Herwitz, Stanley R.
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).
A study was conducted in south Texas to determine the feasibility of using airborne multispectral digital imagery for differentiating the invasive plant Brazilian pepper (Schinus terebinthifolius) from other cover types. Imagery obtained in the visible, near infrared, and mid infrared regions of th...
Castillo, Carlos; Zarco-Tejada, Pablo; Laredo, Mario; Gómez, Jose Alfonso
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
Cherry, Jessica; Crowder, Kerri
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.
Bierwirth, Victoria A.
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.
Zanoni, Vicki; Smith, Charles; Blonski, Slawomir
This paper presents viewgraphs about a partnership between USGS and NASA who are jointly developing an airborne digital imagery characterization capability. The topics include: 1) USGS-NASA Product Characterization Approach; 2) Stennis Character Range; 3) Stennis Geodetic Targets; 4) Stennis Manhole Covers; 5) Stennis Edge Target; 6) Stennis Characterization Site; 7) Delivered Data; 8) Other Data Considerations; 9) Status; 10) Geopositional Assessment Approach; 11) Spatial Assessment Approach; 12) Edge Response; and 13) Results to Date.
This paper discusses the use of satellite imagery, aerial photography, and computerized airborne imagery as applied to environmental mapping, analysis, and monitoring. A project conducted by the City of Irving, Texas involves compliance with national pollutant discharge elimination system (NPDES) requirements stipulated by the Environmental Protection Agency. The purpose of the project was the development and maintenance of a stormwater drainage utility. Digital imagery was collected for a portion of the city to map the City`s porous and impervious surfaces which will then be overlaid with property boundaries in the City`s existing Geographic information System (GIS). This information will allow the City to determine an equitable tax for each land parcel according to the amount of water each parcel is contributing to the stormwater system. Another project involves environmental compliance for warm water discharges created by utility companies. Environmental consultants are using digital airborne imagery to analyze thermal plume affects as well as monitoring power generation facilities. A third project involves wetland restoration. Due to freeway and other forms of construction, plus a major reduction of fresh water supplies, the Southern California coastal wetlands are being seriously threatened. These wetlands, rich spawning grounds for plant and animal life, are home to thousands of waterfowl and shore birds who use this habitat for nesting and feeding grounds. Under the leadership of Southern California Edison (SCE) and CALTRANS (California Department of Transportation), several wetland areas such as the San Dieguito Lagoon (Del Mar, California), the Sweetwater Marsh (San Diego, California), and the Tijuana Estuary (San Diego, California) are being restored and closely monitored using digital airborne imagery.
Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...
Ryan, Robert; Kuper, Philip; Stanley, Thomas; Mondello, Charles
The American Society for Photogrammetry and Remote Sensing (ASPRS) Primary Data Acquisition Division is developing a Digital Imagery Product Guideline in conjunction with NASA, the U.S. Geological Survey (USGS), the National Imagery and Mapping Agency (NIMA), academia, and industry. The goal of the guideline is to offer providers and users of digital imagery a set of recommendatons analogous those defined by the ASPRS Aerial Photography 1995 Draft Standard for film-based imagery. This article offers a general outline and description of the Digital Imagery Product Guideline and Digital Imagery Tutorial/Reference documents for defining digital imagery requirements.
Mapping crop yield variability is one important aspect of precision agriculture. This study was designed to assess airborne digital videography as a tool for mapping grain sorghum yields for precision farming. Color-infrared (CIR) imagery was acquired with a three- camera digital video imaging sys...
Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.
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
Burn, D.M.; Webber, M.A.; Udevitz, M.S.
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.
Li, Wenjing; Lieberman, Rich W.; Nie, Sixiang; Xie, Yihua; Eldred, Michael; Oyama, Jody
Diagnosing cervical cancer in a woman is a multi-step procedure involving examination of the cervix, possible biopsy and follow-up. It is open to subjective interpretation and highly dependent upon the skills of cytologists, colposcopists, and pathologists. In an effort to reduce the subjectiveness of the colposcopist-directed biopsy and to improve the diagnostic accuracy of colposcopy, we have developed new colposcopic imaging systems with accompanying computer aided diagnostic (CAD) techniques to guide a colposcopist in deciding if and where to biopsy. If the biopsy's histopathology, the identification of the disease state at the cellular and near-cellular level, is to be used as the gold standard for CAD, then the location of the histopathologic analysis must match exactly to the location of the biopsy tissue in the digital image. Otherwise, no matter how perfect the histopathology and the quality of the digital imagery, the two data sets cannot be matched and the true sensitivity and specificity of the CAD cannot be ascertained. We report here on new approaches to preserving, continuously, the location and orientation of a biopsy sample with respect to its location in the digital image of the cervix so as to preserve the exact spatial relationship throughout the mechanical aspects of the histopathologic analysis. This new approach will allow CAD to produce a linear diagnosis and pinpoint the location of the tissue under examination.
Bloechl, Kevin; De Angelis, Chris; Gartley, Michael; Kerekes, John; Nance, C. Eric
This paper presents a methodology and results for the comparison of simulated imagery to real imagery acquired with multiple sensors hosted on an airborne platform. The dataset includes aerial multi- and hyperspectral imagery with spatial resolutions of one meter or less. The multispectral imagery includes data from an airborne sensor with three-band visible color and calibrated radiance imagery in the long-, mid-, and short-wave infrared. The airborne hyperspectral imagery includes 360 bands of calibrated radiance and reflectance data spanning 400 to 2450 nm in wavelength. Collected in September 2012, the imagery is of a park in Avon, NY, and includes a dirt track and areas of grass, gravel, forest, and agricultural fields. A number of artificial targets were deployed in the scene prior to collection for purposes of target detection, subpixel detection, spectral unmixing, and 3D object recognition. A synthetic reconstruction of the collection site was created in DIRSIG, an image generation and modeling tool developed by the Rochester Institute of Technology, based on ground-measured reflectance data, ground photography, and previous airborne imagery. Simulated airborne images were generated using the scene model, time of observation, estimates of the atmospheric conditions, and approximations of the sensor characteristics. The paper provides a comparison between the empirical and simulated images, including a comparison of achieved performance for classification, detection and unmixing applications. It was found that several differences exist due to the way the image is generated, including finite sampling and incomplete knowledge of the scene, atmospheric conditions and sensor characteristics. The lessons learned from this effort can be used in constructing future simulated scenes and further comparisons between real and simulated imagery.
Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...
Cavegn, S.; Haala, N.; Nebiker, S.; Rothermel, M.; Tutzauer, P.
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.
Giant salvinia is one of the world’s most noxious aquatic weeds. Researchers employed airborne digital video imagery and an unsupervised computer analysis to derive a map showing giant salvinia and other aquatic and terrestrial features within a study site located in northeast Texas. The map had a...
Phan, Chung; Rupp, Ronald; Agarwal, Sanjeev; Trang, Anh; Nair, Sumesh
The US Army's RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division is evaluating the compressibility of airborne multi-spectral imagery for mine and minefield detection application. Of particular interest is to assess the highest image data compression rate that can be afforded without the loss of image quality for war fighters in the loop and performance of near real time mine detection algorithm. The JPEG-2000 compression standard is used to perform data compression. Both lossless and lossy compressions are considered. A multi-spectral anomaly detector such as RX (Reed & Xiaoli), which is widely used as a core algorithm baseline in airborne mine and minefield detection on different mine types, minefields, and terrains to identify potential individual targets, is used to compare the mine detection performance. This paper presents the compression scheme and compares detection performance results between compressed and uncompressed imagery for various level of compressions. The compression efficiency is evaluated and its dependence upon different backgrounds and other factors are documented and presented using multi-spectral data.
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.
Smithson, Tracy L.; St. Germain, Daniel; Nadeau, Denis
DRDC Valcartier is continuing to developed infrared spectral imagery systems for a variety of military applications. Recently a hybrid airborne spectral imager / broadband imager system has been developed for ground target interrogation (AIRIS). This system employs a Fourier Transform Interferometer system coupled to two 8x8 element detector arrays to create spectral imagery in the region from 2.0 to 12 microns (830 to 5000 cm -1) at a spectral resolution of up to 1 cm -1. In addition, coupled to this sensor are three broadband imagers operating in the visible, mid-wave and long-wave infrared regions. AIRIS uses an on-board tracking capability to: dwell on a target, select multiple targets sequentially, or build a mosaic description of the environment around a specified target point. Currently AIRIS is being modified to include real-time spectral imagery calibration and application processing. In this paper the flexibility of the AIRIS system will be described, its concept of operation discussed and examples of measurements will be shown.
Wright, L.; Karpowicz, B. M.; Kindel, B. C.; Schmidt, S.; Leisso, N.; Kampe, T. U.; Pilewskie, P.
A wide variety of critical information regarding bioclimate, biodiversity, and biogeochemistry is embedded in airborne hyperspectral imagery. Most, if not all of the primary signal relies upon first deriving the surface reflectance of land cover and vegetation from measured hyperspectral radiance. This places stringent requirements on terrain, and atmospheric compensation algorithms to accurately derive surface reflectance properties. An observatory designed to measure bioclimate, biodiversity, and biogeochemistry variables from surface reflectance must take great care in developing an approach which chooses algorithms with the highest accuracy, along with providing those algorithms with data necessary to describe the physical mechanisms that affect the measured at sensor radiance. The Airborne Observation Platform (AOP) part of the National Ecological Observatory Network (NEON) is developing such an approach. NEON is a continental-scale ecological observation platform designed to collect and disseminate data to enable the understanding and forecasting of the impacts of climate change, land use change, and invasive species on ecology. The instrumentation package used by the AOP includes a visible and shortwave infrared hyperspectral imager, waveform LiDAR, and high resolution (RGB) digital camera. In addition to airborne measurements, ground-based CIMEL sun photometers will be used to help characterize atmospheric aerosol loading, and ground validation measurements with field spectrometers will be made at select NEON sites. While the core instrumentation package provides critical information to derive surface reflectance of land surfaces and vegetation, the addition of a Solar Spectral Irradiance Radiometer (SSIR) is being investigated as an additional source of data to help identify and characterize atmospheric aerosol, and cloud contributions contributions to the radiance measured by the hyperspectral imager. The addition of the SSIR provides the opportunity to
Marmorino, George O.; Miller, W. D.; Smith, Geoffrey B.; Bowles, Jeffrey H.
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.
Green, W. B.
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.
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...
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...
Spectral unmixing techniques applied to hyperspectral imagery were examined for mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern United States and northern Mexico. Airborne hyperspectral imagery with 102...
Lorre, J. J.; Lynn, D. J.
Nine specific techniques of combination of techniques developed for applying digital image processing technology to existing astronomical imagery are described. Photoproducts are included to illustrate the results of each of these investigations.
Deutsch, E. S.; Rosenfeld, A.
The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.
Virnstein, R.; Tepera, M.; Beazley, L.
A pilot study is very briefly summarized in the article. The study tested the potential of multi-spectral digital imagery for discrimination of seagrass densities and species, algae, and bottom types. Imagery was obtained with the Compact Airborne Spectral Imager (casi) and two flight lines flown with hyper-spectral mode. The photogrammetric method used allowed interpretation of the highest quality product, eliminating limitations caused by outdated or poor quality base maps and the errors associated with transfer of polygons. Initial image analysis indicates that the multi-spectral imagery has several advantages, including sophisticated spectral signature recognition and classification, ease of geo-referencing, and rapid mosaicking.
Kern, K.; Bauer, C.; Sulzer, W.
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
Rickman, Doug L.; Luvall, Jeffrey C.; Schiller, Stephen; Arnold, James E. (Technical Monitor)
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.
Buzi, Miriam; LaFramboise, William A.
Lockheed Martin's Intelligent Library System (ILS)TM imagery management solution was originally developed for users and distributors of Earth imagery emanating from commercial remote sensing satellites or aircraft. The product is a total hardware and software solution comprised of two main components: SmartArchiverTM digital asset management system and SmartAnalystTM imagery exploration tools. While investigating the latest technologies and developing Intelligent Library System (ILS)TM as a state-of-the-art system, we realized SmartArchiver systems offered robust functionality not available elsewhere for handling large medical imagery files. The SmartArchiver system's features answer the following needs of medical imagery handling: smooth handling of large individual imagery files; easy access to specific imagery or types of imagery; cost-effective storage of historical data and protection of imagery over time; ability to grow an archive to thousands of terabytes; distribution from a central archive to multiple viewing sites; varying levels of resolutions requirements at the viewing stations; strict multi-level security adherence; and automated workflow management. In this paper we detail the features of the system and how they apply to medical imagery management. We also describe how a medical application can be served by the SmartArchiver asset management system.
Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley
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
Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley
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
Chen, L. C.; Lo, C. Y.
Aerial imagery and LIDAR points are two important data sources for building reconstruction in a geospatial area. Aerial imagery implies building contours with planimetric features; LIDAR data explicitly represent building geometries using three-dimensional discrete point clouds. Data integration may take advantage of merits from two data sources in building reconstruction and change detection. However, heterogeneous data may contain a relative displacement because of different sensors and the capture time. To reduce this displacement, data registration should be an essential step. Therefore, this investigation proposes an edge-based approach to register these two data sets in three parts: (1) data preprocessing; (2) feature detection; and (3) data registration. The first step rasterizes laser point clouds into a pseudo-grid digital surface model (PDSM), which describes the relief with the original elevation information. The second step implements topological analyses to detect image edges and three-dimensional structure lines from the aerial image and PDSM. These detected features provide the initial positions of building shapes for registration. The third part registers these two data sets in Hough space to compensate for the displacement. Because each building may have prominent geometric structures, the proposed scheme transforms these two groups of edges, and estimates the correspondence by the Hough distribution. The following procedure then iteratively compares two groups of Hough patterns, which are from an aerial image and LIDAR data. This iterative procedure stops when the displacement is within a threshold. The test area is located in Taipei City, Taiwan. DMC system captured the aerial image with 18-cm spatial resolution. The LIDAR data were scanned with a 10-point density per square meter using the Leica ALS50 system. This study proposed a 50 cm spatial resolution of PDSM, which is slightly larger than the point spacing. The experiment selected two
Information concerning the spatial variation in crop yield has become necessary for site-specific crop management. Traditional satellite imagery has long been used to monitor crop growing conditions and to estimate crop yields over large geographic areas. However, this type of imagery has limited us...
Multispectral and hyperspectral imagery is being used to monitor crop conditions and map yield variability. However, limited research has been conducted to compare the differences between these two types of imagery for assessing crop growth and yield. The objective of this study was to compare airbo...
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...
The objectives of the image gallery are to 1) give users and providers a simple means of identifying appropriate imagery for a given application/feature extraction; and 2) define imagery sufficiently to be described in engineering and acquisition terms. This viewgraph presentation includes a discussion of edge response and aliasing for image processing, and a series of images illustrating the effects of signal to noise ratio (SNR) on images. Another series of images illustrates how images are affected by varying the ground sample distances (GSD).
Soil hyperspectral reflectance imagery was obtained from an airborne imaging spectrometer (400 to 2450 nm with ~10 nm resolution, 2.5 m spatial resolution) flown over six tilled (bare soil) agricultural fields on the Eastern Shore of the Chesapeake Bay (Queen Anne’s county, MD). Surface soil samples...
This study evaluated linear spectral unmixing techniques for mapping the variation in crop yield. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery recorded from one grain sorghum field and a cotton field. A pair of plant and soil spect...
Cotton root rot is a serious and destructive disease that affects cotton production in the southwestern United States. Accurate delineation of cotton root rot infestations is important for cost-effective management of the disease. The objective of this study was to use airborne multispectral imagery...
