Science.gov

Sample records for airborne multispectral imagery

  1. Identification of landslides in clay terrains using Airborne Thematic Mapper (ATM) multispectral imagery

    NASA Astrophysics Data System (ADS)

    Whitworth, Malcolm; Giles, David; Murphy, William

    2002-01-01

    The slopes of the Cotswolds Escarpment in the United Kingdom are mantled by extensive landslide deposits, including both relict and active features. These landslides pose a significant threat to engineering projects and have been the focus of research into the use of airborne remote sensing data sets for landslide mapping. Due to the availability of extensive ground investigation data, a test site was chosen on the slopes of the Cotswolds Escarpment above the village of Broadway, Worcestershire, United Kingdom. Daedalus Airborne Thematic Mapper (ATM) imagery was subsequently acquired by the UK Natural Environment Research Council (NERC) to provide high-resolution multispectral imagery of the Broadway site. This paper assesses the textural enhancement of ATM imagery as an image processing technique for landslide mapping at the Broadway site. Results of three kernel based textural measures, variance, mean euclidean distance (MEUC) and grey level co-occurrence matrix (GLCM) entropy are presented. Problems encountered during textural analysis, associated with the presence of dense woodland within the project area, are discussed and a solution using Principal Component Analysis (PCA) is described. Landslide features in clay dominated terrains can be identified through textural enhancement of airborne multispectral imagery. The kernel based textural measures tested in the current study were all able to enhance areas of slope instability within ATM imagery. Additionally, results from supervised classification of the combined texture-principal component dataset show that texture based image classification can accurately classify landslide regions and that by including a Principal Component image, woodland and landslide classes can be differentiated successfully during the classification process.

  2. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

    USGS Publications Warehouse

    Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John

    2016-01-01

    Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

  3. 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%).

  4. Airborne Imagery

    NASA Technical Reports Server (NTRS)

    1983-01-01

    ATM (Airborne Thematic Mapper) was developed for NSTL (National Space Technology Companies) by Daedalus Company. It offers expanded capabilities for timely, accurate and cost effective identification of areas with prospecting potential. A related system is TIMS, Thermal Infrared Multispectral Scanner. Originating from Landsat 4, it is also used for agricultural studies, etc.

  5. 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...

  6. 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...

  7. Estimating Evapotranspiration over Heterogeneously Vegetated Surfaces using Large Aperture Scintillometer, LiDAR, and Airborne Multispectral Imagery

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    Estimates of evapotranspiration (ET) over heterogeneous areas is challenging especially in water-limited sparsely vegetated environments. New techniques such as airborne full-waveform LiDAR (Light Detection and Ranging) and high resolution multispectral and thermal imagery can provide enough detail of sparse canopies to improve energy balance model estimations as well as footprint analysis of scintillometer data. The objectives of this study were to estimate ET over such areas and develop methodologies for the use of these airborne data technologies. Because of the associated heterogeneity, this study was conducted over the Cibola National wildlife refuge, southern California on an area dominated with tamarisk (salt cedar) forest (90%) interspersed with arrowweed and bare soil (10%). A set of two large aperture scintillometers (LASs) were deployed over the area to provide estimates of sensible heat flux (HLAS). The LASs were distributed over the area in a way that allowed capturing different surface spatial heterogeneity. Bowen ratio systems were used to provide hydrometeorological variables and surface energy balance fluxes (SEBF) (i.e. Rn, G, H, and LE) measurements. Scintillometer-based estimates of HLAS were improved by considering the effect of the corresponding 3D footprint and the associated displacement height (d) and the roughness length (z0) following Geli et al. (2011). The LiDAR data were acquired using the LASSI Lidar developed at Utah State University (USU). The data was used to obtain 1-m spatial resolution DEM's and vegetation canopy height to improve the HLAS estimates. The BR measurements of Rn and G were combined with LAS estimates, HLAS, to provide estimates of LELASas a residual of the energy balance equation. A thermal remote sensing model namely the two source energy balance (TSEB) of Norman et al. (1995) was applied to provide spatial estimates of SEBF. Four airborne images at 1-4 meter spatial resolution acquired using the USU airborne

  8. Analysis of airborne multi-spectral imagery of an oil spill field trial

    SciTech Connect

    Kalnins, V.J.; Freemantle, J.R.; Brown, C.E.

    1996-12-31

    A field trial was conducted at Canadian Forces Base Petawawa in May 1993 by the Emergencies Science Division of Environment Canada to test the effectiveness of remote sensing systems to detect oil spills. Shallow test pools covered with various thicknesses and types of oil were overflown by a number of sensors. Imagery from one of the sensors used, the Multi-element Electro-optical Imaging Scanner (MEIS), has recently been transcribed from high density digital tape and analyzed. The MEIS sensor was flown on a Falcon 20 jet and collected data at 7 different wavelengths from 518 nm to 873 nm. Preliminary results show that one of the slicks, Hydraulic Fluid, can be readily identified by its distinctive color in the visible region. The oil slicks, at least under these very controlled conditions, presented unique spectral signatures which could be identified using normal image processing classification techniques.

  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. 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.

  14. Documenting and Communicating the Dynamics of a Rapidly Changing Cryosphere Through the Use of Repeat Ground-Based, Airborne, and Space-Based Photography and Multispectral Imagery

    NASA Astrophysics Data System (ADS)

    Molnia, B. F.

    2009-04-01

    Alaska supports thousands of glaciers, covering an area of about 75,000 square kilometers. Today, most large low elevation Alaskan glaciers are rapidly retreating and/or thinning in response to increasing temperature. Considering the breadth of Alaska's glacier cover, documenting the response of these glaciers to changing climate is only possible through a comprehensive collection and assessment of ground-based, airborne, and space-based photography and multispectral imagery. Pairing these data with historical imagery provides unequivocal visual evidence of changes within the glacier component of the Alaskan cryosphere. Since 1972, all Alaskan glaciers have been sequentially imaged with space-based multispectral sensors. Additionally, many Alaskan glaciers have been repeatedly photographed from the ground (beginning in 1893), from the air (beginning in 1926), and from space (beginning in the early 1960s). Analysis of this massive compilation of repeat photographs and multispectral images has been used to quantitatively and qualitatively determine the distribution, extent, and multiple decadal-scale behavior of glaciers throughout Alaska. These results have recently been published by the U.S. Geological Survey in "Glaciers of Alaska", Chapter K of the "Satellite Image Atlas of the Glaciers of the World", Professional Paper 1386-K. Additionally, a website ("Glacier and Landscape Change in Response to Changing Climate" - www.usgs.gov/global_change/glaciers/default.asp) has been developed to broadly communicate and distribute this information to the general public, scientists and engineers, the press, civil protection government agencies, and a multitude of other governmental and non-governmental agencies. This poster presents details about the new book and website. For the poster, several areas with extensive records of historic ground-based photography and space-based imagery were selected to demonstrate the effectiveness of this approach to communicate information

  15. Perceptual evaluation of color transformed multispectral imagery

    NASA Astrophysics Data System (ADS)

    Toet, Alexander; de Jong, Michael J.; Hogervorst, Maarten A.; Hooge, Ignace T. C.

    2014-04-01

    Color remapping can give multispectral imagery a realistic appearance. We assessed the practical value of this technique in two observer experiments using monochrome intensified (II) and long-wave infrared (IR) imagery, and color daylight (REF) and fused multispectral (CF) imagery. First, we investigated the amount of detail observers perceive in a short timespan. REF and CF imagery yielded the highest precision and recall measures, while II and IR imagery yielded significantly lower values. This suggests that observers have more difficulty in extracting information from monochrome than from color imagery. Next, we measured eye fixations during free image exploration. Although the overall fixation behavior was similar across image modalities, the order in which certain details were fixated varied. Persons and vehicles were typically fixated first in REF, CF, and IR imagery, while they were fixated later in II imagery. In some cases, color remapping II imagery and fusion with IR imagery restored the fixation order of these image details. We conclude that color remapping can yield enhanced scene perception compared to conventional monochrome nighttime imagery, and may be deployed to tune multispectral image representations such that the resulting fixation behavior resembles the fixation behavior corresponding to daylight color imagery.

  16. Digital rectification of ERTS multispectral imagery

    NASA Technical Reports Server (NTRS)

    Rifman, S. S.

    1973-01-01

    Rectified ERTS multispectral imagery have been produced utilizing all digital techniques, as the first step toward producing precision corrected imagery. Errors arising from attitude and ephemeris sources have been corrected, and the resultant image is represented in a meter/meter mapping utilizing an intensity resampling technique. Early results from available data indicate negligible degradation of the photometric and resolution properties of the source data as a consequence of the geometric correction process. Work utilizing ground control points to produce precision rectified imagery, and including photometric corrections resulting from available sensor calibration data, is currently in progress.

  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. Airborne remote sensing in precision viticolture: assessment of quality and quantity vineyard production using multispectral imagery: a case study in Velletri, Rome surroundings (central Italy)

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

    During 2008 an experimental study aimed to investigate the capabilities of a new Airborne Remote sensing platform as an aid in precision viticulture was conducted. The study was carried out on 2 areas located in the town of Velletri, near Rome; the acquisitions were conducted on 07-08-2008 and on 09-09-2008, using ASPIS (Advanced Spectroscopic Imager System) the new airborne multispectral sensor, capable to acquire 12 narrow spectral bands (10 nm) located in the visible and near-infrared region. Several vegetation indices, for a total of 22 independent variables, were tested for the estimation of different oenological parameters. Anova test showed that several oenochemical parameters, such as sugars and acidity, differ according to the variety taken into consideration. The remotely sensed data were significantly correlated with the following oenochemical parameters: Leaf Surface Exposed (SFE) (correlation coefficient R2 ~ 0.8), wood pruning (R2 ~ 0.8), reducing sugars (R2 ~ 0.6 and Root Mean Square Error ~ 5g/l), total acidity (R2 ~ 0.6 and RMSE ~ 0.5 g/l), polyphenols (R2~ 0.9) and anthocyanins content (R2 ~ 0.89) in order to provide "prescriptives" thematic maps related to the oenological variables of interest, the relationships previously carried out have been applied to the vegetation indices.

  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. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Semantic segmentation of multispectral overhead imagery

    NASA Astrophysics Data System (ADS)

    Prasad, Lakshman; Pope, Paul A.; Sentz, Kari

    2016-05-01

    Land cover classification uses multispectral pixel information to separate image regions into categories. Image segmentation seeks to separate image regions into objects and features based on spectral and spatial image properties. However, making sense of complex imagery typically requires identifying image regions that are often a heterogeneous mixture of categories and features that constitute functional semantic units such as industrial, residential, or commercial areas. This requires leveraging both spectral classification and spatial feature extraction synergistically to synthesize such complex but meaningful image units. We present an efficient graphical model for extracting such semantically cohesive regions. We employ an initial hierarchical segmentation of images into features represented as nodes of an attributed graph that represents feature properties as well as their adjacency relations with other features. This provides a framework to group spectrally and structurally diverse features, which are nevertheless semantically cohesive, based on user-driven identifications of features and their contextual relationships in the graph. We propose an efficient method to construct, store, and search an augmented graph that captures nonadjacent vicinity relationships of features. This graph can be used to query for semantic notional units consisting of ontologically diverse features by constraining it to specific query node types and their indicated/desired spatial interaction characteristics. User interaction with, and labeling of, initially segmented and categorized image feature graph can then be used to learn feature (node) and regional (subgraph) ontologies as constraints, and to identify other similar semantic units as connected components of the constraint-pruned augmented graph of a query image.

  5. 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.

  6. 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.

  7. 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.

  8. 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).

  9. 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.

  10. 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.

  11. 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.

  12. Evaluating the Potential of Multispectral Airborne LIDAR for Topographic Mapping and Land Cover Classification

    NASA Astrophysics Data System (ADS)

    Wichmann, V.; Bremer, M.; Lindenberger, J.; Rutzinger, M.; Georges, C.; Petrini-Monteferri, F.

    2015-08-01

    Recently multispectral LiDAR became a promising research field for enhanced LiDAR classification workflows and e.g. the assessment of vegetation health. Current analyses on multispectral LiDAR are mainly based on experimental setups, which are often limited transferable to operational tasks. In late 2014 Optech Inc. announced the first commercially available multispectral LiDAR system for airborne topographic mapping. The combined system makes synchronic multispectral LiDAR measurements possible, solving time shift problems of experimental acquisitions. This paper presents an explorative analysis of the first airborne collected data with focus on class specific spectral signatures. Spectral patterns are used for a classification approach, which is evaluated in comparison to a manual reference classification. Typical spectral patterns comparable to optical imagery could be observed for homogeneous and planar surfaces. For rough and volumetric objects such as trees, the spectral signature becomes biased by signal modification due to multi return effects. However, we show that this first flight data set is suitable for conventional geometrical classification and mapping procedures. Additional classes such as sealed and unsealed ground can be separated with high classification accuracies. For vegetation classification the distinction of species and health classes is possible.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Estimating alluvial fan surface ages using Landsat 8 multispectral imagery

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Accurate exposure age models are now essential for geomorphological and stratigraphic field research, and generally depend on laboratory analyses such as radiocarbon, cosmogenic nuclide or luminescence approaches. However, these techniques cannot be deployed in situ in the field, meaning other methods are needed to produce a preliminary age model, map depositional surfaces of different ages, and select sampling sites for the types of laboratory analyses outlined above. With the widespread availability of high-resolution multispectral imagery, a promising approach is to use remotely sensed data to discriminate depositional 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. These surfaces have been mapped in detail in the field, have similar granitic compositions, and have well-constrained exposure ages ranging from modern to ~ 125 ka, measured using a high density of 10-Be cosmogenic nuclide samples. We identify a clear age signal recorded in the spectral properties of these surfaces. With increasing exposure age, there is a predictable redshift effect in the reflectance of the surfaces across the visible and short-wave infrared spectrum. Simple calculations, such as the brightness ratio of red/blue wavelengths, produce sensitive power law relationships with exposure age for at least 125 ka, meaning Landsat 8 imagery can be used to estimate surface exposure age remotely, at least in this calibrated dryland location. The ability to remotely sense exposure age has useful implications for field mapping, selecting suitable sampling sites for laboratory-based exposure age techniques, and correlating existing age constraints to previously un-sampled surfaces. We present the uncertainties associated with this spectral approach to exposure dating, evaluate its likely physical origins, and discuss its applicability

  19. Aerosol Remote Sensing Applications for Airborne Multiangle, Multispectral Shortwave Radiometers

    NASA Astrophysics Data System (ADS)

    von Bismarck, Jonas; Ruhtz, Thomas; Starace, Marco; Hollstein, André; Preusker, René; Fischer, Jürgen

    2010-05-01

    Aerosol particles have an important impact on the surface net radiation budget by direct scattering and absorption (direct aerosol effect) of solar radiation, and also by influencing cloud formation processes (semi-direct and indirect aerosol effects). To study the former, a number of multispectral sky- and sunphotometers have been developed at the Institute for Space Sciences of the Free University of Berlin in the past two decades. The latest operational developments were the multispectral aureole- and sunphotometer FUBISS-ASA2, the zenith radiometer FUBISS-ZENITH, and the nadir polarimeter AMSSP-EM, all designed for a flexible use on moving platforms like aircraft or ships. Currently the multiangle, multispectral radiometer URMS/AMSSP (Universal Radiation Measurement System/ Airborne Multispectral Sunphotometer and Polarimeter) is under construction for a Wing-Pod of the high altitude research aircraft HALO operated by DLR. The system is expected to have its first mission on HALO in 2011. The algorithms for the retrieval of aerosol and trace gas properties from the recorded multidirectional, multispectral radiation measurements allow more than deriving standard products, as for instance the aerosol optical depth and the Angstrom exponent. The radiation measured in the solar aureole contains information about the aerosol phasefunction and therefore allows conclusions about the particle type. Furthermore, airborne instrument operation allows vertically resolved measurements. An inversion algorithm, based on radiative transfer simulations and additionally including measured vertical zenith-radiance profiles, allows conclusions about the aerosol single scattering albedo and the relative soot fraction in aerosol layers. Ozone column retrieval is performed evaluating measurements from pixels in the Chappuis absorption band. A retrieval algorithm to derive the water-vapor column from the sunphotometer measurements is currently under development. Of the various airborne

  20. Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

    PubMed Central

    Boucheron, Laura E; Bi, Zhiqiang; Harvey, Neal R; Manjunath, BS; Rimm, David L

    2007-01-01

    Background We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis. Results For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate) is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum) gave a performance increase of 0.57%, compared to performance of the single best RGB band (red). Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains. Conclusion Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery. PMID:17634098

  1. The new airborne Thermal Infrared Multispectral Scanner (TIMS)

    NASA Technical Reports Server (NTRS)

    Kahle, A. B.

    1983-01-01

    A new airborne Thermal Infrared Multispectral Scanner (TIMS) with six bands between 8 and 12 microns is briefly characterized, and some results of remote sensing experiments are reported. The instrument has an instantaneous field of view of 2.5 milliradians, a total field of view of 80 deg, and a NE Delta T of approximately 0.1-0.3 C depending on the band. In the TIMS image of Death Valley, silica-rich rocks were easily separable from the nonsilicates. The Eureka Quartzite stood out in sharp contrast to other Ordovician and Cambrian metasediments, and Tertiary volcanic rocks were easily separable from both. Also distinguishable were various units in the fan gravels.

  2. 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.

  3. 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

  4. Laboratory and field portable system for calibrating airborne multispectral scanners

    SciTech Connect

    Kuhlow, W.W.

    1981-01-01

    Manufacturers of airborne multispectral scanners suggest procedures for calibration and alignment that are usually awkward and even questionable. For example, the procedures may require: separating the scanner from calibration and alignment sources by 100 feet or more, employing folding mirrors, tampering with the detectors after the procedures are finished, etc. Under the best of conditions such procedures require about three hours yielding questionable confidence in the results; under many conditions, however, procedures commonly take six to eight hours, yielding no satisfactory results. EG and G, Inc. has designed and built a calibration and alignment system for airborne scanners which solves those problems, permitting the procedures to be carried out in about two to three hours. This equipment can be quickly disassembled, transported with the scanner in all but the smallest single engine aircraft, and reassembled in a few hours. The subsystems of this equipment are commonly available from manufacturers of optical and electronic equipment. The other components are easily purchased, or fabricated. The scanner discussed is the Model DS-1260 digital line scanner manufactured by Daedalus Enterprises, Inc. It is a dual-sensor system which is operated in one of two combination of sensors: one spectrometer head (which provides simultaneous coverage in ten visible channels) and one thermal infrared detector, or simply two thermal infrared detectors.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Simulation of LANDSAT multispectral scanner spatial resolution with airborne scanner data

    NASA Technical Reports Server (NTRS)

    Hlavka, C. A.

