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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Characteristics of AVIRIS Band Measurements in Desert Agroecosystems in the Area of Blythe, California: Studies of Cotton Spectra - 1

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from Blythe, California, were acquired in June 1997 to study agricultural spectra from different crops and to identify crops in other areas with similar environmental factors and similar spectral properties. The main objectives of this study are: (1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with ground spectra measured by a FieldSpec ASD spectrometer; (2) to explore the use of AVIRIS spectral images for identifying agricultural crops; (3) to study the spectral expression of environmental factors on selected crops; and (4) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. To support our study, on July 18 and 19, 2000, we collected spectra using the FieldSpec spectrometer from selected fields with different crops in the Blythe area of California (longitude 114 deg 33.28 W and latitude 33 deg 25.42 N to longitude 1140 44.53 W and latitude 33 deg 39.77 N). These crops were cotton in different stages of growth, varieties of grass pure or mixed, Sudan grass, Bermuda grass, Teff grass, and alfalfa. Some of the fields were treated with different types of irrigation (i.e., wet to dry conditions). Additional parameters were studied such as the soil water content (WC), pH, and organic matter (OM). The results of this study showed that for crops known to be similar, there is a significant correlation between the spectra that were collected by AVIRIS in 1997 and spectra measured by the FieldSpec (registered) spectrometer in 2000. This correlation allowed development of a spectral library to be used in ENVI-IDL analysis software. This library was used successfully to identify different crops. Furthermore, using IDL algorithms of Spectral Angle Mapper classification (SAM), spectral feature fitting (SFF) and spectral binary encoding (SPE) showed that there is excellent agreement between the predicted and the actual crop type (i.e., the correlation is between 85-90% match). Further use of the AVIRIS images can be of a value to crop identification or crop yield for commercial use.

Hanna, Safwat H. Shakir↗
NASA NTRS1993

On evaluating the accuracy of SAR sea-ice classification using multifrequency polarimetric AIRSAR data

We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.

Drinkwater, Mark R.↗
NASA NTRS1983

Urban land use classification using synthetic aperture radar

Several approaches to the use of radar imagery for land use classification of urban and near-urban areas are presented. The use of L band, horizontal transmit, and horizontal receive data is emphasized because of their general availability. For urban area studies using imaging radar, the effects of processing in an off-zero Doppler or squint mode, of the presence of large diffuse scatters, and of the possibility of height measurements are discussed. Data from the Los Angeles area are illustratively used.

Bryan, M. L.↗
NASA NTRS2001

Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

Dalton, J. Brad↗
NASA NTRS2011

Biochip microsystem for bioinformatics recognition and analysis

A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.

Lue, Jaw-Chyng↗
NASA NTRS2019

Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery

Knowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.

Yao Li↗
NASA NTRS2019

A Robust Vision-Based Algorithm for Detecting and Classifying Small Orbital Debris Using On-Board Optical Cameras

This study develops a vision-based detection and classification algorithm to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. The algorithm operates in near real time and is robust under difficult tasks in moving objects classification such as multiple moving objects, objects with various movement trajectories and speeds, very small or faint objects, and substantial background motion. The performance of the algorithm is optimized and validated using space image data available through simulated environments generated using NASA Marshall Space Flight Centers Dynamic Star Field Simulator of on-board optical sensors and cameras.

Zamani, Yasin↗
NASA NTRS2023

Maldives Climate II: Evaluating the Potential Impacts of Sea Level Rise on Human Development and Coastal Infrastructure

The Republic of the Maldives is a low-lying island nation in the Indian Ocean which has experienced rapid urbanization, landcover changes, and sea level rise over recent years. The growth of tourism, coastal erosion, and urbanization have all driven land reclamation efforts across many islands. As in-situ landcover change monitoring has proven difficult across the vast archipelago, the NASA DEVELOP team collaborated with the Maldives Ministry of Environment, Climate Change, and Technology; USAID; and the U.S. Department of State, to utilize Earth observations to predict sea level rise impacts on coastal infrastructure. The team used a supervised classification algorithm within Google Earth Engine to create land use maps and time series analyses of nine islands and atolls using imagery from Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Sentinel-2 Multispectral Instrument, and PlanetScope, covering a combined period of 2000 through 2023. Additionally, the team projected coastal inundation with a modified deterministic Bathtub model utilizing elevation data from CoastalDEM and 2050-2100 Shared Socioeconomic Pathway scenarios identified in the NASA Sea Level Rise Projection Tool. The team found that islands undergoing urban growth experienced a 23% decrease in vegetation between 2014 and 2022. Furthermore, the model predicted that 51–57% of the study area’s-built environment has a chance of inundation by 2100 under the low and high sea level scenarios. These analyses demonstrate how remote sensing can be used to both track land use changes over time and project how coastlines will be affected by sea level rise.

