery subsets for the area (14,000 km2). From the PHP-based website, users can search the data (date, time of day, etc.) and specify timestep and display size; and then view the image stack as animations or in a matrix form. Extracted metrics for regions of interest (ROIs) can be viewed in different formats, including time-series and scatter plots. Through click and mouseover actions over the hyperlink-enabled data points, users can view the corresponding images. This directly melds the quantitative and qualitative aspects and could be particularly effective for both education as well as anomaly interpretation. We have also extended this project to Google Earth with timestamped GOES and MODIS image overlays, which can be controlled using the temporal slider and linked to a screen chart of ancillary meteorological data. The automated ENVI/IDL script for generating KMZ overlays was also applied for generating same

  6. Multispectral imaging and image processing

    NASA Astrophysics Data System (ADS)

    Klein, Julie

    2014-02-01

    The color accuracy of conventional RGB cameras is not sufficient for many color-critical applications. One of these applications, namely the measurement of color defects in yarns, is why Prof. Til Aach and the Institute of Image Processing and Computer Vision (RWTH Aachen University, Germany) started off with multispectral imaging. The first acquisition device was a camera using a monochrome sensor and seven bandpass color filters positioned sequentially in front of it. The camera allowed sampling the visible wavelength range more accurately and reconstructing the spectra for each acquired image position. An overview will be given over several optical and imaging aspects of the multispectral camera that have been investigated. For instance, optical aberrations caused by filters and camera lens deteriorate the quality of captured multispectral images. The different aberrations were analyzed thoroughly and compensated based on models for the optical elements and the imaging chain by utilizing image processing. With this compensation, geometrical distortions disappear and sharpness is enhanced, without reducing the color accuracy of multispectral images. Strong foundations in multispectral imaging were laid and a fruitful cooperation was initiated with Prof. Bernhard Hill. Current research topics like stereo multispectral imaging and goniometric multispectral measure- ments that are further explored with his expertise will also be presented in this work.

  7. Oil slick studies using photographic and multispectral scanner data.

    NASA Technical Reports Server (NTRS)

    Munday, J. C., Jr.; Macintyre, W. G.; Penney, M. E.; Oberholtzer, J. D.

    1971-01-01

    Field studies of spills of Nos. 6 (Bunker C), 4, and 2 fuel oils and menhaden fish oil in the southern Chesapeake Bay have been supplemented with aerial photographic and multispectral scanner data. Thin films showed best in ultraviolet and blue bands and thick films in the green. Color film was effective for all thicknesses. Thermal infrared imagery provided clear detection, but required field temperature and thickness data to distinguish thickness/emissivity variations from temperature variations. Slick spreading rates agree with the theory of Fay (1969); further study of spreading is in progress.

  8. Characterizing thermal features from multi-spectral remote sensing data using dynamic calibration procedures

    NASA Astrophysics Data System (ADS)

    Hardy, Colin C.

    A thermal infrared remote sensing project was implemented to develop methods for identifying, classifying, and mapping thermal features. This study is directed at geothermal features, with the expectation that new protocols developed here will apply to the wildland fire thermal environment. Airborne multi-spectral digital imagery was acquired over the geothermally active Norris Basin region of Yellowstone National Park, USA. Two image acquisitions were flown, with one near solar noon and the other at night. The five-band image data included thermal infrared (TIR), near-infrared (NIR), and three visible bandpasses. While focused on TIR, the study relied on the multi-spectral visible and NIR data as well as on an ancillary hyperspectral data set. The raw, five-band data were uncalibrated, requiring implementation of two calibration protocols. First, a vicarious calibration procedure was developed to compute reflectance for the visible and NIR bands using an independently calibrated hyperspectral dataset. Second, a dynamic, in-scene calibration procedure was developed for the thermal sensor that exploited natural, pseudo-invariant thermal reference targets instrumented with kinetic temperature recorders. A suite of thermal attributes was derived, including daytime and nighttime radiant temperatures, a temperature difference (DeltaT), albedo, one minus albedo, and apparent thermal inertia (ATI). The albedo terms were computed using a published weighed-average albedo algorithm based on ratios of the narrowband red and NIR reflectances to total solar irradiance for the respective red and NIR bandpasses. In the absence of verifiable "truth," a step-wise chain of unsupervised classification and multivariate analysis exercises was performed, drawing heavily on "fuzzy truth." A final classification synthesizes a "thermal phenomenology" comprised of four components: spectral, statistical, geographical/contextual, and feature space. In situ measurements paired with image data

  9. Assessment of satellite and aircraft multispectral scanner data for strip-mine monitoring

    NASA Technical Reports Server (NTRS)

    Spisz, E. W.; Dooley, J. T.

    1980-01-01

    The application of LANDSAT multispectral scanner data to describe the mining and reclamation changes of a hilltop surface coal mine in the rugged, mountainous area of eastern Kentucky is presented. Original single band satellite imagery, computer enhanced single band imagery, and computer classified imagery are presented for four different data sets in order to demonstrate the land cover changes that can be detected. Data obtained with an 11 band multispectral scanner on board a C-47 aircraft at an altitude of 3000 meters are also presented. Comparing the satellite data with color, infrared aerial photography, and ground survey data shows that significant changes in the disrupted area can be detected from LANDSAT band 5 satellite imagery for mines with more than 100 acres of disturbed area. However, band-ratio (bands 5/6) imagery provides greater contrast than single band imagery and can provide a qualitative level 1 classification of the land cover that may be useful for monitoring either the disturbed mining area or the revegetation progress. However, if a quantitative, accurate classification of the barren or revegetated classes is required, it is necessary to perform a detailed, four band computer classification of the data.

  10. Digital image correlation techniques applied to LANDSAT multispectral imagery

    NASA Technical Reports Server (NTRS)

    Bonrud, L. O. (Principal Investigator); Miller, W. J.

    1976-01-01

    The author has identified the following significant results. Automatic image registration and resampling techniques applied to LANDSAT data achieved accuracies, resulting in mean radial displacement errors of less than 0.2 pixel. The process method utilized recursive computational techniques and line-by-line updating on the basis of feedback error signals. Goodness of local feature matching was evaluated through the implementation of a correlation algorithm. An automatic restart allowed the system to derive control point coordinates over a portion of the image and to restart the process, utilizing this new control point information as initial estimates.