    1986-01-01

    A technique for simulation of low spatial resolution satellite imagery by using high resolution scanner data is described. The scanner data is convolved with the approximate point spread function of the low resolution data and then resampled to emulate low resolution imagery. The technique was successfully applied to Daedalus airborne scanner data to simulate a portion of a LANDSAT multispectra scanner scene.

  16. Automated detection and mapping of crown discolouration caused by jack pine budworm with 2.5 m resolution multispectral imagery

    NASA Astrophysics Data System (ADS)

    Leckie, Donald G.; Cloney, Ed; Joyce, Steve P.

    2005-05-01

    Jack pine budworm ( Choristoneura pinus pinus (Free.)) is a native insect defoliator of mainly jack pine ( Pinus banksiana Lamb.) in North America east of the Rocky Mountains. Periodic outbreaks of this insect, which generally last two to three years, can cause growth loss and mortality and have an important impact ecologically and economically in terms of timber production and harvest. The jack pine budworm prefers to feed on current year needles. Their characteristic feeding habits cause discolouration or reddening of the canopy. This red colouration is used to map the distribution and intensity of defoliation that has taken place that year (current defoliation). An accurate and consistent map of the distribution and intensity of budworm defoliation (as represented by the red discolouration) at the stand and within stand level is desirable. Automated classification of multispectral imagery, such as is available from airborne and new high resolution satellite systems, was explored as a viable tool for objectively classifying current discolouration. Airborne multispectral imagery was acquired at a 2.5 m resolution with the Multispectral Electro-optical Imaging Sensor (MEIS). It recorded imagery in six nadir looking spectral bands specifically designed to detect discolouration caused by budworm and a near-infrared band viewing forward at 35° was also used. A 2200 nm middle infrared image was acquired with a Daedalus scanner. Training and test areas of different levels of discolouration were created based on field observations and a maximum likelihood supervized classification was used to estimate four classes of discolouration (nil-trace, light, moderate and severe). Good discrimination was achieved with an overall accuracy of 84% for the four discolouration levels. The moderate discolouration class was the poorest at 73%, because of confusion with both the severe and light classes. Accuracy on a stand basis was also good, and regional and within stand

  17. 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...

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

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

    DOE PAGES

    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

  4. 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.

  5. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

    Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

    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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Automated road network extraction from high spatial resolution multi-spectral imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Qiaoping

    For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. Spatial statistical analysis of tree deaths using airborne digital imagery

    NASA Astrophysics Data System (ADS)

    Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

    2013-04-01

    High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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%.

  11. 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.

  12. 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...

  13. 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...

  14. 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

  15. 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.

  16. 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.

  17. 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...

  18. Multi-spectral analysis of ice sheets using co-registered SAR and TM imagery

    NASA Technical Reports Server (NTRS)

    Vornberger, P. L.; Bindschadler, R. A.

    1992-01-01

    Landsat Thematic Mapper and airborne Synthetic Aperture Radar (SAR) imagery acquired over an area of south-western Greenland are coregistered and analyzed. Significant corrections to the SAR data were required to account for range-darkening, non-square pixel dimensions, speckle, and relief distortion. In one area, exposed rock was available for use as co-registration control, while in another area it was absent and supraglacial lakes and streams were used. The coregistered scenes highlight many differences between the optical and radar signatures of ice sheets.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Airborne multisensor pod system (AMPS) data: Multispectral data integration and processing hints

    SciTech Connect

    Leary, T.J.; Lamb, A.

    1996-11-01

    The Department of Energy`s Office of Arms Control and Non-Proliferation (NN-20) has developed a suite of airborne remote sensing systems that simultaneously collect coincident data from a US Navy P-3 aircraft. The primary objective of the Airborne Multisensor Pod System (AMPS) Program is {open_quotes}to collect multisensor data that can be used for data research, both to reduce interpretation problems associated with data overload and to develop information products more complete than can be obtained from any single sensor.{close_quotes} The sensors are housed in wing-mounted pods and include: a Ku-Band Synthetic Aperture Radar; a CASI Hyperspectral Imager; a Daedalus 3600 Airborne Multispectral Scanner; a Wild Heerbrugg RC-30 motion compensated large format camera; various high resolution, light intensified and thermal video cameras; and several experimental sensors (e.g. the Portable Hyperspectral Imager of Low-Light Spectroscopy (PHILLS)). Over the past year or so, the Coastal Marine Resource Assessment (CAMRA) group at the Florida Department of Environmental Protection`s Marine Research Institute (FMRI) has been working with the Department of Energy through the Naval Research Laboratory to develop applications and products from existing data. Considerable effort has been spent identifying image formats integration parameters. 2 refs., 3 figs., 2 tabs.

  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. 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

  7. 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.

  8. 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

  9. Sea surface velocities from visible and infrared multispectral atmospheric mapping sensor imagery

    NASA Technical Reports Server (NTRS)

    Pope, P. A.; Emery, W. J.; Radebaugh, M.

    1992-01-01

    High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Use of airborne multispectral video data for water quality evaluation in Sandy Hook, New Jersey

    NASA Astrophysics Data System (ADS)

    Bagheri, Sima; Stein, Matt

    1992-05-01

    A local mission of short duration was carried out to investigate the relationship between signals acquired by an airborne multispectral camera (MSC-02) developed by XYbion Corporation and in situ water sampling. The MSC-02 was used to produce video images in six spectral bands in the reflective and near-infrared region of the spectrum from which all below-surface hydrological signals originate. Images of halon-coated panels were obtained in all bands to calculate relative radiometric calibration functions. These functions were applied to corresponding spectral images to calculate relative radiances of both panel and estuarine water targets. These values were then input to regression equations to establish a correlation between water constituents (organic/inorganic) and MSC-02 signals indicating the degree of eutrophication in the estuary. It is hypothesized that if reliable relationships between MSC-02 data with fine spatial resolution and selected water quality parameters are obtained, then it would be possible to calibrate the concurrently acquired Landsat 5 thematic mapper (TM) data with coarser spatial resolution for monitoring of estuarine water quality.

  4. Simulated radiance profiles for automating the interpretation of airborne passive multi-spectral infrared images.

    PubMed

    Sulub, Yusuf; Small, Gary W

    2008-10-01

    Methodology is developed for simulating the radiance profiles acquired from airborne passive multispectral infrared imaging measurements of ground sources of volatile organic compounds (VOCs). The simulation model allows the superposition of pure-component laboratory spectra of VOCs onto spectral backgrounds that simulate those acquired during field measurements conducted with a downward-looking infrared line scanner mounted on an aircraft flying at an altitude of 2000-3000 ft (approximately 600-900 m). Wavelength selectivity in the line scanner is accomplished through the use of a multichannel Hg:Cd:Te detector with up to 16 integrated optical filters. These filters allow the detection of absorption and emission signatures of VOCs superimposed on the upwelling infrared background radiance within the instrumental field of view (FOV). By combining simulated radiance profiles containing analyte signatures with field-collected background signatures, supervised pattern recognition methods can be employed to train automated classifiers for use in detecting the signatures of VOCs during field measurements. The targeted application for this methodology is the use of the imaging system to detect releases of VOCs during emergency response scenarios. In the work described here, the simulation model is combined with piecewise linear discriminant analysis to build automated classifiers for detecting ethanol and methanol. Field data collected during controlled releases of ethanol, as well as during a methanol release from an industrial facility, are used to evaluate the methodology.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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).

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Detection of gaseous plumes in airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Agassi, Eyal; Hirsch, Eitan; Chamberland, Martin; Gagnon, Marc-André; Eichstaedt, Holger

    2016-05-01

    The thermal hyperspectral sensor Hyper-Cam was mounted on a light aircraft and measured continuous releases of several atmospheric tracers from a height of 2 km. A unique detection algorithm that eliminates the need for clear background estimation was operated over the acquired data with excellent detection results. The data-cubes were acquired in a "target mode", which is a unique method of operation of the Hyper-Cam sensor. This method provides multiple views of the plume which can be exploited to enhance the detection performance. These encouraging results demonstrate the utility of airborne LWIR hyperspectral imaging for efficient detection and mapping of effluent gases for environmental monitoring.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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%.

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Airborne multispectral identification of individual cotton plants using consumer-grade cameras

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Although multispectral remote sensing using consumer-grade cameras has successfully identified fields of small cotton plants, improvements to detection sensitivity are needed to identify individual or small clusters of plants. The imaging sensor of consumer-grade cameras are based on a Bayer patter...

  11. [Study on artificial neural network combined with multispectral remote sensing imagery for forest site evaluation].

    PubMed

    Gong, Yin-Xi; He, Cheng; Yan, Fei; Feng, Zhong-Ke; Cao, Meng-Lei; Gao, Yuan; Miao, Jie; Zhao, Jin-Long

    2013-10-01

    Multispectral remote sensing data containing rich site information are not fully used by the classic site quality evaluation system, as it merely adopts artificial ground survey data. In order to establish a more effective site quality evaluation system, a neural network model which combined remote sensing spectra factors with site factors and site index relations was established and used to study the sublot site quality evaluation in the Wangyedian Forest Farm in Inner Mongolia Province, Chifeng City. Based on the improved back propagation artificial neural network (BPANN), this model combined multispectral remote sensing data with sublot survey data, and took larch as example, Through training data set sensitivity analysis weak or irrelevant factor was excluded, the size of neural network was simplified, and the efficiency of network training was improved. This optimal site index prediction model had an accuracy up to 95.36%, which was 9.83% higher than that of the neural network model based on classic sublot survey data, and this shows that using multi-spectral remote sensing and small class survey data to determine the status of larch index prediction model has the highest predictive accuracy. The results fully indicate the effectiveness and superiority of this method.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields

    NASA Astrophysics Data System (ADS)

    Hamzeh, Saeid; Naseri, Abd Ali; AlaviPanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-10-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image acquired on September 7, 2010 were used as hyperspectral and multispectral satellite imagery. Field data including soil salinity in the sugarcane root zone was collected at 191 locations in 25 fields during September 2010. In the first section of the paper, based on the yield potential of sugarcane as influenced by different soil salinity levels provided by FAO, soil salinity was classified into three classes, low salinity (1.7-3.4 dS/m), moderate salinity (3.5-5.9 dS/m) and high salinity (6-9.5) by applying different classification methods including Support Vector Machine (SVM), Spectral Angle Mapper (SAM), Minimum Distance (MD) and Maximum Likelihood (ML) on Hyperion and Landsat images. In the second part of the paper the performance of nine vegetation indices (eight indices from literature and a new developed index in this study) extracted from Hyperion and Landsat data was evaluated for quantitative mapping of salinity stress. The experimental results indicated that for categorical classification of salinity stress, Landsat data resulted in a higher overall accuracy (OA) and Kappa coefficient (KC) than Hyperion, of which the MD classifier using all bands or PCA (1-5) as an input performed best with an overall accuracy and kappa coefficient of 84.84% and 0.77 respectively. Vice versa for the quantitative estimation of salinity stress, Hyperion outperformed Landsat. In this case, the salinity and water stress index (SWSI) has the best prediction of salinity stress with an R2 of 0.68 and RMSE of 1.15 dS/m for Hyperion followed by Landsat data with an R2 and RMSE of 0.56 and 1.75 dS/m respectively. It was concluded that categorical mapping of salinity stress is the best option

  17. Multispectral Thermal Imagery and Its Application to the Geologic Mapping of the Koobi Fora Formation, Northwestern Kenya

    SciTech Connect

    Green, Mary K.

    2005-12-01

    The Koobi Fora Formation in northwestern Kenya has yielded more hominin fossils dated between 2.1 and 1.2 Ma than any other location on Earth. This research was undertaken to discover the spectral signatures of a portion of the Koobi Fora Formation using imagery from the DOE's Multispectral Thermal Imager (MTI) satellite. Creation of a digital geologic map from MTI imagery was a secondary goal of this research. MTI is unique amongst multispectral satellites in that it co-collects data from 15 spectral bands ranging from the visible to the thermal infrared with a ground sample distance of 5 meters per pixel in the visible and 20 meters in the infrared. The map was created in two stages. The first was to correct the base MTI image using spatial accuracy assessment points collected in the field. The second was to mosaic various MTI images together to create the final Koobi Fora map. Absolute spatial accuracy of the final map product is 73 meters. The geologic classification of the Koobi Fora MTI map also took place in two stages. The field work stage involved location of outcrops of different lithologies within the Koobi Fora Formation. Field descriptions of these outcrops were made and their locations recorded. During the second stage, a linear spectral unmixing algorithm was applied to the MTI mosaic. In order to train the linear spectra unmixing algorithm, regions of interest representing four different classes of geologic material (tuff, alluvium, carbonate, and basalt), as well as a vegetation class were defined within the MTI mosaic. The regions of interest were based upon the aforementioned field data as well as overlays of geologic maps from the 1976 Iowa State mapping project. Pure spectra were generated for each class from the regions of interest, and then the unmixing algorithm classified each pixel according to relative percentage of classes found within the pixel based upon the pure spectra values. A total of four unique combinations of geologic classes

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. [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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Comparison of multispectral airborne scanner reflectance images with ground surface reflectance measurements

    SciTech Connect

    Kollewe, M.; Bienlein, J.; Kollewe, T.; Spitzer, H.

    1996-11-01

    Simultaneously with an airborne data taking campaign near the city of Nurnberg (FRG), performed with an imaging 11-channel scanner of type Daedalus AADS 1268, ground reference measurements of reflectance spectra were conducted with a spectrally high resolving spectroradiometer of type IRIS at selected test sites. Based on a method developed reflectance images are calculated from the aerial raw data. Thus, physical quantities of the surfaces are generated, which are independent of illumination and registration conditions. The airborne scanner reflectance images are compared with ground reference reflectance measurements. The comparison yields deviations up to 35%. They can partially be explained by an inaccurate calibration of the airborne scanner. In addition, errors appear during calculation of the reflectances due to simplifying model assumptions and an inexact knowledge of the values of the model input parameters. It is shown that calibration of the airborne scanner data with the ground reference measurements improves the results, as compared to calibration based on laboratory testbench measurements. 8 refs., 4 figs., 1 tab.

  10. 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.

  11. 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.

  12. 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.

  13. 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.; 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Estimating vegetation coverage in St. Joseph Bay, Florida with an airborne multispectral scanner

    NASA Technical Reports Server (NTRS)

    Savastano, K. J.; Faller, K. H.; Iverson, R. L.

    1984-01-01

    A four-channel multispectral scanner (MSS) carried aboard an aircraft was used to collect data along several flight paths over St. Joseph Bay, FL. Various classifications of benthic features were defined from the results of ground-truth observations. The classes were statistically correlated with MSS channel signal intensity using multivariate methods. Application of the classification measures to the MSS data set allowed computer construction of a detailed map of benthic features of the bay. Various densities of segrasses, various bottom types, and algal coverage were distinguished from water of various depths. The areal vegetation coverage of St. Joseph Bay was not significantly different from the results of a survey conducted six years previously, suggesting that seagrasses are a very stable feature of the bay bottom.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  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. 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.

  9. Estimating evapotranspiration of riparian vegetation using high resolution multispectral, thermal infrared and lidar data

    NASA Astrophysics Data System (ADS)

    Neale, Christopher M. U.; Geli, Hatim; Taghvaeian, Saleh; Masih, Ashish; Pack, Robert T.; Simms, Ronald D.; Baker, Michael; Milliken, Jeff A.; O'Meara, Scott; Witherall, Amy J.

    2011-11-01

    High resolution airborne multispectral and thermal infrared imagery was acquired over the Mojave River, California with the Utah State University airborne remote sensing system integrated with the LASSI imaging Lidar also built and operated at USU. The data were acquired in pre-established mapping blocks over a 2 day period covering approximately 144 Km of the Mojave River floodplain and riparian zone, approximately 1500 meters in width. The multispectral imagery (green, red and near-infrared bands) was ortho-rectified using the Lidar point cloud data through a direct geo-referencing technique. Thermal Infrared imagery was rectified to the multispectral ortho-mosaics. The lidar point cloud data was classified to separate ground surface returns from vegetation returns as well as structures such as buildings, bridges etc. One-meter DEM's were produced from the surface returns along with vegetation canopy height also at 1-meter grids. Two surface energy balance models that use remote sensing inputs were applied to the high resolution imagery, namely the SEBAL and the Two Source Model. The model parameterizations were slightly modified to accept high resolution imagery (1-meter) as well as the lidar-based vegetation height product, which was used to estimate the aerodynamic roughness length. Both models produced very similar results in terms of latent heat fluxes (LE). Instantaneous LE values were extrapolated to daily evapotranspiration rates (ET) using the reference ET fraction, with data obtained from a local weather station. Seasonal rates were obtained by extrapolating the reference ET fraction according to the seasonal growth habits of the different species. Vegetation species distribution and area were obtained from classification of the multispectral imagery. Results indicate that cottonwood and salt cedar (tamarisk) had the highest evapotranspiration rates followed by mesophytes, arundo, mesquite and desert shrubs. This research showed that high

  10. 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. ...

  11. 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.

  12. 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

  13. 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

  14. 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).

  15. 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.

  16. 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.

  17. 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

  18. 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...

  19. 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

  20. Hurricane Georges' Landfall in the Dominican Republic: Detailed Airborne Doppler Radar Imagery

    NASA Technical Reports Server (NTRS)

    Geerts, B.; Heymsfield, G. M.; Tian, L.; Halverson, J. B.; Guillory, A.; Mejia, M. I.

    1999-01-01

    Current understanding of landfalling tropical cyclones is limited, especially with regard to convective scale processes. On 22 September 1998 Hurricane Georges made landfall on the island of Hispaniola, leaving behind a trail of death and devastation, largely the result of excessive rainfall, not sea level surge or wind. Detailed airborne measurements were taken as part of the Third Convection and Moisture Experiment (CAMEX-3). Of Particular interest are the ER-2 nadir X-band Doppler radar (EDOP) data, which provide a first-time high-resolution view of the precipitation and airflow changes as a hurricane interacts with mountainous terrain. The circulation of hurricane Georges underwent an obvious transition during landfall, evident in the rapid increase in minimum sea-level pressure, the subsidence of the eyewall anvil, and a decrease in average ice concentrations in the eyewall. The eye, as seen in satellite imagery, disappeared, but contrary to current understanding, this was not due to eyewall contraction but rather to convective eruption within the eye. The main convective event within the eye, with upper-level updraft magnitudes near 20 m/s and 89 GHz brightness temperatures below 100 K, occurred when the eye moved over the Cordillera Central, the island's main mountain chain. The location, intensity and evolution of this convection indicate that it was coupled to the surface orography. It is likely that surface rain rates increased during landfall, because of effective droplet collection, both in the convection and in the more widespread stratiform rainfall areas over the island. Evidence for this is the increase in radar reflectivity below the bright band of 1-2 dB/km down to ground-level. Such increase was absent offshore. Such low-level rain enhancement, which cannot be detected in satellite images of upwelling infrared or microwave radiation, must be due to the ascent of boundary-layer air over the topography.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. [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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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...

