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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Wildland inventory and resource modeling for Douglas and Carson City Counties, Nevada, using LANDSAT and digital terrain data

The potential of using LANDSAT satellite imagery to map and inventory pinyon-juniper desert forest types in Douglas and Carson City Counties, Nevada was demonstrated. Specific map and statistical products produced include land cover, mechanical operations capability, big game winter range habitat, fire hazard, and forest harvestability. The Nevada Division of Forestry determined that LANDSAT can produce a reliable and low-cost resource data. Added benefits become apparent when the data are linked to a geographical information system (GIS) containing existing ownership, planning, elevation, slope, and aspect information.

Brass, J. A.↗
NASA NTRS2018

Landsat 9 TIRS-2 Performance Results Based on Subsystem-Level Testing

Landsat 9 is the next in the series of Landsat satellites and has a complement of two pushbroom imagers: Operational Land Imager-2 (OLI-2) that samples the solar reflective spectrum with nine channels and Thermal Infrared Sensor-2 (TIRS-2) samples the thermal infrared spectrum with two channels. The first builds of these sensors, OLI and TIRS, were launched on Landsat 8 in 2013 and Landsat 9 is expected to launch in December 2020. TIRS-2 is designed and built to continue the Landsat data record and satisfy the needs of the remote sensing community. There are two sets of requirements considered for planning the component, subsystem and instrument level tests for TIRS-2: performance requirements and Special Calibration Test Requirements (SCTR). The performance requirements specify key spectral, spatial, radiometric, and operational parameters of TIRS-2 while the SCTRs specify parameters of how the instrument is tested. Several requirements can only be verified at the instrument level, but many performance metrics can be assessed earlier in prelaunch testing at the subsystem level. A test program called TIRS Imaging Performance and Cryoshell Evaluation (TIPCE) was developed to characterize TIRS-2 spectral, spatial, and scattered-light rejection performance at the telescope and detector subsystem level. There were three thermal vacuum campaigns in TIPCE that occurred from November 2017 to March 2018. This work shows results of TIPCE data analysis which provide confidence that key requirements will be met at instrument level with a few minor waivers. A full complement of performance testing will be done at the TIRS-2 instrument level for final verification in late 2018 through Spring 2019.

scatter↗
NASA NTRS1977

Computer-aided classification for remote sensing in agriculture and forestry in Northern Italy

A set of results concerning the processing and analysis of data from LANDSAT satellite and airborne scanner is presented. The possibility of performing inventories of irrigated crops-rice, planted groves-poplars, and natural forests in the mountians-beeches and chestnuts, is investigated in the Po valley and in an alphine site of Northern Italy. Accuracies around 95% or better, 70% and 60% respectively are achieved by using LANDSAT data and supervised classification. Discrimination of rice varieties is proved with 8 channels data from airborne scanner, processed after correction of the atmospheric effect due to the scanning angle, with and without linear feature selection of the data. The accuracies achieved range from 65% to more than 80%. The best results are obtained with the maximum likelihood classifier for normal parameters but rather close results are derived by using a modified version of the weighted euclidian distance between points, with consequent decrease in computing time around a factor 3.

Dejace, J.↗
NASA NTRS1999

First Look at Landsat-7 Mission Performance: Technical and Operational Results to Date

A primary goal of the current Landsat-7 mission, launched on April 15, 1999, is to acquire and refresh on a seasonal basis, calibrated ata sets of multispectral digital imagery of the landmass of the Earth The Enhanced Thematic Mapper Plus (ETM+) imager flown on Landsat-7 provides ground spatial resolutions in the panchromatic, reflective and emissive bands of 15, 30 and 60 meters, respectively, for a nominal scene 183 km wide by 170 km long. This mission not only builds on the invaluable 27-year continuous archive of thematic images of the Earth provided by previous Landsat satellites, it also inaugurates a new era of robust data acquisition with an emphasis on global change science. The newly developed Long Term Acquisition Plan (LTAP) is being used to optimize the systematic collection of data from all parts of the globe, populating the U.S.-held archive at the USGS EROS Data Center (EDC) with over 90,000 Landsat scene per year . An additional 73,000 Images are expected to be acquired each year by several international ground stations, for a total downlink of Landsat7 data in excess of 100 terabytes per year. Nearly 20,000 scan of Landsat-7 ETM+ data have already been acquired in the first 100 days of the mission. Early results derived from assessments of the ETM+ instrument, the spacecraft, and the ground processing systems indicate that the image quality is outstanding, clearly the best ever provided by any Landsat mission. Sensor radiometric background stability after the first 100 days in orbit is approximately 0.1 percent. Stability of the Full Aperture Solar Calibrator is approximately 0.3 percent, and mid-scale per pixel noise is approximately 0.6 percent. A ground processing system has been implemented at EDC which is capable of capturing, processing and archiving 250 Landsat scenes 9 per day, and delivering 100 scene products to seems each day. The cost of a systematically-processed Level 1 product has been dropped dramatically to $600, end there is no longer any copyright protection an the data. The net result is that the use of Landsat ETM+ data is expected to grow dramatically, and this growth is expected to benefit all facets of the land remote sensing community.

