Search NASA⌕ Search

SEARCH · Search NASA

Results for “Landsat imagery”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Area estimation of forestlands in southwestern Michigan from LANDSAT imagery

The accuracy of mapping and estimating the area of forestlands in southwestern Michigan from winter and fall LANDSAT images was evaluated. All omission and commission errors in the LANDSAT forest maps were identified and mapped through comparison with an existing detailed forest cover type map. Accuracies ranged from 74.0% to 98.5% and were higher for the winter imagery. Most errors (85%) occurred along the perimeter of forestlands and were less than 4 hectares (10 acres) and size. Other factors affecting interpretation are reported as well as time and image availability considerations.

Karteris, M. A.↗
NASA NTRS1976

A study of mesoscale surface heat and moisture budgets and their relationship to airmass cumulus clouds observed in LANDSAT imagery

The author has identified the following significant results. The three budget analyses show a weak correspondence between LANDSAT cloud patterns and elements of the energy and moisture budgets. It was found that a little more energy is contributed by the ground to heat the air in cloudy areas. Improvements are warranted in the budget models and data coverage necessary to describe the environment. These models can serve as a basis for more complex models of surface air heat and moisture exchanges which would utilize readily available meteorological data on a mesoscale.

Merritt, E. S.↗
NASA NTRS1984

Utilization of digital LANDSAT imagery for the study of granitoid bodies in Rondonia: Case example of the Pedra Branca massif

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.

Parada, N. D. J.↗
NASA NTRS1981

Drift and dispersion studies of ocean-dumped waste using Landsat imagery and current drogues

The drift and dispersion of industrial acid wastes dumped 64 km off the Delaware coast were investigated using 16 Landsat images. Waste plume drift velocities and spread rates were obtained, and principal component analysis was performed to discriminate the acid waste from other pollutants. Waste plumes averaged drifting rates from 0.59 km/hr to 3.39 km/hr into the southwest quadrant, and remained above the thermocline, which formed at depths ranging from 13 m to 24 m. Rapid waste movement toward shore occurred primarily during storms, although plumes were rapidly dispersed and diluted at spread rates in excess of 4 cm/sec. Landsat data analysis also indicates plume width increase of about 1.5 cm/sec during calm sea conditions, which is also in agreement with Falk's (1974) estimates of plume dilution.

Klemas, V.↗
NASA NTRS1980

HCMM and LANDSAT imagery for geological mapping in northwest Queensland

The author has identified the following significant results. Photographic prints made from negatives of day-visible and day-IR cover of selected areas were compared with enhanced color composites generated from LANDSAT computer compatible tapes and films. For geological mapping purposes, HCMM imagery is of limited value. While large scale features like the Mikadoodi anticlinorium, contrasting lithological units, and major structures may be distinguished on day-visible and day-IR cover, the spectral bands are too broad and the resolution too coarse even for regional mapping purposes. The imagery appears to be most useful for drainage studies. Where drainage is seasonal, sequential imagery permits monitoring of broad scale water movement while the day-IR imagery yields valuable information on former channels. In plains areas subject to periodic change of stream courses, comparable IR cover at a larger scale would offer considerable potential for reconstruction of former drainage patterns essential for the correct interpretation of geochemical data relative to mineral exploration.

Cole, M. M.↗
NASA NTRS1979

Evaluating the reforested area for the municipality of Buri by automatic analysis of LANDSAT imagery

The author has identified the following significant results. The class of reforestation (Pinus, Eucalyptus, Araucaria) was defined using iterative image analysis (1-100) and LANDSAT MSS data. Estimates of class area by 1-100 were compared with data supplied by the forestry institute in Sao Paulo. LANDSAT channels 4 and 5 served to differentiate the Pinus, Eucalyptus, and Araucaria from the other trees. Channels 6 and 7 gave best results for differentiating between the classes. A good representative spectral response was obtained for Auraucaria on these two channels. The small relative differences obtained were +4.24% for Araucaria, -7.51% for Pinus, and -32.07% for Eucalyptus.

Dejesusparada, N.↗
NASA NTRS1977

Application of LANDSAT imagery for snow mapping in Norway

The author has identified the following significant results. It was shown that if the snow cover extent was determined from all four LANDSAT bands, there were significant differences in results. The MSS 4 gave the largest snow cover, but only slightly more than MSS 5, whereas MSS 6 and 7 gave the smallest snow area. A study was made to show that there was a relationship between the last date of snow fall and the area covered with snow, as determined from different bands. Imagery obtained shortly after a snow fall showed no significant difference in the snow-covered area when the four bans were compared, whereas, pronounced differences in the snow-covered area were found in images taken after a long period without precipitation.