  14. 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...

  15. Evaluation of ERTS-1 imagery for land use/resource inventory information. [image enhancement of multispectral photography

    NASA Technical Reports Server (NTRS)

    Hardy, E. E.; Skaley, J. E.; Phillips, E. S.

    1974-01-01

    This investigation was to develop a low cost, manual technique for enhancing ERTS-1 imagery and preparing it in suitable format for use by users with wide and varied interests related to land use and natural resources information. The goals were: to develop enhancement techniques based on concepts and practices extant in photographic sciences, to provide a means of allowing productive interpretation of the imagery by manual means, to produce a product at low cost, to provide a product that would have wide applications, and one compatible with existing information systems. Cost of preparation of the photographically enhanced, enlarged negatives and positives and the diazo materials is about 1 cent per square mile. Cost of creating and mapping a land use classification of twelve use types at a scale of 1:250,000 is only $1 per square mile. The product is understood by users, is economical, and is compatible with existing information systems.

  16. 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

  17. Estimation of vegetation parameters by inversion of radiative-transfer models from multispectral imagery supported by ground control measurements

    NASA Astrophysics Data System (ADS)

    Kurz, Franz; Hellwich, Olaf

    2001-09-01

    We propose a general framework to estimate vegetation parameters from multidimensional remote sensing data using physical models and a moderate amount of ground control data. This framework is exemplarily demonstrated for winter wheat fields imaged by the Daedalus multispectral scanner using physical radiative transfer models, like the SAIL and PROSPECT model, combined with a linear empirical model. Results show the invertibility of the model for leaf area index, chlorophyll content, dry matter, and water content. The attained accuracies of these parameters are compared to the amount of ground control data. The vegetation parameters estimated with help of the devised method are intended to be used to derive information about soil heterogeneities that are important for precision farming.

  18. 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.

  19. 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

  20. 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.

  1. Detection of salmonid thermal refugia from airborne thermal infrared (TIR) imagery

    NASA Astrophysics Data System (ADS)

    Dugdale, S. J.; Bergeron, N.; Rousseau, M.

    2010-12-01

    During elevated summer temperatures, salmonid species seek out areas of cool, well-oxygenated river water to alleviate thermal stress. Collectively known as ‘thermal refugia’, these are of great significance to the ability of salmonids to survive increased water temperatures, and a better understanding of their spatial and temporal characteristics may aid mitigation strategies against the possible effects of climate change on rivers. However, thermal refugia are traditionally hard to detect, and their in-river abundance and spatial patterns are largely unknown. Although previous research has examined TIR imaging as a means to sense river temperatures, few have achieved a resolution amenable to the detection of small thermal anomalies typically used by salmonids, with the majority of literature focusing on the general application of thermal imaging to river temperature detection and analysis. From preliminary research, we note that riverine thermal anomalies (as viewed from TIR imagery) can comprise a number of different forms resulting from a diverse range of sources. Given that the structural, spatial and temporal dynamics of thermal refugia in gravel bed rivers are a presumably a function of the complex geomorphological processes within a catchment, the ability to discriminate multi-scale thermal refugia may aid our comprehension not only of the behaviour of salmonids during high temperature events, but also of the geomorphological phenomena that are fundamental in governing river temperature heterogeneity. Initial thermal infrared imagery acquired in August 2009 suggested that while it is possible to manually detect riverine temperature anomalies, the creation of a dedicated remote sensing platform capable of obtaining both TIR and RGB photography easily and with a resolution amenable to refugia detection would greatly aid our ability to discriminate true refugia from other thermal anomalies (false positives). To this end, we have developed a system able to

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: Data analysis and modelling

    NASA Astrophysics Data System (ADS)

    Bates, Paul D.; Wilson, Matthew D.; Horritt, Matthew S.; Mason, David C.; Holden, Nick; Currie, Anthony

    2006-08-01

    SummaryIn this paper, we use an airborne synthetic aperture radar to map river flood inundation synoptically at fine spatial resolution (1.2 m) along a ˜16 km reach of the River Severn, west-central England. Images were obtained at four times through a large flood event between 8th and 17th November 2000 and processed using a statistical active contour algorithm to yield the flood shoreline at each time. Intersection of these data with a high vertical accuracy survey of floodplain topography obtained from airborne laser altimetry permitted the calculation of dynamic changes in inundated area, total reach storage and rates of reach dewatering. In addition, comparison of the data to gauged flow rates, the measured floodplain topography and map data giving the location of embankments and drainage channels on the floodplain yields new insights into the factors controlling the development of inundation patterns at a variety of scales. Finally, the data were used to assess the performance of a simple two-dimensional flood inundation model, LISFLOOD-FP, and allows us, for the first time, to validate the dynamic performance of the model. This process is shown to give new information into structural weaknesses of the model and suggests possible future developments, including the incorporation of a better description of floodplain hydrological processes in the hydraulic model to represent more accurately the dewatering of the floodplain.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Paul, George; Gowda, Prasanna H.; Vara Prasad, P. V.; Howell, Terry A.; Staggenborg, Scott A.; Neale, Christopher M. U.

    2013-09-01

    In this study, Surface Energy Balance Algorithm for Land (SEBAL) was evaluated for its ability to derive aerodynamic components and surface energy fluxes from very high resolution airborne remote sensing data acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2008 (BEAREX08) in Texas, USA. Issues related to hot and cold pixel selection and the underlying assumptions of difference between air and surface temperature (dT) being linearly related to the surface temperature were also addressed. Estimated instantaneous evapotranspiration (ET) and other components of the surface energy balance were compared with measured data from four large precision weighing lysimeter fields, two each managed under irrigation and dryland conditions. Instantaneous ET was estimated with overall mean bias error and root mean square error (RMSE) of 0.13 and 0.15 mm h-1 (23.8 and 28.2%) respectively, where relatively large RMSE was contributed by dryland field. Sensitivity analysis of the hot and cold pixel selection indicated that up to 20% of the variability in ET estimates could be attributed to differences in the surface energy balance and roughness properties of the anchor pixels. Adoption of an excess resistance to heat transfer parameter model into SEBAL significantly improved the instantaneous ET estimates.

  17. 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

  18. 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

  19. 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.

  20. Empirical water depth predictions in Dublin Bay based on satellite EO multispectral imagery and multibeam data using spatially weighted geographical analysis

    NASA Astrophysics Data System (ADS)

    Monteys, Xavier; Harris, Paul; Caloca, Silvia

    2014-05-01

    The coastal shallow water zone can be a challenging and expensive environment within which to acquire bathymetry and other oceanographic data using traditional survey methods. Dangers and limited swath coverage make some of these areas unfeasible to survey using ship borne systems, and turbidity can preclude marine LIDAR. As a result, an extensive part of the coastline worldwide remains completely unmapped. Satellite EO multispectral data, after processing, allows timely, cost efficient and quality controlled information to be used for planning, monitoring, and regulating coastal environments. It has the potential to deliver repetitive derivation of medium resolution bathymetry, coastal water properties and seafloor characteristics in shallow waters. Over the last 30 years satellite passive imaging methods for bathymetry extraction, implementing analytical or empirical methods, have had a limited success predicting water depths. Different wavelengths of the solar light penetrate the water column to varying depths. They can provide acceptable results up to 20 m but become less accurate in deeper waters. The study area is located in the inner part of Dublin Bay, on the East coast of Ireland. The region investigated is a C-shaped inlet covering an area of 10 km long and 5 km wide with water depths ranging from 0 to 10 m. The methodology employed on this research uses a ratio of reflectance from SPOT 5 satellite bands, differing to standard linear transform algorithms. High accuracy water depths were derived using multibeam data. The final empirical model uses spatially weighted geographical tools to retrieve predicted depths. The results of this paper confirm that SPOT satellite scenes are suitable to predict depths using empirical models in very shallow embayments. Spatial regression models show better adjustments in the predictions over non-spatial models. The spatial regression equation used provides realistic results down to 6 m below the water surface, with

  1. 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.

  2. Detection in urban scenario using combined airborne imaging sensors

    NASA Astrophysics Data System (ADS)

    Renhorn, Ingmar; Axelsson, Maria; Benoist, Koen; Bourghys, Dirk; Boucher, Yannick; Briottet, Xavier; De Ceglie, Sergio; Dekker, Rob; Dimmeler, Alwin; Dost, Remco; Friman, Ola; Kåsen, Ingebjørg; Maerker, Jochen; van Persie, Mark; Resta, Salvatore; Schwering, Piet; Shimoni, Michal; Haavardsholm, Trym Vegard

    2012-06-01

    The EDA project "Detection in Urban scenario using Combined Airborne imaging Sensors" (DUCAS) is in progress. The aim of the project is to investigate the potential benefit of combined high spatial and spectral resolution airborne imagery for several defense applications in the urban area. The project is taking advantage of the combined resources from 7 contributing nations within the EDA framework. An extensive field trial has been carried out in the city of Zeebrugge at the Belgian coast in June 2011. The Belgian armed forces contributed with platforms, weapons, personnel (soldiers) and logistics for the trial. Ground truth measurements with respect to geometrical characteristics, optical material properties and weather conditions were obtained in addition to hyperspectral, multispectral and high resolution spatial imagery. High spectral/spatial resolution sensor data are used for detection, classification, identification and tracking.

  3. 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.

  4. 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

  5. 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

  6. Evolution of a highly dilatant fault zone in the grabens of Canyonlands National Park, Utah/USA - integrating field work, 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.

    2015-03-01

    The grabens of the 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 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 model of the highly dilatant fault geometry in profile. Sinkholes observed in the field as well as in airborne imagery give insights in local massive dilatancy and show where water and sediments are transported underground. Based on correlations of paleosols observed in outcrops and GPR profiles, we argue that the grabens in Canyonlands National Park are either older than previously assumed, or that sedimentation rates were much higher in the Pleistocene.

  7. 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.

  8. 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.

  9. 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

  10. 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...

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. MAJOR SOURCE OF SIDE-LOOKING AIRBORNE RADAR IMAGERY FOR RESEARCH AND EXPLORATION: THE U. S. GEOLOGICAL SURVEY.

    USGS Publications Warehouse

    Kover, Allan N.; Jones, John Edwin; ,

    1985-01-01

    The US Geological Survey (USGS) instituted a program in 1980 to acquire side-looking airbore radar (SLAR) data and make these data readily available to the public in a mosaic format comparable to the USGS 1:250,000-scale topographic map series. The SLAR data are also available as strip images at an acquisition scale of 1:250,000 or 1:400,000 (depending on the acquisition system), as a variety of print products and indexes, and in a limited amount in digital form on computer compatible tapes. Three different commercial X-band (3-cm) systems were used to acquire the imagery for producing the mosaics.

  18. 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

  19. 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.

  20. 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.

  1. Correlation of coastal water turbidity and current circulation with ERTS-1 and Skylab imagery

    NASA Technical Reports Server (NTRS)

    Klemas, V.; Otley, M.; Philpot, W.; Wethe, C.; Rogers, R.; Shah, N.

    1974-01-01

    The article reviews investigations of current circulation patterns, suspended sediment concentration, coastal frontal systems, and waste disposal plumes based on visual interpretation and digital analysis of ERTS-1 and Skylab/EREP imagery. Data on conditions in the Delaware Bay area were obtained from 10 ERTS-1 passes and one Skylab pass, with simultaneous surface and airborne sensing. The current patterns and sediments observed by ERTS-1 correlated well with ground-based observations. Methods are suggested which would make it possible to identify certain pollutants and sediment types from multispectral scanner data.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. Optimization of spectral indices and long-term separability analysis for classification of cereal crops using multi-spectral RapidEye imagery

    NASA Astrophysics Data System (ADS)

    Gerstmann, Henning; Möller, Markus; Gläßer, Cornelia

    2016-10-01

    Crop monitoring using remotely sensed image data provides valuable input for a large variety of applications in environmental and agricultural research. However, method development for discrimination between spectrally highly similar crop species remains a challenge in remote sensing. Calculation of vegetation indices is a frequently applied option to amplify the most distinctive parts of a spectrum. Since no vegetation index exist, that is universally best-performing, a method is presented that finds an index that is optimized for the classification of a specific satellite data set to separate two cereal crop types. The η2 (eta-squared) measure of association - presented as novel spectral separability indicator - was used for the evaluation of the numerous tested indices. The approach is first applied on a RapidEye satellite image for the separation of winter wheat and winter barley in a Central German test site. The determined optimized index allows a more accurate classification (97%) than several well-established vegetation indices like NDVI and EVI (<87%). Furthermore, the approach was applied on a RapidEye multi-spectral image time series covering the years 2010-2014. The optimized index for the spectral separation of winter barley and winter wheat for each acquisition date was calculated and its ability to distinct the two classes was assessed. The results indicate that the calculated optimized indices perform better than the standard indices for most seasonal parts of the time series. The red edge spectral region proved to be of high significance for crop classification. Additionally, a time frame of best spectral separability of wheat and barley could be detected in early to mid-summer.

  16. 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.

  17. 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 E.; 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

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. High-resolution imagery applications in the littorals

    NASA Astrophysics Data System (ADS)

    Abileah, Ronald

    2001-12-01

    We focus on three applications of high-resolution imagery in the littorals: mapping bathymetry, monitoring the health of coral reefs, and taking censuses of marine mammals. All three applications show the importance and potential benefits of higher-resolution imagery. Increased radiometric sensitivity and the simultaneous collection of panchromatic and multispectral imagery are also important. An Ikonos image of Maui is used to demonstrate these applications. We also briefly explain some important differences between multispectral remote sensing over water and land.

  4. Airborne remote sensing for Deepwater Horizon oil spill emergency response

    NASA Astrophysics Data System (ADS)

    Kroutil, Robert T.; Shen, Sylvia S.; Lewis, Paul E.; Miller, David P.; Cardarelli, John; Thomas, Mark; Curry, Timothy; Kudaraskus, Paul

    2010-08-01

    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 rig disaster. The ASPECT aircraft was released from service on August 9, 2010 after having flown over 75 missions that included over 250 hours of flight operation. ASPECT's initial mission responsibility was to provide air quality monitoring (i.e., identification of vapor species) during various oil burning operations. The ASPECT airborne wide-area infrared remote sensing spectral data was used to evaluate the hazard potential of vapors being produced from open water oil burns near the Deepwater Horizon rig site. Other significant remote sensing data products and innovations included the development of an advanced capability to correctly identify, locate, characterize, and quantify surface oil that could reach beaches and wetland areas. This advanced identification product provided the Incident Command an improved capability to locate surface oil in order to improve the effectiveness of oil skimmer vessel recovery efforts directed by the US Coast Guard. This paper discusses the application of infrared spectroscopy and multispectral infrared imagery to address significant issues associated with this national crisis. More specifically, this paper addresses the airborne remote sensing capabilities, technology, and data analysis products developed specifically to optimize the resources and capabilities of the Deepwater Horizon Incident Command structure personnel and their remediation efforts.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. Perceptual evaluation of colorized nighttime imagery

    NASA Astrophysics Data System (ADS)

    Toet, Alexander; de Jong, Michael J.; Hogervorst, Maarten A.; Hooge, Ignace T. C.

    2014-02-01

    We recently presented a color transform that produces fused nighttime imagery with a realistic color appearance (Hogervorst and Toet, 2010, Information Fusion, 11-2, 69-77). To assess the practical value of this transform we performed two experiments in which we compared human scene recognition for monochrome intensified (II) and longwave infrared (IR) imagery, and color daylight (REF) and fused multispectral (CF) imagery. First we investigated the amount of detail observers can perceive in a short time span (the gist of the scene). Participants watched brief image presentations and provided a full report of what they had seen. Our results show that REF and CF imagery yielded the highest precision and recall measures, while both II and IR imagery yielded significantly lower values. This suggests that observers have more difficulty extracting information from monochrome than from color imagery. Next, we measured eye fixations of participants who freely explored the images. Although the overall fixation behavior was similar across image modalities, the order in which certain details were fixated varied. Persons and vehicles were typically fixated first in REF, CF and IR imagery, while they were fixated later in II imagery. In some cases, color remapping II imagery and fusion with IR imagery restored the fixation order of these image details. We conclude that color remapping can yield enhanced scene perception compared to conventional monochrome nighttime imagery, and may be deployed to tune multispectral image representation such that the resulting fixation behavior resembles the fixation behavior for daylight color imagery.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Coastal survey with a multispectral video system

    NASA Astrophysics Data System (ADS)

    Niedrauer, Terren M.

    1991-09-01

    Xybion Corporation has developed an airborne multispectral measurement system (AMMS) as part of a small business innovative research contract with the Department of Commerce. The AMMS is a low-cost portable system that can provide multispectral data suitable for frequent measurement and mapping. It has been used for measurement of estuarine concentrations of chlorophyll and suspended sediments and mapping of submerged aquatic vegetation fields. Other applications include the identification of tree and plant species, the detection of crop stress, and the detection of man-made objects in a background of vegetation. The AMMS provides high spatial resolution multispectral image data in six user-defined bands in the 400- 900 nm wavelength region. The AMMS includes a highly innovative, computer-controlled, intensified, multispectral video camera (IMC), a spectroradiometer, a S-VHS VCR, and a portable IBM-PC-compatible computer system. An airborne trial over Cheseapeake Bay in June 1990 showed its ability to detect variations in water parameters. Simultaneous measurements from a ship provided sea-surface data, including continuous fluorometer readings, and discrete samples of chlorophyll, suspended sediments, and several other water parameters. Two spectroradiometers were included in the airborne equipment. One pointed downward to provide a high-resolution spectrum of a large water area under the plane. The other spectroradiometer measured downwelling irradiance. This allowed for conversion of the upwelling radiances measured by the IMC into reflectances. Calibrations for the IMC and the spectroradiometers were done before and after the trials. The results of this airborne trial are presented.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Resolution Enhancement of Multilook Imagery

    SciTech Connect

    Galbraith, Amy E.

    2004-07-01

    This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The important topic of aliasing is examined in the context of the POCS resolution enhancement algorithm performance. In addition, the extension of the method to multispectral sensor images is discussed and an example is shown using multispectral confocal fluorescence imaging microscope data. Finally, the remote sensing issues of atmospheric path radiance and directional reflectance variations are explored to determine their effect on the resolution enhancement performance.

  5. Landsat imagery: a unique resource

    USGS Publications Warehouse

    Miller, H.; Sexton, N.; Koontz, L.

    2011-01-01

    Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

  6. 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

  7. Multispectral imaging using a single bucket detector

    NASA Astrophysics Data System (ADS)

    Bian, Liheng; Suo, Jinli; Situ, Guohai; Li, Ziwei; Fan, Jingtao; Chen, Feng; Dai, Qionghai

    2016-04-01

    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.

  8. 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.