  11. Topography Dependent Photometric Correction of SELENE Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Steutel, D.; Ohtake, M.

    2003-12-01

    The SELENE mission to the Moon in 2005 includes the Multiband Imager (MI) [1], a visible/near-infrared imaging spectrometer, and the Terrain Camera (TC), a 10m panchromatic stereoimager for global topography. The ˜1TB of TC data will take years to reduce; initial photometric correction of MI data will not include the effect of topography. We present a method for prioritizing analysis of TC data so topography can be included in photometric correction of MI data at the earliest time to regions of the lunar surface where the effects of topography are most significant. We have calculated the general quantified dependence of photometric correction on incidence angle, emission angle, phase angle, and local topographic slopes. To calculate photometric correction we use the method used for Clementine [2,3] with the following corrections: The factor of 2 is included in the XL function (see [3]), P(α ,g) = (1-g2)/(1+g2+2gcos(α ))1.5, and g1 = D*R30 + E. In order to predict the topography of the Moon to determine the regional distribution of local slopes at the resolution of MI (20m and 62m), we performed a fractal analysis on existing topographic data derived from Clementine LIDAR [4], Earth-based radar of Tycho crater [5], and Apollo surface-based stereoimagery [6]. The fractal parameter H, which describes the relationship between scale and roughness, is 0.65+/-0.02, 0.64+/-0.01, and 0.69+/-0.06 [6] at the 20-75km, 150m-1.5km, and 0.1-10mm scales, respectively. Based on the consistency of H at these disparate scales, we interpolate H=0.65+/-0.03 (a weighted average) at the 20m and 62m scales of the MI cameras. The second fractal parameter, σ (L0), is calculated from Clementine LIDAR data for overlapping 3x3 degree segments over the lunar surface. From this, we predict local topographic slopes for all regions on the Moon -60° to +60° at the 20m and 62m scales based on H=0.65 and σ (L0) as determined for each pixel. These results allow us to prioritize TC data analysis to maximize the scientific return from MI data during the first years of data analysis. This work was supported by the Japan Society for the Promotion of Science and the National Science Foundation's East Asia Summer Institutes. References: [1] Ohtake, M. LPSC XXXIV, abs 1976, 2003. [2] McEwen, A.S. LPSC XXVII, 841-842, 1996. [3] McEwen, A. et al. LPSC XXIX, abs 1466, 1998. [4] Smith, D.E. et al., JGR, 102(E1), 1591-1611, 1997. [5] Margot, J.-L. et al. JGR, 104(E5), 11875-11882, 1999. [6] Helfenstein, P. & M.K. Shepard. Icarus, 141, 107-131, 1999.

  12. Satellite imagery of the earth

    USGS Publications Warehouse

    Merifield, P.M.; Cronin, J.; Foshee, L.L.; Gawarecki, S.J.; Neal, J.T.; Stevenson, R.E.; Stone, R.O.; Williams, R.S., Jr.

    1969-01-01

    Photography of the Earth from spacecraft has application to both atmospheric and Earth sciences. Gemini and Apollo photographs have furnished information on sea surface roughness, areas of potential upwelling and oceanic current systems. Regional geologic structures and geomorphologic features are also recorded in orbital photographs. Infrared satellite imagery provides meteorological and hydrological data and is potentially useful for locating fresh water springs along coastal areas, sources of geothermal power and volcanic activity. Ground and airborne surveys are being undertaken to create a basis for the interpretation of data obtained from future satellite systems.

  13. Multispectral remote sensing as stratigraphic and structural tool, Wind River Basin and Big Horn Basin areas, Wyoming

    SciTech Connect

    Lang, H.R.; Adams, S.L.; Conel, J.E.; Mcguffie, B.A.; Paylor, E.D.; Walker, R.E.

    1987-04-01

    The use of Landsat TM, Airborne Imaging Spectrometer, and airborne Thermal IR Multispectral Scanner data in the geological evaluation of two sites in central Wyoming is described and illustrated with diagrams, maps, photographs, sample images, and tables of numerical data. The value of the remotely sensed information on the areal variation of attitude, sequence, thickness, and lithology of exposed strata is demonstrated; details of the data analysis are given; and the specialized software packages employed are briefly characterized. 46 references.

  14. Multispectral Resource Sampler Workshop

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The utility of the multispectral resource sampler (MRS) was examined by users in the following disciplines: agriculture, atmospheric studies, engineering, forestry, geology, hydrology/oceanography, land use, and rangelands/soils. Modifications to the sensor design were recommended and the desired types of products and number of scenes required per month were indicated. The history, design, capabilities, and limitations of the MRS are discussed as well as the multilinear spectral array technology which it uses. Designed for small area inventory, the MRS can provide increased temporal, spectral, and spatial resolution, facilitate polarization measurement and atmospheric correction, and test onboard data compression techniques. The advantages of using it along with the thematic mapper are considered.

  15. Multispectral imaging axicons.

    PubMed

    Bialic, Emilie; de la Tocnaye, Jean-Louis de Bougrenet

    2011-07-10

    Large-aperture linear diffractive axicons are optical devices providing achromatic nondiffracting beams with an extended depth of focus when illuminated by white light sources. Annular apertures introduce chromatic foci separation, making chromatic imaging possible despite important radiometric losses. Recently, a new type of diffractive axicon has been introduced, by multiplexing concentric annular axicons with appropriate sizes and periods, called a multiple annular linear diffractive axicon (MALDA). This new family of conical optics combines multiple annular axicons in different ways to optimize color foci recombination, separation, or interleaving. We present different types of MALDA, give an experimental illustration of the use of these devices, and describe the manufacturing issues related to their fabrication to provide color imaging systems with long focal depths and good diffraction efficiency. Application to multispectral image analysis is discussed. PMID:21743576

  16. Multispectral scanner optical system

    NASA Technical Reports Server (NTRS)

    Stokes, R. C.; Koch, N. G. (Inventor)

    1980-01-01

    An optical system for use in a multispectral scanner of the type used in video imaging devices is disclosed. Electromagnetic radiation reflected by a rotating scan mirror is focused by a concave primary telescope mirror and collimated by a second concave mirror. The collimated beam is split by a dichroic filter which transmits radiant energy in the infrared spectrum and reflects visible and near infrared energy. The long wavelength beam is filtered and focused on an infrared detector positioned in a cryogenic environment. The short wavelength beam is dispersed by a pair of prisms, then projected on an array of detectors also mounted in a cryogenic environment and oriented at an angle relative to the optical path of the dispersed short wavelength beam.