/ Trials were conducted using an airborne video system operating in the visible, near-infrared, and thermal wavelengths to detect two known oil spill releases during darkness at a distance of 10 nautical miles from the shore in St. Vincent's Gulf, South Australia. The oil spills consisted of two 20-liter samples released at 2-h intervals, one sample consisted of paraffinic neutral material and the other of automotive diesel oil. A tracking buoy was sent overboard in conjunction with the release of sample 1, and its movement monitored by satellite relay. Both oil residues were overflown by a light aircraft equipped with thermal, visible, and infrared imagers at a period of approximately 1 h after the release of the second oil residue. Trajectories of the oil residue releases were also modeled and the results compared to those obtained by the airborne video and the tracking buoy. Airborne imagery in the thermal wavelengths successfully located and mapped both oil residue samples during nighttime conditions. Results from the trial suggest that the most advantageous technique would be the combined use of the tracking beacon to obtain an approximate location of the oil spill and the airborne imagery to ascertain its extent and characteristics.KEY WORDS: Airborne video; Thermal imagery; Global positioning; Oil-spill monitoring; Tracking beacon PMID:9732519
Fisher, Timothy E.
Proposed digital image processor improved version of Programmable Remapper, which performs geometric and radiometric transformations on digital images. Features include overlapping and variably sized preimages. Overcomes some of limitations of image-warping circuit boards implementing only those geometric tranformations expressible in terms of polynomials of limited order. Also overcomes limitations of existing Programmable Remapper and made to perform transformations at video rate.
Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan
Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.
Green, W. B.
The paper discusses the camera systems capable of recording black and white and color imagery developed for the Viking Lander imaging experiment. Each Viking Lander image consisted of a matrix of numbers with 512 rows and an arbitrary number of columns up to a maximum of about 9,000. Various techniques were used in the processing of the Viking Lander images, including: (1) digital geometric transformation, (2) the processing of stereo imagery to produce three-dimensional terrain maps, and (3) computer mosaicking of distinct processed images. A series of Viking Lander images is included.
Shen, Sylvia S.; Lewis, Paul E.
On April 28, 2010, the Environmental Protection Agency's (EPA) Airborne Spectral Photometric Environmental Collection Technology (ASPECT) aircraft was deployed to Gulfport, Mississippi to provide airborne remotely sensed air monitoring and situational awareness data and products in response to the Deepwater Horizon oil spill disaster. The ASPECT aircraft was released from service on August 9, 2010 after having flown over 85 missions that included over 325 hours of flight operation. This paper describes several advanced analysis capabilities specifically developed for the Deepwater Horizon mission to correctly locate, identify, characterize, and quantify surface oil using ASPECT's multispectral infrared data. The data products produced using these advanced analysis capabilities provided the Deepwater Horizon Incident Command with a capability that significantly increased the effectiveness of skimmer vessel oil recovery efforts directed by the U.S. Coast Guard, and were considered by the Incident Command as key situational awareness information.
Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Strub, Richard; Newcomer, Jeffrey A.
The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Pan, Z.; Glennie, C. L.; Fernandez-Diaz, J. C.
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.
Rossini, M.; Fava, F.; Cogliati, S.; Meroni, M.; Marchesi, A.; Panigada, C.; Giardino, C.; Busetto, L.; Migliavacca, M.; Amaducci, S.; Colombo, R.
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.
Zhu, Q.; Jiang, W.; Zhang, J.
In this paper, a feature line based method for building detection and reconstruction from oblique airborne imagery is presented. With the development of Multi-View Stereo technology, increasing photogrammetric softwares are provided to generate textured meshes from oblique airborne imagery. However, errors in image matching and mesh segmentation lead to the low geometrical accuracy of building models, especially at building boundaries. To simplify massive meshes and construct accurate 3D building models, we integrate multi-view images and meshes by using feature lines, in which contour lines are used for building detection and straight skeleton for building reconstruction. Firstly, through the contour clustering method, buildings can be quickly and robustly detected from meshes. Then, a feature preserving mesh segmentation method is applied to accurately extract 3D straight skeleton from meshes. Finally, straight feature lines derived from multi-view images are used to rectify inaccurate parts of 3D straight skeleton of buildings. Therefore, low quality model can be refined by the accuracy improvement of mesh feature lines and rectification with feature lines of multi-view images. The test dataset in Zürich is provided by ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. The experiments reveal that the proposed method can obtain convincing and high quality 3D building models from oblique airborne imagery.
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.
Klingler, J W; Andrews, L T; Leighton, R F
A computer-based educational system for the study of cardiovascular imaging is described. This system, based on HyperCard * and a standard Macintosh II, integrates hypertext retrieval, computer graphics, sound, and medical images into a single interactive environment stored on a standard hard disk. This 'hypermedia' approach allows arbitrary complexity coupled with direct, immediate, easy traversal of the images and related text, which provides the opportunity for students to move at their own pace, choose their own direction through the material and repeat as often as desired. Storage on magnetic medium allows for easy updating with new studies and material in order to keep pace with advances in medical imaging technology. The system could be mastered onto CD-ROM for ease of distribution if so desired. The system includes a tutorial on the basics of digital image representation and example studies from cineangiography, nuclear medicine, echocardiography and magnetic resonance imaging of the heart. Quantitative techniques for evaluation of left ventricular function are explained using computer graphics overlays on the original medical images. Color encoded functional images are also included as an aid to visualization of ventricular performance data. The system has proven useful as a primer for digital imaging in cardiology prior to specific case study in a traditional mentor relationship. PMID:1458869
Kozoderov, Vladimir V; Dmitriev, Egor V
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
Linne von Berg, Dale; Anderson, Scott A.; Bird, Alan; Holt, Niel; Kruer, Melvin; Walls, Thomas J.; Wilson, Michael L.
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.
Hauss, Bruce I.; Agravante, Hiroshi H.; Eberhard, C. D.; Luebkemann, Karen M.; Samec, Thomas K.; Wagner, Thomas M.; Rihaczek, August W.; Hershkowitz, Stephen J.; Mitchell, R. L.; Perahia, E.; Arnush, Donald; Lakshmanan, Sridhar
In a target-rich battlefield environment, a shipboard or an airborne radar must maintain situational awareness while tracking and identifying targets. Often the opportunity to dwell on each target long enough for confident identification via high resolution SAR/ISAR imaging will not exist, especially for those engagement geometries where the relative translational motion of the aircraft does not result in large rotation rates. Inadvertent aircraft tactical dither often generates enough target rotational during a brief imaging interval to allow the formation of an ISAR image with low crossrange resolution. We have developed an automated identification procedure that utilizes this resolution, along with high range resolution, to produce confident target identification. The advanced signal processing algorithms employed extract feature measurements from the complex ISAR image. including accurate measurements of the two-dimensional positions, amplitudes and range extents of the dominant target scatterers. A deformable template matching procedure is used to correlate these 'measured features' with those predicted for each candidate aircraft in a database generated from readily available diagrams, photographs and CAD models. After obtaining the optimal fit between the measured and predicted features for each candidate aircraft, the 'most likely' candidate is selected using a conventional Bayes classifier.
With advances in available bandwidth from spacecraft and between terrestrial control centers, digital motion imagery and video is becoming more practical as a data gathering tool for science and engineering, as well as for sharing missions with the public. The digital motion imagery and video industry has done a good job of creating standards for compression, distribution, and physical interfaces. Compressed data streams can easily be transmitted or distributed over radio frequency, internet protocol, and other data networks. All of these standards, however, can make sharing video between spacecraft and terrestrial control centers a frustrating and complicated task when different standards and protocols are used by different agencies. This paper will explore the challenges presented by the abundance of motion imagery and video standards, interfaces and protocols with suggestions for common formats that could simplify interoperability between spacecraft and ground support systems. Real-world examples from the International Space Station will be examined. The paper will also discuss recent trends in the development of new video compression algorithms, as well likely expanded use of Delay (or Disruption) Tolerant Networking nodes.
Holopainen, M.; Vastaranta, M.; Karjalainen, M.; Karila, K.; Kaasalainen, S.; Honkavaara, E.; Hyyppä, J.
Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry and interferometry. Airborne stereo imagery can be used in deriving photogrammetric point clouds, as very-high-resolution synthetic aperture radar (SAR) data are used in radargrammetry and interferometry. ALS is capable of mapping both the terrain and tree heights in mixed forest conditions, which is an advantage over aerial images or SAR data. However, in many jurisdictions, a detailed ALS-based digital terrain model is already available, and that enables linking photogrammetric or SAR-derived heights to heights above the ground. In other words, in forest conditions, the height of single trees, height of the canopy and/or density of the canopy can be measured and used in estimation of forest inventory attributes. In this paper, first we review experiences of the use of digital stereo imagery and spaceborne SAR in estimation of forest inventory attributes in Finland, and we compare techniques to ALS. In addition, we aim to present new implications based on our experiences.
Lamri, Takfarinas; Djemaï, Safouane; Hamoudi, Mohamed; Zoheir, Basem; Bendaoud, Abderrahmane; Ouzegane, Khadidja; Amara, Massinissa
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.
Khamsin, I.; Zulkarnain, M.; Razak, K. A.; Rizal, S.
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.
Smith Charles M.
This work was performed under NASA's Verification and Validation (V&V) Program as an independent check of data supplied by EarthWatch, Incorporated, through the Earth Science Enterprise Scientific Data Purchase (SDP) Program. This document serves as the basis of reporting results associated with validation of orthorectified interferometric interferometric radar imagery and digital elevation models (DEM). This validation covers all datasets provided under the first campaign (Central America & Virginia Beach) plus three earlier missions (Indonesia, Red River: and Denver) for a total of 13 missions.
Banks, Paul T.
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.
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.
Frost, V. S.; Perry, M. S.; Dellwig, L. F.; Holtzman, J. C.
The geological data content of Seasat A SAR imagery was assessed by correlating images of the Southern Appalachians with optical and digital techniques using a digital enhancement algorithm. The evaluation was performed in terms of lithology, lineaments, and geological structure. Digital correlation of the images was found to be more effective than optical correlation as a geological mapping instrument when considered in the light of ground truth data. The digital enhancement algorithm consists of a mean square error analysis which preserves the edge structure in the SAR imagery and decreases the noise content. Additionally, digital correlations allowed for faster computer processing of the imagery.
Marmorino, George O.; Smith, Geoffrey B.; Miller, W. D.; Bowles, Jeffrey H.
Municipal wastewater discharged into the ocean through a submerged pipe, or outfall, can rise buoyantly to the sea surface, resulting in a near-field mixing zone and, in the presence of an ambient ocean current, an extended surface plume. In this paper, data from a CASI (Compact Airborne Spectrographic Imager) and an airborne infrared (IR) camera are shown to detect a municipal wastewater discharge off the southeast coast of Florida, U.S.A., through its elevated levels of chromophoric dissolved organic matter plus detrital material (CDOM) and cooler sea surface temperatures. CDOM levels within a ~15-m-diameter surface 'boil' are found to be about twice those in the ambient shelf water, and surface temperatures near the boil are lower by ~0.4°C, comparable to the vertical temperature difference across the ambient water column. The CASI and IR imagery show a nearly identically shaped buoyant plume, consistent with a fully surfacing discharge, but the IR data more accurately delineate the area of most rapid dilution as compared with previous in-situ measurements. The imagery also allows identification of ambient oceanographic processes that affect dispersion and transport in the far field. This includes an alongshore front, which limits offshore dispersion of the discharge, and shoreward-propagating nonlinear internal waves, which may be responsible for an enhanced onshore transport of the discharge.
Empirical relationships between remotely sensed vegetation indices and density information, such as leaf area index or ground cover (GC), are commonly used to derive spatial information in many precision farming operations. In this study, we modified an existing methodology that does not depend on e...
Phillips, D. A.; Jackson, M. E.; Meertens, C.
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.
Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.
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
This report has been prepared to supplement a forthcoming chapter on formal methods in the FAA Digital Systems Validation Handbook. Its purpose is as follows: to outline the technical basis for formal methods in computer science; to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used on board aircraft; and to suggest factors for consideration when formal methods are offered in support of certification. These latter factors assume the context for software development and assurance described in RTCA document DO-178B, 'Software Considerations in Airborne Systems and Equipment Certification,' Dec. 1992.
Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.
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.
This study examined linear spectral unmixing techniques for mapping the variation in crop yield for precision agriculture. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery collected from a grain sorghum field and a cotton field. A pair...
Remote sensing technology was used to distinguish corn infested with European corn borers, Ostrinia nubilalis, from corn that was not infested. In 2004 and 2005, eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery. Manual inocu...
Akasheh, O. Z.; Neale, C. M.
Middle Rio Grande River (MRGR) is the main source of fresh water for the population of New Mexico as well as for irrigated agriculture. Extensive water diversion over the last few decades has affected the composition of the native Riparian vegetation such as Cottonwood population and enhanced the spread of introduced species harmful to the river system like Tamarisk and Russian Olives. High resolution airborne remote sensing is a powerful technique for riparian vegetation mapping and monitoring. Airborne multispectral digital images were acquired over the riparian corridor of the MRGR, New Mexico in June 1999 and July 2001, using the Utah State University (USU) airborne digital imaging system. The imagery were corrected for vignetting effects, geometric lens distortions, rectified to a map base, mosaicked, verified in the field, classified and checked for accuracy. Areas of the vegetation classes and in-stream features were extracted and presented per reach of the river. In this paper a relationship was developed between the total surface water area mapped and both the river water flow rate and water table readings. The consequence of this relationship on riparian vegetation distribution along the river was studied and graphically demonstrated. Strong relationship was found between the total surface water area and water flow rate. In addition the reduction in surface water area resulted in reduction of native trees downstream.
Park, Joong Yong
The objective of this research is to investigate possible strategies for the fusion of airborne laser data with passive optical data for object space classification. A significant contribution of our work is the development and implementation of a data-level fusion technique, direct digital image georeferencing (DDIG). In DDIG, we use navigation data from an integrated system (composed of global positioning system (GPS) and inertial measurement unit (IMU)) to project three-dimensional data points measured with the University of Florida's airborne laser swath mapping (ALSM) system onto digital aerial photographs. As an underlying math model, we use the familiar collinearity condition equations. After matching the ALSM object space points to their corresponding image space pixels, we resample the digital photographs using cubic convolution techniques. We call the resulting images pseudo-ortho-rectified images (PORI) because they are orthographic at the ground surface but still exhibit some relief displacement for elevated objects; and because they have been resampled using a interpolation technique. Our accuracy tests on these PORI images show that they are planimetrically correct to about 0.4 meters. This accuracy is sufficient to remove most of the effects of the central perspective projection and enable a meaningful fusion of the RGB data with the height and intensity data produced by the laser. PORI images may also be sufficiently accurate for many other mapping applications, and may in some applications be an attractive alternative to traditional photogrammetric techniques. A second contribution of our research is the development of several strategies for the fusion of data from airborne laser and camera systems. We have conducted our work within the sensor fusion paradigm formalized in the optical engineering community. Our work explores the fusion of these two types of data for precision mapping applications. Specifically, we combine three different types of
Sun, Yihang; Kerekes, John
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.
Dmitriev, E. V.
Recent research efforts have been focused on building a system of hyperspectral aerial sounding of forest vegetation on regional scales. The components of this system are developed using data obtained in the course of measurement campaigns in Tver forestry test sites. Hyperspectral airborne surveys are conducted using a Russian video spectrometer produced by the NPO Lepton company. The technique for recognizing ground-based objects is based on Bayesian classification principles with the feature space optimization. The choice of the most informative spectral channels is based on the step-up method. We propose an approach allowing the choice of channels to be more stable. We compare the classification of timber stands on the basis of hyperspectral imagery with ground-based data to demonstrate the consistency of the system developed.
van Eekeren, Adam W. M.; van Huis, Jasper R.; Eendebak, Pieter T.; Baan, Jan
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.
Hively, W. Dean; McCarty, Gregory W.; Reeves, James B., III; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.
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.