  9. An aerial multispectral thermographic survey of the Oak Ridge Reservation for selected areas K-25, X-10, and Y-12, Oak Ridge, Tennessee

    SciTech Connect

    Ginsberg, I.W.

    1996-10-01

    During June 5-7, 1996, the Department of Energy`s Remote Sensing Laboratory performed day and night multispectral surveys of three areas at the Oak Ridge Reservation: K-25, X-10, and Y-12. Aerial imagery was collected with both a Daedalus DS1268 multispectral scanner and National Aeronautics and Space Administration`s Thermal Infrared Multispectral System, which has six bands in the thermal infrared region of the spectrum. Imagery from the Thermal Infrared Multispectral System was processed to yield images of absolute terrain temperature and of the terrain`s emissivities in the six spectral bands. The thermal infrared channels of the Daedalus DS1268 were radiometrically calibrated and converted to apparent temperature. A recently developed system for geometrically correcting and geographically registering scanner imagery was used with the Daedalus DS1268 multispectral scanner. The corrected and registered 12-channel imagery was orthorectified using a digital elevation model. 1 ref., 5 figs., 5 tabs.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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 ...

  20. Use of airborne hyperspectral imagery to investigate the influence of soil nitrogen supplies and variable-rate fertilization to winter wheat growth

    NASA Astrophysics Data System (ADS)

    Song, Xiaoyu; Yan, Guangjian; Wang, Jihua; Liu, Liangyun; Xue, Xuzhang; Li, Cunjun; Huang, Wenjiang

    2007-10-01

    Advanced technology in airborne detection of crop growth can help optimize the strategies of fertilization, and help maximize the grain output by adjusting field inputs. In this study, Push-broom Hyperspectral Image sensor (PHI) was used to investigate the influence of soil nitrogen supplied and variable-rate fertilization to the growth of winter wheat. The objective was to determine to what extent the reflectance obtained in the 80 visible and near-infrared (NIR) wavebands (from 410nm to 832nm) might be related to differences of variance of soil nitrogen and variable-rate fertilization. Management plots were arranged at Beijing Precision Farming Experimental Station. Three flights were made during the wheat growing season. Several field experiments, including the crop sampling, soil sampling and variable-rate fertilization were carried out in the field. Data were analyzed for each flight and each band separately. Some spectrum indices were derived from PHI images and statistical correlation analysis were carried out among the spectrum indices and soil nitrogen, variable-rate fertilization amount. In addition, the spectrum indices difference between elongation stage and grain filling stage are calculated and the correlation analysis was also carried out. The analysis results indicated that the reflectance of winter wheat is significantly influenced at certain wavelength by the soil nitrogen and the variable-rate fertilization. The soil nitrogen effect was detectable in all the three flights. Differences in response due to soil nitrogen variance were most evident at spectrum indices, such as dλ red, INFLEX, Green/Red, NIRness, DVI and RDVI. Furthermore, analysis results also indicated that the variable fertilization can reduce the growth difference of winter wheat caused by spatial distribution difference of soil nitrogen.

  1. 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.

  2. Multispectral image visualization through first-order fusion.

    PubMed

    Socolinsky, Diego A; Wolff, Lawrence B

    2002-01-01

    We present a new formalism for the treatment and understanding of multispectral images and multisensor imagery based on first-order contrast information. Although little attention has been paid to the utility of multispectral contrast, we develop a theory for multispectral contrast that enables us to produce an optimal grayscale visualization of the first-order contrast of an image with an arbitrary number of bands. We demonstrate how our technique can reveal significantly more interpretive information to an image analyst, who can use it in a number of image understanding algorithms. Existing grayscale visualization strategies are reviewed. A variety of experimental results are presented to support the performance of the new method. PMID:18244686

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Multispectral imaging for biometrics

    NASA Astrophysics Data System (ADS)

    Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

    2005-03-01

    Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

  10. Multispectral imaging probe

    DOEpatents

    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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Urban area structuring mapping using an airborne polarimetric SAR image

    NASA Astrophysics Data System (ADS)

    Simonetto, Elisabeth; Malak, Charbel

    2009-09-01

    For several years, image classification and pattern recognition algorithms have been developed for the land coverage mapping using radar and multispectral imagery with medium to large pixel size. As several satellites now distribute submetric-pixel and metric-pixel images (for example QUICKBIRD,TERRASAR-X), the research turns to the study of the structure of cities: building structuring, grassy areas, road networks, etc, and the physical description of the urban surfaces. In that context, we propose to underline new potentialities of submetric-pixel polarimetric SAR images. We deal with the characterization of roofs and the mapping of trees. For that purpose, a first analysis based on photo-interpretation and the assessement of several polarimetric descriptors is carried out. Then, an image classification scheme is built using the polarimetric H/alpha-Wishart algorithm, followed by a decision tree. This one is based on the most pertinent polarimetric descriptors and aims at reducing the classification errors. The result proves the potential of such data. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA.

  16. Testing the combined use of LIDAR and High-Resolution Multispectral data for Automatic detection of Landslides in the Marecchia valley, Italy.

    NASA Astrophysics Data System (ADS)

    Lagomarsino, D.; Tanteri, L.; Forzieri, G.; Battistini, A.; Catani, F.

    2012-04-01

    The purpose of this work is to test a method to automatically detect landslides using change detection techniques on airborne sensor data. High spatial resolution multispectral and digital surface model data acquired in two different times are used to identify landslides on a 80 km transect of the Marecchia valley, Italy. Multispectral ADS40 and Light Detection and Ranging (LiDAR) data, acquired in October 2009 and November 2010, were used in this study. High spatial resolution color-infrared digital aerial image data from ADS40 sensor has 4 spectral bands: Red, Green, Blue and NIR. The imagery data has a 12-bit radiometric depth, with 0.2 meter pixel size. Airborne laser scanning data collected by LiDAR sensors were provided in Digital Terrain Model (DTM) and Digital Surface Model (DSM) form with 1-meter spatial resolution and 0.2 meters vertical accuracy. An expert system for change detection and classification of landscapes has been developed; a pixel-oriented approach based on multi-temporal tree classification algorithm was implemented. The tool is driven by a priori knowledge related to the expected temporal variations of remote sensing multispectral and digital surface model data. Detection of land use/cover changes focuses on temporal variations of remote sensing data by discriminating: devegetation, rivegetation, urbanization, demolition, landslide and river bed transitions. In order to better identify the landslide class, further analyses on morphological factors was performed. For this purpose several geo-morphological factors, for which a change can be related to landslide occurrence, were analyzed. A database of the landslides occurred between the two acquisition was built and then statistical analyses were performed to correlate the presence of a landslide with the variations of selected morphological features between the two acquisitions. In order to establish wether or not a parameter variation is an exclusive characteristic of a landslide some

  17. A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. 1: Introduction

    NASA Technical Reports Server (NTRS)

    Vangenderen, J. L. (Principal Investigator); Lock, B. F.

    1976-01-01

    The author has identified the following significant results. This research program has developed a viable methodology for producing small scale rural land use maps in semi-arid developing countries using imagery obtained from orbital multispectral scanners.

  18. Crude oil, petroleum product, and water discrimination on terrestrial substrates with airborne imaging spectroscopy

    NASA Astrophysics Data System (ADS)

    Allen, C. Scott; Krekeler, Mark P. S.

    2011-06-01

    The Deepwater Horizon explosion and subsequent sinking produced the largest oil spill in U.S. history. One of the most prominent portions of the response is mapping the extent to which oil has reached thousands of miles of shoreline. The most common method of detecting oil remains visual spotting from airframes, supplemented by panchromatic / multispectral aerial photography and satellite imagery. While this imagery provides a synoptic view, it is often ambiguous in its ability to discriminate water from hydrocarbon materials. By employing spectral libraries for material identification and discrimination, imaging spectroscopy supplements traditional imaging techniques by providing specific criteria for more accurate petroleum detection and discrimination from water on terrestrial backgrounds. This paper applies a new hydrocarbon-substrate spectral library to SpecTIR HST-3 airborne imaging spectroscopy data from the Hurricane Katrina disaster in 2005. Using common material identification algorithms, this preliminary analysis demonstrates the applicability and limitations of hyperspectral data to petroleum/water discrimination in certain conditions. The current work is also the first application of the petroleum-substrate library to imaging spectroscopy data and shows potential for monitoring long term impacts of Deepwater Horizon.

  19. 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.

  20. 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.

  1. 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.

  2. Common aperture multispectral sensor flight test program

    SciTech Connect

    Bird, R.S.; Kaufman, C.S.

    1996-11-01

    This paper will provide an overview of the Common Aperture Multispectral Sensor (CAMS) Hardware Demonstrator. CAMS is a linescanning sensor that simultaneously collected digital imagery over the Far-IR (8 to 12 {mu}m) and visible spectral (0.55 to 1.1 PM) spectral bands, correlated at the pixel level. CAMS was initially sponsored by the U.S. Naval Air System Commands F/A-18 program office (PMA-265). The current CAMS field tests are under the direction of Northrop-Grumman for the Defense Nuclear Agency (DNA) in support of the Follow-On Open Skies Sensor Evaluation Program (FOSEP) and are scheduled to be conducted in April 1996. 8 figs., 4 tabs.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  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. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Lossless compression algorithm for multispectral imagers

    NASA Astrophysics Data System (ADS)

    Gladkova, Irina; Grossberg, Michael; Gottipati, Srikanth

    2008-08-01

    Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Research for NOAA NESDIS has been directed to finding for the characteristics of satellite atmospheric Earth science Imager sensor data what level of Lossless compression ratio can be obtained as well as appropriate types of mathematics and approaches that can lead to approaching this data's entropy level. Conventional lossless do not achieve the theoretical limits for lossless compression on imager data as estimated from the Shannon entropy. In a previous paper, the authors introduce a lossless compression algorithm developed for MODIS as a proxy for future NOAA-NESDIS satellite based Earth science multispectral imagers such as GOES-R. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. In decompression, the algorithm uses a statistically computed look up table to iteratively predict each channel from a channel decompressed in the previous iteration. In this paper we present a new approach which fundamentally differs from our prior work. In this new approach, instead of having a single predictor for each pair of bands we introduce a piecewise spatially varying predictor which significantly improves the compression results. Our new algorithm also now optimizes the sequence of channels we use for prediction. Our results are evaluated by comparison with a state of the art wavelet based image compression scheme, Jpeg2000. We present results on the 14 channel subset of the MODIS imager, which serves as a proxy for the GOES-R imager. We

  15. Digital preprocessing and classification of multispectral earth observation data

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1976-01-01

    The development of airborne and satellite multispectral image scanning sensors has generated wide-spread interest in application of these sensors to earth resource mapping. These point scanning sensors permit scenes to be imaged in a large number of electromagnetic energy bands between .3 and 15 micrometers. The energy sensed in each band can be used as a feature in a computer based multi-dimensional pattern recognition process to aid in interpreting the nature of elements in the scene. Images from each band can also be interpreted visually. Visual interpretation of five or ten multispectral images simultaneously becomes impractical especially as area studied increases; hence, great emphasis has been placed on machine (computer) techniques for aiding in the interpretation process. This paper describes a computer software system concept called LARSYS for analysis of multivariate image data and presents some examples of its application.

  16. [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.

  17. Multispectral Thermal Imager: overview

    NASA Astrophysics Data System (ADS)

    Bell, W. Randy; Weber, Paul G.

    2001-08-01

    The Multispectral Thermal Imager, MTI, is a research and development project sponsored by the United States Department of Energy. The primary mission is to demonstrate advanced multispectral and thermal imaging from a satellite, including new technologies, data processing and analysis techniques. The MTI builds on the efforts of a number of earlier efforts, including Landsat, NASA remote sensing missions, and others, but the MTI incorporates a unique combination of attributes. The MTI satellite was launched on 12 March 2000 into a 580 km x 610 km, sun-synchronous orbit with nominal 1 am and 1 pm equatorial crossing times. The Air Force Space Test Program provided the Orbital Sciences Taurus launch vehicle. The satellite has a design lifetime of a year, with the goal of three years. The satellite and payload can typically observe six sites per day, with either one or two observations per site from nadir and off-nadir angles. Data are stored in the satellite memory and down-linked to a ground station at Sandia National Laboratory. Data are then forwarded to the Data Processing and Analysis Center at Los Alamos National Laboratory for processing, analysis and distribution to the MTI team and collaborators. We will provide an overview of the Project, a few examples of data products, and an introduction to more detailed presentations in this special session.

  18. 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.

  19. Airborne Transparencies.

    ERIC Educational Resources Information Center

    Horne, Lois Thommason

    1984-01-01

    Starting from a science project on flight, art students discussed and investigated various means of moving in space. Then they made acetate illustrations which could be used as transparencies. The projection phenomenon made the illustrations look airborne. (CS)

  20. Agricultural applications for thermal infrared multispectral scanner data

    NASA Technical Reports Server (NTRS)

    Pelletier, R. E.; Ochoa, M. C.; Hajek, B. F.

    1985-01-01

    The use of the Thermal Infrared Multispectral Scanner (TIMS) data in agricultural landscapes is discussed. The TIMS allows for narrow-band analysis in the 8.2-11.6 micron range at spatial resolutions down to 5 meters in cell size. A coastal plain region in SE Alabama was studied using the TIMS. The crop/plant vigor, canopy density, and thermal response changes for soils obtained from thermal imagery are examined. The application of TIMS data to hydrologic and topographic issues, inventory and conservation monitoring, and the enhancement and extraction of cartographic features is described.

  1. 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.

  2. Snapshot spectral and polarimetric imaging; target identification with multispectral video

    NASA Astrophysics Data System (ADS)

    Bartlett, Brent D.; Rodriguez, Mikel D.

    2013-05-01

    As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

  3. 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

  4. 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.

  5. 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.

  6. Multispectral imaging radar

    NASA Technical Reports Server (NTRS)

    Porcello, L. J.; Rendleman, R. A.

    1972-01-01

    A side-looking radar, installed in a C-46 aircraft, was modified to provide it with an initial multispectral imaging capability. The radar is capable of radiating at either of two wavelengths, these being approximately 3 cm and 30 cm, with either horizontal or vertical polarization on each wavelength. Both the horizontally- and vertically-polarized components of the reflected signal can be observed for each wavelength/polarization transmitter configuration. At present, two-wavelength observation of a terrain region can be accomplished within the same day, but not with truly simultaneous observation on both wavelengths. A multiplex circuit to permit this simultaneous observation has been designed. A brief description of the modified radar system and its operating parameters is presented. Emphasis is then placed on initial flight test data and preliminary interpretation. Some considerations pertinent to the calibration of such radars are presented in passing.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. Multispectral bilateral video fusion.

    PubMed

    Bennett, Eric P; Mason, John L; McMillan, Leonard

    2007-05-01

    We present a technique for enhancing underexposed visible-spectrum video by fusing it with simultaneously captured video from sensors in nonvisible spectra, such as Short Wave IR or Near IR. Although IR sensors can accurately capture video in low-light and night-vision applications, they lack the color and relative luminances of visible-spectrum sensors. RGB sensors do capture color and correct relative luminances, but are underexposed, noisy, and lack fine features due to short video exposure times. Our enhanced fusion output is a reconstruction of the RGB input assisted by the IR data, not an incorporation of elements imaged only in IR. With a temporal noise reduction, we first remove shot noise and increase the color accuracy of the RGB footage. The IR video is then normalized to ensure cross-spectral compatibility with the visible-spectrum video using ratio images. To aid fusion, we decompose the video sources with edge-preserving filters. We introduce a multispectral version of the bilateral filter called the "dual bilateral" that robustly decomposes the RGB video. It utilizes the less-noisy IR for edge detection but also preserves strong visible-spectrum edges not in the IR. We fuse the RGB low frequencies, the IR texture details, and the dual bilateral edges into a noise-reduced video with sharp details, correct chrominances, and natural relative luminances. PMID:17491451

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. Geometric-optics forest canopy modelling for high spatial resolution imagery

    SciTech Connect

    Fournier, R.A., Edwards, G.; Gauthier, R.P.

    1996-11-01

    This research studies processes influencing the radiometric appearance of a forest at fine spatial resolution. A canopy radiance model, Treatment of Radiance Emerging from Light Interactions in a Treed Environment (TRELITE), was formulated using a geometric-optical approach. This model explored the relationship between image radiometric textures and canopy physical parameters. TRELITE`s geometric parameters of influence were tree shape, pixel dimension, source and viewing directions, and forest configuration. TRELITE`s optical parameters and interaction processes were collimated and sky irradiance, surface reflectivity, object transmissivity, and projected and mutual shading. Simulated airborne images were generated from a physical representation of these parameters. Four conifer plantation test sites were chosen to evaluate the influence of the modelled parameters on the scene radiance. The Multispectral Electro-Optical Imaging Scanner (MEIS-II), with 45 cm spatial resolution for eight channels spanning visible to near-infrared, measured scene radiance. MEIS image radiance patterns were analyzed for single trees, in four monospecific stands. The influence on the simulated radiance of the modelled canopy factors in TRELITE were examined, on a single tree basis, to determine relative importance in high spatial resolution imagery. Several modelling options were tested. Among them, the most appropriate tree outline shape was the truncated ellipse. Details of simulated images, particularly those in shaded areas, compared more favorably with airborne images when both collimated and diffuse illumination were modelled. Three processes emerged which were imperative to successful simulation: mutual shading (on-object and between object), bidirectional reflectance, and light transmissivity through crowns. 9 refs., 2 figs., 2 tabs.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Investigation of Skylab imagery for regional planning. [New York, New Jersey, and Connecticut

    NASA Technical Reports Server (NTRS)

    Harting, W. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

  11. Superresolution image reconstruction using panchromatic and multispectral image fusion

    NASA Astrophysics Data System (ADS)

    Elbakary, M. I.; Alam, M. S.

    2008-08-01

    Hyperspectral imagery is used for a wide variety of applications, including target detection, tacking, agricultural monitoring and natural resources exploration. The main reason for using hyperspectral imagery is that these images reveal spectral information about the scene that is not available in a single band. Unfortunately, many factors such as sensor noise and atmospheric scattering degrade the spatial quality of these images. Recently, many algorithms are introduced in the literature to improve the resolution of hyperspectral images using co-registered high special-resolution imagery such as panchromatic imagery. In this paper, we propose a new algorithm to enhance the spatial resolution of low resolution hyperspectral bands using strongly correlated and co-registered high special-resolution panchromatic imagery. The proposed algorithm constructs the superresolution bands corresponding to the low resolution bands to enhance the resolution using a global correlation enhancement technique. The global enhancement is based on the least square regression and the histogram matching to improve the estimated interpolation of the spatial resolution. The introduced algorithm is considered as an improvement for Price’s algorithm which uses the global correlation only for the spatial resolution enhancement. Numerous studies are conducted to investigate the effect of the proposed algorithm for achieving the enhancement compared to the traditional algorithm for superresolution enhancement. Experiments results obtained using hyperspectral data derived from airborne imaging sensor are presented to verify the superiority of the proposed algorithm.