  17. Multispectral Microimager for Astrobiology

    NASA Technical Reports Server (NTRS)

    Sellar, R. Glenn; Farmer, Jack D.; Kieta, Andrew; Huang, Julie

    2006-01-01

    A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

  18. MSS D Multispectral Scanner System

    NASA Technical Reports Server (NTRS)

    Lauletta, A. M.; Johnson, R. L.; Brinkman, K. L. (Principal Investigator)

    1982-01-01

    The development and acceptance testing of the 4-band Multispectral Scanners to be flown on LANDSAT D and LANDSAT D Earth resources satellites are summarized. Emphasis is placed on the acceptance test phase of the program. Test history and acceptance test algorithms are discussed. Trend data of all the key performance parameters are included and discussed separately for each of the two multispectral scanner instruments. Anomalies encountered and their resolutions are included.

  19. Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph; McKellip, Rodney

    2006-01-01

    Hurricane Katrina hit southeastern Louisiana and the Mississippi Gulf Coast as a Category 3 hurricane with storm surges as high as 9 m. Katrina devastated several coastal towns by destroying or severely damaging hundreds of homes. Several Federal agencies are assessing storm impacts and assisting recovery using high-spatial-resolution remotely sensed data from satellite and airborne platforms. High-quality IKONOS satellite imagery was collected on September 2, 2005, over southwestern Mississippi. Pan-sharpened IKONOS multispectral data and ERDAS IMAGINE software were used to classify post-storm land cover for coastal Hancock and Harrison Counties. This classification included a storm debris category of interest to FEMA for disaster mitigation. The classification resulted from combining traditional unsupervised and supervised classification techniques. Higher spatial resolution aerial and handheld photography were used as reference data. Results suggest that traditional classification techniques and IKONOS data can map wood-dominated storm debris in open areas if relevant training areas are used to develop the unsupervised classification signatures. IKONOS data also enabled other hurricane damage assessment, such as flood-deposited mud on lawns and vegetation foliage loss from the storm. IKONOS data has also aided regional Katrina vegetation damage surveys from multidate Land Remote Sensing Satellite and Moderate Resolution Imaging Spectroradiometer data.

  20. Vegetation cover mapping at multiple scales using MODIS, Landsat, RapidEye, and Aircraft imageries in the Texas High Plains

    NASA Astrophysics Data System (ADS)

    Rajan, N.; Gowda, P. H.; Maas, S. J.; Basu, S.; Nair, S. S.

    2009-12-01

    Vegetation cover is an important input variable in many earth and environmental studies. In many of these studies, vegetation cover information is needed at different spatial scales. Hence, remote sensing is a popular tool to estimate vegetation cover. Numerous spectral-based models are available in the literature for mapping vegetation cover. However, very limited information is available on their ability to perform well at spatial scales different from the scale at which the model was developed. In this study, we used a procedure based on the Perpendicular Vegetation Index (PVI) to estimate vegetation cover. Using this procedure, vegetation cover is estimated from the ratio of the PVI of an image pixel to the PVI of full vegetation canopy (100% ground cover). The major advantages of this procedure compared to several other methods are that this method does not rely on empirical relationships, and can use raw remote sensing data without converting it into surface reflectance or normalization to account scene-to scene difference in vegetation. Previous studies conducted during the summer growing seasons of 2006, 2007 and 2008 in the Texas High Plains (THP) show that the method could estimate vegetation cover from Landsat imagery with an average error of less than 6%, and from high-resolution aerial images (obtained using TTAMRSS, the Texas Tech Airborne Multispectral Remote Sensing System) with an average error of less than 3%. In this study, we used this procedure to estimate vegetation cover of 10 large agricultural fields in the THP with Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m resolution) and with the RapidEye (5 m resolution) imageries. The results were compared with ground-based observations and vegetation cover derived from Landsat and high resolution aircraft imageries.

  1. Fourth Airborne Geoscience Workshop

    NASA Technical Reports Server (NTRS)

    1991-01-01

    The focus of the workshop was on how the airborne community can assist in achieving the goals of the Global Change Research Program. The many activities that employ airborne platforms and sensors were discussed: platforms and instrument development; airborne oceanography; lidar research; SAR measurements; Doppler radar; laser measurements; cloud physics; airborne experiments; airborne microwave measurements; and airborne data collection.

  2. Evaluating AISA+ hyperspectral imagery for mapping black mangrove along the South Texas Gulf Coast

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Mangrove wetlands are economically and ecologically important ecosystems and accurate assessment of these wetlands with remote sensing can assist in their management and conservation. This study was conducted to evaluate airborne AISA+ hyperspectral imagery and image transformation and classificatio...

  3. Mapping Black Mangrove Along the South Texas Gulf Coast Using AISA+ Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Mangrove wetlands are economically and ecologically important ecosystems and accurate assessment of these wetlands with remote sensing can assist in their management and conservation. This study was conducted to evaluate airborne hyperspectral imagery and image compression and classification techniq...

  4. Airborne laser

    NASA Astrophysics Data System (ADS)

    Lamberson, Steven E.

    2002-06-01

    The US Air Force Airborne Laser (ABL) is an airborne, megawatt-class laser system with a state-of-the-art atmospheric compensation system to destroy enemy ballistic missiles at long ranges. This system will provide both deterrence and defense against the use of such weapons during conflicts. This paper provides an overview of the ABL weapon system including: the notional operational concept, the development approach and schedule, the overall aircraft configuration, the technologies being incorporated in the ABL, and the risk reduction approach being utilized to ensure program success.