Odegaard, H.↗
NASA NTRS1976

Comparisons of cloud cover evaluated from LANDSAT imagery and meteorological stations across the British Isles

The author has identified the following significant results. This stage of the study has confirmed the initial supposition that LANDSAT data could be analyzed to provide useful data on cloud amount, and that useful light would be thrown thereby on the performance of the ground observer of this aspect of the state of the sky. This study, in comparison with previous studies of a similar nature using data from meteorological satellites, has benefited greatly from the much higher resolution data provided by LANDSAT. This has permitted consideration of not only the overall performance of the surface observer in estimating total cloud cover, but also his performance under different sky conditions.

Barrett, E. C.↗
NASA NTRS2016

Snow Process Estimation Over the Extratropical Andes Using a Data Assimilation Framework Integrating MERRA Data and Landsat Imagery

A data assimilation framework was implemented with the objective of obtaining high resolution retrospective snow water equivalent (SWE) estimates over several Andean study basins. The framework integrates Landsat fractional snow covered area (fSCA) images, a land surface and snow depletion model, and the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis as a forcing data set. The outputs are SWE and fSCA fields (1985-2015) at a resolution of 90 m that are consistent with the observed depletion record. Verification using in-situ snow surveys showed significant improvements in the accuracy of the SWE estimates relative to forward model estimates, with increases in correlation (0.49-0.87) and reductions in root mean square error (0.316 m to 0.129 m) and mean error (-0.221 m to 0.009 m). A sensitivity analysis showed that the framework is robust to variations in physiography, fSCA data availability and a priori precipitation biases. Results from the application to the headwater basin of the Aconcagua River showed how the forward model versus the fSCA-conditioned estimate resulted in different quantifications of the relationship between runoff and SWE, and different correlation patterns between pixel-wise SWE and ENSO. The illustrative results confirm the influence that ENSO has on snow accumulation for Andean basins draining into the Pacific, with ENSO explaining approximately 25% of the variability in near-peak (1 September) SWE values. Our results show how the assimilation of fSCA data results in a significant improvement upon MERRA-forced modeled SWE estimates, further increasing the utility of the MERRA data for high-resolution snow modeling applications.

SWE↗
DOE OSTI2025

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland

The author has identified the following significant results. Based on tests, it is obvious that practically all major LANDSAT winter linears found are geologically significant features. Most of them are chains of bogs, lakes, rivers, and cultivated areas covered by ice and/or snow, i.e., unforested linear topographic lows. They need no explanation other than that they are extensive fracture zones of the basement.

Tuominen, H. V.↗
NASA NTRS1983

Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

Parada, N. D. J.↗
NASA NTRS1977

Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland

The author has identified the following significant results. Several regional lineaments appear to correlate with the distribution of ore deposits and showings. Combined study of LANDSAT summer and winter mosaics and color composites of geological, geomorphological, and geophysical maps makes the correlation more perceptible. The revealed pattern of significant lineaments in northern Finland is fairly regular. The most significant lineaments seen in LANDSAT mosaics are not detectable in single images.

Tuominen, H. V.↗
NASA NTRS1978

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Williams, D. L.↗
NASA NTRS1981

Statewide lake classification utilizing LANDSAT imagery for the state of Wisconsin

A cooperative program between the Wisconsin Department of Natural Resources and the University of Wisconsin-Madison resulted in the assessment of the trophic condition of approximately 3,000 significant inland lakes in Wisconsin. The feasibility of using both photographic and digital representations of LANDSAT multispectral scanner data for lake classification was investigated. The result was the development of a nearly automated system which, with minimal human interaction, locates and extracts the lake data, then corrects the data for atmospheric effects, and finally classifies all the significant lakes in the state as to trophic condition.

Martin, R. H.↗
NASA NTRS1991

Protecting rain forests and forager's rights using LANDSAT imagery

Creating rain forest reserves is vital given the global decline in biodiversity. Yet, the plants and animals that will be protected from untrammeled commercial exploitation within such reserves constitute essential resources for indigenous foragers and farmers. Balancing the needs of local subsistence level populations with the goals of national and international conservation agencies requires a thorough understanding of the mutual impacts that arise from the interaction of park and people. In the Ituri forest of Zaire, LANDSAT TM image analysis and GPS ground truth data were used to locate human settlements so that boundaries of the proposed Okapi Reserve could be chosen to minimize its impact on the subsistence practices of the local foragers and farmers. Using satellite imagery in conjunction with cultural information should help to ensure traditional resource exploitation rights of indigenous peoples whilst simultaneously protecting the largest contiguous area of undisturbed forest.

Wilkie, David S.↗
NASA NTRS1978

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

Tom, C.↗