Williams, Darrel L.↗
NASA NTRS1977

Multispectral remote observations of hydrologic features on the North Slope of Alaska

Visible and near-infrared Landsat satellite imagery and active and passive aircraft microwave data are used to analyze some hydrologic features in Arctic Alaska. Lake studies using passive microwave imagery reveal that an increase in the microwave brightness temperature correlates with an increase in ice thickness. Synthetic Aperture Radar (SAR) imagery allows determination of lakes that are frozen to the bottom under certain conditions. Landsat imagery of lakes can be used to study summer ice cover dissipation, an indicator of lake depth. River channel morphometry and morphology studies are accomplished using SAR data with good (25 m) resolution. Landsat imagery is shown to be useful for analyzing interannual variations in the extent of river icings (aufeis). Snow depth variations are shown to be potentially discernable using passive microwave data. Finally, the present and potential applications of these remote sensing studies are discussed; these data are useful for locating potable water sources, planning construction in good locations, and for analyzing interannual climate fluctuations.

Hall, D. K.↗
NASA NTRS2018

Ecosystem Carbon Emissions from 2015 Forest Fires in Interior Alaska

In the summer of 2015, hundreds of wildfires burned across the state of Alaska, and consumed more than 1.6 million ha of boreal forest and wetlands in the Yukon-Koyukuk region. Mapping of 113 large wildfires using Landsat satellite images from before and after 2015 indicated that nearly 60% of this area was burned at moderate-to-high severity levels. Field measurements near the town of Tanana on the Yukon River were carried out in July of 2017 in both unburned and 2015 burned forested areas (nearly adjacent to one-another) to visually verify locations of different Landsat burn severity classes (low, moderate, or high). Results: Field measurements indicated that the loss of surface organic layers in boreal ecosystem fires is a major factor determining post-fire soil temperature changes, depth of thawing, and carbon losses from the mineral topsoil layer. Measurements in forest sites showed that soil temperature profiles to 30 cm depth at burned forest sites increased by an average of 8o - 10o C compared to unburned forest sites. Sampling and laboratory analysis indicated a 65% reduction in soil carbon content and a 58% reduction in soil nitrogen content in severely burned sample sites compared to soil mineral samples from nearby unburned spruce forests. Conclusions: Combined with nearly unprecedented forest areas severely burned in the Interior region of Alaska in 2015, total ecosystem fire emission of carbon to the atmosphere exceeded most previous estimates for the state.

Ecosystem↗
NASA NTRS2021

Remote Sensing of Wetland Area Loss and Gain in the Western Barataria Basin (Louisiana, U.S.A.) since Hurricane Katrina

The goal of this study was to analyze the recent record of Landsat satellite imagery to better understand spatial patterns and infer processes of change in marshland vegetation cover in coastal Louisiana wetlands. The study area covered subbasins of the western Barataria Basin near the Bayou Lafourche in southeastern Louisiana. Bayou Lafourche's estuaries have seen some of the highest rates of wetland conversion to open water of any coastal zone in the United States. The Landsat Normalized Difference Water Index (NDWI) was used in this study to map changes in land/water fractions at a 30-m pixel resolution between October 2005 (post-Katrina) and October 2018. Validation boat surveys were conducted in July 2020 to visually verify the presence or absence of (>1 m) emergent vegetation growing on marshlands across several subbasins, with photographs collected at more than 150 target locations along the route. Based on NDWI change, a total of 42.3 km2 was estimated to fall into the category of wetland loss since 2005. The leading subbasins for these recent wetland-to-water conversions made up most of the southwestern portion of the study area just north of Port Fourchon. The consistently low distance detected between the majority of wetland loss cells and locations of historical oil and gas wells implies that effects of well drilling and extraction have had a continuing negative impact on marshland degradation in the basin. Conversely, a total of 34 km2 was estimated to fall into the category of recent wetland gain, with much of the new vegetation growth verified to have been restored within several shoreline protection and dredging projects. It was concluded that the positive contributions made by such shoreline enhancement and marshland nourishment projects in Lafourche Parish to offset wetland losses over the past 15 years should not be underestimated.