  5. An interactive lake survey program. [airborne multispectral sensor image processing

    NASA Technical Reports Server (NTRS)

    Smith, A. Y.

    1977-01-01

    Consideration is given to the development and operation of the interactive lake survey program developed by the Jet Propulsion Laboratory and the Environmental Protection Agency. The program makes it possible to locate, isolate, and store any number of water bodies on the basis of a given digital image. The stored information may be used to generate statistical analyses of each body of water including the lake surface area and the shoreline perimeter. The hardware includes a 360/65 host computer, a Ramtek G100B display controller, and a trackball cursor. The system is illustrated by the LAKELOC operation as it would be applied to a Landsat scene, noting the FARINA and STATUS programs. The water detection algorithm, which increases the accuracy with which water and land data may be separated, is discussed.

  6. Multispectral Analysis of Indigenous Rock Art Using Terrestrial Laser Scanning

    NASA Astrophysics Data System (ADS)

    Skoog, B.; Helmholz, P.; Belton, D.

    2016-06-01

    Multispectral analysis is a widely used technique in the photogrammetric and remote sensing industry. The use of Terrestrial Laser Scanning (TLS) in combination with imagery is becoming increasingly common, with its applications spreading to a wider range of fields. Both systems benefit from being a non-contact technique that can be used to accurately capture data regarding the target surface. Although multispectral analysis is actively performed within the spatial sciences field, its extent of application within an archaeological context has been limited. This study effectively aims to apply the multispectral techniques commonly used, to a remote Indigenous site that contains an extensive gallery of aging rock art. The ultimate goal for this research is the development of a systematic procedure that could be applied to numerous similar sites for the purpose of heritage preservation and research. The study consisted of extensive data capture of the rock art gallery using two different TLS systems and a digital SLR camera. The data was combined into a common 2D reference frame that allowed for standard image processing to be applied. An unsupervised k-means classifier was applied to the multiband images to detect the different types of rock art present. The result was unsatisfactory as the subsequent classification accuracy was relatively low. The procedure and technique does however show potential and further testing with different classification algorithms could possibly improve the result significantly.

  7. Multispectral Thermal Infrared Mapping of Sulfur Dioxide Plumes: A Case Study from the East Rift Zone of Kilauea Volcano, Hawaii

    NASA Technical Reports Server (NTRS)

    Realmuto, V. J.; Sutton, A. J.; Elias, T.

    1996-01-01

    The synoptic perspective and rapid mode of data acquisition provided by remote sensing are well-suited for the study of volcanic SO2 plumes. In this paper we describe a plume-mapping procedure that is based on image data acquired with NASA's airborne Thermal Infrared Multispectral Scanner (TIMS).

  8. The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

    NASA Technical Reports Server (NTRS)

    He, Yubin; Blakeslee, Richard; Goodman, Michael; Hall, John

    2010-01-01

    NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA's well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when "chasing" a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an

  9. Multi-spectral synthetic image generation for ground vehicle identification training

    NASA Astrophysics Data System (ADS)

    May, Christopher M.; Pinto, Neil A.; Sanders, Jeffrey S.

    2016-05-01

    There is a ubiquitous and never ending need in the US armed forces for training materials that provide the warfighter with the skills needed to differentiate between friendly and enemy forces on the battlefield. The current state of the art in battlefield identification training is the Recognition of Combat Vehicles (ROC-V) tool created and maintained by the Communications - Electronics Research, Development and Engineering Center Night Vision and Electronic Sensors Directorate (CERDEC NVESD). The ROC-V training package utilizes measured visual and thermal imagery to train soldiers about the critical visual and thermal cues needed to accurately identify modern military vehicles and combatants. This paper presents an approach to augment the existing ROC-V imagery database with synthetically generated multi-spectral imagery that will allow NVESD to provide improved training imagery at significantly lower costs.

  10. High-precision geometric correction of airborne remote sensing revisited: the multiquadric interpolation

    NASA Astrophysics Data System (ADS)

    Ehlers, Manfred; Fogel, David N.

    1994-12-01

    For a geographic analysis of multispectral scanner data from aircraft and their integration in spatial databases and geographic integration systems (GIS), geometric registration/rectification of the scanner imagery is required as a first step. Usually, one has to rely on global mapping functions such as polynomial equations as provided by most commercial image processing systems. These techniques have been proven to be very effective and accurate for satellite images. However, there are a umber of shortcomings when this method is applied to aircraft data. We see the multiquadric interpolation method as a promising alternative. The multiquadric function was first developed for the interpolation of irregular surfaces. It could be modified, however, to be used for image correction of remotely sensed data. In this form, it is particularly suited for the rectification of remote sensing images of large scale and locally varying geometric distortions. The multiquadric interpolation method yields a perfect fit at the used control points (CPs). With this, it is necessary to withhold independent test points that can be used for accuracy assessment. Within the registration/rectification process, all CPs contribute to the geometric warping of any given pixel in the image. Their effects, however, are weighted inversely to the distances between CPs and the current pixel location. The paper presents the multiquadric interpolation techniques and demonstrates successful application with airborne scanner data.

  11. Summaries of the Seventh JPL Airborne Earth Science Workshop January 12-16, 1998. Volume 1; AVIRIS Workshop

    NASA Technical Reports Server (NTRS)

    Green, Robert O. (Editor)

    1998-01-01

    This publication contains the summaries for the Seventh JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 12-16, 1998. The main workshop is divided into three smaller workshops, and each workshop has a volume as follows: (1) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Workshop; (2) Airborne Synthetic Aperture Radar (AIRSAR) Workshop; and (3) Thermal Infrared Multispectral Scanner (TIMS) Workshop. This Volume 1 publication contains 58 papers taken from the AVIRIS workshop.