remote sensing↗
NASA NTRS2004

Classification of Particle Shapes from Lidar Depolarization Ratios in Convective Ice Clouds Compared to in situ Observations During CRYSTAL-FACE

This manuscript describes a method to class@ cirrus cloud ice particle shape using lidar depolarization measurements as a basis for segregating different particle shape regimes. Measurements from the ER-2 Cloud Physics Lidar (CPL) system during CRYSTAL-FACE provide the basis for this work. While the CPL onboard the ER-2 aircraft was providing remote sensing measurements of cirrus clouds, the Cloud Particle Imager (CPI) onboard the WB-57 aircraft was flying inside those same clouds to sample particle sizes. The results of classifying particle shapes using the CPL data are compared to the in situ measurements made using the CPI , and there is found to be good agreement between the particle shape inferred from the CPL data and that actually measured by the CPI. If proven practical, application of this technique to spaceborne observations could lead to large-scale classification of cirrus cloud particle shapes.

Noel, Vincent↗
NASA NTRS1982

Antarctic sea ice concentrations inferred from Nimbus 5 ESMR and Landsat imagery

Landsat Multispectral Scanner near-infrared band images (MSS-7) are used to calculate Antarctic ice concentration values and these results are quantitatively compared to those derived from Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperature data. The set of images includes regions near the ice edge and near the continental boundary during late winter or spring. The percentage of ice cover is derived from the microwave data, using an algorithm that incorporates the brightness temperature emissivity and interpolated climatological physical temperatures and that is not dependent on spatial resolution. Cloud-free Landsat images are used to provide an alternative determination of large-scale ice concentrations, but this method is limited in its ability to resolve individual ice flows, especially near the ice edge. A proportional classification procedure is applied to Landsat data based on observed reflection and the results are correlated with similarly-derived ESMR ice concentration values. The corresponding ice concentration values are found to agree to + or - 15%, with the largest uncertainties occurring in regions of low ice concentration.

Comiso, J. C.↗
NASA NTRS1989

Passive millimeter-wave imaging - A tool for remote sensing

This paper describes a program of airborne radiometric imaging at 90 GHz and 140 GHz. Using high sensitivity (below 1 K) and high angular resolution (0.5-1.0 degree), high quality images have been made. The following measurements are discussed: cloud and fog penetration at 90 GHz, discrimination between agricultural and urban areas, discrimination between different vegetation types, detection of vehicles on roads, detection and classification of airports and airplanes, ship detection and quantitative oil spill sensing. The application of information enhancement techniques with automatic and real time application aspects is also described, and results of applied techniques for contrast and contour enhancement are shown.

Suess, Helmut↗
NASA NTRS2021

Maya Forest Water Resources II: Mapping Inundation Below the Forest Canopy in the Maya Tri-National Forest

To monitor seasonal flooding within the tri-National Maya Forest the team completed the methodology started by the Summer 2021 term to analyze changes in inundation dynamic throughout 2017. The team analyzed inundation dynamics in Google Earth Engine (GEE) using Earth observation products from the Landsat 8 Operational Land Imager (OLI), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 2, and International Space Station (ISS) Global Ecosystem Dynamics Investigation LiDAR (GEDI). The team improved the landcover classification using the Random Forest algorithm in GEE by adding canopy height data derived from GEDI, elevation and slope data from Copernicus, and additional multi-spectral band ratios from Landsat 8. The pixel-based land cover classification produced an overall accuracy of 88%. Experiments measuring inundation extent using L-band SAR included comparing results with a priori knowledge, topography datasets, and auxiliary datasets. We iteratively tested and found threshold values for identifying forested inundation using the ratio for HH divided by HV. The resulting methodology and products helped end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) manage land and water resources and protect communities.

Stephanie Jiménez↗
NASA NTRS1993

Classification of Martian deltas

Water-borne sediments in streams are deposited, upon eventual cessation of flow, either as deltas or as alluvial fans or plains. Deltas and alluvial fans share a common characteristic; both may be described as deposition Al plains at the mouth of a river or stream. A delta is formed where a stream or river deposits its sedimentary load into a standing body of water such as an ocean or lake. An alluvial fan is produced where a stream loses capacity by a greatly decreased gradient. A delta has subaerial and subaqueous components, but an alluvial fan is entirely subaerial. In terrestrial conditions, deltas and alluvial fans are reasonably distinct landforms. The juxtaposition of concomitant features composition and internal structure are sufficiently explicit as to avoid any confusion regarding their proper identification on Mars, the recognition of deltas and their distinction from alluvial fans is made difficult by low resolution imaging. Further, although it may be demonstrated that standing bodies of water existed on the surface of Mars, many of these bodies may have existed for extremely short periods of time (a few days to months); hence, distinctive shoreline features were not developed. Thus, in an attempt to derive a Martian classification of deltas, the inclusion of wholly subaerial deposits may be unavoidable. A simple, broad, morphological classification of Martian deltas, primarily on planimetric shape, includes digitate deltas, fan-shaped deltas, and re-entrant deltas. A fourth, somewhat problematical class includes featureless plains at the end of many valley systems.

