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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.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Land use project (comparison of LANDSAT with aircraft-derived land cover data for a proposed highway project)

The Maryland Automated Geographic Information System is described as well as the development of a general land cover classification with level 2 separation for vegetation categories for a 95,000-acre study area in Howard and Anne Arundel Counties. An accuracy analysis was performed on two subsections of the entire study area. The 1:24,000 scale land use map and the high in altitude infrared photography were determined to the best source of ground truth for the analysis. Results show that (1) delineation of deciduous and coniferous forested areas from LANDSAT data compared well with results from infrared photography; (2) general classification of agricultural areas showed acceptable results; (3) delineation of residential areas had the highest error rates (difference in interpretation and cover type assignment methods was a primary factor); and (4) LANDSAT-derived land cover data is to be used as an ancillary data source in a Maryland statewide land cover inventory.

Rugoski, T.↗
NASA NTRS1975

Enhancement and evaluation of Skylab photography for potential land use inventories, part 1

The author has identified the following significant results. Three sites were evaluated for land use inventory: Finger Lakes - Tompkins County, Lower Hudson Valley - Newburgh, and Suffolk County - Long Island. Special photo enhancement processes were developed to standardize the density range and contrast among S190A negatives. Enhanced black and white enlargements were converted to color by contact printing onto diazo film. A color prediction model related the density values on each spectral band for each category of land use to the spectral properties of the various diazo dyes. The S190A multispectral system proved to be almost as effective as the S190B high resolution camera for inventorying land use. Aggregate error for Level 1 averaged about 12% while Level 2 aggregate error averaged about 25%. The S190A system proved to be much superior to LANDSAT in inventorying land use, primarily because of increased resolution.

Hardy, E. E.↗
NASA NTRS1994

Land Use Patterns and Fecal Contamination of Coastal Waters in Western Puerto Rico

The Department of Environmental Health of the Graduate School of Public Health of the Medical Sciences Campus, University of Puerto Rico (UPR-RCM) conducted this research project on how different patterns of land use affect the microbiological quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Coastal shellfish growing areas, stream and ocean bathing beaches, and pristine marine sites in the Bay are affected by the discharge of the three study rivers. Satellite imagery was used to study watershed land uses which serve as point and nonpoint sources of pathogens affecting stream and coastal water users. The study rivers drain watersheds of different size and type of human activity (including different human waste treatment and disposal facilities). Land use and land cover in the study watersheds were interpreted, classified and mapped using remotely sensed images from NASA's Landsat Thematic Mapper (TM). This study found there is a significant relationship between watershed land cover and microbiological water quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Land covers in the Guanajibo, Anasco, and Yaguez watersheds were classified into forested areas, pastures, agricultural zones and urban areas so as to determine relative contributions to fecal water contamination. The land cover classification was made processing TM images with IDRISI and ERDAS software.

Norat, Jose↗
NASA NTRS1976

Toward the modeling of land use change: A spatial analysis using remote sensing and historical data

It was hypothesized that the chronological observation of land use change could be shown to follow a predictable pattern and these patterns could be correlated with other statistical data to develop transition probabilities suitable for modeling purposes. A literature review and preliminary research, however, indicated a totally stochastic approach was not practical for simulating land use change and thus a more deterministic approach was adopted. The approach used assumes the determinants of the land use conversion process are found in the market place, where land transactions among buyers and sellers occur. Only one side of the market transaction process is studied, however, namely, the purchaser's desires in securing an ideal or suitable site. The problem was to identify the ideal qualities, quantities or attributes desired in an industrial site (or housing development), and to formulate a general algorithmic statement capable of identifying potential development sites. Research procedures involved developing a list of variables previously noted in the literature to be related to site selection and streamlining the list to a set suitable for statistical testing. A sample of 157 industries which have located (or relocated) in the 16-county Knoxville metropolitan region since 1950 was selected for industrial location analysis. Using NASA color infrared photography and Tennessee Valley Authority historical aerial photography, data were collected on the spatial characteristics of each industrial location event. These data were then subjected to factor analysis to determine the interrelations of variables.