  12. Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun

    2014-10-01

    Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are

  13. UAV-based multi-spectral environmental monitoring

    NASA Astrophysics Data System (ADS)

    Arnold, Thomas; De Biasio, Martin; Fritz, Andreas; Frank, Albert; Leitner, Raimund

    2012-06-01

    This paper describes an airborne multi-spectral imaging system which is able to simultaneously capture three visible (400-670nm at 50% FWHM) and three near infrared channels (670-1000nm at 50% FWHM). The rst prototype was integrated in a Schiebel CAMCOPTER®S-100 VTOL (Vertical Take-O and Landing) UAV (Unmanned Aerial Vehicle) for initial test ights in spring 2010. The UAV was own over land containing various types of vegetation. A miniaturized version of the initial multi-spectral imaging system was developed in 2011 to t into a more compact UAV. The imaging system captured six bands with a minimal spatial resolution of approx. 10cm x 10cm (depending on altitude). Results show that the system is able to resist the high vibration level during ight and that the actively stabilized camera gimbal compensates for rapid roll/tilt movements of the UAV. After image registration the acquired images are stitched together for land cover mapping and ight path validation. Moreover the system is able to distinguish between dierent types of vegetation and soil. Future work will include the use of spectral imaging techniques to identify spectral features that are related to water stress, nutrient deciency and pest infestation. Once these bands have been identied, narrowband lters will be incorporated into the airborne system.

  14. Synergistic use of MOMS-01 and Landsat TM data. [Modular Optoelectronic Multispectral Scanner

    NASA Technical Reports Server (NTRS)

    Rothery, David A.; Francis, Peter W.

    1987-01-01

    Imagery covering the Socompa volcano and debris avalanche deposit in northern Chile was acquired by MOMS-01 when the sun was low in the western sky. Illumination from the west shows many important topographic features to advantage. These are inconspicuous or indistinguishable on Landsat TM images acquired at higher solar elevation. The effective spatial resolution of MOMS-01 is similar to that of the TM and its capacity for spectral discrimination is less. A technique has been developed to combine the multispectral information offered by TM with the topographic detail visible on MOMS-01 imagery recorded at a time of low solar elevation.

  15. USGS and NASA Digital Imagery Product Characterization

    NASA Technical Reports Server (NTRS)

    Zanoni, Vicki; Smith, Charles; Blonski, Slawomir

    2004-01-01

    This paper presents viewgraphs about a partnership between USGS and NASA who are jointly developing an airborne digital imagery characterization capability. The topics include: 1) USGS-NASA Product Characterization Approach; 2) Stennis Character Range; 3) Stennis Geodetic Targets; 4) Stennis Manhole Covers; 5) Stennis Edge Target; 6) Stennis Characterization Site; 7) Delivered Data; 8) Other Data Considerations; 9) Status; 10) Geopositional Assessment Approach; 11) Spatial Assessment Approach; 12) Edge Response; and 13) Results to Date.

  16. Interpretation of multispectral and infrared thermal surveys of the Suez Canal Zone, Egypt

    NASA Technical Reports Server (NTRS)

    Elshazly, E. M.; Hady, M. A. A. H.; Hafez, M. A. A.; Salman, A. B.; Morsy, M. A.; Elrakaiby, M. M.; Alaassy, I. E. E.; Kamel, A. F.

    1977-01-01

    Remote sensing airborne surveys were conducted, as part of the plan of rehabilitation, of the Suez Canal Zone using I2S multispectral camera and Bendix LN-3 infrared passive scanner. The multispectral camera gives four separate photographs for the same scene in the blue, green, red, and near infrared bands. The scanner was operated in the microwave bands of 8 to 14 microns and the thermal surveying was carried out both at night and in the day time. The surveys, coupled with intensive ground investigations, were utilized in the construction of new geological, structural lineation and drainage maps for the Suez Canal Zone on a scale of approximately 1:20,000, which are superior to the maps made by normal aerial photography. A considerable number of anomalies belonging to various types were revealed through the interpretation of the executed multispectral and infrared thermal surveys.

  17. Seasonal vegetation differences from ERTS imagery

    NASA Technical Reports Server (NTRS)

    Ashley, M. D.; Rea, J.

    1975-01-01

    Knowledge of the times when crop and forest vegetation experience seasonally related changes in development is important in understanding growth and yield relationships. This article describes how densitometry of earth resources technology satellite (ERTS-1) multispectral scanner (MSS) imagery can be used to identify such phenological events. Adjustments for instrument calibration, aperture size, gray-scale differences between overpasses, and normalization of changing solar elevation are considered in detail. Seasonal vegetation differences can be identified by densitometry of band 5 (0.6-0.7 microns) and band 7 (0.8-1.1 microns) MSS imagery. Band-to-band ratios of the densities depicted the changes more graphically than the individual band readings.

  18. Environmental applications utilizing digital aerial imagery

    SciTech Connect

    Monday, H.M.

    1995-06-01

    This paper discusses the use of satellite imagery, aerial photography, and computerized airborne imagery as applied to environmental mapping, analysis, and monitoring. A project conducted by the City of Irving, Texas involves compliance with national pollutant discharge elimination system (NPDES) requirements stipulated by the Environmental Protection Agency. The purpose of the project was the development and maintenance of a stormwater drainage utility. Digital imagery was collected for a portion of the city to map the City`s porous and impervious surfaces which will then be overlaid with property boundaries in the City`s existing Geographic information System (GIS). This information will allow the City to determine an equitable tax for each land parcel according to the amount of water each parcel is contributing to the stormwater system. Another project involves environmental compliance for warm water discharges created by utility companies. Environmental consultants are using digital airborne imagery to analyze thermal plume affects as well as monitoring power generation facilities. A third project involves wetland restoration. Due to freeway and other forms of construction, plus a major reduction of fresh water supplies, the Southern California coastal wetlands are being seriously threatened. These wetlands, rich spawning grounds for plant and animal life, are home to thousands of waterfowl and shore birds who use this habitat for nesting and feeding grounds. Under the leadership of Southern California Edison (SCE) and CALTRANS (California Department of Transportation), several wetland areas such as the San Dieguito Lagoon (Del Mar, California), the Sweetwater Marsh (San Diego, California), and the Tijuana Estuary (San Diego, California) are being restored and closely monitored using digital airborne imagery.