Desai, A. R.; DuBois, S.; Singh, A.; Serbin, S.; Goulden, M.; Baldocchi, D. D.; Oechel, W. C.; Kruger, E. L.; Townsend, P. A.
Changes in drought frequency and intensity are likely to be some of the largest climate anomalies to influence the net productivity of ecosystems, especially in already water-limited regions. However, the physiological mechanisms that drive this response are limited by primarily infrequent and small-scale leaf-level measurements. Here, we integrated eddy covariance flux tower estimates of gross primary productivity (GPP) across an elevation-gradient in California with airborne imagery from the NASA HyspIRI Preparatory campaign to evaluate the potential of hyperspectral imagery to detect responses of GPP to prolonged drought. We observed a number of spectral features in the visible, infrared, and shortwave infrared regions that yielded stronger linkages than traditional broadband indices with space and time variation in GPP across a range of ecosystems in California experiencing water stress in the past three years. Further, partial least squares regression (PLSR) modeling offers the ability to generate predictive models of GPP from narrowband hyperspectral remote sensing that directly links plant chemistry and spectral properties to productivity, and could serve as a significant advance over broadband remote sensing of GPP anomalies.
Wang, X.; Li, P.
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.
Meerdink, S.; Roberts, D. A.; Roth, K. L.
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
Ryba, Ken; Selby, Linda; Brown, Roy
This study was undertaken to explore the use of a digital camera for mental imagery training of a vocational task with two young adult men with Down syndrome. The results indicate that these particular men benefited from the use of a collaborative training process that involved mental imagery for learning a series of photocopying operations. An…
Kozoderov, Vladimir; Kondranin, Timofei; Dmitriev, Egor; Kamentsev, Vladimir
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
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. ...
Wohlfeil, J.; Hirschmüller, H.; Piltz, B.; Börner, A.; Suppa, M.
Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM) are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images' relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.
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
Vetrivel, A.; Duarte, D.; Nex, F.; Gerke, M.; Kerle, N.; Vosselman, G.
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).
Naraghi, M.; Stromberg, W.; Daily, M.
Geologic analysis of radar imagery requires accurate spatial rectification to allow rock type discrimination and meaningful exploitation of multisensor data files. A procedure is described which removes distortions produced by most sources including the heretofore elusive problem of terrain induced effects. Rectified imagery is presented which displays geologic features not apparent in the distorted data.
Scott, N. V.; Hooper, B. A.; Anderson, S. P.
Tidal flats are highly dynamic areas with strong horizontal and vertical density gradients and energetic currents capable of shaping bathymetry, as well as modulating the salinity, temperature, and sediment concentration of the surrounding waters. As part of the ONR Tidal Flat Dynamics program, Areté Associates' Airborne Remote Optical Spotlight System - Multispectral Polarimeter (AROSS-MSP) was flown over a tidal flat in Skagit Bay, Washington to characterize the spatial structure of the velocities and the sediment concentrations. Time-series imagery reveals a robust surface front generated during the flood to ebb tidal cycle. The front is characterized by different optical properties on either side of a foam line, and by horizontal streaks in water clarity perpendicular to the foam line in the muddier, fresher water (Figure 1). These streaks may be the result of shear instabilities which are given visibility by buoyant fine-grained suspensions. Temperature and salinity time series from data stations in the cross-shelf direction were analyzed via empirical orthogonal functions (EOF). Sudden changes in the trend of first temperature EOF at a place behind the tidal front where abundant fresh water channels meet very cool ocean waters associated with the flood tide suggest mixing. The possibility of cross-shelf variability in mixing is also suggested by the changes in the horizontal Richardson number. The horizontal Richardson number shows a minimum value at the same location as the first temperature EOF suggesting that turbulent shear is large enough to cause mixing.
Jorgensen, Christopher F.; Stutzman, Ryan J.; Anderson, Lars C.; Decker, Suzanne E.; Powell, Larkin A.; Schacht, Walter H.; Fontaine, Joseph J.
Question: What is the precision of five methods of measuring vegetation structure using ground-based digital imagery and processing techniques? Location: Lincoln, Nebraska, USA Methods: Vertical herbaceous cover was recorded using digital imagery techniques at two distinct locations in a mixed-grass prairie. The precision of five ground-based digital imagery vegetation analysis (DIVA) methods for measuring vegetation structure was tested using a split-split plot analysis of covariance. Variability within each DIVA technique was estimated using coefficient of variation of mean percentage cover. Results: Vertical herbaceous cover estimates differed among DIVA techniques. Additionally, environmental conditions affected the vertical vegetation obstruction estimates for certain digital imagery methods, while other techniques were more adept at handling various conditions. Overall, percentage vegetation cover values differed among techniques, but the precision of four of the five techniques was consistently high. Conclusions: DIVA procedures are sufficient for measuring various heights and densities of standing herbaceous cover. Moreover, digital imagery techniques can reduce measurement error associated with multiple observers' standing herbaceous cover estimates, allowing greater opportunity to detect patterns associated with vegetation structure.
Francis, E. J.; Asner, G. P.
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
Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.
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.
Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre
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%).
Wu, C.; Barkan, B.; Huneycutt, B.; Leang, C.; Pang, S.
Basic engineering data regarding the Interim Digital SAR Processor (IDP) and the digitally correlated Seasat synthetic aperature radar (SAR) imagery are presented. The correlation function and IDP hardware/software configuration are described, and a preliminary performance assessment presented. The geometric and radiometric characteristics, with special emphasis on those peculiar to the IDP produced imagery, are described.
Newcomer, Jeffrey A.; Dominquez, Roseanne; Hall, Forrest G. (Editor)
For BOREAS, the TIMS imagery, along with the other remotely sensed images, was collected to provide spatially extensive information over the primary study areas. The level-0 TIMS images cover the time periods of 16-Apr-1994 to 20-Apr-1994 and 06-Sep-1994 to 17-Sep-1994. The images are available in their original uncalibrated format.
A study was conducted on a south Texas rangeland area to evaluate aerial color-infrared (CIR) photography and CIR digital imagery combined with unsupervised image analysis techniques to map broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby]. Accuracy assessments performed on compute...
Maurer, H. E.; Oderman, W.; Crosswell, W. F.
A data set is described which consists of digitized synthetic aperture radar (SAR) imagery plus correlative data and some preliminary analysis results. This data set should be of value to experimenters who are interested in the SAR instrument and its application to the detection and monitoring of oil on water and other distributed targets.
Nguyen, A.T.; Stow, D.A.; Hope, A.S.
Airborne digital camera systems have gained popularity in recent years due to their flexibility, high geometric fidelity and spatial resolution, and fast data turn-around time. However, a common problem that plagues these types of framing systems is vignetting which causes falloff in image brightness away from principle nadir point. This paper presents a simple method for vignetting correction by utilizing laboratory images of a uniform illumination source. Multiple lab images are averaged and inverted to create digital correction templates which then are applied to actual airborne data. The vignette correction was effective in removing the systematic falloff in spectral values. We have shown that the vignette correction is a necessary part of the preprocessing of raw digital airborne remote sensing data. The consequences of not correcting for these effects are demonstrated in the context of monitoring of salt marsh habitat. 4 refs.
Newcomer, Jeffrey A.; Dominquez, Roseanne; Hall, Forrest G. (Editor)
The level-0 AOCI imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOREAS study areas. The AOCI was the only remote sensing instrument flown with wavelength bands specific to the investigation of various aquatic parameters such as chlorophyll content and turbidity. Only one flight of the AOCI instrument was made onboard the ER-2 aircraft on 21-Jul-1994 over the SSA.
Schmauder, G. C.; Kent, G.; Smith, K. D.; Driscoll, N. W.; Maloney, J. M.
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
Color pictures generated from digital images are frequently used by geologists, foresters, range managers, and others. These color products are preferred over black and white pictures because the human eye is more sensitive to color differences than to various shades of gray. Color discrimination is a function of perception, and therefore colors in these color composites are generally described subjectively, which can lead to ambiguous color communication. Numerous color-coordinate systems are available that quantitively relate digital triplets representing amounts of red, free, and blue to the parameters of hue, saturation, and intensity perceived by the eye. Most of these systems implement a complex transformation of the primary colors to a color space that is hard to visualize, thus making it difficult to relate digital triplets to perception parameters. This paper presents a color-communcation scheme that relates colors on a color triangle to corresponding values of "hue" (H), "saturation" (S), and chromaticity coordinates (x,y,z). The scheme simplifies the relation between red, green, and blue (RGB) digital triplets and the color generated by these triplets. Some examples of the use of the color-communication scheme in digital image processing are presented.
Bowley, C. J.; Burke, H. H. K.; Barnes, J. C.
In support of the Southeastern Virginia Urban Plume Study (SEV-UPS), GOES satellite imagery was analyzed for the month of August 1979. The analyzed GOES images provide an additional source of meteorological input useful in the evaluation of air quality data collected during the month long period of the SEV-UPS experiment. In addition to the imagery analysis, GOES digitized data were analyzed for the period of August 6 to 11, during which a regional haze pattern was detectable in the imagery. The results of the study indicate that the observed haze patterns correspond closely with areas shown in surface based measurements to have reduced visibilities and elevated pollution levels. Moreover, the results of the analysis of digitized data indicate that digital reflectance counts can be directly related to haze intensity both over land and ocean. The model results agree closely with the observed GOES digital reflectance counts, providing further indication that satellite remote sensing can be a useful tool for monitoring regional elevated pollution episodes.
Based on a previous study on an airborne remote sensing system with automatic camera stabilization for crop management, multispectral imagery was acquired using the MS-4100 multispectral camera at different flight altitudes over a 115 ha cotton field. After the acquired images were geo-registered an...
Shendryk, I.; Tulbure, M. G.; Broich, M.
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
Maeda, Y.; Fukushima, A.; Imai, Y.; Tanahashi, Y.; Nakama, E.; Ohta, S.; Kawazoe, K.; Akune, N.
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.
Woodell, Glenn A.; Jobson, Daniel J.; Rahman, Zia-ur
Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.
Liu, Xue; Li, Qingting; Fang, Junyong; Tong, Qingxi; Zheng, Lanfen
Remote sensing, especially airborne remote sensing, can be an invaluable technique for quick response to natural disasters. Timely acquired images by airborne remote sensing can provide very important information for the headquarters and decision makers to be aware of the disaster situation, and make effective relief arrangements. The image acquisition and processing of Multi-mode Airborne Digital Camera System (MADC) and its application in Wenchuan earthquake disaster monitoring are presented in this paper. MADC system is a novel airborne digital camera developed by Institute of Remote Sensing Applications, Chinese Academy of Sciences. This camera system can acquire high quality images in three modes, namely wide field, multi-spectral (hyper-spectral) and stereo conformation. The basic components and technical parameters of MADC are also presented in this paper. MADC system played a very important role in the disaster monitoring of Wenchuan earthquake. In particular, the map of dammed lakes in Jianjiang river area was produced and provided to the front line headquarters. Analytical methods and information extraction techniques of MADC are introduced. Some typical analytical and imaging results are given too. Suggestions for the design and configuration of the airborne sensors are discussed at the end of this paper.
Naumann, M.; Geist, M.; Bill, R.; Niemeyer, F.; Grenzdörffer, G.
The main focus of the paper is a comparative study in which we have investigated, whether automatically generated digital surface models (DSM) obtained from unmanned aerial systems (UAS) imagery are comparable with DSM obtained from terrestrial laser scanning (TLS). The research is conducted at a pilot dike for coastal engineering. The effort and the achievable accuracy of both DSMs are compared. The error budgets of these two methods are investigated and the models obtained in each case compared against each other.
Spencer, M. M.; Wolf, J. M.; Schall, M. A.
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%.
Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.
As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.
The problems encountered when attempting to register Landsat Thematic Mapper (TM) data to U.S. geological survey digital elevation models (DEMs) are examined. It is shown that TM and DEM data are not available in the same map projection, necessitating geometric transformation of one of the data type, that the TM data are not accurately located in their nominal projection, and that TM data have higher resolution than most DEM data, but oversampling the DEM data to TM resolution introduces systematic noise. Further work needed in this area is discussed.
Bassani, C.; Cavalli, R. M.; Fasulli, L.; Palombo, A.; Pascucci, S.; Santini, F.; Pignatti, S.
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) . 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
Cho, Moses Azong; Skidmore, Andrew; Corsi, Fabio; van Wieren, Sipke E.; Sobhan, Istiak
The main objective was to determine whether partial least squares (PLS) regression improves grass/herb biomass estimation when compared with hyperspectral indices, that is normalised difference vegetation index (NDVI) and red-edge position (REP). To achieve this objective, fresh green grass/herb biomass and airborne images (HyMap) were collected in the Majella National Park, Italy in the summer of 2005. The predictive performances of hyperspectral indices and PLS regression models were then determined and compared using calibration ( n = 30) and test ( n = 12) data sets. The regression model derived from NDVI computed from bands at 740 and 771 nm produced a lower standard error of prediction (SEP = 264 g m -2) on the test data compared with the standard NDVI involving bands at 665 and 801 nm (SEP = 331 g m -2), but comparable results with REPs determined by various methods (SEP = 261 to 295 g m -2). PLS regression models based on original, derivative and continuum-removed spectra produced lower prediction errors (SEP = 149 to 256 g m -2) compared with NDVI and REP models. The lowest prediction error (SEP = 149 g m -2, 19% of mean) was obtained with PLS regression involving continuum-removed bands. In conclusion, PLS regression based on airborne hyperspectral imagery provides a better alternative to univariate regression involving hyperspectral indices for grass/herb biomass estimation in the Majella National Park.
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...
Vegetation indices derived from remotely sensed imagery are commonly used to estimate crop yields. Spectral unmixing techniques provide an alternative approach to quantifying crop canopy abundance within each pixel of an image and have the potential for mapping crop yield variability. The objective ...
Canopy structural and chemical data are needed for senescent, mixed-grass prairie landscapes in autumn, yet models driven by image data are lacking for rangelands dominated by non-photosynthetically active vegetation (NPV). Here, we report how aerial hyperspectral imagery might be modeled to predic...
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...
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...
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...
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...
Drenth, B.J.; Abraham, J.D.; Grauch, V.J.S.; Labson, V.F.; Hodges, G.
This report contains digital data and supporting explanatory files describing data types, data formats, and survey procedures for a high-resolution airborne gravity gradient (AGG) survey at Great Sand Dunes National Park, Alamosa and Saguache Counties, south-central Colorado. In the San Luis Valley, the Great Sand Dunes survey covers a large part of Great Sand Dunes National Park and Preserve. The data described were collected from a high-resolution AGG survey flown in February 2012, by Fugro Airborne Surveys Corp., on contract to the U.S. Geological Survey. Scientific objectives of the AGG survey are to investigate the subsurface structural framework that may influence groundwater hydrology and seismic hazards, and to investigate AGG methods and resolution using different flight specifications. Funding was provided by an airborne geophysics training program of the U.S. Department of Defense's Task Force for Business & Stability Operations.
Abedi, Maysam; Norouzi, Gholam-Hossain
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
Yun, H.-C.; Kim, J.-B.; Lee, J.-S.; Kang, I.-J.
As global warming and has caused the number of abnormal changes, lots of damage has arisen recently due to natural disaster. To prevent and cope with these annually repeated natural hazards, the disaster management is required including the systematic management. Currently the national and related agencies are producing the flood hazard map and flood e map in case of disaster management and recovery, and coping with the disaster using them for building recovery plan, grasping disaster status and cause analysis. The hazard map is the one which indicates the calamity danger districts including the degree of risk in general and called the degree of disaster risk map or disaster expectation map and it means the map which marks the hazard zones by estimating the areas to coping with the natural disaster in the inclusive concept. Now that such hazard map should be understood easily from the place of the person concerned in the disaster, the production of new type of map which can be easily understood visually rather than the map by diagram. In this study, new concept disaster prevention map based on digital image and disaster attribute information was constructed. The various disaster information such as the areas of inundation of river, submergence and landslip caused by severe rain storm and typhoon is marked in the hazard information map, and the rescue route and refuge area are also marked by setting the damage-expected areas. The disaster prevention map is able to support quick decision making for disaster management and resident education.