  12. A program system for efficient multispectral classification

    NASA Astrophysics Data System (ADS)

    Åkersten, S. I.

    Pixelwise multispectral classification is an important tool for analyzing remotely sensed imagery data. The computing time for performing this analysis becomes significantly large when large, multilayer images are analyzed. In the classical implementation of the supervised multispectral classification assuming gaussian-shaped multidimensional class-clusters, the computing time is furthermore approximately proportional to the square of the number of image layers. This leads to very appreciable CPU-times when large numbers of multispectral channels are used and/or temporal classification is performed. In order to decrease computer time, a classification program system has been implemented which has the following characteristics: (1) a simple one-dimensional box classifier, (2) a multidimensional box classifier, (3) a class-pivotal "canonical" classifier utilizing full maximum likelihood and making full use of within-class and between-class statistical characteristics, (4) a hybrid classifier (2 and 3 combined), and (5) a local neighbourhood filtering algorithm producing generalized classification results. The heart of the classifier is the class-pivotal canonical classifier. This algorithm is based upon an idea of Dye suggesting the use of linear transformations making possible a simultaneous evaluation of a measure of the pixel being likely not to belong to the candidate class as well as computing its full maximum likelihood ratio. In case it is more likely to be misclassified the full maximum likelihood evaluation can be truncated almost immediately, i.e. the candidate class can often be rejected using only one or two of the available transformed spectral features. The result of this is a classifier with CPU-time which is empirically shown to be linearly dependent upon the number of image layers. The use of the hybrid classifier lowers the CPU-time with another factor of 3-4. Furthermore, for certain problems like classifying water-non water a single spectral band

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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

  18. 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)…

  19. 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.

  20. 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.

  1. Multispectral fluorescence imaging of atherosclerosis

    SciTech Connect

    Davenport, C.M.C.

    1992-01-01

    Multispectral fluorescence imaging is a new diagnostic technique with the potential to provide improved detection and classification of atherosclerotic disease. This technique involves imaging the fluorescence response of a tissue region through a tunable band-pass filtering device. The result is a set of image in which each individual image is composed of the fluorescence emission within a specified band of wavelengths. Multispectral imaging combined with angioscopic technology allows direct access to important spectral information and spatial attributes providing the potential for more informed clinical decisions about which, if any, treatment modality is indicated. In this dissertation, the system requirements for an angioscopic system with multispectral imaging capability are identified. This analysis includes a description of the necessary optical components and their characteristics as well as the experimental determination of spectral radiance values for the fluorescence response of human aorta specimens and the estimation of anticipated signal-to-noise ratios for the spectral images. Other issues investigated include the number of spectral images required to provide good classification potential and the best normalization method to be utilized. Finally, the potential utility of the information contained within a multispectral data set is demonstrated. Two methods of utilizing the multispectral data are presented. The first method involves generating a ratio-image from the ratio of the intensities of two spectrally filtered images. The second method consists of using histologically verified training data to train a projector and then applying that projector to a set of spectral images. The result provides improved contrast image. White-light images (generated using an incandescent light source), total-fluorescence images (the fluorescence response without spectral filtering), ratio-images, and optimized contrast images are compared. T

  2. 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.

  3. 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.

  4. 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.

  5. Airborne thermography applications in Argentina

    NASA Astrophysics Data System (ADS)

    Castro, Eduardo H.; Selles, Eduardo J.; Costanzo, Marcelo; Franco, Oscar; Diaz, Jose

    2002-03-01

    Forest fires in summer and sheep buried under the snow in winter have become important problems in the south of our country, in the region named Patagonia. We are studying to find a solution by means of an airborne imaging system whose construction we have just finished. It is a 12 channel multispectral airborne scanner system that can be mounted in a Guarani airplane or in a Learjet; the first is a non- pressurized aircraft for flight at low height and the second is a pressurized one for higher flights. The scanner system is briefly described. Their sensors can detect radiation from the ultra violet to the thermal infrared. The images are visualized in real time in a monitor screen and can be stored in the hard disc of the PC for later processing. The use of this scanner for some applications that include the prevention and fighting of forest fires and the study of the possibility of detection of sheep under snow in the Patagonia is now being accomplished. Theoretical and experimental results in fire detection and a theoretical model for studying the possibility of detection of the buried sheep are presented.

  6. 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.

  7. Landsat-D thematic mapper simulation using aircraft multispectral scanner data

    NASA Technical Reports Server (NTRS)

    Clark, J.; Bryant, N. A.

    1977-01-01

    A simulation of imagery from the upcoming Landsat-D Thematic Mapper was accomplished by using selected channels of aircraft 24-channel multispectral scanner data. The purpose was to simulate Thematic Mapper 30-meter resolution imagery, to compare its spectral quality with the original aircraft MSS data, and to determine changes in thematic classification accuracy for the simulated imagery. The original resolution of approximately 7.5 meters IFOV and simulated resolution of 15, 30, and 60 meters were used to indicate the trend of spectral quality and classification accuracy. The study was based in a 6.5 square kilometer area of urban Los Angeles having a diversity of land use. The original imagery was reduced in resolution by two related methods: pixel matrix averaging, and matrix smoothing with a unity box filter, followed by matrix averaging. Thematic land use classification using training sites and a Bayesian maximum-likelihood algorithm was performed at three levels of standard deviation - 1.0, 2.0, and 3.0 sigma. Plots of relative standard deviation showed that for larger training sites with a normal distribution of data, as the resolution decreased, the distribution range of density values decreased. Also, the classification accuracies for three levels of standard deviation increased as resolution decreased. However, the indication is that a point of diminishing returns had been reached, and 30 meters IFOV should be the best for multispectral classification of urban scenes.

  8. Applicability of ERTS-1 imagery to the study of suspended sediment and aquatic fronts

    NASA Technical Reports Server (NTRS)

    Klemas, V.; Srna, R.; Treasure, W.; Otley, M.

    1973-01-01

    Imagery from three successful ERTS-1 passes over the Delaware Bay and Atlantic Coastal Region have been evaluated to determine visibility of aquatic features. Data gathered from ground truth teams before and during the overflights, in conjunction with aerial photographs taken at various altitudes, were used to interpret the imagery. The overpasses took place on August 16, October 10, 1972, and January 26, 1973, with cloud cover ranging from about zero to twenty percent. (I.D. Nos. 1024-15073, 1079-15133, and 1187-15140). Visual inspection, density slicing and multispectral analysis of the imagery revealed strong suspended sediment patterns and several distinct types of aquatic interfaces or frontal systems.

  9. Remote sensing of benthic microalgal biomass with a tower-mounted multispectral scanner

    NASA Technical Reports Server (NTRS)

    Jobson, D. J.; Katzberg, S. J.; Zingmark, R. G.

    1980-01-01

    A remote sensing instrument was mounted on a 50-ft tower overlooking North Inlet Estuary, South Carolina in order to conduct a remote sensing study of benthic microalgae. The instrument was programmed to take multispectral imagery data along a 90 deg horizontal frame in six spectral bands ranging from 400-1050 nm and had a ground resolution of about 3 cm. Imagery measurements were encoded in digital form on magnetic tape and were stored, decoded, and manipulated by computer. Correlation coefficients were calculated on imagery data and chlorophyll a concentrations derived from ground truth data. The most significant correlation occurred in the blue spectral band with numerical values ranging from -0.81 to -0.88 for three separate sampling periods. Mean values of chlorophyll a for a larger section of mudflat were estimated using regression equations. The scanner has provided encouraging results and promises to be a useful tool in sampling the biomass of intertidal benthic microalgae.

  10. Multispectral polarized scene projector (MPSP)

    NASA Astrophysics Data System (ADS)

    Yu, Haiping; Wei, Hong; Guo, Lei; Wang, Shenggang; Li, Le; Lippert, Jack R.; Serati, Steve; Gupta, Neelam; Carlen, Frank R.

    2011-06-01

    This newly developed prototype Multispectral Polarized Scene Projector (MPSP), configured for the short wave infrared (SWIR) regime, can be used for the test & evaluation (T&E) of spectro-polarimetric imaging sensors. The MPSP system generates both static and video images (up to 200 Hz) with 512×512 spatial resolution with active spatial, spectral, and polarization modulation with controlled bandwidth. It projects input SWIR radiant intensity scenes from stored memory with user selectable wavelength (850-1650 nm) and bandwidth (12-100 nm), as well as polarization states (six different states) controllable on a pixel by pixel basis. The system consists of one spectrally tunable liquid crystal filter with variable bandpass, and multiple liquid crystal on silicon (LCoS) spatial light modulators (SLMs) for intensity control and polarization modulation. In addition to the spectro-polarimetric sensor test, the instrument also simulates polarized multispectral images of military scenes/targets for hardware-in-the loop (HIL) testing.

  11. EAARL coastal topography and imagery-Fire Island National Seashore, New York, 2009

    USGS Publications Warehouse

    Vivekanandan, Saisudha; Klipp, E.S.; Nayegandhi, Amar; Bonisteel-Cormier, J.M.; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Fredericks, Xan; Stevens, Sara

    2010-01-01

    These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired on July 9 and August 3, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral CIR camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar

  12. EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

    USGS Publications Warehouse

    Nagle, David B.; Nayegandhi, Amar; Yates, Xan; Brock, John C.; Wright, C. Wayne; Bonisteel, Jamie M.; Klipp, Emily S.; Segura, Martha

    2010-01-01

    These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 2007. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral CIR camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area

  13. Qualitative and quantitative comparisons of multispectral night vision colorization techniques

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng; Dong, Wenjie; Blasch, Erik P.

    2012-08-01

    Multispectral images enable robust night vision (NV) object assessment over day-night conditions. Furthermore, colorized multispectral NV images can enhance human vision by improving observer object classification and reaction times, especially for low light conditions. NV colorization techniques can produce the colorized images that closely resemble natural scenes. Qualitative (subjective) and quantitative (objective) comparisons of NV colorization techniques proposed in the past decade are made and two categories of coloring methods, color fusion and color mapping, are discussed and compared. Color fusion directly combines multispectral NV images into a color-version image by mixing pixel intensities at different color planes, of which a channel-based color fusion method is reviewed. Color-mapping usually maps the color properties of a false-colored NV image (source) onto that of a true-color daylight target picture (reference). Four coloring-mapping methods-statistical matching, histogram matching, joint histogram matching, and look-up table (LUT)-are presented and compared, including a new color-mapping method called joint-histogram matching (JHM). The experimental NV imagery includes visible (Red-Green-Blue), image-intensified, near infrared, and long-wave infrared images. The qualitative evaluations are conducted by visual inspections of the colorized images, whereas the quantitative evaluations are achieved by a newly proposed metric, objective evaluation index. From the experimental results according to both qualitative and quantitative evaluations, the following conclusions can be drawn: the segmentation-based colorization method produces very impressive and realistic colors but requires intense computations; color fusion and LUT-based methods run very fast but with less realistic results; the statistic-matching method always provides acceptable results; histogram matching and joint-histogram matching can generate impressive and vivid colors when the color

  14. A qualitative evaluation of Landsat imagery of Australian rangelands

    USGS Publications Warehouse

    Graetz, R.D.; Carneggie, David M.; Hacker, R.; Lendon, C.; Wilcox, D.G.

    1976-01-01

    The capability of multidate, multispectral ERTS-1 imagery of three different rangeland areas within Australia was evaluated for its usefulness in preparing inventories of rangeland types, assessing on a broad scale range condition within these rangeland types, and assessing the response of rangelands to rainfall events over large areas. For the three divergent rangeland test areas, centered on Broken W, Alice Springs and Kalgoorlie, detailed interpretation of the imagery only partially satisfied the information requirements set. It was most useful in the Broken Hill area where fenceline contrasts in range condition were readily visible. At this and the other sites an overstorey of trees made interpretation difficult. Whilst the low resolution characteristics and the lack of stereoscopic coverage hindered interpretation it was felt that this type of imagery with its vast coverage, present low cost and potential for repeated sampling is a useful addition to conventional aerial photography for all rangeland types.

  15. Genetic programming approach to extracting features from remotely sensed imagery

    SciTech Connect

    Theiler, J. P.; Perkins, S. J.; Harvey, N. R.; Szymanski, J. J.; Brumby, Steven P.

    2001-01-01

    Multi-instrument data sets present an interesting challenge to feature extraction algorithm developers. Beyond the immediate problems of spatial co-registration, 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. We describe a genetic programming/supervised classifier software system, called Genie, which evolves and combines spatio-spectral image processing tools for remotely sensed imagery. We describe our representation of candidate image processing pipelines, and discuss our set of primitive image operators. Our primary application has been in the field of geospatial feature extraction, including wildfire scars and general land-cover classes, using publicly available multi-spectral imagery (MSI) and hyper-spectral imagery (HSI). Here, we demonstrate our system on Landsat 7 Enhanced Thematic Mapper (ETM+) MSI. We exhibit an evolved pipeline, and discuss its operation and performance.

  16. A novel multispectral glacier mapping method and its performance in Greenland

    NASA Astrophysics Data System (ADS)

    Citterio, M.; Fausto, R. S.; Ahlstrom, A. P.; Andersen, S. B.

    2014-12-01

    Multispectral land surface classification methods are widely used for mapping glacier outlines. Significant post-classification manual editing is typically required, and mapping glacier outlines over larger regions remains a rather labour intensive task. In this contribution we introduce a novel method for mapping glacier outlines from multispectral satellite imagery, requiring only minor manual editing.Over the last decade GLIMS (Global Land Ice Measurements from Space) improved the availability of glacier outlines, and in 2012 the Randolph Glacier Inventory (RGI) attained global coverage by compiling existing and new data sources in the wake of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). With the launch of Landsat 8 in 2013 and the upcoming ESA (European Space Agency) Sentinel 2 missions, the availability of multispectral imagery may grow faster than our ability to process it into timely and reliable glacier outline products. Improved automatic classification methods would enable a full exploitation of these new data sources.We outline the theoretical basis of the proposed classification algorithm, provide a step by step walk-through from raw imagery to finished ice cover grids and vector glacier outlines, and evaluate the performance of the new method in mapping the outlines of glaciers, ice caps and the Greenland Ice Sheet from Landsat 8 OLI imagery. The classification output is compared against manually digitized ice margin positions, the RGI vectors, and the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) aerophotogrammetric map of Greenland ice masses over a sector of the Disko Island surge cluster in West Greenland, the Qassimiut ice sheet lobe in South Greenland, and the A.P. Olsen ice cap in NE Greenland.

  17. Multispectral determination of vegetative cover in corn crop canopy

    NASA Technical Reports Server (NTRS)

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

    1972-01-01

    The relationship between different amounts of vegetative ground cover and the energy reflected by corn canopies was investigated. Low altitude photography and an airborne multispectral scanner were used to measure this reflected energy. Field plots were laid out, representing four growth stages of corn. Two plot locations were chosen-on a very dark and a very light surface soil. Color and color infrared photographs were taken from a vertical distance of 10 m. Estimates of ground cover were made from these photographs and were related to field measurements of leaf area index. Ground cover could be predicted from leaf area index measurements by a second order equation. Microdensitometry and digitzation of the three separated dye layers of color infrared film showed that the near infrared dye layer is most valuable in ground cover determinations. Computer analysis of the digitized photography provided an accurate method of determining precent ground cover.

  18. Novel automatic target recognition approach for multispectral data

    NASA Astrophysics Data System (ADS)

    Salazar, Jose S.; Koch, Mark W.; Yocky, David A.

    2002-11-01

    Automating the detection and identification of significant threats using multispectral (MS) imagery is a critical issue in remote sensing. Unlike previous multispectral target recognition approaches, we utilize a three-stage process that not only takes into account the spectral content, but also the spatial information. The first stage applies a matched filter to the calibrated MS data. Here, the matched filter is tuned to the spectral components of a given target and produces an image intensity map of where the best matches occur. The second stage represents a novel detection algorithm, known as the focus of attention (FOA) stage. The FOA performs an initial screening of the data based on intensity and size checks on the matched filter output. Next, using the target's pure components, the third stage performs constrained linear unmixing on MS pixels within the FOA detected regions. Knowledge sources derived from this process are combined using a sequential probability ratio test (SPRT). The SPRT can fuse contaminated, uncertain and disparate information from multiple sources. We demonstrate our approach on identifying a specific target using actual data collected in ideal conditions and also use approximately 35 square kilometers of urban clutter as false alarm data.

  19. Gimbaled multispectral imaging system and method

    DOEpatents

    Brown, Kevin H.; Crollett, Seferino; Henson, Tammy D.; Napier, Matthew; Stromberg, Peter G.

    2016-01-26

    A gimbaled multispectral imaging system and method is described herein. In an general embodiment, the gimbaled multispectral imaging system has a cross support that defines a first gimbal axis and a second gimbal axis, wherein the cross support is rotatable about the first gimbal axis. The gimbaled multispectral imaging system comprises a telescope that fixed to an upper end of the cross support, such that rotation of the cross support about the first gimbal axis causes the tilt of the telescope to alter. The gimbaled multispectral imaging system includes optics that facilitate on-gimbal detection of visible light and off-gimbal detection of infrared light.

  20. Characterization of instream hydraulic and riparian habitat conditions and stream temperatures of the Upper White River Basin, Washington, using multispectral imaging systems

    USGS Publications Warehouse

    Black, Robert W.; Haggland, Alan; Crosby, Greg

    2003-01-01

    Instream hydraulic and riparian habitat conditions and stream temperatures were characterized for selected stream segments in the Upper White River Basin, Washington. An aerial multispectral imaging system used digital cameras to photograph the stream segments across multiple wavelengths to characterize fish habitat and temperature conditions. All imageries were georeferenced. Fish habitat features were photographed at a resolution of 0.5 meter and temperature imageries were photographed at a 1.0-meter resolution. The digital multispectral imageries were classified using commercially available software. Aerial photographs were taken on September 21, 1999. Field habitat data were collected from August 23 to October 12, 1999, to evaluate the measurement accuracy and effectiveness of the multispectral imaging in determining the extent of the instream habitat variables. Fish habitat types assessed by this method were the abundance of instream hydraulic features such as pool and riffle habitats, turbulent and non-turbulent habitats, riparian composition, the abundance of large woody debris in the stream and riparian zone, and stream temperatures. Factors such as the abundance of instream woody debris, the location and frequency of pools, and stream temperatures generally are known to have a significant impact on salmon. Instream woody debris creates the habitat complexity necessary to maintain a diverse and healthy salmon population. The abundance of pools is indicative of a stream's ability to support fish and other aquatic organisms. Changes in water temperature can affect aquatic organisms by altering metabolic rates and oxygen requirements, altering their sensitivity to toxic materials and affecting their ability to avoid predators. The specific objectives of this project were to evaluate the use of an aerial multispectral imaging system to accurately identify instream hydraulic features and surface-water temperatures in the Upper White River Basin, to use the

  1. Use of a Multispectral Uav Photogrammetry for Detection and Tracking of Forest Disturbance Dynamics

    NASA Astrophysics Data System (ADS)

    Minařík, R.; Langhammer, J.