Remote Sensing↗
NASA NTRS2018

Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

Time Series↗
NASA NTRS1993

Spectral variations in a collection of AVIRIS imagery

The advent of AVIRIS presents to the scientific community the first opportunity to examine high quality hyperspectral data over areas of interest, while recent developments promise even better data in the future. With these data we may address questions such as: (1) Is such high spectral resolution (0.01 micron) necessary?; and (2) How can we take advantage of the AVIRIS experience in specifying an improved future Landsat satellite? In this paper we describe the use of relatively broadband measurements (20-50 nm) to represent spectral variability. The problem of generality is addressed through consideration of 28 AVIRIS scenes, although analysis of additional areas is clearly desirable. Section 2 defines the expansion of spectra in terms of basis functions, section 3 describes the application to AVIRIS data, and the conclusion, section 4, relates these preliminary results to possible future remote sensing instrumentation such as the planned Landsat 8.

Price, John C.↗
NASA NTRS1982

A legislator's guide to LANDSAT

The LANDSAT satellite is an effective tool in meeting the natural resources data requirements of state and federal legislation. The availability of data from the satellite is beginning to have an impact on state legislature activities. An overview of the history, operation, and data analysis techniques, is presented as well as a discussion of the advantages and limitations of this method of remote sensing. Applications are discussed in the areas of (1) land resource planning and management; (2) coastal zone management; (3) agriculture; (4) forestry; (5) routing and siting; (6) environmental monitoring; and (7) geological exploration. National and state sources from which information about LANDSAT technology is available are listed.

Source record↗
NASA NTRSDate not supplied

Limitations to Biomass Estimation for FAV Using NDVI Analysis of Satellite Acquisitions

The distribution and standing biomass (mass per unit area) of Floating Aquatic Vegetation (FAV)provide assessment metrics for productivity of vegetative communities. Remote sensing acquisition data has been used to estimate standing biomass in various ecosystems using vegetation indices, particularly the normalized difference vegetation index (NDVI), comparing the relative strength of radiation absorbance and reflectance of vegetation in specific wavebands. Obstacles to estimating vegetation biomass using NDVI reported are related to diversity of the vegetation community and high-density saturation. We evaluate the potential for using NDVI derived estimates for FAV biomass in the California Delta by focusing on patches of predominantly single species and compare biomass estimates for specific patches with measurement of total biomass and partitioning within the vegetation canopy. Using Landsat satellite acquisitions, biomass estimates are made for individual pixels and vegetation samples were collected from those same pixels. Focus on patches of predominantly single FAV species resulted in successful estimation of standing biomass beyond that previously reported in other ecosystems. A saturation response for the estimations was observed, however, with a much higher threshold high than previously reported for diverse population aquatic ecosystems. We discuss the likely cause for the saturation phenomenon and potential improvement utilizing altered spectral indices possible with higher spectral resolution from satellites carrying higher waveband multispectral and hyperspectral instruments.

Biomass↗
NASA NTRS2010

Florida Agriculture - Utilizing TRMM to Analyze Sea Breeze Thunderstorm Patterns During El Nino Southern Oscillations and Their Effects Upon Available Fresh Water for South Florida Agricultural Planning and Management

This project utilizes Tropical Rainfall Measuring Mission (TRMM) and Landsat satellite data to assess the impact of sea breeze precipitation upon areas of agricultural land use in southern Florida. Water is a critical resource to agriculture, and the availability of water for agricultural use in Florida continues to remain a key issue. Recent projections of statewide water use by 2020 estimate that 9.3 billion gallons of water per day will be demanded, and agriculture represents 47% of this demand (Bronson 2003). Farmers have fewer options for water supplies than public users and are often limited to using available supplies from surface and ground water sources which depend in part upon variable weather patterns. Sea breeze thunderstorms are responsible for much of the rainfall delivered to Florida during the wet season (May-October) and have been recognized as an important overall contributor of rainfall in southern Florida (Almeida 2003). TRMM satellite data was used to analyze how sea breeze-induced thunderstorms during El Nino and La Nina affected interannual patterns of precipitation in southern Florida from 1998-2009. TRMM's Precipitation Radar and Microwave Imager provide data to quantify water vapor in the atmosphere, precipitation rates and intensity, and the distribution of precipitation. Rainfall accumulation data derived from TRMM and other microwave sensors were used to analyze the temporal and spatial variations of rainfall during each phase of the El Nino Southern Oscillation (ENSO). Through the use of TRMM and Landsat, slight variations were observed, but it was determined that neither sea breeze nor total rainfall patterns in South Florida were strongly affected by ENSO during the study period. However, more research is needed to characterize the influence of ENSO on summer weather patterns in South Florida. This research will provide the basis for continued observations and study with the Global Precipitation Measurement Mission.