STS-53 Discovery, Orbiter Vehicle (OV) 103, Department of Defense (DOD) mission Hand-held Earth-oriented Real-time Cooperative, User-friendly, Location, targeting, and Environmental System (Hercules) spaceborne experiment equipment is documented in this table top view. HERCULES is a joint NAVY-NASA-ARMY payload designed to provide real-time high resolution digital electronic imagery and geolocation (latitude and longitude determination) of earth surface targets of interest. HERCULES system consists of (from left to right): a specially modified GRID Systems portable computer mounted atop NASA developed Playback-Downlink Unit (PDU) and the Naval Research Laboratory (NRL) developed HERCULES Attitude Processor (HAP); the NASA-developed Electronic Still Camera (ESC) Electronics Box (ESCEB) including removable imagery data storage disks and various connecting cables; the ESC (a NASA modified Nikon F-4 camera) mounted atop the NRL HERCULES Inertial Measurement Unit (HIMU) containing the three
Akutsu, Osamu; Ohta, Masataka; Isobe, Tamio; Ando, Hisamitsu, Noguchi, Takahiro; Shimizu, Masayuki
Disasters caused by heavy rain in urban areas bring a damage such as chaos in the road and railway transport systems, power failure, breakdown of the telephone system and submersion of built up areas, subways and underground shopping arcades, etc. It is important to obtain high precision elevation data which shows the detailed landform because a slight height difference affects damages by flood very considerably. Therefore, The Geographical Survey Institute (GSI) is preparing 5m grid digital terrain model (DTM) based on precise ground elevation data taken by using airborne laser scanner. This paper describes the process and an example of the use of a 5m grid digital data set.
Arvesen, J. C.; Dotson, R. C.
The DMS (Digital Mapping System) has been a sensor component of all DC-8 and P-3 IceBridge flights since 2009 and has acquired over 3 million JPEG images over Arctic and Antarctic land and sea ice. The DMS imagery is primarily used for identifying and locating open leads for LiDAR sea-ice freeboard measurements and documenting snow and ice surface conditions. The DMS is a COTS Canon SLR camera utilizing a 28mm focal length lens, resulting in a 10cm GSD and swath of ~400 meters from a nominal flight altitude of 500 meters. Exterior orientation is provided by an Applanix IMU/GPS which records a TTL pulse coincident with image acquisition. Notable for virtually all IceBridge flights is that parallel grids are not flown and thus there is no ability to photogrammetrically tie any imagery to adjacent flight lines. Approximately 800,000 Level-3 DMS Surface Model data products have been delivered to NSIDC, each consisting of a Digital Elevation Model (GeoTIFF DEM) and a co-registered Visible Overlay (GeoJPEG). Absolute elevation accuracy for each individual Elevation Model is adjusted to concurrent Airborne Topographic Mapper (ATM) Lidar data, resulting in higher elevation accuracy than can be achieved by photogrammetry alone. The adjustment methodology forces a zero mean difference to the corresponding ATM point cloud integrated over each DMS frame. Statistics are calculated for each DMS Elevation Model frame and show RMS differences are within +/- 10 cm with respect to the ATM point cloud. The DMS Surface Model possesses similar elevation accuracy to the ATM point cloud, but with the following advantages: · Higher and uniform spatial resolution: 40 cm GSD · 45% wider swath: 435 meters vs. 300 meters at 500 meter flight altitude · Visible RGB co-registered overlay at 10 cm GSD · Enhanced visualization through 3-dimensional virtual reality (i.e. video fly-through) Examples will be presented of the utility of these advantages and a novel use of a cell phone camera for
Capaldo, P.; Crespi, M.; Fratarcangeli, F.; Nascetti, A.; Pieralice, F.
The interest for the radargrammetric approach to Digital Surface Models (DSMs) generation has been growing in last years thanks to the availability of very high resolution imagery acquired by new SAR (Synthetic Aperture Radar) sensors, as COSMO-SkyMed, Radarsat-2 and TerraSAR-X, which are able to supply imagery up to 1 m ground resolution. DSMs radargrammetric generation approach consists of two basic steps, as for the standard photogrammetry applied to optical imagery: the imagery (at least a stereo pair) orientation and the image matching for the generation of the points cloud. The steps of the radargrammetric DSMs generation have been implemented into SISAR (Software per Immagini Satellitari ad Alta Risoluzione), a scientific software developed at Geodesy and Geomatics Institute of the University of Rome "La Sapienza". Moreover, starting from the radargrammetric orientation model, a tool for the Rational Polynomial Coefficients (RPCs) for SAR images have been implemented. The possibility to generate RPCs, re-parametrizing a rigorous orientation model through a standardized set of coefficients which can be managed by a Rational Polynomial Coefficients (RPFs) model (similarly to optical high resolution imagery) sounds of particular interest since, at present, the most part of SAR imagery (except from Radarsat-2) is not supplied with RPCs, although the corresponding RPFs model is available in several commercial software. In particular the RPCs model has been used in the matching process and in the stereo restitution for the DSMs generation, with the advantage of shorter computational time. This paper discusses the application and the results of the implemented algorithm for radargrammetric DSMs generation from TerraSAR-X SpotLight imagery, acquired in Spotlight mode over Trento (Northern Italy). Urban and extra-urban (forested, cultivated) areas were considered in two different tiles, and a final overall accuracy ranging from 4.5 to 6 meters was achieved as regards
Evans, C. A.; Todd, N. S.
The Astromaterials Acquisition & Curation Office at NASA's Johnson Space Center (JSC) is the designated facility for curating all of NASA's extraterrestrial samples. Today, the suite of collections includes the lunar samples from the Apollo missions, cosmic dust particles falling into the Earth's atmosphere, meteorites collected in Antarctica, comet and interstellar dust particles from the Stardust mission, asteroid particles from Japan's Hayabusa mission, solar wind atoms collected during the Genesis mission, and space-exposed hardware from several missions. To support planetary science research on these samples, JSC's Astromaterials Curation Office hosts NASA's Astromaterials Curation digital repository and data access portal [http://curator.jsc.nasa.gov/], providing descriptions of the missions and collections, and critical information about each individual sample. Our office is designing and implementing several informatics initiatives to better serve the planetary research community. First, we are re-hosting the basic database framework by consolidating legacy databases for individual collections and providing a uniform access point for information (descriptions, imagery, classification) on all of our samples. Second, we continue to upgrade and host digital compendia that summarize and highlight published findings on the samples (e.g., lunar samples, meteorites from Mars). We host high resolution imagery of samples as it becomes available, including newly scanned images of historical prints from the Apollo missions. Finally we are creating plans to collect and provide new data, including 3D imagery, point cloud data, micro CT data, and external links to other data sets on selected samples. Together, these individual efforts will provide unprecedented digital access to NASA's Astromaterials, enabling preservation of the samples through more specific and targeted requests, and supporting new planetary science research and collaborations on the samples.
Geli, H. M.; Taghvaeian, S.; Neale, C. M.; Pack, R.; Watts, D. R.; Osterberg, J.
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
Iwaszczuk, D.; Stilla, U.
Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality.
Hellden, U.; Stern, M.
The possible use of LANDSAT imagery and digital data for monitoring desertification indicators in Tunisia was studied. Field data were sampled in Tunisia for estimation of mapping accuracy in maps generated through interpretation of LANDSAT false color composites and processing of LANDSAT computer compatible tapes respectively. Temporal change studies were carried out through geometric registration of computer classified windows from 1972 to classified data from 1979. Indications on land degradation were noted in some areas. No important differences, concerning results, between the interpretation approach and the computer processing approach were found.
Klemas, V. (Principal Investigator); Bartlett, D.; Rogers, R.; Reed, L.
The author has identified the following significant results. Analysis of ERTS-1 color composite images using analogy processing equipment confirmed that all the major wetlands plant species were distinguishable at ERTS-1 scale. Furthermore, human alterations of the coastal zone were easily recognized since such alterations typically involve removal of vegetative cover resulting in a change of spectral signature. The superior spectral resolution of the CCTs as compared with single band or composite imagery has indeed provided good discrimination through digital analysis of the CCTs with the added advantage of rapid production of thematic maps and data.
Virlet, Nicolas; Lebourgeois, Valentine; Martinez, Sébastien; Costes, Evelyne; Labbé, Sylvain; Regnard, Jean-Luc
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
Virlet, Nicolas; Lebourgeois, Valentine; Martinez, Sébastien; Costes, Evelyne; Labbé, Sylvain; Regnard, Jean-Luc
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
Love, E.; Hammack, R.; Harbert, W.; Sams, J.; Veloski, G.; Ackman, T.
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.
Love, E.; Hammack, R.W.; Harbert, W.P.; Sams, J.I.; Veloski, G.A.; Ackman, T.E.
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.
Zhang, Yongjun; Zheng, Maoteng; Huang, Xu; Xiong, Jinxin
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
Gong, K.; Fritsch, D.
Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising.
Coluzzi, R.; Guariglia, A.; Lacovara, B.; Lasaponara, R.; Masini, N.
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  and investigated in 2005 by using QuickBird imagery . 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
Misurec, J.; Kopačková, V.; Lhotáková, Z.; Albrechtova, J.; Campbell, P. K. E.
The Ore Mountains are an example of the region that suffered from severe environmental pollution caused by long-term coal mining and heavy industry leading to massive dieback of the local Norway spruce forests between the 1970's and 1990's. The situation became getting better at the end of 1990's after pollution loads significantly decreased. In 1998 and 2013, airborne hyperspectral data (with sensor ASAS and APEX, respectively) were used to study recovery of the originally damaged forest stands and compared them with those that have been less affected by environmental pollution. The field campaign (needle biochemical analysis, tree defoliation etc.) accompanied hyperspectral imagery acquisition. An analysis was conducted assessing a set of 16 vegetation indices providing complex information on foliage, biochemistry and canopy biophysics and structure. Five of them (NDVI, NDVI705, VOG1, MSR and TCARI/OSAVI) showing the best results were employed to study spatial gradients as well as temporal changes. The detected gradients are in accordance with ground truth data on representative trees. The obtained results indicate that the original significant differences between the damaged and undamaged stands have been generally levelled until 2013, although it is still possible to detect signs of the previous damages in several cases.
Cavalieri, Donald J.; Markus, Thorsten; Hall, Dorothy K.; Gasiewski, Albin J.; Klein, Marian; Ivanoff, Alvaro
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.
Guo, L.J.; Moore, J.M. )
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.
Kosmatin Fras, M.; Kerin, A.; Mesarič, M.; Peterman, V.; Grigillo, D.
Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.
Wright, David L.; Bradley, Jerry A.; Hodge, Steven M.
A high-speed digital data acquisition and signal averaging system for borehole, surface, and airborne radio-frequency geophysical measurements was designed and built by the US Geological Survey. The system permits signal averaging at rates high enough to achieve significant signal-to-noise enhancement in profiling, even in airborne applications. The first field use of the system took place in Greenland in 1987 for recording data on a 150 by 150-km grid centered on the summit of the Greenland ice sheet. About 6000-line km were flown and recorded using the new system. The data can be used to aid in siting a proposed scientific corehole through the ice sheet.
Zhang, W.; Hu, B.; Woods, M.
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.
Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela
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.
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.
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.
Abd-Elrahman, Amr; Sassi, Naoufal; Wilkinson, Ben; Dewitt, Bon
The georeferencing accuracy of a ground-based mobile mapping system designated for agricultural applications is tested. The system integrates a hyperspectral sensor, digital camera, global navigation satellite system receivers, and an inertial navigation system. Acquired imagery was synchronized with GPS time using custom hardware and software solutions developed in-house. The imaging platform was mounted on a forklift and used to conduct three imaging missions along a paved road segment and agricultural beds. Sixteen ground control points were established in each site and used to calibrate the system and test the positional accuracy. The control point coordinates were determined using GNSS and total station observations independent from the imaging data. The navigation data were postprocessed to extract sensor positions and attitude along the imaging trajectories. The pushbroom hyperspectral images were georeferenced using ReSe Parge software, while the digital camera images were analyzed using Agisoft PhotoScan software. Control point coordinates extracted from the georeferenced imagery were compared to corresponding ground-surveyed coordinates. The maximum root mean square errors obtained for the hyperspectral images in all experiments were 2.4 and 3.1 cm in the easting and northing directions, respectively. These results were achieved using only two control points at both ends of the scan line to estimate the boresight offsets. The RMSE values of the orthorectified image constructed using the digital camera images and two control points at each end of the agricultural site were 1.6 and 2.6 cm in the easting and northing directions.
Goodwin, Nicholas; Coops, Nicholas C.; Stone, Christine
Pine plantations in Australia are subject to a range of abiotic and biotic damaging agents that affect tree health and productivity. In order to optimise management decisions, plantation managers require regular intelligence relating to the status and trends in the health and condition of trees within individual compartments. Remote sensing technology offers an alternative to traditional ground-based assessment of these plantations. Automated estimation of foliar crown health, especially in degraded crowns, can be difficult due to mixed pixels when there is low or fragmented vegetation cover. In this study we apply a linear spectral unmixing approach to high spatial resolution (50 cm) multispectral imagery to quantify the fractional abundances of the key image endmembers: sunlit canopy, shadow, and soil. A number of Pinus radiata tree crown attributes were modelled using multiple linear regression and endmember fraction images. We found high levels of significance ( r2 = 0.80) for the overall crown colour and colour of the crown leader ( r2 = 0.79) in tree crowns affected by the fungal pathogen Sphaeropsis sapinea, which produces both needle necrosis and chlorosis. Results for stands associated with defoliation and chlorosis through infestation by the aphid Essigella californica were lower with an r2 = 0.33 for crown transparency and r2 = 0.31 for proportion of crown affected. Similar analysis of data from a nitrogen deficient site produced an outcome somewhat in between the other two damaging agents. Overall the sunlit canopy image fraction has been the most important variable used in the modelling of forest condition for all damaging agents.
Pullanagari, R. R.; Kereszturi, Gábor; Yule, I. J.
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.
Mostafa, Mohamed Mohamed Rashad
In this thesis, the development and testing of an airborne fully digital multi-sensor system for kinematic mapping is presented. The system acquires two streams of data, namely navigation data and imaging data. The navigation data are obtained by integrating an accurate strapdown Inertial Navigation System with two GPS receivers. The imaging data are acquired by two digital cameras, configured in such a way so as to reduce their geometric limitations. The two digital cameras capture strips of overlapping nadir and oblique images. The INS/GPS-derived trajectory contains the full translational and rotational motion of the carrier aircraft. Thus, image exterior orientation information is extracted from the trajectory, during postprocessing. This approach eliminates the need for ground control when computing 3D positions of objects that appear in the field of view of the system imaging component. Test flights were conducted over the campus of The University of Calgary. Two approaches for calibrating the system are presented, namely pre-mission calibration and in-flight calibration. Testing the system in flight showed that best ground point positioning accuracy at 1:12000 average image scale is 0.2 m (RMS) in easting and northing and 0.3 m (RMS) in height. Preliminary results indicate that major applications of such a system in the future are in the field of digital mapping, at scales of 1:10000 and smaller, and the generation of digital elevation models for engineering applications.
Sanchez, Richard D.
High-resolution airborne digital cameras with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) technology may offer a real-time means to gather accurate topographic map information by reducing ground control and eliminating aerial triangulation. Past evaluations of this integrated system over relatively flat terrain have proven successful. The author uses Emerge Digital Sensor System (DSS) combined with Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing to examine the positional mapping accuracy in rough terrain. The positional accuracy documented in this study did not meet large-scale mapping requirements owing to an apparent system mechanical failure. Nonetheless, the findings yield important information on a new approach for mapping in Antarctica and other remote or inaccessible areas of the world.