  19. Improved Airborne System for Sensing Wildfires

    NASA Technical Reports Server (NTRS)

    McKeown, Donald; Richardson, Michael

    2008-01-01

    The Wildfire Airborne Sensing Program (WASP) is engaged in a continuing effort to develop an improved airborne instrumentation system for sensing wildfires. The system could also be used for other aerial-imaging applications, including mapping and military surveillance. Unlike prior airborne fire-detection instrumentation systems, the WASP system would not be based on custom-made multispectral line scanners and associated custom- made complex optomechanical servomechanisms, sensors, readout circuitry, and packaging. Instead, the WASP system would be based on commercial off-the-shelf (COTS) equipment that would include (1) three or four electronic cameras (one for each of three or four wavelength bands) instead of a multispectral line scanner; (2) all associated drive and readout electronics; (3) a camera-pointing gimbal; (4) an inertial measurement unit (IMU) and a Global Positioning System (GPS) receiver for measuring the position, velocity, and orientation of the aircraft; and (5) a data-acquisition subsystem. It would be necessary to custom-develop an integrated sensor optical-bench assembly, a sensor-management subsystem, and software. The use of mostly COTS equipment is intended to reduce development time and cost, relative to those of prior systems.

  20. Photogeologic mapping in central southwest Bahia, using LANDSAT-1 multispectral images. [Brazil

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Ohara, T.

    1981-01-01

    The interpretation of LANDSAT multispectral imagery for geologic mapping of central southwest Bahia, Brazil is described. Surface features such as drainage, topography, vegetation and land use are identified. The area is composed of low grade Precambrian rocks covered by Mezozoic and Cenozoic sediments. The principal mineral prospects of economic value are fluorite and calcareous rocks. Gold, calcite, rock crystal, copper, potassium nitrate and alumina were also identified.

  1. Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

    NASA Technical Reports Server (NTRS)

    Manohar, Mareboyana; Tilton, James C.

    1994-01-01

    A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

  2. Utilizing SAR and Multispectral Integrated Data for Emergency Response

    NASA Astrophysics Data System (ADS)

    Havivi, S.; Schvartzman, I.; Maman, S.; Marinoni, A.; Gamba, P.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar) these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD) for SAR data and Covariance Equalization (CE) for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX) and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a complete scene for

  3. Retinal oxygen saturation evaluation by multi-spectral fundus imaging

    NASA Astrophysics Data System (ADS)

    Khoobehi, Bahram; Ning, Jinfeng; Puissegur, Elise; Bordeaux, Kimberly; Balasubramanian, Madhusudhanan; Beach, James

    2007-03-01

    Purpose: To develop a multi-spectral method to measure oxygen saturation of the retina in the human eye. Methods: Five Cynomolgus monkeys with normal eyes were anesthetized with intramuscular ketamine/xylazine and intravenous pentobarbital. Multi-spectral fundus imaging was performed in five monkeys with a commercial fundus camera equipped with a liquid crystal tuned filter in the illumination light path and a 16-bit digital camera. Recording parameters were controlled with software written specifically for the application. Seven images at successively longer oxygen-sensing wavelengths were recorded within 4 seconds. Individual images for each wavelength were captured in less than 100 msec of flash illumination. Slightly misaligned images of separate wavelengths due to slight eye motion were registered and corrected by translational and rotational image registration prior to analysis. Numerical values of relative oxygen saturation of retinal arteries and veins and the underlying tissue in between the artery/vein pairs were evaluated by an algorithm previously described, but which is now corrected for blood volume from averaged pixels (n > 1000). Color saturation maps were constructed by applying the algorithm at each image pixel using a Matlab script. Results: Both the numerical values of relative oxygen saturation and the saturation maps correspond to the physiological condition, that is, in a normal retina, the artery is more saturated than the tissue and the tissue is more saturated than the vein. With the multi-spectral fundus camera and proper registration of the multi-wavelength images, we were able to determine oxygen saturation in the primate retinal structures on a tolerable time scale which is applicable to human subjects. Conclusions: Seven wavelength multi-spectral imagery can be used to measure oxygen saturation in retinal artery, vein, and tissue (microcirculation). This technique is safe and can be used to monitor oxygen uptake in humans. This work

  4. Densitometry of ERTS-1 imagery to access vegetation change

    NASA Technical Reports Server (NTRS)

    Ashley, M. D.; Rea, J.

    1974-01-01

    Density measurements of ERTS-1 multispectral scanner (MSS) imagery can be used to evaluate phenological changes in vegetation. It was found that the density ratios for MSS bands 5 and 7 best characterize vegetation change. The ratio increases with vegetative progression and decreases with vegetative recession. The use of a densitometer aperture as small as 0.4 mm does not adversely affect the accuracy of readings on forest sites.

  5. Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.

    PubMed

    Michez, Adrien; Piégay, Hervé; Lisein, Jonathan; Claessens, Hugues; Lejeune, Philippe

    2016-03-01

    competes successfully with those developed using more expensive imagery, such as multi-spectral and hyperspectral airborne imagery. The high overall accuracy results obtained by the classification of the diseased alders open the door to applications dedicated to monitoring of the health conditions of riparian forest. Our methodological framework will allow UAS users to manage large imagery metric datasets derived from those dense time series. PMID:26850712

  6. Auditory Imagery: Empirical Findings

    ERIC Educational Resources Information Center

    Hubbard, Timothy L.

    2010-01-01

    The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d)…

  7. CCD image acquisition for multispectral teledetection

    NASA Astrophysics Data System (ADS)

    Peralta-Fabi, R.; Peralta, A.; Prado, Jorge M.; Vicente, Esau; Navarette, M.

    1992-08-01

    A low cost high-reliability multispectral video system has been developed for airborne remote sensing. Three low weight CCD cameras are mounted together with a photographic camera in a keviar composite self-contained structure. The CCD cameras are remotely controlled have spectral filters (80 nm at 50 T) placed in front of their optical system and all cameras are aligned to capture the same image field. Filters may be changed so as to adjust spectral bands according to the object s reflectance properties but a set of bands common to most remote sensing aircraft and satellites are usually placed covering visible and near JR. This paper presents results obtained with this system and some comparisons as to the cost resolution and atmospheric correction advantages with respect to other more costly devices. Also a brief description of the Remotely Piloted Vehicle (RPV) project where the camera system will be mounted is given. The images so obtained replace the costlier ones obtained by satellites in severai specific applications. Other applications under development include fire monitoring identification of vegetation in the field and in the laboratory discrimination of objects by color for industrial applications and for geological and engineering surveys. 1.