    2016-06-01

    This study presents a new methodological approach for assessment of spatial and qualitative aspects of forest disturbance based on the use of multispectral imaging camera with the UAV photogrammetry. We have used the miniaturized multispectral sensor Tetracam Micro Multiple Camera Array (μ-MCA) Snap 6 with the multirotor imaging platform to get multispectral imagery with high spatial resolution. The study area is located in the Sumava Mountains, Central Europe, heavily affected by windstorms, followed by extensive and repeated bark beetle (Ips typographus [L.]) outbreaks in the past 20 years. After two decades, there is apparent continuous spread of forest disturbance as well as rapid regeneration of forest vegetation, related with changes in species and their diversity. For testing of suggested methodology, we have launched imaging campaign in experimental site under various stages of forest disturbance and regeneration. The imagery of high spatial and spectral resolution enabled to analyse the inner structure and dynamics of the processes. The most informative bands for tree stress detection caused by bark beetle infestation are band 2 (650nm) and band 3 (700nm), followed by band 4 (800 nm) from the, red-edge and NIR part of the spectrum. We have identified only three indices, which seems to be able to correctly detect different forest disturbance categories in the complex conditions of mixture of categories. These are Normalized Difference Vegetation Index (NDVI), Simple 800/650 Ratio Pigment specific simple ratio B1 and Red-edge Index.

  2. Estimating supraglacial lake depth in West Greenland using Landsat 8 and comparison with other multispectral methods

    NASA Astrophysics Data System (ADS)

    Pope, A.; Scambos, T. A.; Moussavi, M.; Tedesco, M.; Willis, M.; Shean, D.; Grigsby, S.

    2016-01-01

    Liquid water stored on the surface of ice sheets and glaciers impacts surface mass balance, ice dynamics, and heat transport. Multispectral remote sensing can be used to detect supraglacial lakes and estimate their depth and area. In this study, we use in situ spectral and bathymetric data to assess lake depth retrieval using the recently launched Landsat 8 Operational Land Imager (OLI). We also extend our analysis to other multispectral sensors to evaluate their performance with similar methods. Digital elevation models derived from WorldView stereo imagery (pre-lake filling and post-drainage) are used to validate spectrally derived depths, combined with a lake edge determination from imagery. The optimal supraglacial lake depth retrieval is a physically based single-band model applied to two OLI bands independently (red and panchromatic) that are then averaged together. When OLI- and WorldView-derived depths are differenced, they yield a mean and standard deviation of 0.0 ± 1.6 m. This method is then applied to OLI data for the Sermeq Kujalleq (Jakobshavn Isbræ) region of Greenland to study the spatial and intra-seasonal variability of supraglacial lakes during summer 2014. We also give coefficients for estimating supraglacial lake depth using a similar method with other multispectral sensors.

  3. Testing the discrimination and detection limits of WorldView-2 imagery on a challenging invasive plant target

    NASA Astrophysics Data System (ADS)

    Robinson, T. P.; Wardell-Johnson, G. W.; Pracilio, G.; Brown, C.; Corner, R.; van Klinken, R. D.

    2016-02-01

    Invasive plants pose significant threats to biodiversity and ecosystem function globally, leading to costly monitoring and management effort. While remote sensing promises cost-effective, robust and repeatable monitoring tools to support intervention, it has been largely restricted to airborne platforms that have higher spatial and spectral resolutions, but which lack the coverage and versatility of satellite-based platforms. This study tests the ability of the WorldView-2 (WV2) eight-band satellite sensor for detecting the invasive shrub mesquite (Prosopis spp.) in the north-west Pilbara region of Australia. Detectability was challenged by the target taxa being largely defoliated by a leaf-tying biological control agent (Gelechiidae: Evippe sp. #1) and the presence of other shrubs and trees. Variable importance in the projection (VIP) scores identified bands offering greatest capacity for discrimination were those covering the near-infrared, red, and red-edge wavelengths. Wavelengths between 400 nm and 630 nm (coastal blue, blue, green, yellow) were not useful for species level discrimination in this case. Classification accuracy was tested on three band sets (simulated standard multispectral, all bands, and bands with VIP scores ≥1). Overall accuracies were comparable amongst all band-sets (Kappa = 0.71-0.77). However, mesquite omission rates were unacceptably high (21.3%) when using all eight bands relative to the simulated standard multispectral band-set (9.5%) and the band-set informed by VIP scores (11.9%). An incremental cover evaluation on the latter identified most omissions to be for objects <16 m2. Mesquite omissions reduced to 2.6% and overall accuracy significantly improved (Kappa = 0.88) when these objects were left out of the confusion matrix calculations. Very high mapping accuracy of objects >16 m2 allows application for mapping mesquite shrubs and coalesced stands, the former not previously possible, even with 3 m resolution hyperspectral

  4. Small UAV-Acquired, High-resolution, Georeferenced Still Imagery

    SciTech Connect

    Ryan Hruska

    2005-09-01

    Currently, small Unmanned Aerial Vehicles (UAVs) are primarily used for capturing and down-linking real-time video. To date, their role as a low-cost airborne platform for capturing high-resolution, georeferenced still imagery has not been fully utilized. On-going work within the Unmanned Vehicle Systems Program at the Idaho National Laboratory (INL) is attempting to exploit this small UAV-acquired, still imagery potential. Initially, a UAV-based still imagery work flow model was developed that includes initial UAV mission planning, sensor selection, UAV/sensor integration, and imagery collection, processing, and analysis. Components to support each stage of the work flow are also being developed. Critical to use of acquired still imagery is the ability to detect changes between images of the same area over time. To enhance the analysts’ change detection ability, a UAV-specific, GIS-based change detection system called SADI or System for Analyzing Differences in Imagery is under development. This paper will discuss the associated challenges and approaches to collecting still imagery with small UAVs. Additionally, specific components of the developed work flow system will be described and graphically illustrated using varied examples of small UAV-acquired still imagery.

  5. Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop

    NASA Technical Reports Server (NTRS)

    Realmuto, Vincent J. (Editor)

    1993-01-01

    This is volume 2 of a three volume set of publications that contain the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on October 25-26. The summaries for this workshop appear in Volume 1. The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27. The summaries for this workshop appear in Volume 2. The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29. The summaries for this workshop appear in Volume 3.

  6. Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 1: AVIRIS Workshop

    NASA Technical Reports Server (NTRS)

    Green, Robert O. (Editor)

    1992-01-01

    This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5. The summaries are contained in Volumes 1, 2, and 3, respectively.

  7. Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 3: AIRSAR Workshop

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob (Editor)

    1993-01-01

    This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Spectrometer (AVIRIS) workshop, on October 25-26, whose summaries appear in Volume 1; The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27, whose summaries appear in Volume 2; and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29, whose summaries appear in this volume, Volume 3.

  8. Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop

    NASA Technical Reports Server (NTRS)

    Realmuto, Vincent J. (Editor)

    1992-01-01

    This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.

  9. Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 1: AVIRIS Workshop

    NASA Technical Reports Server (NTRS)

    Green, Robert O. (Editor)

    1995-01-01

    This publication is the first of three containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in this volume; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in Volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2.

  10. Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 2: TIMS Workshop

    NASA Technical Reports Server (NTRS)

    Realmuto, Vincent J. (Editor)

    1995-01-01

    This publication is the second volume of the summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop on January 23-24. The summaries for this workshop appear in Volume 1; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop on January 25-26. The summaries for this workshop appear in volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop on January 26. The summaries for this workshop appear in this volume.

  11. Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 1: AVIRIS Workshop

    NASA Technical Reports Server (NTRS)

    Green, Robert O. (Editor)

    1993-01-01

    This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D. C. October 25-29, 1993 The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, October 25-26 (the summaries for this workshop appear in this volume, Volume 1); The Thermal Infrared Multispectral Scanner (TMIS) workshop, on October 27 (the summaries for this workshop appear in Volume 2); and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, October 28-29 (the summaries for this workshop appear in Volume 3).

  12. Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 3: AIRSAR Workshop

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob (Editor)

    1992-01-01

    This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.

  13. Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 3: AIRSAR Workshop

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob (Editor)

    1995-01-01

    This publication is the third containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in Volume 1; (2) The Airborne synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in this volume; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2.

  14. Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

    NASA Astrophysics Data System (ADS)

    McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

    2016-02-01

    We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

  15. High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology

    PubMed Central

    Boyle, Sarah A.; Kennedy, Christina M.; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E.; de la Sancha, Noé U.

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making. PMID:24466287

  16. High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

    PubMed

    Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

  17. Spectral stratigraphy: multispectral remote sensing as a stratigraphic tool, Wind River/Big Horn basin, Wyoming

    SciTech Connect

    Lang, H.R.; Paylor, E.D.

    1987-05-01

    Stratigraphic and structural analyses of the Wind River and Big Horn basins areas of central Wyoming are in progress. One result has been the development of a new approach to stratigraphic and structural analysis that uses photogeologic and spectral interpretation of multispectral image data to remotely characterize the attitude, thickness, and lithology of strata. New multispectral systems that have only been available since 1982 are used with topographic data to map upper paleozoic and Mesozoic strata exposed on the southern margin of the Bighorn Mountains. Thematic Mapper (TM) satellite data together with topographic data are used to map lithologic contacts, measure dip and strike, and develop a stratigraphic column that is correlated with conventional surface and subsurface sections. Aircraft-acquired Airborne Imaging Spectrometer and Thermal Infrared Multispectral Scanner data add mineralogical information to the TM column, including the stratigraphic distribution of quartz, calcite, dolomite, montmorillonite, and gypsum. Results illustrate an approach that has general applicability in other geologic investigations that could benefit from remotely acquired information about areal variations in attitude, sequence, thickness, and lithology of strata exposed at the Earth's surface. Application of their methods elsewhere is limited primarily by availability of multispectral and topographic data and quality of bedrock exposures.

  18. A multispectral sorting device for wheat kernels

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A low-cost multispectral sorting device was constructed using three visible and three near-infrared light-emitting diodes (LED) with peak emission wavelengths of 470 nm (blue), 527 nm (green), 624 nm (red), 850 nm, 940 nm, and 1070 nm. The multispectral data were collected by rapidly (~12 kHz) blin...

  19. Sandia multispectral analyst remote sensing toolkit (SMART).

    SciTech Connect

    Post, Brian Nelson; Smith, Jody Lynn; Geib, Peter L.; Nandy, Prabal; Wang, Nancy Nairong

    2003-03-01

    This remote sensing science and exploitation work focused on exploitation algorithms and methods targeted at the analyst. SMART is a 'plug-in' to commercial remote sensing software that provides algorithms to enhance the utility of the Multispectral Thermal Imager (MTI) and other multispectral satellite data. This toolkit has been licensed to 22 government organizations.

  20. Evaluation of terrestrial photogrammetric point clouds derived from thermal imagery

    NASA Astrophysics Data System (ADS)

    Metcalf, Jeremy P.; Olsen, Richard C.

    2016-05-01

    Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.

  1. Algorithms for lineaments detection in processing of multispectral images

    NASA Astrophysics Data System (ADS)

    Borisova, D.; Jelev, G.; Atanassov, V.; Koprinkova-Hristova, Petia; Alexiev, K.

    2014-10-01

    Satellite remote sensing is a universal tool to investigate the different areas of Earth and environmental sciences. The advancement of the implementation capabilities of the optoelectronic devices which are long-term-tested in the laboratory and the field and are mounted on-board of the remote sensing platforms further improves the capability of instruments to acquire information about the Earth and its resources in global, regional and local scales. With the start of new high-spatial and spectral resolution satellite and aircraft imagery new applications for large-scale mapping and monitoring becomes possible. The integration with Geographic Information Systems (GIS) allows a synergistic processing of the multi-source spatial and spectral data. Here we present the results of a joint project DFNI I01/8 funded by the Bulgarian Science Fund focused on the algorithms of the preprocessing and the processing spectral data by using the methods of the corrections and of the visual and automatic interpretation. The objects of this study are lineaments. The lineaments are basically the line features on the earth's surface which are a sign of the geological structures. The geological lineaments usually appear on the multispectral images like lines or edges or linear shapes which is the result of the color variations of the surface structures. The basic geometry of a line is orientation, length and curve. The detection of the geological lineaments is an important operation in the exploration for mineral deposits, in the investigation of active fault patterns, in the prospecting of water resources, in the protecting people, etc. In this study the integrated approach for the detecting of the lineaments is applied. It combines together the methods of the visual interpretation of various geological and geographical indications in the multispectral satellite images, the application of the spatial analysis in GIS and the automatic processing of the multispectral images by Canny

  2. Modeling space-based multispectral imaging systems with DIRSIG

    NASA Astrophysics Data System (ADS)

    Brown, Scott D.; Sanders, Niek J.; Goodenough, Adam A.; Gartley, Michael

    2011-06-01

    The Landsat Data Continuity Mission (LDCM) focuses on a next generation global coverage, imaging system to replace the aging Landsat 5 and Landsat 7 systems. The major difference in the new system is the migration from the multi-spectral whiskbroom design employed by the previous generation of sensors to modular focal plane, multi-spectral pushbroom architecture. Further complicating the design shift is that the reflective and thermal acquisition capability is split across two instruments spatially separated on the satellite bus. One of the focuses of the science and engineering teams prior to launch is the ability to provide seamless data continuity with the historic Landsat data archive. Specifically, the challenges of registering and calibrating data from the new system so that long-term science studies are minimally impacted by the change in the system design. In order to provide the science and engineering teams with simulated pre-launch data, an effort was undertaken to create a robust end-to-end model of the LDCM system. The modeling environment is intended to be flexible and incorporate measured data from the actual system components as they were completed and integrated. The output of the modeling environment needs to include not only radiometrically robust imagery, but also the meta-data necessary to exercise the processing pipeline. This paper describes how the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model has been utilized to model space-based, multi-spectral imaging (MSI) systems in support of systems engineering trade studies. A mechanism to incorporate measured focal plane projections through the forward optics is described. A hierarchal description of the satellite system is presented including the details of how a multiple instrument platform is described and modeled, including the hierarchical management of temporally correlated jitter that allows engineers to explore impacts of different jitter sources on instrument

  3. Multispectral Image Processing for Plants

    NASA Technical Reports Server (NTRS)

    Miles, Gaines E.

    1991-01-01

    The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

  4. Image quality degradation and retrieval errors introduced by registration and interpolation of multispectral digital images

    SciTech Connect

    Henderson, B.G.; Borel, C.C.; Theiler, J.P.; Smith, B.W.

    1996-04-01

    Full utilization of multispectral data acquired by whiskbroom and pushbroom imagers requires that the individual channels be registered accurately. Poor registration introduces errors which can be significant, especially in high contrast areas such as boundaries between regions. We simulate the acquisition of multispectral imagery in order to estimate the errors that are introduced by co-registration of different channels and interpolation within the images. We compute the Modulation Transfer Function (MTF) and image quality degradation brought about by fractional pixel shifting and calculate errors in retrieved quantities (surface temperature and water vapor) that occur as a result of interpolation. We also present a method which might be used to estimate sensor platform motion for accurate registration of images acquired by a pushbroom scanner.

  5. Estimation of thermal flux and emissivity of the land surface from multispectral aircraft data

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.

    1989-01-01

    In order to evaluate the importance of surface thermal flux and emissivity variations on surface and boundary layer processes, a technique that uses thermal data from an airborne multispectral scanner to determine the surface skin temperature and thermal emissivity over a regional area has been developed. These values are used to estimate the total flux density emanating from the surface and at the top of the atmosphere. Data from the multispectral atmospheric mapping sensor (MAMS) collected during the First ISLSCP Field Experiment (FIFE) are used to develop the technique, and to show the time and space variability of the flux values. The ground truth data available during FIFE provide a unique resource to evaluate this technique.

  6. Structural geologic interpretations from radar imagery

    USGS Publications Warehouse

    Reeves, Robert G.

    1969-01-01

    Certain structural geologic features may be more readily recognized on sidelooking airborne radar (SLAR) images than on conventional aerial photographs, other remote sensor imagery, or by ground observations. SLAR systems look obliquely to one or both sides and their images resemble aerial photographs taken at low sun angle with the sun directly behind the camera. They differ from air photos in geometry, resolution, and information content. Radar operates at much lower frequencies than the human eye, camera, or infrared sensors, and thus "sees" differently. The lower frequency enables it to penetrate most clouds and some precipitation, haze, dust, and some vegetation. Radar provides its own illumination, which can be closely controlled in intensity and frequency. It is narrow band, or essentially monochromatic. Low relief and subdued features are accentuated when viewed from the proper direction. Runs over the same area in significantly different directions (more than 45° from each other), show that images taken in one direction may emphasize features that are not emphasized on those taken in the other direction; optimum direction is determined by those features which need to be emphasized for study purposes. Lineaments interpreted as faults stand out on radar imagery of central and western Nevada; folded sedimentary rocks cut by faults can be clearly seen on radar imagery of northern Alabama. In these areas, certain structural and stratigraphic features are more pronounced on radar images than on conventional photographs; thus radar imagery materially aids structural interpretation.

  7. Barrier Island Shorelines Extracted from Landsat Imagery

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-10-13

    The shoreline is a common variable used as a metric for coastal erosion or change (Himmelstoss and others, 2010). Although shorelines are often extracted from topographic data (for example, ground-based surveys and light detection and ranging [lidar]), image-based shorelines, corrected for their inherent uncertainties (Moore and others, 2006), have provided much of our understanding of long-term shoreline change because they pre-date routine lidar elevation survey methods. Image-based shorelines continue to be valuable because of their higher temporal resolution compared to costly airborne lidar surveys. A method for extracting sandy shorelines from 30-meter (m) resolution Landsat imagery is presented here.

  8. Barrier Island Shorelines Extracted from Landsat Imagery

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The shoreline is a common variable used as a metric for coastal erosion or change (Himmelstoss and others, 2010). Although shorelines are often extracted from topographic data (for example, ground-based surveys and light detection and ranging [lidar]), image-based shorelines, corrected for their inherent uncertainties (Moore and others, 2006), have provided much of our understanding of long-term shoreline change because they pre-date routine lidar elevation survey methods. Image-based shorelines continue to be valuable because of their higher temporal resolution compared to costly airborne lidar surveys. A method for extracting sandy shorelines from 30-meter (m) resolution Landsat imagery is presented here.

  9. Fast application multispectral camouflage appliques

    NASA Astrophysics Data System (ADS)

    Meeker, David L.; Hall, Kenneth G.