Cho, Moses Azong; Skidmore, Andrew K.; Sobhan, Istiak
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
Bonrud, L. O.; Henrikson, P. J.
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.
Klemas, V.; Bartlett, D.; Rogers, R.; Reed, L.
Digital analysis of ERTS-1 imagery was used in an attempt to map and inventory the significant ecological communities of Delaware's coastal zone. Eight vegetation and land use discrimination classes were selected: (1) phragmites communis (Giant Reed grass); (2) spartina alterniflora (Salt marsh cord grass); (3) spartina patens (Salt marsh hay); (4) shallow water and exposed mud; (5) deep water (2 meters); (6) forest; (7) agriculture; and (8) exposed sand and concrete. Canonical analysis showed that classification accuracy was quite good with spartina alterniflora, exposed sand-concrete, and forested land - all discriminated with between 94% and 100% accuracy. The shallow water-mud and deep water categories were classified with accuracies of 88% and 93% respectively. Phragmites communis showed a classification accuracy of 83% with all confusion occurring with spartina patens which may be due to use of mixed stands of these species as training sets. Discrimination of spartina patens was very poor (accuracy 52%).
Gorbatsevich, V.; Vizilter, Yu.; Knyaz, V.; Zheltov, S.
A technique for automated face detection and its pose estimation using single image is developed. The algorithm includes: face detection, facial features localization, face/background segmentation, face pose estimation, image transformation to frontal view. Automatic face/background segmentation is performed by original graph-cut technique based on detected feature points. The precision of face orientation estimation based on monocular digital imagery is addressed. The approach for precision estimation is developed based on comparison of synthesized facial 2D images and scanned face 3D model. The software for modelling and measurement is developed. The special system for non-contact measurements is created. Required set of 3D real face models and colour facial textures is obtained using this system. The precision estimation results demonstrate the precision of face pose estimation enough for further successful face recognition.
Hanson, Bradford C.; Dellwig, Louis F.
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.
Mars, J.C.; Crowley, J.K.
Remotely sensed hyperspectral and digital elevation data from southeastern Idaho are combined in a new method to assess mine waste contamination. Waste rock from phosphorite mining in the area contains selenium, cadmium, vanadium, and other metals. Toxic concentrations of selenium have been found in plants and soils near some mine waste dumps. Eighteen mine waste dumps and five vegetation cover types in the southeast Idaho phosphate district were mapped by using Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) imagery and field data. The interaction of surface water runoff with mine waste was assessed by registering the AVIRIS results to digital elevation data, enabling determinations of (1) mine dump morphologies, (2) catchment watershed areas above each mine dump, (3) flow directions from the dumps, (4) stream gradients, and (5) the extent of downstream wetlands available for selenium absorption. Watersheds with the most severe selenium contamination, such as the South Maybe Canyon watershed, are associated with mine dumps that have large catchment watershed areas, high stream gradients, a paucity of downstream wetlands, and dump forms that tend to obstruct stream flow. Watersheds associated with low concentrations of dissolved selenium, such as Angus Creek, have mine dumps with small catchment watershed areas, low stream gradients, abundant wetlands vegetation, and less obstructing dump morphologies. ?? 2002 Elsevier Science Inc. All rights reserved.
Bulatov, Dimitri; Ziems, Marcel; Rottensteiner, Franz; Pohl, Melanie
Road databases are known to be an important part of any geodata infrastructure, e.g. as the basis for urban planning or emergency services. Updating road databases for crisis events must be performed quickly and with the highest possible degree of automation. We present a semi-automatic algorithm for road verification using textured 3D city models, starting from aerial or even UAV-images. This algorithm contains two processes, which exchange input and output, but basically run independently from each other. These processes are textured urban terrain reconstruction and road verification. The first process contains a dense photogrammetric reconstruction of 3D geometry of the scene using depth maps. The second process is our core procedure, since it contains various methods for road verification. Each method represents a unique road model and a specific strategy, and thus is able to deal with a specific type of roads. Each method is designed to provide two probability distributions, where the first describes the state of a road object (correct, incorrect), and the second describes the state of its underlying road model (applicable, not applicable). Based on the Dempster-Shafer Theory, both distributions are mapped to a single distribution that refers to three states: correct, incorrect, and unknown. With respect to the interaction of both processes, the normalized elevation map and the digital orthophoto generated during 3D reconstruction are the necessary input - together with initial road database entries - for the road verification process. If the entries of the database are too obsolete or not available at all, sensor data evaluation enables classification of the road pixels of the elevation map followed by road map extraction by means of vectorization and filtering of the geometrically and topologically inconsistent objects. Depending on the time issue and availability of a geo-database for buildings, the urban terrain reconstruction procedure has semantic models
Su, Y.; Guo, Q.; Collins, B.; Fry, D.; Kelly, M.
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
Roberti, Joshua A.; SanClements, Michael D.; Loescher, Henry W.; Ayres, Edward
Even though fine-root turnover is a highly studied topic, it is often poorly understood as a result of uncertainties inherent in its sampling, e.g., quantifying spatial and temporal variability. While many methods exist to quantify fine-root turnover, use of minirhizotrons has increased over the last two decades, making sensor errors another source of uncertainty. Currently, no standardized methodology exists to test and compare minirhizotron camera capability, imagery, and performance. This paper presents a reproducible, laboratory-based method by which minirhizotron cameras can be tested and validated in a traceable manner. The performance of camera characteristics was identified and test criteria were developed: we quantified the precision of camera location for successive images, estimated the trueness and precision of each camera's ability to quantify root diameter and root color, and also assessed the influence of heat dissipation introduced by the minirhizotron cameras and electrical components. We report detailed and defensible metrology analyses that examine the performance of two commercially available minirhizotron cameras. These cameras performed differently with regard to the various test criteria and uncertainty analyses. We recommend a defensible metrology approach to quantify the performance of minirhizotron camera characteristics and determine sensor-related measurement uncertainties prior to field use. This approach is also extensible to other digital imagery technologies. In turn, these approaches facilitate a greater understanding of measurement uncertainties (signal-to-noise ratio) inherent in the camera performance and allow such uncertainties to be quantified and mitigated so that estimates of fine-root turnover can be more confidently quantified. PMID:25391023
Sadowy, Gregory; Ghaemi, Hirad; Hensley, Scott
NASA/JPL has developed SweepSAR technique that breaks typical Synthetic Aperture Radar (SAR) trade space using time-dependent multi-beam DBF on receive. Developing SweepSAR implementation using array-fed reflector for proposed DESDynI Earth Radar Mission concept. Performed first-of-a-kind airborne demonstration of the SweepSAR concept at Ka-band (35.6 GHz). Validated calibration and antenna pattern data sufficient for beam forming in elevation. (1) Provides validation evidence that the proposed Deformation Ecosystem Structure Dynamics of Ice (DESDynI) SAR architecture is sound. (2) Functions well even with large variations in receiver gain / phase. Future plans include using prototype DESDynI SAR digital flight hardware to do the beam forming in real-time onboard the aircraft.
Bamber, Jonathan L.; Ekholm, Simon; Krabill, William B.
A 2.5 km resolution digital elevation model (DEM) of the Greenland ice sheet was produced from the 336 days of the geodetic phase of ERS-1. During this period the altimeter was operating in ice-mode over land surfaces providing improved tracking around the margins of the ice sheet. Combined with the high density of tracks during the geodetic phase, a unique data set was available for deriving a DEM of the whole ice sheet. The errors present in the altimeter data were investigated via a comparison with airborne laser altimeter data obtained for the southern half of Greenland. Comparison with coincident satellite data showed a correlation with surface slope. An explanation for the behavior of the bias as a function of surface slope is given in terms of the pattern of surface roughness on the ice sheet.
Kettermann, M.; Grützner, C.; van Gent, H. W.; Urai, J. L.; Reicherter, K.; Mertens, J.
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.
Fuyi, Tan; Boon Chun, Beh; Mat Jafri, Mohd Zubir; Hwee San, Lim; Abdullah, Khiruddin; Mohammad Tahrin, Norhaslinda
The problem of difficulty in obtaining cloud-free scene at the Equatorial region from satellite platforms can be overcome by using airborne imagery. Airborne digital imagery has proved to be an effective tool for land cover studies. Airborne digital camera imageries were selected in this present study because of the airborne digital image provides higher spatial resolution data for mapping a small study area. The main objective of this study is to classify the RGB bands imageries taken from a low-altitude Cropcam UAV for land cover/use mapping over USM campus, penang Island, Malaysia. A conventional digital camera was used to capture images from an elevation of 320 meter on board on an UAV autopilot. This technique was cheaper and economical compared with other airborne studies. The artificial neural network (NN) and maximum likelihood classifier (MLC) were used to classify the digital imageries captured by using Cropcam UAV over USM campus, Penang Islands, Malaysia. The supervised classifier was chosen based on the highest overall accuracy (<80%) and Kappa statistic (<0.8). The classified land cover map was geometrically corrected to provide a geocoded map. The results produced by this study indicated that land cover features could be clearly identified and classified into a land cover map. This study indicates the use of a conventional digital camera as a sensor on board on an UAV autopilot can provide useful information for planning and development of a small area of coverage.
Killpack, Cody C.; Budge, Scott E.
The ability to create 3D models, using registered texel images (fused ladar and digital imagery), is an important topic in remote sensing. These models are automatically generated by matching multiple texel images into a single common reference frame. However, rendering a sequence of independently registered texel images often provides challenges. Although accurately registered, the model textures are often incorrectly overlapped and interwoven when using standard rendering techniques. Consequently, corrections must be done after all the primitives have been rendered, by determining the best texture for any viewable fragment in the model. Determining the best texture is difficult, as each texel image remains independent after registration. The depth data is not merged to form a single 3D mesh, thus eliminating the possibility of generating a fused texture atlas. It is therefore necessary to determine which textures are overlapping and how to best combine them dynamically during the render process. The best texture for a particular pixel can be defined using 3D geometric criteria, in conjunction with a real-time, view-dependent ranking algorithm. As a result, overlapping texture fragments can now be hidden, exposed, or blended according to their computed measure of reliability.
Brook, Anna; Wittenberg, Lea
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.
Padgett, Curtis W.; Ansar, Adnan I.; Brennan, Shane; Cheng, Yang; Clouse, Daniel S.; Almeida, Eduardo
When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in
Kringer, K.; Tusch, M.; Geitner, C.; Meißl, G.; Rutzinger, M.
Especially in mountainous regions like the Alps the formation of soil is highly influenced by relief characteristics. Among all factors included in Jenny's (1941) model for soil development, relief is the one most commonly used in approaches to create digital soil maps and to derive soil properties from secondary data sources (McBratney et al. 2003). Elevation data, first order (slope, aspect) and second order derivates (plan, profile and cross-sectional curvature) as well as complex morphometric parameters (various landform classifications, e.g., Wood 1996) and compound indices (e.g., topographic wetness indices, vertical distance to drainage network, insolation) can be calculated from digital elevation models (DEM). However, while being an important source of information for digital soil mapping on small map scales, "conventional" DEMs are of limited use for the design of large scale conceptual soil maps for small areas due to rather coarse raster resolutions with cell sizes ranging from 20 to 100 meters. Slight variations in elevation and small landform features might not be discernible even though they might have a significant effect to soil formation, e.g., regarding the influence of groundwater in alluvial soils or the extent of alluvial fans. Nowadays, Airborne LiDAR (Light Detection And Ranging) provides highly accurate data for the elaboration of high-resolution digital terrain models (DTM) even in forested areas. In the project LASBO (Laserscanning in der Bodenkartierung) the applicability of digital terrain models derived from LiDAR for the identification of soil-relevant geomorphometric parameter is investigated. Various algorithms which were initially designed for coarser raster data are applied on high-resolution DTMs. Test areas for LASBO are located in the region of Bruneck (Italy) and near the municipality of Kramsach in the Inn Valley (Austria). The freely available DTM for Bruneck has a raster resolution of 2.5 meters while in Kramsach a DTM with
Chabrillat, Sabine; Guillaso, Stephane; Rabe, Andreas; Foerster, Saskia; Guanter, Luis
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
Frankel, Kurt L.; Dolan, James F.
Range-front alluvial fan deposition in arid environments is episodic and results in multiple fan surfaces and ages. These distinct landforms are often defined by descriptions of their surface morphology, desert varnish accumulation, clast rubification, desert pavement formation, soil development, and stratigraphy. Although quantifying surface roughness differences between alluvial fan units has proven to be difficult in the past, high-resolution airborne laser swath mapping (ALSM) digital topographic data are now providing researchers with an opportunity to study topography in unprecedented detail. Here we use ALSM data to calculate surface roughness on two alluvial fans in northern Death Valley, California. We define surface roughness as the standard deviation of slope in a 5-m by 5-m moving window. Comparison of surface roughness values between mapped fan surfaces shows that each unit is statistically unique at the 99% confidence level. Furthermore, there is an obvious smoothing trend from the presently active channel to a deposit with cosmogenic 10Be and 36Cl surface exposure ages of ˜70 ka. Beyond 70 ka, alluvial landforms become progressively rougher with age. These data suggest that alluvial fans in arid regions smooth out with time until a threshold is crossed where roughness increases at greater wavelength with age as a result of surface runoff and headward tributary incision into the oldest surfaces.
Virlet, Nicolas; Costes, Evelyne; Martinez, Sébastien; Kelner, Jean-Jacques; Regnard, Jean-Luc
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
Virlet, Nicolas; Costes, Evelyne; Martinez, Sébastien; Kelner, Jean-Jacques; Regnard, Jean-Luc
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
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...
Cole, M. M. (Principal Investigator); Owen-Jones, E. S.
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.
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...
Song, Ahram; Chang, Anjin; Choi, Jaewan; Choi, Seokkeun; Kim, Yongil
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
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
Hall, Forrest G. (Editor); Newcomer, Jeffrey A.; Dominguez, Roseanne
For BOREAS, the NS001 TMS imagery, along with the other remotely sensed images, was collected in order to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fPAR and LAI. Data collections occurred over the study areas during the 1994 field campaigns.
Using commercial digital cameras in conjunction with Unmanned Aerial Systems (UAS) to generate 3-D Digital Surface Models (DSMs) and orthomosaics is emerging as a cost-effective alternative to Light Detection and Ranging (LiDAR). Powerful software applications such as Pix4D and APS can automate the generation of DSM and orthomosaic products from a handful of inputs. However, the accuracy of these models is relatively untested. The objectives of this study were to generate multiple DSM and orthomosaic pairs of the same area using Pix4D and APS from flights of imagery collected with a lightweight UAS. The accuracy of each individual DSM was assessed in addition to the consistency of the method to model one location over a period of time. Finally, this study determined if the DSMs automatically generated using lightweight UAS and commercial digital cameras could be used for detecting changes in elevation and at what scale. Accuracy was determined by comparing DSMs to a series of reference points collected with survey grade GPS. Other GPS points were also used as control points to georeference the products within Pix4D and APS. The effectiveness of the products for change detection was assessed through image differencing and observance of artificially induced, known elevation changes. The vertical accuracy with the optimal data and model is ≈ 25 cm and the highest consistency over repeat flights is a standard deviation of ≈ 5 cm. Elevation change detection based on such UAS imagery and DSM models should be viable for detecting infrastructure change in urban or suburban environments with little dense canopy vegetation.
Metcalf, Jeremy P.; Olsen, Richard C.
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.
Cole, M. M. (Principal Investigator); Owen-Jones, S.
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.