  8. Multispectral imaging method and apparatus

    DOEpatents

    Sandison, D.R.; Platzbecker, M.R.; Vargo, T.D.; Lockhart, R.R.; Descour, M.R.; Richards-Kortum, R.

    1999-07-06

    A multispectral imaging method and apparatus are described which are adapted for use in determining material properties, especially properties characteristic of abnormal non-dermal cells. A target is illuminated with a narrow band light beam. The target expresses light in response to the excitation. The expressed light is collected and the target's response at specific response wavelengths to specific excitation wavelengths is measured. From the measured multispectral response the target's properties can be determined. A sealed, remote probe and robust components can be used for cervical imaging. 5 figs.

  9. Multispectral imaging method and apparatus

    DOEpatents

    Sandison, David R.; Platzbecker, Mark R.; Vargo, Timothy D.; Lockhart, Randal R.; Descour, Michael R.; Richards-Kortum, Rebecca

    1999-01-01

    A multispectral imaging method and apparatus adapted for use in determining material properties, especially properties characteristic of abnormal non-dermal cells. A target is illuminated with a narrow band light beam. The target expresses light in response to the excitation. The expressed light is collected and the target's response at specific response wavelengths to specific excitation wavelengths is measured. From the measured multispectral response the target's properties can be determined. A sealed, remote probe and robust components can be used for cervical imaging

  10. Primer on Use of Multi-Spectral and Infra Red Imaging for On-Site Inspections

    SciTech Connect

    Henderson, J R

    2010-10-26

    The purpose of an On-Site Inspection (OSI) is to determine whether a nuclear explosion has occurred in violation of the Comprehensive Nuclear Test Ban Treaty (CTBT), and to gather information which might assist in identifying the violator (CTBT, Article IV, Paragraph 35) Multi-Spectral and Infra Red Imaging (MSIR) is allowed by the treaty to detect observables which might help reduce the search area and thus expedite an OSI and make it more effective. MSIR is permitted from airborne measurements, and at and below the surface to search for anomalies and artifacts (CTBT, Protocol, Part II, Paragraph 69b). The three broad types of anomalies and artifacts MSIR is expected to be capable of observing are surface disturbances (disturbed earth, plant stress or anomalous surface materials), human artifacts (man-made roads, buildings and features), and thermal anomalies. The purpose of this Primer is to provide technical information on MSIR relevant to its use for OSI. It is expected that this information may be used for general background information, to inform decisions about the selection and testing of MSIR equipment, to develop operational guidance for MSIR use during an OSI, and to support the development of a training program for OSI Inspectors. References are provided so readers can pursue a topic in more detail than the summary information provided here. The following chapters will provide more information on how MSIR can support an OSI (Section 2), a short summary what Multi-Spectral Imaging and Infra Red Imaging is (Section 3), guidance from the CTBT regarding the use of MSIR (Section 4), and a description of several nuclear explosion scenarios (Section 5) and consequent observables (Section 6). The remaining sections focus on practical aspects of using MSIR for an OSI, such as specification and selection of MSIR equipment, operational considerations for deployment of MISR equipment from an aircraft, and the conduct of field exercises to mature MSIR for an OSI

  11. Hyperspectral Transformation from EO-1 ALI Imagery Using Pseudo-Hyperspectral Image Synthesis Algorithm

    NASA Astrophysics Data System (ADS)

    Tien Hoang, Nguyen; Koike, Katsuaki

    2016-06-01

    Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution. However, hyperspectral remote sensing resources are limited both in temporal and spatial coverage. Therefore, simulation of hyperspectral imagery from multispectral imagery with a small number of bands must be one of innovative topics. Based on this background, we have recently developed a method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into hyperspectral imagery using the correlation of reflectance at the corresponding bands between Landsat and EO-1 Hyperion data. This study extends PHISA to simulate pseudo-hyperspectral imagery from EO-1 ALI imagery. The pseudo-hyperspectral imagery has the same number of bands as that of high-quality Hyperion bands and the same swath width as ALI scene. The hyperspectral reflectance data simulated from the ALI data show stronger correlation with the original Hyperion data than the one simulated from Landsat data. This high correlation originates from the concurrent observation by the ALI and Hyperion sensors that are on-board the same satellite. The accuracy of simulation results are verified by a statistical analysis and a surface mineral mapping. With a combination of the advantages of both ALI and Hyperion image types, the pseudo-hyperspectral imagery is proved to be useful for detailed identification of minerals for the areas outside the Hyperion coverage.

  12. Correlation between lidar-derived intensity and passive optical imagery

    NASA Astrophysics Data System (ADS)

    Metcalf, Jeremy P.; Kim, Angela M.; Kruse, Fred A.; Olsen, Richard C.

    2014-06-01

    When LiDAR data are collected, the intensity information is recorded for each return, and can be used to produce an image resembling those acquired by passive imaging sensors. This research evaluated LiDAR intensity data to determine its potential for use as baseline imagery where optical imagery are unavailable. Two airborne LiDAR datasets collected at different point densities and laser wavelengths were gridded and compared with optical imagery. Optech Orion C200 laser data were compared with a corresponding 1541 nm spectral band from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Optech ALTM Gemini LiDAR data collected at 1064 nm were compared to the WorldView-2 (WV-2) 949 - 1043 nm NIR2 band. Intensity images were georegistered and spatially resampled to match the optical data. The Pearson Product Moment correlation coefficient was calculated between datasets to determine similarity. Comparison for the full LiDAR datasets yielded correlation coefficients of approximately 0.5. Because LiDAR returns from vegetation are known to be highly variable, a Normalized Difference Vegetation Index (NDVI) was calculated utilizing the optical imagery, and intensity and optical imagery were separated into vegetation and nonvegetation categories. Comparison of the LiDAR intensity for non-vegetated areas to the optical imagery yielded coefficients greater than 0.9. These results demonstrate that LiDAR intensity data may be useful in substituting for optical imagery where only LiDAR is available.