    1995-05-01

    With reconnaissance surveillance, and target acquisition systems becoming increasingly sophisticated in both sensor performance and processing capabilities, there exists a requirement to increase the camoufleur's ability to control and manipulate target signatures beyond those currently available. To assist in accomplishing this, a hybrid technology is required: one that combines the features of multispectral signature control, rapid deployment, and low cost. The WES fixed-facility CCD team is developing a suite of signature controlling materials termed 'Multispectral Camouflage Appliques' (MCSs). Due to the nature of this material, the spectral characteristics (e.g. emmissivity, radar scattering properties, UV-NIR reflectance, color) can be controlled with great latitude by the designer, by adding underlying material layers or external coatings. It is the ability of the designer to manipulate the fundamental characteristics of the MCA material that allows its uniqueness and maximum utility. THe first series of MCAs are composed of an adhesive-backed metal foil overlaid with a visual color coating that is transparent in the thermal IR wavelengths. The effect is that of a visual camouflage combined with a thermal mirror that reflects emissions of the natural surroundings. The 'peel and stick' adhesive backing provides a rapid method of applying MCAs to fixed and semimobile assets that would be beneficial to bare base and force projection msisions. Dual uses of this material include drug and border aerial surveillance as position markers that are visually disguised from ground observation but provide high contrast in thermal IR imaging systems by reflecting cold sky temperatures.

  10. Cucumber disease diagnosis using multispectral images

    NASA Astrophysics Data System (ADS)

    Feng, Jie; Li, Hongning; Shi, Junsheng; Yang, Weiping; Liao, Ningfang

    2009-07-01

    In this paper, multispectral imaging technique for plant diseases diagnosis is presented. Firstly, multispectral imaging system is designed. This system utilizes 15 narrow-band filters, a panchromatic band, a monochrome CCD camera, and standard illumination observing environment. The spectral reflectance and color of 8 Macbeth color patches are reproduced between 400nm and 700nm in the process. In addition, spectral reflectance angle and color difference is obtained through measurements and analysis of color patches using spectrometer and multispectral imaging system. The result shows that 16 narrow-bands multispectral imaging system realizes good accuracy in spectral reflectance and color reproduction. Secondly, a horticultural plant, cucumber' familiar disease are the researching objects. 210 multispectral samples are obtained by multispectral and are classified by BP artificial neural network. The classification accuracies of Sphaerotheca fuliginea, Corynespora cassiicola, Pseudoperonospora cubensis are 100%. Trichothecium roseum and Cladosporium cucumerinum are 96.67% and 90.00%. It is confirmed that the multispectral imaging system realizes good accuracy in the cucumber diseases diagnosis.

  11. MULTISPECTRAL REMOTE SENSING OF CARBONATE ROCKS IN THE CONFUSION RANGE, UTAH.

    USGS Publications Warehouse

    Crowley, James K.

    1984-01-01

    Multispectral imagery recorded by the NASA/Bendix 24-channel aircraft scanner over the Confusion Range, Utah, proved to be extremely sensitive to lithologic variations in exposed carbonate rocks. Major carbonate units within a 16-km**2 study area were readily distinguished, and some aspects of their structure and stratigraphy could be inferred from image spectral signatures. Spectral data channels centered at 1. 6 and 2. 2 mu m accounted for much of the data sensitivity to lithologic differences. Rock texture, organic matter content, and weathering expression were important lithologic factors producing spectral variation.

  12. Implementation of ILLIAC 4 algorithms for multispectral image interpretation. [earth resources data

    NASA Technical Reports Server (NTRS)

    Ray, R. M.; Thomas, J. D.; Donovan, W. E.; Swain, P. H.

    1974-01-01

    Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed.

  13. Multispectral techniques for general geological surveys evaluation of a four-band photographic system

    NASA Technical Reports Server (NTRS)

    Crowder, D., F.

    1969-01-01

    A general geological survey at 1:62,500 scale of the well exposed rocks of the White Mountains and the adjacent volcanic desert plateau is reported. The tuffs, granites, sedimentary rocks and metavolcanic rocks in this arid region are varicolored and conventional black and white aerial photographs have been a useful mapping aid. A large number of true color and false color aerial photographs and multispectral viewer screen images of the study area are evaluated in order to consider what imagery is the most useful for distinguishing rock types. Photographs of true color film are judged the most useful for recognizing geographic locations.

  14. Fusion of Hyperspectral and Vhr Multispectral Image Classifications in Urban Areas

    NASA Astrophysics Data System (ADS)

    Hervieu, Alexandre; Le Bris, Arnaud; Mallet, Clément

    2016-06-01

    An energetical approach is proposed for classification decision fusion in urban areas using multispectral and hyperspectral imagery at distinct spatial resolutions. Hyperspectral data provides a great ability to discriminate land-cover classes while multispectral data, usually at higher spatial resolution, makes possible a more accurate spatial delineation of the classes. Hence, the aim here is to achieve the most accurate classification maps by taking advantage of both data sources at the decision level: spectral properties of the hyperspectral data and the geometrical resolution of multispectral images. More specifically, the proposed method takes into account probability class membership maps in order to improve the classification fusion process. Such probability maps are available using standard classification techniques such as Random Forests or Support Vector Machines. Classification probability maps are integrated into an energy framework where minimization of a given energy leads to better classification maps. The energy is minimized using a graph-cut method called quadratic pseudo-boolean optimization (QPBO) with ?-expansion. A first model is proposed that gives satisfactory results in terms of classification results and visual interpretation. This model is compared to a standard Potts models adapted to the considered problem. Finally, the model is enhanced by integrating the spatial contrast observed in the data source of higher spatial resolution (i.e., the multispectral image). Obtained results using the proposed energetical decision fusion process are shown on two urban multispectral/hyperspectral datasets. 2-3% improvement is noticed with respect to a Potts formulation and 3-8% compared to a single hyperspectral-based classification.

  15. CNR LARA Project: Evaluation of two years of airborne imaging spectrometry

    SciTech Connect

    Bianchi, R.; Cavalli, R.M.; Fiumi, L.; Marino, C.M.

    1996-10-01

    Since last July 1994 the Daedalus AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) instrument, acquired by CNR (Italian National Research Council) in the framework of its LARA (Airborne Laboratory for Environmental Studies) Project, has been intensively operative. A number of MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) deployments have been carried out in Italy and Europe in cooperation with national and international institutions on a variety of sites, including active volcanoes, coastlines, lagoons and ocean, vegetated and cultivated areas, oil polluted surfaces, waste discharges, and archeological sites. Two years of activity have shown the high system efficiency, from the survey to data preprocessing and dissemination. 12 refs., 3 figs.

  16. Assessment of Pen Branch delta and corridor vegetation changes using multispectral scanner data 1992--1994

    SciTech Connect

    1996-01-01

    Airborne multispectral scanner data were used to monitor natural succession of wetland vegetation species over a three-year period from 1992 through 1994 for Pen Branch on the Savannah River Site in South Carolina. Image processing techniques were used to identify and measure wetland vegetation communities in the lower portion of the Pen Branch corridor and delta. The study provided a reliable means for monitoring medium- and large-scale changes in a diverse environment. Findings from the study will be used to support decisions regarding remediation efforts following the cessation of cooling water discharge from K reactor at the Department of Energy`s Savannah River Site in South Carolina.

  17. Remote sensing techniques applied to multispectral recognition of the Aranjuez pilot zone

    NASA Technical Reports Server (NTRS)

    Lemos, G. L.; Salinas, J.; Rebollo, M.

    1977-01-01

    A rectangular (7 x 14 km) area 40 km S of Madrid was remote-sensed with a three-stage recognition process. Ground truth was established in the first phase, airborne sensing with a multispectral scanner and photographic cameras were used in the second phase, and Landsat satellite data were obtained in the third phase. Agronomic and hydrological photointerpretation problems are discussed. Color, black/white, and labeled areas are displayed for crop recognition in the land-use survey; turbidity, concentrations of pollutants and natural chemicals, and densitometry of the water are considered in the evaluation of water resources.

  18. Multispectral Scanner for Monitoring Plants

    NASA Technical Reports Server (NTRS)

    Gat, Nahum

    2004-01-01

    A multispectral scanner has been adapted to capture spectral images of living plants under various types of illumination for purposes of monitoring the health of, or monitoring the transfer of genes into, the plants. In a health-monitoring application, the plants are illuminated with full-spectrum visible and near infrared light and the scanner is used to acquire a reflected-light spectral signature known to be indicative of the health of the plants. In a gene-transfer- monitoring application, the plants are illuminated with blue or ultraviolet light and the scanner is used to capture fluorescence images from a green fluorescent protein (GFP) that is expressed as result of the gene transfer. The choice of wavelength of the illumination and the wavelength of the fluorescence to be monitored depends on the specific GFP.

  19. Multispectral sensing of moisture stress

    NASA Technical Reports Server (NTRS)

    Olson, C. E., Jr.

    1970-01-01

    Laboratory reflectance data, and field tests with multispectral remote sensors provide support for this hypotheses that differences in moisture content and water deficits are closely related to foliar reflectance from woody plants. When these relationships are taken into account, automatic recognition techniques become more powerful than when they are ignored. Evidence is increasing that moisture relationships inside plant foliage are much more closely related to foliar reflectance characteristics than are external variables such as soil moisture, wind, and air temperature. Short term changes in water deficits seem to have little influence on foliar reflectance, however. This is in distinct contrast to significant short-term changes in foliar emittance from the same plants with changing wind, air temperature, incident radiation, or water deficit conditions.

  20. Application of ERTS-1 imagery in coastal studies

    NASA Technical Reports Server (NTRS)

    Magoon, O. T.; Berg, D. W.; Hallermeier, R. J.

    1973-01-01

    The basic ERTS output is four black-and-white photographs presenting the same scene recorded in each multispectral scanner band. Mosaics covering large regions at a 1:250,000 scale can be compiled from these photographs. Office study of the image of each band separately, in combination with other bands, and in conjunction with other available data (navigation charts, tide tables, etc.) permits extraction of data useful in coastal engineering planning and coastal processes studies. Specific examples in which significant information on regional shoreline configuration or nearshore water movements has been obtained from unenhanced ERTS imagery are: (1) tidal inlet configuration; (2) navigation information; and (3) nearshore water movements.

  1. Classifying and monitoring water quality by use of satellite imagery

    NASA Technical Reports Server (NTRS)

    Scherz, J. P.; Crane, D. R.; Rogers, R. H.

    1975-01-01

    A technique in which LANDSAT measurements from very clear lakes are subtracted from measurements from other lakes in order to remove atmospheric and surface noise effects to obtain a residual signal dependent only on the material suspended in the water is described. This residual signal is used by the Multispectral Data Analysis System as a basis for producing color categorized imagery showing lakes by type and concentration of suspended material. Several hundred lakes in the Madison and Spooner, Wisconsin area were categorized for tannin or non-tannin waters and for the degree of algae, silt, weeds, and bottom effects.

  2. EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

    USGS Publications Warehouse

    Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Brock, J.C.; Wright, C.W.; Nagle, D.B.; Klipp, E.S.; Vivekanandan, Saisudha; Fredericks, Xan; Stevens, Sara

    2010-01-01

    These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar(EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and

  3. Study on multispectral imaging detection and recognition

    NASA Astrophysics Data System (ADS)

    Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

    2009-07-01

    Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

  4. Remote sensing of clouds by multispectral sensors.

    PubMed

    Lindner, B L; Isaacs, R G

    1993-05-20

    A multispectral minimization approach that uses the wavelength dependence of the radiance rather than the magnitude of the radiance is advocated for the retrieval of cloud optical thickness, phase, and particle size by future sensors.

  5. Multispectral imaging with vertical silicon nanowires

    PubMed Central

    Park, Hyunsung; Crozier, Kenneth B.

    2013-01-01

    Multispectral imaging is a powerful tool that extends the capabilities of the human eye. However, multispectral imaging systems generally are expensive and bulky, and multiple exposures are needed. Here, we report the demonstration of a compact multispectral imaging system that uses vertical silicon nanowires to realize a filter array. Multiple filter functions covering visible to near-infrared (NIR) wavelengths are simultaneously defined in a single lithography step using a single material (silicon). Nanowires are then etched and embedded into polydimethylsiloxane (PDMS), thereby realizing a device with eight filter functions. By attaching it to a monochrome silicon image sensor, we successfully realize an all-silicon multispectral imaging system. We demonstrate visible and NIR imaging. We show that the latter is highly sensitive to vegetation and furthermore enables imaging through objects opaque to the eye. PMID:23955156

  6. Multispectral palmprint recognition using a quaternion matrix.

    PubMed

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

  7. Multispectral Palmprint Recognition Using a Quaternion Matrix

    PubMed Central

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

  8. Ozone Hole Airborne Arctic Stratospheric Expedition (Pre-Flight)

    NASA Technical Reports Server (NTRS)

    1989-01-01

    The first segment of this video gives an overview of the Ozone Hole Airborne Arctic Stratospheric Expedition, an international effort using balloon payloads, ground based instruments, and airborne instruments to study ozone depletion and the hole in the ozone over Antarctica which occurs every spring. False color imagery taken from NASA's Nimbus 7 satellite which documents daily changes in ozone is also shown. The second segment of this video shows actual take-off and flight footage of the two aircraft used in the experiment: the DC-8 Flying Laboratory and the high flying ER-2.

  9. Digital techniques for processing Landsat imagery

    NASA Technical Reports Server (NTRS)

    Green, W. B.

    1978-01-01

    An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

  10. Applications of Landsat imagery to a coastal inlet stability study

    NASA Technical Reports Server (NTRS)

    Wang, Y.-H.

    1981-01-01

    Polcyn and Lyzenga (1975) and Middleton and Barber (1976) have demonstrated that it is possible to correlate the radiance values of a multispectral imagery, such as Landsat imagery, with the depth related information. The present study is one more example of such an effort. Two sets of Landsat magnetic tape were obtained and displayed on the screen of an Image-100 computer. Spectral analysis was performed to produce various signatures, their extent, and location. Subsequent ground truth observations and measurements were gathered by means of hydrographic surveys and low altitude aerial photographs for interpretation and calibration of the Landsat data. Finally, a coastal engineering assessment based on the Landsat data was made. Recommendations regarding the navigational canal alignment and dredging practice are presented in the light of inlet stability.

  11. Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Hayden, David; Thompson, David R.; Castano, Rebecca

    2013-01-01

    Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

  12. Mapping cultivable land from satellite imagery with clustering algorithms

    NASA Astrophysics Data System (ADS)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  13. Remote sensing of ocean currents using ERTS imagery

    NASA Technical Reports Server (NTRS)

    Maul, G. A.

    1973-01-01

    Major ocean currents such as the Loop Current in the eastern Gulf of Mexico have surface manifestations which can be exploited for remote sensing. Surface chlorophyll-a concentrations, which contribute to the shift in color from blue to green in the open sea, were found to have high spatial variability; significantly lower concentrations were observed in the current. The cyclonic edge of the current is an accumulation zone which causes a peak in chlorophyll concentration. The dynamics also cause surface concentrations of algae, which have a high reflectance in the near infrared. Combining these observations gives rise to an edge effect which can show up as a bright lineation on multispectral imagery delimiting the current's boundary under certain environmental conditions. When high seas introduce bubbles, white caps, and foam, the reflectance is dominated by scattering rather than absorption. This has been detected in ERTS imagery and used for current location.

  14. Spline function approximation techniques for image geometric distortion representation. [for registration of multitemporal remote sensor imagery

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1975-01-01

    Least squares approximation techniques were developed for use in computer aided correction of spatial image distortions for registration of multitemporal remote sensor imagery. Polynomials were first used to define image distortion over the entire two dimensional image space. Spline functions were then investigated to determine if the combination of lower order polynomials could approximate a higher order distortion with less computational difficulty. Algorithms for generating approximating functions were developed and applied to the description of image distortion in aircraft multispectral scanner imagery. Other applications of the techniques were suggested for earth resources data processing areas other than geometric distortion representation.

  15. Evaluation of ERTS-1 imagery in mapping and managing soil and range resources in the Sand Hills region of Nebraska

    NASA Technical Reports Server (NTRS)

    Drew, J. V. (Principal Investigator); Seevers, P. M.

    1974-01-01

    The author has identified the following significant results. 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 multitemporal 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. Four resource maps of the Upper Loup Natural Resource District located entirely within the Sand Hills region were prepared from ERTS-1 imagery.

  16. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  17. An evaluation of the use of ERTS-1 satellite imagery for grizzly bear habitat analysis. [Montana

    NASA Technical Reports Server (NTRS)

    Varney, J. R.; Craighead, J. J.; Sumner, J. S.

    1974-01-01

    Improved classification and mapping of grizzly habitat will permit better estimates of population density and distribution, and allow accurate evaluation of the potential effects of changes in land use, hunting regulation, and management policies on existing populations. Methods of identifying favorable habitat from ERTS-1 multispectral scanner imagery were investigated and described. This technique could reduce the time and effort required to classify large wilderness areas in the Western United States.

  18. Processing of SeaMARC swath sonar imagery

    SciTech Connect

    Pratson, L.; Malinverno, A.; Edwards, M.; Ryan, W. )

    1990-05-01

    Side-scan swath sonar systems have become an increasingly important means of mapping the sea floor. Two such systems are the deep-towed, high-resolution SeaMARC I sonar, which has a variable swath width of up to 5 km, and the shallow-towed, lower-resolution SeaMARC II sonar, which has a swath width of 10 km. The sea-floor imagery of acoustic backscatter output by the SeaMARC sonars is analogous to aerial photographs and airborne side-looking radar images of continental topography. Geologic interpretation of the sea-floor imagery is greatly facilitated by image processing. Image processing of the digital backscatter data involves removal of noise by median filtering, spatial filtering to remove sonar scans of anomalous intensity, across-track corrections to remove beam patterns caused by nonuniform response of the sonar transducers to changes in incident angle, and contrast enhancement by histogram equalization to maximize the available dynamic range. Correct geologic interpretation requires submarine structural fabrics to be displayed in their proper locations and orientations. Geographic projection of sea-floor imagery is achieved by merging the enhanced imagery with the sonar vehicle navigation and correcting for vehicle attitude. Co-registration of bathymetry with sonar imagery introduces sea-floor relief and permits the imagery to be displayed in three-dimensional perspectives, furthering the ability of the marine geologist to infer the processes shaping formerly hidden subsea terrains.

  19. Using high resolution multispectral imaging to map Pacific coral reefs in support of UNESCO's World Heritage Central Pacific project

    NASA Astrophysics Data System (ADS)

    Siciliano, Daria; Olsen, Richard C.