Müller, Johann; Gärtner-Roer, Isabelle; Thee, Patrick; Ginzler, Christian
High-resolution digital elevation models (DEMs) generated by airborne remote sensing are frequently used to analyze landform structures (monotemporal) and geomorphological processes (multitemporal) in remote areas or areas of extreme terrain. In order to assess and quantify such structures and processes it is necessary to know the absolute accuracy of the available DEMs. This study assesses the absolute vertical accuracy of DEMs generated by the High Resolution Stereo Camera-Airborne (HRSC-A), the Leica Airborne Digital Sensors 40/80 (ADS40 and ADS80) and the analogue camera system RC30. The study area is located in the Turtmann valley, Valais, Switzerland, a glacially and periglacially formed hanging valley stretching from 2400 m to 3300 m a.s.l. The photogrammetrically derived DEMs are evaluated against geodetic field measurements and an airborne laser scan (ALS). Traditional and robust global and local accuracy measurements are used to describe the vertical quality of the DEMs, which show a non Gaussian distribution of errors. The results show that all four sensor systems produce DEMs with similar accuracy despite their different setups and generations. The ADS40 and ADS80 (both with a ground sampling distance of 0.50 m) generate the most accurate DEMs in complex high mountain areas with a RMSE of 0.8 m and NMAD of 0.6 m They also show the highest accuracy relating to flying height (0.14‰). The pushbroom scanning system HRSC-A produces a RMSE of 1.03 m and a NMAD of 0.83 m (0.21‰ accuracy of the flying height and 10 times the ground sampling distance). The analogue camera system RC30 produces DEMs with a vertical accuracy of 1.30 m RMSE and 0.83 m NMAD (0.17‰ accuracy of the flying height and two times the ground sampling distance). It is also shown that the performance of the DEMs strongly depends on the inclination of the terrain. The RMSE of areas up to an inclination <40° is better than 1 m. In more inclined areas the error and outlier occurrence
Carroll, Matthew W; Glaser, John A; Hellmich, Richard L; Hunt, Thomas E; Sappington, Thomas W; Calvin, Dennis; Copenhaver, Ken; Fridgen, John
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
The first live High Definition Television (HDTV) from a spacecraft was in November, 2006, nearly ten years before the 2016 SpaceOps Conference. Much has changed since then. Now, live HDTV from the International Space Station (ISS) is routine. HDTV cameras stream live video views of the Earth from the exterior of the ISS every day on UStream, and HDTV has even flown around the Moon on a Japanese Space Agency spacecraft. A great deal has been learned about the operations applicability of HDTV and high resolution imagery since that first live broadcast. This paper will discuss the current state of real-time and file based HDTV and higher resolution video for space operations. A potential roadmap will be provided for further development and innovations of high-resolution digital motion imagery, including gaps in technology enablers, especially for deep space and unmanned missions. Specific topics to be covered in the paper will include: An update on radiation tolerance and performance of various camera types and sensors and ramifications on the future applicability of these types of cameras for space operations; Practical experience with downlinking very large imagery files with breaks in link coverage; Ramifications of larger camera resolutions like Ultra-High Definition, 6,000 [pixels] and 8,000 [pixels] in space applications; Enabling technologies such as the High Efficiency Video Codec, Bundle Streaming Delay Tolerant Networking, Optical Communications and Bayer Pattern Sensors and other similar innovations; Likely future operations scenarios for deep space missions with extreme latency and intermittent communications links.
Yang, Z. H.; Zhang, Y. S.; Zheng, T.; Lai, W. B.; Zou, Z. R.; Zou, B.
Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.
Shendryk, Iurii; Tulbure, Mirela; Broich, Mark; McGrath, Andrew; Alexandrov, Sergey; Keith, David
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
Sadowy, Gregory A.; Ghaemi, Hirad; Hensley, Scott C.
SweepSAR is a wide-swath synthetic aperture radar technique that is being studied for application on the future Earth science radar missions. This paper describes the design of an airborne radar demonstration that simulates an 11-m L-band (1.2-1.3 GHz) reflector geometry at Ka-band (35.6 GHz) using a 40-cm reflector. The Ka-band SweepSAR Demonstration system was flown on the NASA DC-8 airborne laboratory and used to study engineering performance trades and array calibration for SweepSAR configurations. We present an instrument and experiment overview, instrument calibration and first results.
Erickson, Ricky A.; Moren, Stephen E.; Skalka, Marion S.
Providing a flexible and reliable source of IR target imagery is absolutely essential for operation of an IR Scene Projector in a hardware-in-the-loop simulation environment. The Kinetic Kill Vehicle Hardware-in-the-Loop Simulator (KHILS) at Eglin AFB provides the capability, and requisite interfaces, to supply target IR imagery to its Wideband IR Scene Projector (WISP) from three separate sources at frame rates ranging from 30 - 120 Hz. Video can be input from a VCR source at the conventional 30 Hz frame rate. Pre-canned digital imagery and test patterns can be downloaded into stored memory from the host processor and played back as individual still frames or movie sequences up to a 120 Hz frame rate. Dynamic real-time imagery to the KHILS WISP projector system, at a 120 Hz frame rate, can be provided from a Silicon Graphics Onyx computer system normally used for generation of digital IR imagery through a custom CSA-built interface which is available for either the SGI/DVP or SGI/DD02 interface port. The primary focus of this paper is to describe our technical approach and experience in the development of this unique SGI computer and WISP projector interface.
Yoo, J.; Fritz, H. M.; Haas, K. A.; Work, P. A.; Barnes, C. F.; Cho, Y.
Celerity of incident waves in the nearshore is observed from oblique video imagery collected at Myrtle Beach, S.C.. The video camera covers the field view of length scales O(100) m. Celerity of waves propagating in shallow water including the surf zone is estimated by applying advanced image processing and analysis methods to the individual video images sampled at 3 Hz. Original image sequences are processed through video image frame differencing, directional low-pass image filtering to reduce the noise arising from foam in the surf zone. The breaking wave celerity is computed along a cross-shore transect from the wave crest tracks extracted by a Radon transform-based line detection method. The observed celerity from the nearshore video imagery is larger than the linear wave celerity computed from the measured water depths over the entire surf zone. Compared to the nonlinear shallow water wave equation (NSWE)-based celerity computed using the measured depths and wave heights, in general, the video-based celerity shows good agreements over the surf zone except the regions across the incipient wave breaking locations. In the regions across the breaker points, the observed wave celerity is even larger than the NSWE-based celerity due to the transition of wave crest shapes. The observed celerity using the video imagery can be used to monitor the nearshore geometry through depth inversion based on the nonlinear wave celerity theories. For this purpose, the exceeding celerity across the breaker points needs to be corrected accordingly compared to a nonlinear wave celerity theory applied.
Pomalaza, J. C. (Principal Investigator); Pomalaza, C. A.; Espinoza, J.
The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.
Newcomer, Jeffrey A.; Dominguez, Roseanne; Hall, Forrest G. (Editor)
The level-0 Daedalus Thematic Mapper Simulator (TMS) imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOReal Ecosystem-Atmosphere Study (BOREAS) study areas. This information includes detailed land cover and biophysical parameter maps such as fraction of Photosynthetically Active Radiation (fPAR) and Leaf Area Index (LAI). Two flights of the Daedalus TMS instrument were made onboard the ER-2 aircraft on 16-Sep-1994 and 17-Sep-1994.
Parent, Jason R.; Volin, John C.; Civco, Daniel L.
Information on land cover is essential for guiding land management decisions and supporting landscape-level ecological research. In recent years, airborne light detection and ranging (LiDAR) and high resolution aerial imagery have become more readily available in many areas. These data have great potential to enable the generation of land cover at a fine scale and across large areas by leveraging 3-dimensional structure and multispectral information. LiDAR and other high resolution datasets must be processed in relatively small subsets due to their large volumes; however, conventional classification techniques cannot be fully automated and thus are unlikely to be feasible options when processing large high-resolution datasets. In this paper, we propose a fully automated rule-based algorithm to develop a 1 m resolution land cover classification from LiDAR data and multispectral imagery. The algorithm we propose uses a series of pixel- and object-based rules to identify eight vegetated and non-vegetated land cover features (deciduous and coniferous tall vegetation, medium vegetation, low vegetation, water, riparian wetlands, buildings, low impervious cover). The rules leverage both structural and spectral properties including height, LiDAR return characteristics, brightness in visible and near-infrared wavelengths, and normalized difference vegetation index (NDVI). Pixel-based properties were used initially to classify each land cover class while minimizing omission error; a series of object-based tests were then used to remove errors of commission. These tests used conservative thresholds, based on diverse test areas, to help avoid over-fitting the algorithm to the test areas. The accuracy assessment of the classification results included a stratified random sample of 3198 validation points distributed across 30 1 × 1 km tiles in eastern Connecticut, USA. The sample tiles were selected in a stratified random manner from locations representing the full range of
Lang, M; Vain, A; Bunce, R G H; Jongman, R H G; Raet, J; Sepp, K; Kuusemets, V; Kikas, T; Liba, N
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
Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad
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.
Humbert, Angelika; Steinhage, Daniel
The Fimbulisen, an ice shelf located roughly between 3°W-8°E at the coast of Dronning Maud Land, East Antarctica, consists of the fast flowing extension of Jutulstraumen and slower moving parts west and east of it. The largely rifted western part of the Fimbulisen is the subject of this study, which combines observations and modelling. Airborne radio echo sounding performed by the Alfred Wegener Institute between 1996 and 2008 with a frequency of 150 MHz and pulse length of 60 ns, respectively 600 ns, is analysed in order to study the internal structure of the ice in parts of the rift zone and to estimate the ice thickness in this area precisely. High-resolution radar imagery acquired by the TerraSAR-X in 2008 and 2009 is used to evaluate principal deformation axis at characteristic locations, to detect crack modes as well as to classify zones of similar structural characteristics. These zones were incorporated in a 2D diagnostic ice flow model as sub-domains with variable stress enhancement factor and thus treated as zones of different damage related stiffness. The temperature-dependent stiffness is calculated by applying the solution of a validated 3D temperature model of the ice shelf and thus the simulations focus on the softening effect caused by cracks. Extensive parameter studies show the effect of the stress enhancement factor on the principal deformation rates and axis. Comparison with the estimated deformation pattern aims to confine the softening effect for each zone separately.
Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.
A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.
Dieck, J.J.; Robinson, Larry
The Upper Midwest Environmental Sciences Center (UMESC) has used aerial photography to map land cover/land use on federally owned and managed lands for over 20 years. Until recently, that process used 23- by 23-centimeter (9- by 9-inch) analog aerial photos to classify vegetation along the Upper Mississippi River System, on National Wildlife Refuges, and in National Parks. With digital aerial cameras becoming more common and offering distinct advantages over analog film, UMESC transitioned to an entirely digital mapping process in 2009. Though not without challenges, this method has proven to be much more accurate and efficient when compared to the analog process.
This paper describes a digital processing algorithm and its associated system design for producing images from Synthetic Aperture Radar (SAR) data. The proposed system uses the Fast Fourier Transform (FFT) approach to perform the two-dimensional correlation process. The range migration problem, which is often a major obstacle to efficient processing, can be alleviated by approximating the locus of echoes from a point target by several linear segments. SAR data corresponding to each segment is correlated separately, and the results are coherently summed to produce full-resolution images. This processing approach exhibits greatly improved computation efficiency relative to conventional digital processing methods.
This work was performed under NASA's Verification and Validation Program as an independent check of data supplied by Positive Systems, Inc. through the Earth Science Enterprise's Scientific Data Purchase (SDP) Program. This document serves as the basis for reporting results associated with validation of multispectral imagery according to the specifications of contract NAS 13-98049. The validation was performed under the Positive Systems Imaging System Validation Work Instruction CRSP-WI-28: Spectral registration, spatial resolution, endlaps, sidelaps, and image quality were evaluated. The validation was proceded by Shipment Verification, as described in the Work Instruction CRSP-WI-22: Every image was passed through an automatic ingest verification and thumbnail review process to identify omissions, problems with media integrity, and gross errors in data quality. Validation of metadata files is not within the scope of this report, but it was performed separately.
Palaseanu-Lovejoy, Monica; Thatcher, Cindy A.; Barras, John A.
This study explores the feasibility of using airborne lidar surveys to derive high-resolution digital elevation models (DEMs) and develop an automated procedure to extract levee longitudinal elevation profiles for both federal levees in Atchafalaya Basin and local levees in Lafourche Parish. Generally, the use of traditional manual surveying methods to map levees is a costly and time consuming process that typically produces cross-levee profiles every few hundred meters, at best. The purpose of our paper is to describe and test methods for extracting levee crest elevations in an efficient, comprehensive manner using high resolution lidar generated DEMs. In addition, the vertical uncertainty in the elevation data and its effect on the resultant estimate of levee crest heights is addressed in an assessment of whether the federal levees in our study meet the USACE minimum height design criteria.
The amount and distribution of gaps in vegetation canopy is a useful indicator of multiple ecosystem processes and functions. We describe a semi-automated approach for estimating canopy-gap size distributions in rangelands from high-resolution (HR) digital images using image interpretation by observ...
Kuehl, C. Stephen
Video signal system performance can be compromised in a military aircraft cockpit management system (CMS) with the tailoring of vintage Electronics Industries Association (EIA) RS170 and RS343A video interface standards. Video analog interfaces degrade when induced system noise is present. Further signal degradation has been traditionally associated with signal data conversions between avionics sensor outputs and the cockpit display system. If the CMS engineering process is not carefully applied during the avionics video and computing architecture development, extensive and costly redesign will occur when visual sensor technology upgrades are incorporated. Close monitoring and technical involvement in video standards groups provides the knowledge-base necessary for avionic systems engineering organizations to architect adaptable and extendible cockpit management systems. With the Federal Communications Commission (FCC) in the process of adopting the Digital HDTV Grand Alliance System standard proposed by the Advanced Television Systems Committee (ATSC), the entertainment and telecommunications industries are adopting and supporting the emergence of new serial/parallel digital video interfaces and data compression standards that will drastically alter present NTSC-M video processing architectures. The re-engineering of the U.S. Broadcasting system must initially preserve the electronic equipment wiring networks within broadcast facilities to make the transition to HDTV affordable. International committee activities in technical forums like ITU-R (former CCIR), ANSI/SMPTE, IEEE, and ISO/IEC are establishing global consensus on video signal parameterizations that support a smooth transition from existing analog based broadcasting facilities to fully digital computerized systems. An opportunity exists for implementing these new video interface standards over existing video coax/triax cabling in military aircraft cockpit management systems. Reductions in signal
Urban, F. E.; Reynolds, R. L.; Neff, J. C.; Fernandez, D. P.; Reheis, M. C.; Goldstein, H.; Grote, E.; Landry, C.
Improved measurement and observation of dust emission and deposition in the American west would advance understanding of (1) landscape conditions that promote or suppress dust emission, (2) dynamics of dryland and montane ecosystems, (3) premature melting of snow cover that provides critical water supplies, and (4) possible effects of dust on human health. Such understanding can be applied to issues of land management, water-resource management, as well as the safety and well-being of urban and rural inhabitants. We have recently expanded the scope of particulate measurement in the Upper Colorado River basin through the establishment of total-suspended-particulate (TSP) measurement stations located in Utah and Colorado with bi-weekly data (filter) collection, along with protocols for characterizing dust-on-snow (DOS) layers in Colorado mountains. A sub-network of high-resolution digital cameras has been co-located with several of the TSP stations, as well as at other strategic locations. These real-time regional dust-event detection cameras are internet-based and collect digital imagery every 6-15 minutes. Measurements of meteorological conditions to support these collections and observations are provided partly by CLIM-MET stations, four of which were deployed in 1998 in the Canyonlands (Utah) region. These stations provide continuous, near real-time records of the complex interaction of wind, precipitation, vegetation, as well as dust emission and deposition, in different land-use settings. The complementary datasets of dust measurement and observation enable tracking of individual regional dust events. As an example, the first DOS event of water year 2012 (Nov 5, 2011), as documented at Senator Beck Basin, near Silverton, Colorado, was also recorded by the camera at Island-in-the-Sky (200 km to the northwest), as well as in aeolian activity and wind data from the Dugout Ranch CLIM-MET station (170 km to the west-northwest). At these sites, strong winds and the
Blodget, H. W.; Brown, G. F.