Billiot, Amanda↗
NASA NTRS2011

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗
NASA NTRS1982

A Temporal Approach to Monitor Surface Mine Reclamation Progress via LANDSAT

Using LANDSAT satellite imagery, the mine reclamation process can be studied on a temporal and continuing basis. Not only can the progress of reclamation be readily monitored, but also a breakdown in the mining reclamation process can be detected. In viewing reclamation, it is important to monitor the mined site well past initial revegation stages. With present mining law and bonding procedures, fast revegetational growth is encouraged, often leading to poor soil fertilizing and inappropriate stabilizing species. As a result, the initial reclamation may exhibit good qualities for one or two years but then may experience vegetational deterioration after the state has relinquished the mining company from it's responsibility. It is this small-scale breakdown in the reclamation process that was detected using an unsupervised classification technique with eight-year temporal LANDSAT imagery coverage.

Davis, A. L.↗
NASA NTRS1976

Satellite data for surface-mine inventory

To determine the feasibility of satellite data for surface-mine inventory, particularly as it applies to coal, a case study was conducted in Maryland. A band-ratio method was developed to measure disturbed surface areas, and it proved to be extendible both temporally and geographically. This method was used to measure area changes in the region over three time periods from September 1972 through July 1974 and to map the entire two-county area for 1973. For mines ranging between 31 and 244 acres (12 to 98 hectares) the measurement accuracy of total affected acreage was determined to be 92%. Mines of 120 acres (50 hectares) and larger were measured with greater accuracy, some within one percent of the actual area. The ability to identify, classify, and measure strip-mine surfaces in a two-county area (1,541 square kilometers - 595 square miles) of western Maryland was demonstrated through the use of computer processing. On the basis of these results the use of LANDSAT satellite data and multilevel sampling of aircraft and field verification inspections, multispectral analysis of digital data is shown to be an effective, rapid, and accurate means of monitoring the surface mining cycle.

Anderson, A. T.↗
DOE OSTI2025

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m −2 ) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m −2 (mean ≈ 350 g m −2 ), while predicted values ranged from 0 to ∼4000 g m −2 (mean ≈ 275 g m −2 ), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m −2 and R 2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Climate change↗
DOE OSTI2020

Dynamics and drivers of land use and land cover changes in Bangladesh

Abstract Bangladesh has undergone dramatic land use and land cover changes (LULCC) in recent years, but no quantitative analysis of LULCC drivers at the national scale exists so far. Here, we quantified the drivers of major LULCC in combination with biophysical and socioeconomic observations at the sub-district level. We used Landsat satellite data to interpret LULCC from 2000 to 2010 and employed a Global Surface Water Dataset to account for the influences of water seasonality. The results suggest that major LULCC in Bangladesh occur between agricultural land and waterbodies and between forest and shrubland. Exclusion of seasonal waterbodies can improve the accuracy of our LULCC results and driver analysis. Although the gross gain and loss of agricultural land are large on the local scale, the net change (gross gain minus gross loss) at a country scale is almost negligible. Climate dynamics and extreme events and changes in urban and rural households were driving the changes from forest to shrubland in the southeast region. The conversion from agricultural land to standing waterbodies in the southwest region was mainly driven by urban household dynamics, population growth, distance to cities and major roads, and precipitation dynamics. This study, which is the first effort accounting for water seasonality and quantifying biophysical and socioeconomic drivers of LULCC at the national scale, provides a perspective on overall LULCC and underlying drivers over a decadal time scale and national spatial scale and can serve as a scientific basis for developing land policies in Bangladesh.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evapotranspiration of advanced perennial bioenergy grasses produced on marginal land in the U.S. Midwest

The production of dedicated energy crops for biofuel and co-products can help develop a sustainable and viable bioeconomy under a changing climate. The co-production of perennial bioenergy and commodity crops in an agricultural landscape has the potential to reduce greenhouse gas emissions and provide numerous ecosystem services. However, as production of advanced, higher-yielding cultivars occurs, their impact on water resources needs to be considered. Estimates of evapotranspiration (ET) of perennial grasses compared to commodity crops are not always consistent in the literature. In this study, ET was estimated using an energy-balance model with Landsat satellite imagery and ground-based weather data to compare the large-scale production of advanced switchgrass cultivars (‘Independence’, ‘Liberty’, and ‘Carthage’), predecessor cultivars (‘Shawnee’ and ‘Sunburst’), and other perennial grasses (big bluestem and a low-diversity mixture) to corn grown continuously on marginal soils in the U.S. Midwest. Results showed significant differences in ET between corn and perennial grass treatments at four of the five field sites. However, differences between crop treatments were not consistent across sites, nor were the differences between advanced and predecessor switchgrass varieties. Production year played a large role in daily and cumulative ET across all sites. Differences in crop biomass yield between establishment and post-establishment years may contribute to these interannual differences. Site and interannual variations in precipitation and temperature may also be major contributing factors. Overall, the results of this study indicate that differences in ET between perennial bioenergy grasses and corn are likely dependent upon location of production and weather conditions.

09 BIOMASS FUELS↗