Dehon, R. A.↗
NASA NTRS1973

Remote sensing in Iowa agriculture

The author has identified the following significant results. After receiving the ERTS-1 imagery, three methods of analysis of this imagery have been used. Observations noted are as follows: (1) Use of color additive and density slicing-color coding appears potentially useful for crop identification and automatic classification in Iowa for this time frame. The influence of soil association differences on the spectral response of the imagery will probably have to be taken into account for any automatic crop identification procedure to be successful. Small fields and the diversity of Iowa's cropping patterns also will cause significant problems for crop classifications. (2) The presence of high clouds and associated hazy atmospheric conditions markedly reduces the resolution of the ERTS-1 imagery. (3) Utilization of filtered 2 1/2 inch projectors is quite difficult because of multiple image registration problems. This procedure does, however, allow the interpreter to achieve image enlargement and the enhancement of response differences using two image projections.

Mahlstede, J. P.↗
NASA NTRS1987

Determine precipitation rates from visible and infrared satellite images of clouds by pattern recognition technique

A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.

Weinman, James A.↗
NASA NTRS1993

Satellite inventory of Minnesota forest resources

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

Bauer, Marvin E.↗
NASA NTRS1999

Constrained Vapor Bubble

The nonisothermal Constrained Vapor Bubble, CVB, is being studied to enhance the understanding of passive systems controlled by interfacial phenomena. The study is multifaceted: 1) it is a basic scientific study in interfacial phenomena, fluid physics and thermodynamics; 2) it is a basic study in thermal transport; and 3) it is a study of a heat exchanger. The research is synergistic in that CVB research requires a microgravity environment and the space program needs thermal control systems like the CVB. Ground based studies are being done as a precursor to flight experiment. The results demonstrate that experimental techniques for the direct measurement of the fundamental operating parameters (temperature, pressure, and interfacial curvature fields) have been developed. Fluid flow and change-of-phase heat transfer are a function of the temperature field and the vapor bubble shape, which can be measured using an Image Analyzing Interferometer. The CVB for a microgravity environment, has various thin film regions that are of both basic and applied interest. Generically, a CVB is formed by underfilling an evacuated enclosure with a liquid. Classification depends on shape and Bond number. The specific CVB discussed herein was formed in a fused silica cell with inside dimensions of 3x3x40 mm and, therefore, can be viewed as a large version of a micro heat pipe. Since the dimensions are relatively large for a passive system, most of the liquid flow occurs under a small capillary pressure difference. Therefore, we can classify the discussed system as a low capillary pressure system. The studies discussed herein were done in a 1-g environment (Bond Number = 3.6) to obtain experience to design a microgravity experiment for a future NASA flight where low capillary pressure systems should prove more useful. The flight experiment is tentatively scheduled for the year 2000. The SCR was passed on September 16, 1997. The RDR is tentatively scheduled for October, 1998.

Huang, J.↗
NASA NTRS2009

The Morphology of Passively Evolving Galaxies at Z-2 from HST/WFC3 in the Hubble Ultra Deep Field

We discuss near-IR images of six passive galaxies (SSFR< 10(exp -2)/Gyr) at redshift 1.3 < z < 2.4 with stellar mass M approx 10(exp 11) solar mass, selected from the Great Observatories Origins Deep Survey (GOODS), obtained with WFC3/IR and the Hubble Space Telescope (HST). These WFC3 images provide the deepest and highest angular resolution view of the optical rest-frame morphology of such systems to date. We find that the light profile of these; galaxies is generally regular and well described by a Sersic model with index typical of today's spheroids. We confirm the existence of compact and massive early-type galaxies at z approx. 2: four out of six galaxies have T(sub e) approx. 1 kpc or less. The WFC3 images achieve limiting surface brightness mu approx. 26.5 mag/sq arcsec in the F160W bandpass; yet there is no evidence of a faint halo in the five compact galaxies of our sample, nor is a halo observed in their stacked image. We also find very weak "morphological k-correction" in the galaxies between the rest-frame UV (from the ACS z band), and the rest-frame optical (WFC3 H band): the visual classification, Sersic indices and physical sizes of these galaxies are independent or only mildly dependent on the wavelength, within the errors.

Cassata, P.↗