Digitally enhanced LANDSAT MSS data were used to discriminate among basalt flows of historical to Tertiary age, at a test site in Northwestern Saudi Arabia. Spectral signatures compared favorably with a field-defined classification that permits discrimination among five groups of basalt flows on the basis of geomorphic criteria. Characteristics that contributed to age definition include: surface texture, weathering, color, drainage evolution, and khabrah development. The inherent gradation in the evolution of geomorphic parameters, however, makes visual extrapolation between areas subjective. Therefore, incorporation of spectrally-derived volcanic units into the mapping process should produce more quantitatively consistent age groupings.
Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.
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
Large-scale Digital Surface Models (DSM) are very useful for many geoscience and urban applications. Recently developed dense image matching methods have popularized the use of image-based very high resolution DSM. Many commercial/public tools that implement matching methods are available for perspective images, but there are rare handy tools for satellite stereo images. In this paper, a software package, RPC (rational polynomial coefficient) stereo processor (RSP), is introduced for this purpose. RSP implements a full pipeline of DSM and orthophoto generation based on RPC modelled satellite imagery (level 1+), including level 2 rectification, geo-referencing, point cloud generation, pan-sharpen, DSM resampling and ortho-rectification. A modified hierarchical semi-global matching method is used as the current matching strategy. Due to its high memory efficiency and optimized implementation, RSP can be used in normal PC to produce large format DSM and orthophotos. This tool was developed for internal use, and may be acquired by researchers for academic and non-commercial purpose to promote the 3D remote sensing applications.
Spence, Clay D.; Sajda, Paul; Pearson, John C.
An important problem in image analysis is finding small objects in large images. The problem is challenging because (1) searching a large image is computationally expensive, and (2) small targets (on the order of a few pixels in size) have relatively few distinctive features which enable them to be distinguished from non-targets. To overcome these challenges we have developed a hierarchical neural network (HNN) architecture which combines multi-resolution pyramid processing with neural networks. The advantages of the architecture are: (1) both neural network training and testing can be done efficiently through coarse-to-fine techniques, and (2) such a system is capable of learning low-resolution contextual information to facilitate the detection of small target objects. We have applied this neural network architecture to two problems in which contextual information appears to be important for detecting small targets. The first problem is one of automatic target recognition (ATR), specifically the problem of detecting buildings in aerial photographs. The second problem focuses on a medical application, namely searching mammograms for microcalcifications, which are cues for breast cancer. Receiver operating characteristic (ROC) analysis suggests that the hierarchical architecture improves the detection accuracy for both the ATR and microcalcification detection problems, reducing false positive rates by a significant factor. In addition, we have examined the hidden units at various levels of the processing hierarchy and found what appears to be representations of road location (for the ATR example) and ductal/vasculature location (for mammography), both of which are in agreement with the contextual information used by humans to find these classes of targets. We conclude that this hierarchical neural network architecture is able to automatically extract contextual information in imagery and utilize it for target detection.
Burke, James J.; Snyder, Harry L.
Two hundred-fifty transparencies, displaying a new digital database consisting of 25 degraded versions (5 blur levels x 5 noise levels) of each of 10 digitized, first-generation positive transparencies, were used in two experiments involving 15 trained military photo-interpreters. Each image is 86 mm square and represents 40962 8-bit pixels. In the "interpretation" experiment, each photo-interpreter (judge) spent approximately two days extracting Essential Elements of Information (EEI's) from one degraded version of each scene at a constant blur level (FWHM = 40, 84 or 322 μm). In the scaling experiment, each judge assigned a numerical value to each of the 250 images, according to its perceived position on a 10-point NATO-standardized scale (0 = useless through 9 = nearly perfect), to the nearest 0.1 unit. Eighty-eight of the 100 possible values were used by the judges, indicating that 62 categories are needed to scale these hardcopy images. The overall correlation between the scaling and interpretation results was 0.9. Though the main effect of blur was not significant (p = 0.146) in the interpretation experiment, that of noise was significant (p = 0.005), and all main factors (blur, noise, scene, order of battle) and most interactions were statistically significant in the scaling experiment.
Conn, R. B.
A highly-reliable, fault-tolerant reconfigurable computer system for aircraft applications was developed. The development and application reliability and fault-tolerance assessment techniques are described. Particular emphasis is placed on the needs of an all-digital, fly-by-wire control system appropriate for a passenger-carrying airplane.
This report is based on one prepared as a chapter for the FAA Digital Systems Validation Handbook (a guide to assist FAA certification specialists with advanced technology issues). Its purpose is to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used in critical applications; and to suggest factors for consideration when formal methods are offered in support of certification. The presentation concentrates on the rationale for formal methods and on their contribution to assurance for critical applications within a context such as that provided by DO-178B (the guidelines for software used on board civil aircraft); it is intended as an introduction for those to whom these topics are new.
Haran, T. M.; Scambos, T. A.
An image enhancement approach is used to develop a new digital elevation map of West Antarctica, combining multiple MODIS images and both radar altimetry and ICESat laser altimetry Digital Elevation Model (DEM) data. The method combines the wide image coverage of MODIS, and its high radiometric sensitivity (which equates to high sunward slope sensitivity), with the high precision and accuracy of ICESat and combined ICESat and radar altimetry DEMs. We calibrate brightness-to-slope relationships for several MODIS images of the central West Antarctic using smoothed DEMs derived from both sources. Using the calibrations, we then created, first, a slope map of the ice sheet surface from the image data (regressing slope information from many images), and then integrated this absolute slope map to yield complete DEMs for the region. ICESat (as of September 2007) has acquired a series of eleven near-repeat tracks over the Antarctic during the period September 2003 to April 2007, covering the continent to 86 deg S. ICESat data are acquired as a series of spot elevations, averaging a ~60m diameter surface region every ~172m. However, ICESat track paths have spacings wide enough (2 km at 85 deg; 20 - 50 km at 75 deg) that some surface ice dynamical features (e.g. flowlines, undulations, ice rises) are missed by the track data used to construct the ICESat DEM. Radar altimetry can provide some of the missing data north of 81.5 deg, but only to a maximum resolution of about 5 km. A set of cloud-cleared MODIS band 1 data from both the Aqua and Terra platforms acquired during the 2003-2004 austral summer, used in generating the Mosaic of Antarctica, MOA, surface morphology image map, were used for the image enhancement. Past analyses of the slope-brightness relationship for MODIS have shown ice surface slope precisions of +/- 0.00015. ICESat spot elevations have nominal precisions of ~5 cm under ideal conditions, although thin-cloud effects and mislocation errors can magnify these
The form of clastic particles provides information about debris history including abrasion and transportation which are vital to geomorphological research because of its usefulness for differentiating subglacial debris form englacialy, supraglacialy and fluvially transported sediments, and for understanding subglacial processes. There are numerous attempts to clastic particles form assessment, both qualitative and quantitative and advance in technology enables the use of digital imaging and image processing in order to calculate the precise indicators of shape and roundness (small-scale surface features superimposed on shape and roundness are not a subject of this study). Computer calculations are fast, reliable and objective and its use decrease probability of errors. They are applicable to till deposits analysis and may help in understanding the processes of glacial deposition. Till deposits consist of a mixture of various fractions of sediment, where coarser and thinner grains are together activated, entrained in ice, transported, deposited and post-depositional transformed together in the same time and conditions. That implies similarity of processes acting on the particles, but not necessarily theirs effects. Physical properties of grain are of great significance for its vulnerability to acting forces. An important feature of the tills is grain size, which has a high volatility in a sample. The hypothesis of this issue suggests it is possible that different fractions of till sediment have significantly different form characteristics. Verification of the thesis is important because standardly only one fraction is selected to analysis and to draw conclusions from. Main objective is to test differences in clast morphology for different till fraction. In order to answer the research problem, the author has examined samples from a contemporary glaciated region, Nordenskiöld glacier foreland in central Spitsbergen. During the field work samples were collected from
Prakash, A.; Haselwimmer, C. E.; Gens, R.; Womble, J. N.; Ver Hoef, J.
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.
Tise, Bertice L.; Dubbert, Dale F.
A digital IF receiver (DRX) module directly compatible with advanced radar systems such as synthetic aperture radar (SAR) systems. The DRX can combine a 1 G-Sample/sec 8-bit ADC with high-speed digital signal processor, such as high gate-count FPGA technology or ASICs to realize a wideband IF receiver. DSP operations implemented in the DRX can include quadrature demodulation and multi-rate, variable-bandwidth IF filtering. Pulse-to-pulse (Doppler domain) filtering can also be implemented in the form of a presummer (accumulator) and an azimuth prefilter. An out of band noise source can be employed to provide a dither signal to the ADC, and later be removed by digital signal processing. Both the range and Doppler domain filtering operations can be implemented using a unique pane architecture which allows on-the-fly selection of the filter decimation factor, and hence, the filter bandwidth. The DRX module can include a standard VME-64 interface for control, status, and programming. An interface can provide phase history data to the real-time image formation processors. A third front-panel data port (FPDP) interface can send wide bandwidth, raw phase histories to a real-time phase history recorder for ground processing.
Gramenopoulos, N. (Principal Investigator)
The author has identified the following significant results. For the recognition of terrain types, spatial signatures are developed from the diffraction patterns of small areas of ERTS-1 images. This knowledge is exploited for the measurements of a small number of meaningful spatial features from the digital Fourier transforms of ERTS-1 image cells containing 32 x 32 picture elements. Using these spatial features and a heuristic algorithm, the terrain types in the vicinity of Phoenix, Arizona were recognized by the computer with a high accuracy. Then, the spatial features were combined with spectral features and using the maximum likelihood criterion the recognition accuracy of terrain types increased substantially. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. Nonlinear transformations of the feature vectors are required so that the terrain class statistics become approximately Gaussian. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month but vary substantially between seasons.
Pratson, L.; Malinverno, A.; Edwards, M.; Ryan, W. )
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.
Kent, Dennis C.
There are numerous technological challenges in the Tactical Reconnaissance (Tac Recce) arena as the digital imagery era dawns. Foremost among them are the problems of imagery transmission bandwidth and the storage of the collected imagery. In this paper I seek to address these problems in an interrelated manner. I do not propose any new technological innovation, but rather a fundamental change in the philosophy of the collection, transmission, and storage of tactical imagery. The core of the approach requires that the area being imaged has already been imaged before (old imagery). This is reasonable given satellite, long range, UAV, and tactical imagery collection systems presently planned for, anticipated data collection rates, and how hot spots are repeatedly imaged. In addition, the Defense Airborne Reconnaissance Office (DARO) expects to be imaging tens of thousands of square kilometers each day within the next decade. When new tasking to collect imaging is received, imagery collected before by some imagery collection system must be taken with the aircraft (A/C) or person sent out to collect new imagery. As the new imagery is collected, the old and new imagery of the same area would be automatically registered. The old imagery can be pre-scaled, pre-warped, pre-rotated, etc., in order to maximize the efficiency of this process. The registered images can be spatially and spectrally thresholded in order to isolate significant deltas. Automatic target cueing (ATC)/automatic target recognition (ATR) could be used on both images for comparison to further isolate new objects of interest. Segmentation techniques could then be used to extract objects or regions of interest from the new image and only these objects or regions would be transmitted to the ground, a relay aircraft, or a satellite. Once at the ground station or long-term storage site, the new information could be inserted into the original image, thus minimizing the amount of storage space required as areas
James, M. R.; Robson, S.
We describe a framework for deriving sequences of digital elevation models (DEMs) for the analysis of active lava flows using oblique stereo-pair time-lapse imagery. A photo-based technique was favoured over laser-based alternatives due to low equipment cost, high portability and capability for network expansion, with images of advancing flows captured by digital SLR cameras over durations of up to several hours. However, under typical field scale scenarios, relative camera orientations cannot be rigidly maintained (e.g. through the use of a stereo bar), preventing the use of standard stereo time-lapse processing software. Thus, we trial semi-automated DEM-sequence workflows capable of handling the small camera motions, variable image quality and restricted photogrammetric control that result from the practicalities of data collection at remote and hazardous sites. The image processing workflows implemented either link separate close-range photogrammetry and traditional stereo-matching software, or are integrated in a single software package based on structure-from-motion (SfM). We apply these techniques in contrasting case studies from Kilauea volcano, Hawaii and Mount Etna, Sicily, which differ in scale, duration and image texture. On Kilauea, the advance direction of thin fluid lava lobes was difficult to forecast, preventing good distribution of control. Consequently, volume changes calculated through the different workflows differed by ∼10% for DEMs (over ∼30 m2) that were captured once a minute for 37 min. On Mt. Etna, more predictable advance (∼3 m h-1 for ∼3 h) of a thicker, more viscous lava allowed robust control to be deployed and volumetric change results were generally within 5% (over ∼500 m2). Overall, the integrated SfM software was more straightforward to use and, under favourable conditions, produced results comparable to those from the close-range photogrammetry pipeline. However, under conditions with limited options for photogrammetric
Wensley, J. H.; Levitt, K. N.; Green, M. W.; Goldberg, J.; Neumann, P. G.
This volume is concerned with the architecture of a fault tolerant digital computer for an advanced commercial aircraft. All of the computations of the aircraft, including those presently carried out by analogue techniques, are to be carried out in this digital computer. Among the important qualities of the computer are the following: (1) The capacity is to be matched to the aircraft environment. (2) The reliability is to be selectively matched to the criticality and deadline requirements of each of the computations. (3) The system is to be readily expandable. contractible, and (4) The design is to appropriate to post 1975 technology. Three candidate architectures are discussed and assessed in terms of the above qualities. Of the three candidates, a newly conceived architecture, Software Implemented Fault Tolerance (SIFT), provides the best match to the above qualities. In addition SIFT is particularly simple and believable. The other candidates, Bus Checker System (BUCS), also newly conceived in this project, and the Hopkins multiprocessor are potentially more efficient than SIFT in the use of redundancy, but otherwise are not as attractive.
Ratner, R. S.; Shapiro, E. B.; Zeidler, H. M.; Wahlstrom, S. E.; Clark, C. B.; Goldberg, J.
This final report summarizes the work on the design of a fault tolerant digital computer for aircraft. Volume 2 is composed of two parts. Part 1 is concerned with the computational requirements associated with an advanced commercial aircraft. Part 2 reviews the technology that will be available for the implementation of the computer in the 1975-1985 period. With regard to the computation task 26 computations have been categorized according to computational load, memory requirements, criticality, permitted down-time, and the need to save data in order to effect a roll-back. The technology part stresses the impact of large scale integration (LSI) on the realization of logic and memory. Also considered was module interconnection possibilities so as to minimize fault propagation.
Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.
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
Hasell, P. G., Jr.
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.