    2007-10-01

    Concerns over worldwide declines in marine resources have prompted the search for innovative solutions for their conservation and management, particularly for coral reef ecosystems. Rapid advances in sensor resolution, coupled with image analysis techniques tailored to the unique optical problems of marine environments have enabled the derivation of detailed benthic habitat maps of coral reef habitats from multispectral satellite imagery. Such maps delineate coral reefs' main ecological communities, and are essential for management of these resources as baseline assessments. UNESCO's World Heritage Central Pacific Project plans to afford protection through World Heritage recognition to a number of islands and atolls in the central Pacific Ocean, including the Phoenix Archipelago in the Republic of Kiribati. Most of these islands however lack natural resource maps needed for the identification of priority areas for inclusion in a marine reserve system. Our project provides assistance to UNESCO's World Heritage Centre and the Kiribati Government by developing benthic and terrestrial habitat maps of the Phoenix Islands from high-resolution multispectral imagery. The approach involves: (i) the analysis of new Quickbird multispectral imagery; and (ii) the use of MARXAN, a simulated annealing algorithm that uses a GIS interface. Analysis of satellite imagery was performed with ENVI®, and includes removal of atmospheric effects using ATCOR (a MODTRAN4 radiative transfer model); de-glinting and water column correction algorithms; and a number of unsupervised and supervised classifiers. Previously collected ground-truth data was used to train classifications. The resulting habitat maps are then used as input to MARXAN. This algorithm ultimately identifies a proportion of each habitat to be set aside for protection, and prioritizes conservation areas. The outputs of this research are being delivered to the UNESCO World Heritage Centre office and the Kiribati Government as

  20. Auditory imagery: empirical findings.

    PubMed

    Hubbard, Timothy L

    2010-03-01

    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) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia) are considered. It is concluded that auditory imagery (a) preserves many structural and temporal properties of auditory stimuli, (b) can facilitate auditory discrimination but interfere with auditory detection, (c) involves many of the same brain areas as auditory perception, (d) is often but not necessarily influenced by subvocalization, (e) involves semantically interpreted information and expectancies, (f) involves depictive components and descriptive components, (g) can function as a mnemonic but is distinct from rehearsal, and (h) is related to musical ability and experience (although the mechanisms of that relationship are not clear). PMID:20192565

  1. Auditory imagery: empirical findings.

    PubMed

    Hubbard, Timothy L

    2010-03-01

    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) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia) are considered. It is concluded that auditory imagery (a) preserves many structural and temporal properties of auditory stimuli, (b) can facilitate auditory discrimination but interfere with auditory detection, (c) involves many of the same brain areas as auditory perception, (d) is often but not necessarily influenced by subvocalization, (e) involves semantically interpreted information and expectancies, (f) involves depictive components and descriptive components, (g) can function as a mnemonic but is distinct from rehearsal, and (h) is related to musical ability and experience (although the mechanisms of that relationship are not clear).

  2. An airborne laser polarimeter system (ALPS) for terrestrial physics research

    NASA Technical Reports Server (NTRS)

    Kalshoven, James E., Jr.; Dabney, Philip W.

    1988-01-01

    The design of a multispectral polarized laser system for characterizing the depolarization properties of the earth's surface is described. Using a laser as the light source, this airborne system measures the Stokes parameters of the surface to simultaneously arrive at the polarization degree, azimuthal angle, and ellipticity for each wavelength. The technology will be studied for the feasibility of expansion of the sensor to do surface polarization imaging. The data will be used in support of solar polarization studies and to develop laser radiometry as a tool in environmental remote sensing.

  3. Development of Bayesian-based transformation method of Landsat imagery into pseudo-hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Hoang, Nguyen Tien; Koike, Katsuaki

    2015-10-01

    It has been generally accepted that hyperspectral remote sensing is more effective and provides greater accuracy than multispectral remote sensing in many application fields. EO-1 Hyperion, a representative hyperspectral sensor, has much more spectral bands, while Landsat data has much wider image scene and longer continuous space-based record of Earth's land. This study aims to develop a new method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into pseudo hyperspectral imagery using the correlation between Landsat and EO-1 Hyperion data. At first Hyperion scene was precisely pre-processed and co-registered to Landsat scene, and both data were corrected for atmospheric effects. Bayesian model averaging method (BMA) was applied to select the best model from a class of several possible models. Subsequently, this best model is utilized to calculate pseudo-hyperspectral data by R programming. Based on the selection results by BMA, we transform Landsat imagery into 155 bands of pseudo-hyperspectral imagery. Most models have multiple R-squared values higher than 90%, which assures high accuracy of the models. There are no significant differences visually between the pseudo- and original data. Most bands have Pearson's coefficients < 0.95, and only a small fraction has the coefficients < 0.93 like outliers in the data sets. In a similar manner, most Root Mean Square Error values are considerably low, smaller than 0.014. These observations strongly support that the proposed PHISA is valid for transforming Landsat data into pseudo-hyperspectral data from the outlook of statistics.

  4. Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

    NASA Technical Reports Server (NTRS)

    Oswald, Hayden; Molthan, Andrew L.

    2011-01-01

    Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

  5. Multispectral Imaging from Mars PATHFINDER

    NASA Technical Reports Server (NTRS)

    Ferrand, William H.; Bell, James F., III; Johnson, Jeffrey R.; Bishop, Janice L.; Morris, Richard V.

    2007-01-01

    The Imager for Mars Pathfinder (IMP) was a mast-mounted instrument on the Mars Pathfinder lander which landed on Mars Ares Vallis floodplain on July 4, 1997. During the 83 sols of Mars Pathfinders landed operations, the IMP collected over 16,600 images. Multispectral images were collected using twelve narrowband filters at wavelengths between 400 and 1000 nm in the visible and near infrared (VNIR) range. The IMP provided VNIR spectra of the materials surrounding the lander including rocks, bright soils, dark soils, and atmospheric observations. During the primary mission, only a single primary rock spectral class, Gray Rock, was recognized; since then, Black Rock, has been identified. The Black Rock spectra have a stronger absorption at longer wavelengths than do Gray Rock spectra. A number of coated rocks have also been described, the Red and Maroon Rock classes, and perhaps indurated soils in the form of the Pink Rock class. A number of different soil types were also recognized with the primary ones being Bright Red Drift, Dark Soil, Brown Soil, and Disturbed Soil. Examination of spectral parameter plots indicated two trends which were interpreted as representing alteration products formed in at least two different environmental epochs of the Ares Vallis area. Subsequent analysis of the data and comparison with terrestrial analogs have supported the interpretation that the rock coatings provide evidence of earlier martian environments. However, the presence of relatively uncoated examples of the Gray and Black rock classes indicate that relatively unweathered materials can persist on the martian surface.

  6. Multi-spectral IR reflectography

    NASA Astrophysics Data System (ADS)

    Fontana, Raffaella; Bencini, Davide; Carcagnì, Pierluigi; Greco, Marinella; Mastroianni, Maria; Materazzi, Marzia; Pampaloni, Enrico; Pezzati, Luca

    2007-07-01

    A variety of scientific investigation methods applied to paintings are, by now, an integral part of the repair process, both to plan the restoration intervention and to monitor its various phases. Optical techniques are widely diffused and extremely well received in the field of painting diagnostics because of their effectiveness and safety. Among them infrared reflectography is traditionally employed in non-destructive diagnostics of ancient paintings to reveal features underlying the pictorial layer thanks to transparency characteristics to NIR radiation of the materials composing the paints. High-resolution reflectography was introduced in the 90s at the Istituto Nazionale di Ottica Applicata, where a prototype of an innovative scanner was developed, working in the 900-1700 nm spectral range. This technique was recently improved with the introduction of an optical head, able to acquire simultaneously the reflectogram and the color image, perfectly superimposing. In this work we present a scanning device for multi-spectral IR reflectography, based on contact-less and single-point measurement of the reflectance of painted surfaces. The back-scattered radiation is focused on square-shaped fiber bundle that carries the light to an array of 14 photodiodes equipped with pass-band filters so to cover the NIR spectral range from 800 to 2500 nm

  7. Integration of visible-through microwave-range multispectral image data sets for geologic mapping

    NASA Technical Reports Server (NTRS)

    Kruse, Fred A.; Dietz, John B.

    1991-01-01

    Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

  8. Estimating true color imagery for GOES-R

    NASA Astrophysics Data System (ADS)

    Grossberg, Michael D.; Shahriar, Fazlul; Gladkova, Irina; Alabi, Paul K.; Hillger, Donald W.; Miller, Steven D.

    2011-06-01

    The Advanced Baseline Imager (ABI) on GOES-R will help NOAA's objective of engaging and educating the public on environmental issues by providing near real-time imagery of the earth-atmosphere system. True color satellite images are beneficial to the public, as well as to scientists, who use these images as an important "decision aid" and visualization tool. Unfortunately, ABI only has two visible bands (cyan and red) and does not directly produce the three bands (blue, green, and red) used to create true color imagery. We have developed an algorithm that will produce quantitative true color imagery from ABI. Our algorithm estimates the three tristimulus values of the international standard CIE 1931 XYZ colorspace for each pixel of the ABI image, and thus is compatible with a wide range of software packages and hardware devices. Our algorithm is based on a non-linear statistical regression framework that incorporate both classification and local multispectral regression using training data. We have used training data from the hyper-spectral imager Hyperion. Our algorithm to produce true color images from the ABI is not specific to ABI and may be applicable to other satellites which, like the ABI, do not have the ability to directly produce RGB imagery.

  9. Identifying tree crown delineation shapes and need for remediation on high resolution imagery using an evidence based approach

    NASA Astrophysics Data System (ADS)

    Leckie, Donald G.; Walsworth, Nicholas; Gougeon, François A.

    2016-04-01

    In order to fully realize the benefits of automated individual tree mapping for tree species, health, forest inventory attribution and forest management decision making, the tree delineations should be as good as possible. The concept of identifying poorly delineated tree crowns and suggesting likely types of remediation was investigated. Delineations (isolations or isols) were classified into shape types reflecting whether they were realistic tree shapes and the likely kind of remediation needed. Shape type was classified by an evidence based rules approach using primitives based on isol size, shape indices, morphology, the presence of local maxima, and matches with template models representing trees of different sizes. A test set containing 50,000 isols based on an automated tree delineation of 40 cm multispectral airborne imagery of a diverse temperate-boreal forest site was used. Isolations representing single trees or several trees were the focus, as opposed to cases where a tree is split into several isols. For eight shape classes from regular through to convolute, shape classification accuracy was in the order of 62%; simplifying to six classes accuracy was 83%. Shape type did give an indication of the type of remediation and there were 6% false alarms (i.e., isols classed as needing remediation but did not). Alternately, there were 5% omissions (i.e., isols of regular shape and not earmarked for remediation that did need remediation). The usefulness of the concept of identifying poor delineations in need of remediation was demonstrated and one suite of methods developed and shown to be effective.

  10. MISR Field Campaign Imagery

    Atmospheric Science Data Center

    2014-07-23

      MISR Support of Field Campaigns Aerosol Arctic Research of the Composition of the ... Daily ARCTAS Aerosol Polar Imagery ​Gulf of Mexico Atmospheric Composition and Climate Study ( GoMACCS ) ​July - ...

  11. MISR Imagery and Articles

    Atmospheric Science Data Center

    2016-05-27

    ... of select parameters available in the MISR Level 3 global data products Field Campaigns :  Imagery supporting field ... explore the links between atmospheric aerosols, climate change, and ultraviolet rays. Following the World Trade Center plume ...

  12. 1994-1995 CNR LARA project airborne hyperspectral campaigns

    SciTech Connect

    Bianchi, R.; Cavalli, R.M.; Fiumi, L.

    1996-08-01

    CNR established a new laboratory for airborne hyperspectral imaging devoted to environmental problems and since the end of last June 1994 the project (LARA Project) is fully operative to provide hyperspectral data to the national and international scientific community. The Daedalus AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) instrument, acquired by CNR (Italian National Research Council) in the framework of its LARA (Airborne Laboratory for Environmental Studies) Project, has been intensively operative. A number of MIVIS deployments have been carried out in Italy and Europe in cooperation with national and international institutions on a variety of sites, including active volcanoes, coastlines, lagoons and ocean, vegetated and cultivated areas, oil polluted surfaces, waste discharges, and archeological sites. One year of activity has shown the high system efficiency, from the survey to data preprocessing and dissemination.

  13. Unsupervised classification of remote multispectral sensing data

    NASA Technical Reports Server (NTRS)

    Su, M. Y.

    1972-01-01

    The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

  14. Photogrammetric Processing Using ZY-3 Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

    2015-03-01

    This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are

  15. Optimal out-of-band correction for multispectral remote sensing.

    PubMed

    Chen, Wei

    2012-11-20

    In this paper, an optimal out-of-band (OOB) correction transform (OOBCT) for dealing with onboard Visible/Infrared Imaging Radiometer Suite (VIIRS) OOB effects is proposed. This paper addresses the OOB response issue without consideration of the impact of other error sources on the correction processing. The OOBCT matrix is derived by minimizing an objective function of error summation between the expected and realistic recovered band-averaged spectral radiances. Using the VIIRS filter transmittance functions for all multiband sensors obtained from prelaunch laboratory measurements and a simulated dataset obtained from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) hyperspectral data, the OOBCT matrix is numerically computed. The processing of the OOB correction is straightforward and can be performed by a product between the OOBCT matrix and a measured multispectral image vector. The experimental results with both AVIRIS and Hyperspectral Imager for the Coastal Ocean datasets demonstrate that the ratios of average errors of recovered band-averaged spectral radiances divided by the measured radiances with the OOB responses are less than 4%. The average values of the relative errors for all pixels and bands indicate that the OOBCT method outperforms the works reported in literature.

  16. Airborne Remote Sensing of River Flow and Morphology

    NASA Astrophysics Data System (ADS)

    Zuckerman, S.; Anderson, S. P.; McLean, J.; Redford, R.

    2014-12-01

    River morphology, surface slope and flow are some of the fundamental measurements required for surface water monitoring and hydrodynamic research. This paper describes a method of combining bathymetric lidar with space-time processing of mid-wave infrared (MWIR) imagery to simultaneously measure bathymetry, currents and surface slope from an airborne platform. In May 2014, Areté installed a Pushbroom Imaging Lidar for Littoral Surveillance (PILLS) and a FLIR SC8000 MWIR imaging system sampling at 2 Hz in a small twin-engine aircraft. Data was collected over the lower Colorado River between Picacho Park and Parker. PILLS is a compact bathymetric lidar based on streak-tube sensor technology. It provides channel and bank topography and water surface elevation at 1 meter horizontal scales and 25 cm vertical accuracy. Surface currents are derived from the MWIR imagery by tracking surface features using a cross correlation algorithm. This approach enables the retrieval of currents along extended reaches at the forward speed of the aircraft with spatial resolutions down to 5 m with accuracy better than 10 cm/s. The fused airborne data captures current and depth variability on scales of meters over 10's of kilometers collected in just a few minutes. The airborne MWIR current retrievals are combined with the bathymetric lidar data to calculate river discharge which is then compared with real-time streamflow stations. The results highlight the potential for improving our understanding of complex river environments with simultaneous collections from multiple airborne sensors.

  17. Characterization of forest crops with a range of nutrient and water treatments using AISA Hyperspectral Imagery.

    SciTech Connect

    Gong, Binglei; Im, Jungho; Jensen, John, R.; Coleman, Mark; Rhee, Jinyoung; Nelson, Eric

    2012-07-01

    This research examined the utility of Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imagery for estimating the biomass of three forest crops---sycamore, sweetgum and loblolly pine--planted in experimental plots with a range of fertilization and irrigation treatments on the Savannah River Site near Aiken, South Carolina.

  18. MITAS: multisensor imaging technology for airborne surveillance

    NASA Astrophysics Data System (ADS)

    Thomas, John D.

    1991-08-01

    MITAS, a unique and low-cost solution to the problem of collecting and processing multisensor imaging data for airborne surveillance operations has been developed, MITAS results from integrating the established and proven real-time video processing, target tracking, and sensor management software of TAU with commercially available image exploitation and map processing software. The MITAS image analysis station (IAS) supports airborne day/night reconnaissance and surveillance missions involving low-altitude collection platforms employing a suite of sensors to perform reconnaissance functions against a variety of ground and sea targets. The system will detect, locate, and recognize threats likely to be encountered in support of counternarcotic operations and in low-intensity conflict areas. The IAS is capable of autonomous, near real-time target exploitation and has the appropriate communication links to remotely located IAS systems for more extended analysis of sensor data. The IAS supports the collection, fusion, and processing of three main imaging sensors: daylight imagery (DIS), forward looking infrared (FLIR), and infrared line scan (IRLS). The MITAS IAS provides support to all aspects of the airborne surveillance mission, including sensor control, real-time image enhancement, automatic target tracking, sensor fusion, freeze-frame capture, image exploitation, target data-base management, map processing, remote image transmission, and report generation.

  19. Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Jubanski, J.; Ballhorn, U.; Kronseder, K.; Franke, J.; Siegert, F.

    2013-06-01

    Quantification of tropical forest above-ground biomass (AGB) over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+) projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia) through correlating airborne light detection and ranging (LiDAR) to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52). Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC) showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG) emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

  20. Case studies of aerosol remote sensing with the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

    NASA Astrophysics Data System (ADS)

    Diner, D. J.; Xu, F.; Garay, M. J.; Martonchik, J. V.; Kalashnikova, O. V.; Davis, A. B.; Rheingans, B.; Geier, S.; Jovanovic, V.; Bull, M.

    2012-12-01

    The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) is an 8-band (355, 380, 445, 470, 555, 660, 865, 935 nm) pushbroom camera, measuring polarization in the 470, 660, and 865 nm bands, mounted on a gimbal to acquire multiangular observations over a ±67° along-track range with 10-m spatial resolution across an 11-km wide swath. Among the instrument objectives are exploration of methodologies for combining multiangle, multispectral, polarimetric, and imaging observations to retrieve the optical depth and microphysical properties of tropospheric aerosols. AirMSPI was integrated on NASA's ER-2 high-altitude aircraft in 2010 and has successfully completed a number of flights over land and ocean targets in the Southern California vicinity. In this paper, we present case studies of AirMSPI imagery, interpreted using vector radiative transfer theory. AirMSPI observations over California's Central Valley are compared with model calculations using aerosol properties reported by the Fresno AERONET sunphotometer. Because determination of the radiative impact of different types of aerosols requires accurate attribution of the source of the reflected light along with characterization of the aerosol optical and microphysical properties, we explore the sensitivity of the Fresno measurements to variations in different aerosol properties, demonstrating the value of combining intensity and polarimetry at multiple view angles and spectral bands for constraining particle microphysical properties. Images over ocean to be presented include scenes over nearly cloud-free skies and scenes containing scattered clouds. It is well known that imperfect cloud screening confounds the determination of aerosol impact on radiation; it is perhaps less well appreciated that the effect of cloud reflections in the water can also be problematic. We calculate the magnitude of this effect in intensity and polarization and discuss its potential impact on aerosol retrievals, underscoring the value