  13. Multistage, Multiband and sequential imagery to identify and quantify non-forest vegetation resources

    NASA Technical Reports Server (NTRS)

    Driscoll, R. S.

    1971-01-01

    Analysis and recognition processing of multispectral scanner imagery for plant community classification and interpretations of various film-filter-scale aerial photographs are reported. Data analyses and manuscript preparation of research on microdensitometry for plant community and component identification and remote estimates of biomass are included.

  14. Evolving spatio-spectral feature extraction algorithms for hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Galbraith, Amy E.

    2002-11-01

    Hyperspectral imagery data sets present an interesting challenge to feature extraction algorithm developers. Beyond the immediate problem of dealing with the sheer amount of spectral information per pixel in a hyperspectral image, the remote sensing scientist must explore a complex algorithm space in which both spatial and spectral signatures may be required to identify a feature of interest. Rather than carry out this algorithm exploration by hand, we are interested in developing learning systems that can evolve these algorithms. We describe a genetic programming/supervised classifier software system, called GENIE, which evolves image processing tools for remotely sensed imagery. Our primary application has been land-cover classification from satellite imagery. GENIE was developed to evolve classification algorithms for multispectral imagery, and the extension to hyperspectral imagery presents a chance to test a genetic programming system by greatly increasing the complexity of the data under analysis, as well as a chance to find interesting spatio-spectral algorithms for hyperspectral imagery. We demonstrate our system on publicly available imagery from the new Hyperion imaging spectrometer onboard the NASA Earth Observing-1 (EO-1) satellite.

  15. Wideband radar for airborne minefield detection

    NASA Astrophysics Data System (ADS)

    Clark, William W.; Burns, Brian; Dorff, Gary; Plasky, Brian; Moussally, George; Soumekh, Mehrdad

    2006-05-01

    Ground Penetrating Radar (GPR) has been applied for several years to the problem of detecting both antipersonnel and anti-tank landmines. RDECOM CERDEC NVESD is developing an airborne wideband GPR sensor for the detection of minefields including surface and buried mines. In this paper, we describe the as-built system, data and image processing techniques to generate imagery, and current issues with this type of radar. Further, we will display images from a recent field test.

  16. Application of ERTS-1 imagery in mapping and managing soil and range resources in the Sand Hills region of Nebraska

    NASA Technical Reports Server (NTRS)

    Seevers, P. M.; Lewis, D. T.; Drew, J. V.

    1974-01-01

    Interpretations of imagery from the Earth Resources Technology Satellite (ERTS-1) indicate that soil associations and attendant range sites can be identified on the basis of vegetation and topography using multi-temporal imagery. Optical density measurements of imagery from the visible red band of the multispectral scanner (MSS band 5) obtained during the growing season were related to field measurements of vegetative biomass, a factor that closely parallels range condition class on specific range sites. ERTS-1 imagery also permitted inventory and assessment of center-pivot irrigation systems in the Sand Hills region in relation to soil and topographic conditions and energy requirements.

  17. Multispectral scanner (MSS), ERTS-1

    NASA Technical Reports Server (NTRS)

    Arlauskas, J.

    1973-01-01

    The multispectral scanner onboard ERTS-A spacecraft provides simultaneous images in three visible bands and one near infrared band. The instrument employs fiber optics to transfer optical images to the detectors and photomultiplier tubes. Detector outputs are digitized and multiplexed for transmission from the spacecraft by analog to digital processor.

  18. Multispectral Landsat images of Antartica

    SciTech Connect

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

    1988-01-01

    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  19. Sub-meter Commercial Imagery Coverage for the Earth's Polar Regions

    NASA Astrophysics Data System (ADS)

    Morin, P. J.; Peterman, K.

    2013-12-01

    A complete, high resolution satellite imagery view of the Earth's Polar Regions is important to understand a wide variety of scientific, logistical and geospatial problems. To address this need, near complete sub-meter licensed commercial imagery coverage of the Earth's Polar Regions and all ice on earth is now available to US federal employees and US federally funded researchers with a US federal purpose through the NGA Commercial Imagery Program and the Polar Geospatial Center. Included are historical sub-meter mono and stereo imagery from DigitalGlobe, Inc.'s IKONOS, Geoeye-1, and Quickbird as well as historical imagery and new collects from Worldview-1 and 2. The imagery is available in both 'unprocessed' and orthorectified formats. The orthos are both image strips and mosaics. An orthomosaic of the earth became available in August. Additionally, multispectral imagery is aquired by NGA from WV-2 (8 band) and IKONOS (4 band) with every pan shot. The Polar Geospatial Center has developed the capacity to process as many as 5000 scenes or approximately one third of the US lower 48 states a day. This enables researchers to request imagery for large geographic areas to be custom processed to their specifications. To make this imagery more easily accessible for researchers, the Polar Geospatial Center has developed an imagery mosaic, viewer and web services for 60% of Antarctica, 80% of Greenland and 50% of Alaska. Areas are updated as new imagery is collected. We will discuss data access requirements and limitations, current capabilities, and future direction.

  20. Spatial Resolution Characterization for AWiFS Multispectral Images

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Ryan, Robert E.; Pagnutti, Mary; Stanley, Thomas

    2006-01-01

    Within the framework of the Joint Agency Commercial Imagery Evaluation program, the National Aeronautics and Space Administration, the National Geospatial-Intelligence Agency, and the U.S. Geological Survey cooperate in the characterization of high-to-moderate-resolution commercial imagery of mutual interest. One of the systems involved in this effort is the Advanced Wide Field Sensor (AWiFS) onboard the Indian Remote Sensing (IRS) Reourcesat-1 satellite, IRS-P6. Spatial resolution of the AWiFS multispectral images was characterized by estimating the value of the system Modulation Transfer Function (MTF) at the Nyquist spatial frequency. The Nyquist frequency is defined as half the sampling frequency, and the sampling frequency is equal to the inverse of the ground sample distance. The MTF was calculated as a ratio of the Fourier transform of a profile across an AWiFS image of the Lake Pontchartrain Causeway Bridge and the Fourier transform of a profile across an idealized model of the bridge for each spectral band evaluated. The mean MTF value for the AWiFS imagery evaluated was estimated to be 0.1.