Jung, Won Jo
The 3-OC is one of the newest digital three line scanners on the market. Unlike other three line scanners using a single optical system, the 3-OC uses three different optical systems moving together. Therefore, this thesis aimed to develop a photogrammetric model for the 3-OC. To precisely relate ground space and the corresponding image space, all the exterior orientation (E.O.) parameters of image lines need to be estimated using a bundle block adjustment. The biggest hurdle in this problem is the large number of exterior orientation parameters because one image strip of the 3-OC usually contains tens of thousands of lines. To reduce the number of unknown E.O. parameters, the E.O. parameters of all the three cameras at an instant imaging time were represented by transformed parameters with respect to the gimbal rotation center. As a result, the unknown E.O. parameters were reduced to one third of original number of parameters. However, the number of E.O. parameters is still too big and estimating these E.O. parameters requires enough observations which are practically very difficult to obtain. To resolve this problem, there have been two kinds of approaches. One is reducing the number of unknown parameters and the other is providing fictitious observations using a stochastic model. As the title of this thesis implies, a stochastic trajectory model was implemented in this thesis. The stochastic relationships between two adjacent lines, as described in previous work, were expanded to the stochastic relationships between two adjacent image observations, so that the E.O. parameters of the lines between two adjacent observations can be recovered by interpolation. By providing enough pass points, it was possible to recover all the E.O. parameters accurately. In addition, the number of unknown E.O. parameters was drastically reduced as well. In this thesis, aerial triangulations of the suggested photogrammetric model were performed with self-calibrating some of the
Gubbels, T.L.; Isacks, B.L. ); Ellis, J.M. )
The central Andean plateau is one of the Earth's most remote and poorly mapped regions. The plateau has an average elevation of 3.7 km, and extends from central Peru to at least 30[degrees]S latitude. The plateau and flanking Subandean foldthrust belt (FTB) reach their greatest width near 20[degrees]S, and at this latitude both the FTB and the basin within the plateau (Altiplano basin) are areas of active hydrocarbon exploration. We have used Landsat TM imagery, stereoscopic SPOT imagery, and digital topography to construct a crustal-scale transect across the central Andes in order to better understand Andean tectonics at this latitude. Beginning at the Peru-Chile trench and continuing to the east, the transect crosses the Coastal Cordillera, Longitudinal Valley, Active Magmatic Arc, Altiplano basin, Eastern Cordillera, Subandean fold-thrust belt, and Subandean foreland basin. A digital elevation model across the entire region illustrates that the magmatic arc, Altiplano basin, and Eastern cordillera all lie within the plateau region. Satellite imagery across the transect illustrates the characteristic geology, structure, and geomorphology of each of the major morphotectonic regions, as well as the nature of their boundaries. The transect has led us to a number of new insights on Andean tectonics at this latitude. Most importantly, it supports a two-stage model of Andean Cenozoic growth in which a widespread Oligocene to mid-Miocene compressional deformation in the Altiplano and Eastern Cordillera is followed in the late Miocene and Pliocene by thrusting localized east of the Eastern Cordillera, forming the Subandean fold-thrust belt.
Parada, N. D. J.; Almeido, R., Jr.
The applicability of LANDSAT MSS imagery for discriminating geobotanical associations observed in zones of cassiterite-rich metasomatic alterations in the granitic body of Serra da Pedra Branca was investigated. Computer compatible tapes of dry and rainy season imagery were analyzed. Image enlargement, corrections, linear contrast stretch, and ratioing of noncorrelated spectral bands were performed using the Image 100 with a grey scale of 256 levels between zero and 255. Only bands 5 and 7 were considered. Band ratioing of noncorrelated channels (5 and 7) of rainy season imagery permits distinction of areas with different vegetation coverage percentage, which corresponds to geobotanial associations in the area studied. The linear contrast stretch of channel 5, especially of the dry season image is very unsatisfactory in this area.
Glass, C. M.
Digital processors for spaceborne imaging radars and application of the technology developed for airborne SAR systems are considered. Transferring algorithms and implementation techniques from airborne to spaceborne SAR processors offers obvious advantages. The following topics are discussed: (1) a quantification of the differences in processing algorithms for airborne and spaceborne SARs; and (2) an overview of three processors for airborne SAR systems.
Lovegreen, J. R.; Prosser, W. J.; Millet, R. A.
A site in the Great Valley subsection of the Valley and Ridge physiographic province in eastern Pennsylvania was studied to evaluate the use of digital and analog image processing for geologic investigations. Ground truth at the site was obtained by a field mapping program, a subsurface exploration investigation and a review of available published and unpublished literature. Remote sensing data were analyzed using standard manual techniques. LANDSAT-1 imagery was analyzed using digital image processing employing the multispectral Image 100 system and using analog color processing employing the VP-8 image analyzer. This study deals primarily with linears identified employing image processing and correlation of these linears with known structural features and with linears identified manual interpretation; and the identification of rock outcrops in areas of extensive vegetative cover employing image processing. The results of this study indicate that image processing can be a cost-effective tool for evaluating geologic and linear features for regional studies encompassing large areas such as for power plant siting. Digital image processing can be an effective tool for identifying rock outcrops in areas of heavy vegetative cover.
Bagnardi, Marco; González, Pablo J.; Hooper, Andrew
Resolving changes in topography through time using accurate high-resolution digital elevation models (DEMs) is key to understanding active volcanic processes. For the first time in a volcanic environment, we utilize very high-resolution tri-stereo optical imagery acquired by the Pleiades-1 satellite constellation and generate a 1 m resolution DEM of Fogo Volcano, Cape Verde -- the most active volcano in the Eastern Atlantic region. Point cloud density is increased by a factor of 6.5 compared to conventional stereo imagery, and the number of 1 m2 pixels with no height measurements is reduced by 43%. We use the DEM to quantify topographic changes associated with the 2014-2015 eruption at Fogo. Height differences between the posteruptive Pleiades-1 DEM and the preeruptive topography from TanDEM-X give a lava flow volume of 45.83 ± 0.02 × 106 m3, emplaced over an area of 4.8 km2 at a mean rate of 6.8 m3 s-1.
Sim, C. K.; Lim, H. S.; Mat Jafri, M. Z.; Abdullah, K.
This study aims to investigate the performance of digital camcorder datasets for land cover classification. The chosen study area was the Universiti Sains Malaysia campus in Penang, Peninsular Malaysia. We encountered difficulties in obtaining cloud-free scenes because Malaysia is an equatorial region. This problem can be overcome by using airborne images. Digital images were taken from a low-altitude light aircraft (Cessna 172Q) at an average altitude of 2.44 km above sea level. The color image was separated into three bands (i.e., red, green, and blue) for multispectral analysis. We compared the performance of traditional methods (i.e., minimum distance and maximum likelihood) and advanced methods (i.e., frequency-based contextual and neural network (NN) techniques). The classified land cover map was geometrically corrected to provide a geocode map. This study presents preliminary findings vis-à-vis the potential application of an ordinary digital camcorder in local urban studies. The NN classifier produced the best result among the tested methods. A high degree of accuracy was achieved by the NN technique.
Will, R. M.; Li, A.; Glenn, N. F.; Benner, S. G.; Spaete, L.; Ilangakoon, N. T.
Soil organic carbon distribution and the factors influencing this distribution are important for understanding carbon stores, vegetation dynamics, and the overall carbon cycle. Linking soil organic carbon (SOC) with aboveground vegetation biomass may provide a method to better understand SOC distribution in semiarid ecosystems. The Reynolds Creek Critical Zone Observatory (RC CZO) in Idaho, USA, is approximately 240 square kilometers and is situated in the semiarid Great Basin of the sagebrush-steppe ecosystem. Full waveform airborne lidar data and Next-Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-ng) collected in 2014 across the RC CZO are used to map vegetation biomass and SOC and then explore the relationships between them. Vegetation biomass is estimated by identifying vegetation species, and quantifying distribution and structure with lidar and integrating the field-measured biomass. Spectral data from AVIRIS-ng are used to differentiate non-photosynthetic vegetation (NPV) and soil, which are commonly confused in semiarid ecosystems. The information from lidar and AVIRIS-ng are then used to predict SOC by partial least squares regression (PLSR). An uncertainty analysis is provided, demonstrating the applicability of these approaches to improving our understanding of the distribution and patterns of SOC across the landscape.
Brook, A.; Ben Dor, E.
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.
Calhoun, Tracy; Melendrez, Dave
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
Shean, David E.; Alexandrov, Oleg; Moratto, Zachary M.; Smith, Benjamin E.; Joughin, Ian R.; Porter, Claire; Morin, Paul
We adapted the automated, open source NASA Ames Stereo Pipeline (ASP) to generate digital elevation models (DEMs) and orthoimages from very-high-resolution (VHR) commercial imagery of the Earth. These modifications include support for rigorous and rational polynomial coefficient (RPC) sensor models, sensor geometry correction, bundle adjustment, point cloud co-registration, and significant improvements to the ASP code base. We outline a processing workflow for ∼0.5 m ground sample distance (GSD) DigitalGlobe WorldView-1 and WorldView-2 along-track stereo image data, with an overview of ASP capabilities, an evaluation of ASP correlator options, benchmark test results, and two case studies of DEM accuracy. Output DEM products are posted at ∼2 m with direct geolocation accuracy of <5.0 m CE90/LE90. An automated iterative closest-point (ICP) co-registration tool reduces absolute vertical and horizontal error to <0.5 m where appropriate ground-control data are available, with observed standard deviation of ∼0.1-0.5 m for overlapping, co-registered DEMs (n = 14, 17). While ASP can be used to process individual stereo pairs on a local workstation, the methods presented here were developed for large-scale batch processing in a high-performance computing environment. We are leveraging these resources to produce dense time series and regional mosaics for the Earth's polar regions.
Blair, J. Bryan; Rabine, David L.; Hofton, Michelle A.
The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter designed and developed at NASA's Goddard Space Flight Center. LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25 m wide footprints. The entire time history of the outgoing and return pulses is digitized, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with decimeter accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 nsec, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the U.S. and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.
Pedrós, Roberto; Martinez-Lozano, Jose A.; Utrillas, Maria P.; Gómez-Amo, José L.; Tena, Fernando
The Digital Airborne Imaging Spectrometer Experiment (DAISEX) was carried out for the European Space Agency (ESA) in order to develop the potential of spaceborne imaging spectroscopy for a range of different scientific applications. DAISEX involved simultaneous data acquisitions using different airborne imaging spectrometers over test sites in southeast Spain (Barrax) and the Upper Rhine valley (Colmar, France, and Hartheim, Germany). This paper presents the results corresponding to the column-integrated aerosol optical properties from ground-based spectroradiometer measurements over the Barrax area during the DAISEX campaign days in the years 1998, 1999, and 2000. The instruments used for spectral irradiance measurements were two Licor 1800 and one Optronic OL-754 spectroradiometers. The analysis of the spectral aerosol optical depth in the visible range shows in all cases the predominance of the coarse-particle mode over the fine-particle mode. The analysis of the back trajectories of the air masses indicates a predominance of marine-type aerosols in the lower atmospheric layers in all cases. Overall, the results obtained show that during the DAISEX there was a combination of maritime aerosols with smaller continental aerosols.
Vaudour, E.; Gilliot, J. M.; Bel, L.; Lefevre, J.; Chehdi, K.
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
Ultra high resolution digital aerial photography has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands...
Darvishzadeh, Roshanak; Atzberger, Clement; Skidmore, Andrew; Schlerf, Martin
Statistical and physical models have seldom been compared in studying grasslands. In this paper, both modeling approaches are investigated for mapping leaf area index (LAI) in a Mediterranean grassland (Majella National Park, Italy) using HyMap airborne hyperspectral images. We compared inversion of the PROSAIL radiative transfer model with narrow band vegetation indices (NDVI-like and SAVI2-like) and partial least squares regression (PLS). To assess the performance of the investigated models, the normalized RMSE (nRMSE) and R2 between in situ measurements of leaf area index and estimated parameter values are reported. The results of the study demonstrate that LAI can be estimated through PROSAIL inversion with accuracies comparable to those of statistical approaches ( R2 = 0.89, nRMSE = 0.22). The accuracy of the radiative transfer model inversion was further increased by using only a spectral subset of the data ( R2 = 0.91, nRMSE = 0.18). For the feature selection wavebands not well simulated by PROSAIL were sequentially discarded until all bands fulfilled the imposed accuracy requirements.
Ambrosia, Vincent G.; Myers, Jeffrey S.; Ekstrand, Robert E.; Fitzgerald, Michael T.
A simple method for enhancing the spatial and spectral resolution of disparate data sets is presented. Two data sets, digitized aerial photography at a nominal spatial resolution 3,7 meters and TMS digital data at 24.6 meters, were coregistered through a bilinear interpolation to solve the problem of blocky pixel groups resulting from rectification expansion. The two data sets were then subjected to intensity-saturation-hue (ISH) transformations in order to 'blend' the high-spatial-resolution (3.7 m) digitized RC-10 photography with the high spectral (12-bands) and lower spatial (24.6 m) resolution TMS digital data. The resultant merged products make it possible to perform large-scale mapping, ease photointerpretation, and can be derived for any of the 12 available TMS spectral bands.
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 ...
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.
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.
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.
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
Parada, N. D. J. (Principal Investigator); Almeidafilho, R.; Payolla, B. L.; Depinho, O. G.; Bettencourt, J. S.
Analysis of digital multispectral MSS-LANDSAT images enhanced through computer techniques and enlarged to a video scale of 1:100.000, show the main geological and structura features of the Pedra Branca granitic massif in Rondonia. These are not observed in aerial photographs or adar images. Field work shows that LANDSAT photogeological units correspond to different facies of granitic rocks in the Pedra Branca massif. Even under the particular characteristics of Amazonia (Tropical Forest, deep weathering, and Quaternary sedimentary covers), an adequate utilization of orbital remote sensing images can be important tools for the orientation of field works.
Park, Isaac W.
This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.
Paradella, W. R. (Principal Investigator)
The use of spectral attributes criteria was investigated, based on measures of statistical distance of separability between thematic classes in MSS digital LANDSAT imagery, in order to select the best subsets of channels in composite colors for the detection and discrimination of lithological units in the lower valley of Curaca River, State of Bahia, Brazil. Three situations were investigated: (1) selection of the three best channels, considering all of the original bands (channels 4, 5, 6, and 7); (2) selection of the three best bands, considering the six MSS band-ratios (channels 4/5, 4/6. 4/7, 5/6, 5/7, and 6/7); and (3) selection of the three best bands in a hybrid approach (the four original bands and the six ratios). A visual analysis was done on color composite images using the selected sets. Results show that the hybrid product (bands 4, 5/7, and 7 with green, blue, and red respectively) and the Normal Color Composite (bands 4, 5, and 7 with blue, green, and red colors respectively) had the best performance.
Berger, Z.; Brovey, R.L.; Merembeck, B.F.; Hopkins, H.R.
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.
Zhang, J.; Hambright, K.; Xiao, X.
Characterizing the temporal and spatial change of algae blooms across lake systems is difficult through conventional sampling methodologies. The application of remote sensing to lake water quality has improved significantly over recent years. However there are seldom reports about in situ photos from GPS digital camera and the new satellite Landsat 8 OLI monitoring algae blooms in freshwater lakes. A pilot study was carried out in Lake Texoma in Oklahoma on April 25th 2013. At each site (12 sites in total), pigments (chlorophyll a and phycocyanin concentration), in situ spectral data and digital photos had been acquired using Hydrolab DS5X sonde (calibrated routinely against laboratory standards), ASD FieldSpec and GPS camera, respectively. The field spectral data sets were transformed to blue, green and red ranges which match the spectral resolution of Landsat 8 OLI images by average spectral reflectance signature to the first four Landsat 8 OLI bands. Comparing with other ratio indices, red/ blue was the best ratio index which can be employed in predicting phycocyanin and chlorophyll a concentration; and pigments (phycocyanin and chlorophyll a) concentration in whole depth should be selected to be detected using remote sensing method in Lake Texoam in the followed analysis. An image based darkest pixel subtraction method was used to process atmospheric correction of Landsat 8 OLI images. After atmospheric correction, the DN values were extracted and used to compute ratio of band4 (Red)/ band1(Blue). Higher correlation coefficients existed in both between resampled spectral reflectance and ratio of red/ blue of photo DN values (R2=0.9425 n=12) and between resampled spectral reflectance and ratio of red/ blue of Landsat 8 OLI images DN values (R2=0.8476 n=12). Finally, we analyzed the correlation between pigments concentrations in whole depth and DN values ratio red/ blue of both Landsat 8 OLI images and digital photos. There were higher correlation coefficients
Park, Isaac W
This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods. PMID:22350421