Honea, R. B.↗
DOE OSTI2025

A framework for testing soil carbon dynamics post land-use transition in a multisector dynamics model

Soil carbon plays a crucial role in the global carbon cycle. Changes in land use can determine whether carbon is stored or is emitted into the atmosphere as carbon dioxide, which has broad implications for the human and Earth systems. These feedbacks to the carbon cycle and their socio-economic drivers are modelled by many global multisector dynamics models to project future possibilities for the human-Earth system. One notable model of this class is the Global Change Analysis Model (GCAM), which uses a simplified process to model soil organic carbon (SOC) content after land-use transition across 384 land units. While the current GCAM soil carbon framework is based on scientific principles, it has not been tested against experimental data. This work examines rates of SOC change from GCAM input data. Specifically, first order rate constants derived from model inputs were compared to values from two syntheses to assess GCAM’s accuracy. Welch’s t-tests and linear models were used to determine if rate constants were consistent across all tested geographical areas and land-use transition types. While we found that there was general agreement on the direction and magnitude (i.e., rate) of SOC change, the rate constant derived from GCAM and empirical values differed strongly in a subset of specific instances. These results indicate that GCAM’s current SOC dynamics during land use transition successfully capture broad patterns of change in this critical carbon pool, but should be interpreted with caution at finer spatial scales. One potential cause of these discrepancies is our highly aggregated variable, soil timescale, which could be made more granular to improve accuracy. When using economically rooted multisector dynamics models, such as GCAM, it is critical to understand such model limitations for representing specific Earth system processes.

carbon↗
NASA NTRS2023

Uncertainty in Land-Use Adaptation Persists Despite Crop Model Projections Showing Lower Impacts Under High Warming

Climate change is expected to impact crop yields and alter resource availability. However, the understanding of the potential of agricultural land-use adaptation and its costs under climate warming is limited. Here, we use a global land system model to assess land-use-based adaptation and its cost under a set of crop model projections, including CO2 fertilization, based on climate model outputs. In our simulations of a low-emissions scenario, the land system responds through slight changes in cropland area in 2100, with costs close to zero. For a high emissions scenario and impacts uncertainty, the response tends toward cropland area changes and investments in technology, with average adaptation costs between −1.5 and +19 US$05 per ton of dry matter per year. Land-use adaptation can reduce adverse climate effects and use favorable changes, like local gains in crop yields. However, variance among high-emissions impact projections creates challenges for effective adaptation planning.

Agriculture↗
NASA NTRS2004

Communications: Mosquito Habitats, Land Use, and Malaria Risk in Belize from Satellite Imagery

Satellite imagery of northern Belize is used to examine the distribution of land use and breeding habitats of the malaria vector the Anopheles mosquito. A land cover classification based on multispectral SPOT and multitemporal Radarsat images identified eleven land cover classes, including agricultural, forest, and marsh types. Two of the land cover types, Typha domingensis marsh and flooded forest, are Anopheles vestitipennis larval habitats, and one, Eleocharis spp. marsh, is the larval habitat for Anopheles albimanus. Geographic Information Systems (GIS) analyses of land cover demonstrate that the amount of Typha domingensis in a marsh is positively correlated with the amount of agricultural land in the adjacent upland, and negatively correlated with the amount of adjacent forest. This finding is consistent with the hypothesis that nutrient (phosphorus) runoff from agricultural lands is causing an expansion of Typha domingensis in northern Belize. Thus, land use induced expansion of Anopheles vestitipennis larval habitat is potentially increasing malaria risk in Belize, and in other regions where Anopheles vestitipennis is a major malaria vector.

Pope, Kevin↗
DOE OSTI2021

Response to “how robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels?”

Malins et al. (2020) recently published "How robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels?", provided their narrative from the model improvements in GTAP-BIO over time, made several critical points regarding this model, and argued that the implemented improvements in this model tended to decrease Induce Land Use Changes (ILUC) emissions. Furthermore, they also provided several critical points regarding the Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) emissions model. In this response to Malins et al. we address these critiques point-by-point by providing our detailed responses to key issues: 1) the GTAP-BIO model and its improvements over time; 2) the inclusion of cropland pasture in the model; 3) the observed land use changes in the US that have been the bases for improvements in GTAP-BIO model, 4) the time trends in corn price and yield to challenge the concept of the yield to price response; 5) some sources of land intensification in crop production; 6) the FAO notifications with respect to the comparison between harvested area and arable land; and 7) the GTAP-BIO results for multiple cropping. We also provided responses to Malins et al. critical points regarding the CCLUB emissions model. We hope that this response letter will open more constructive discussion among the LUC modeling community to remain focused on the big picture regarding agriculture's role as a very effective GHG mitigation tool that can shape the new policies to govern the production and consumption of biofuels.

09 BIOMASS FUELS↗
NASA NTRS1975

Remote sensing for land use analysis

Preparation of cataloging and indexing reports of land use remote sensor data is described. Topics discussed include: land use mapping and scribing; collation of LANDSAT investigation reports; and reformating and collation of Skylab 4 tabular and plot data for data bank entry.

Source record↗
DOE OSTI2022

Bacterial community dynamics explain carbon mineralization and assimilation in soils of different land-use history

Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Bacterial community structure and function vary with respect to land use; yet the ecological drivers of this variation remain poorly described and difficult to predict. For this work, we conducted a multi-substrate DNA-stable isotope probing experiment across cropland, old-field, and forest habitats to link carbon mineralization dynamics with the dynamics of bacterial growth and carbon assimilation. We tracked the movement of 13 C derived from five distinct carbon sources as it was assimilated into bacterial DNA over time. We show that carbon mineralization, community composition, and carbon assimilation dynamics all differed with respect to land use. We also show that microbial community dynamics affect carbon assimilation dynamics and are associated with soil DNA content. Soil DNA yield is easy to measure and may be useful in predicting microbial community dynamics linked to soil carbon cycling. Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Microbial communities vary with respect to land use, but we still have an incomplete understanding of how variation in community structure links to variation in community function. DNA stable isotope probing (DNA-SIP) is a high-resolution method that can identify specific microbial taxa that assimilate carbon in situ. We conducted a large-scale multi-substrate DNA-SIP experiment to explore differences in bacterial activity across land-use regimes. We show that microbial community dynamics vary with land use, that these dynamics are linked to soil carbon cycling, and that they are associated with easily measured soil properties.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

Extracting land use information from the earth resources technology satellite data by conventional interpretation methods

A procedure for obtaining land use data from satellite imagery by the use of conventional interpretation methods is presented. The satellite is described briefly, and the advantages of various scales and multispectral scanner bands are discussed. Methods for obtaining satellite imagery and the sources of this imagery are given. Equipment used in the study is described, and samples of land use maps derived from satellite imagery are included together with the land use classification system used. Accuracy percentages are cited and are compared to those of a previous experiment using small scale aerial photography.

Vegas, P. L.↗
DOE OSTI2020

Land Use in Computable General Equilibrium Models

Constant Elasticity of Transformation (CET) functions are widely used to allocate land across uses in Computable General Equilibrium (CGE) models. These models fail to maintain area of land in balance. Several ways have been used or offered to fix this problem. This paper first examines the extent to which the CET approach may generate imbalances in area of land and identifies determinants of such imbalances. It then evaluates the merits, properties, and welfare impacts of the available approaches that restore area of land in balance. We show that heterogeneity in land prices (land rents) is the main source of imbalance in area of land, not the curvature of the CET function. Furthermore, we show that the available approaches that restore area of land in balance either introduce ad hoc adjustments in land allocation or undermine the conventional welfare assessments of the CET results and ignore the opportunity costs of land transformation. The CGE models which applied stochastic productivity distribution functions to allocate land among uses maintain area of land in balance, but they suffer from important limitations and ignore costs of land transformation.

Taheripour, Farzad↗
DOE OSTI2024

Global spatially explicit carbon emissions from land-use change over the past six decades (1961–2020)

Land-use change (LUC) is a major source of global anthropogenic carbon emissions that contribute to climate change. However, current estimates of LUC-induced emissions vary widely with differences in data and models, making it challenging to identify and manage emissions hotspots by location and LUC activity. Here, we estimated spatially explicit carbon fluxes associated with global major gross land-use transitions based on a new bookkeeping model (i.e., LUCE). Between 1961 and 2020, LUC induced 215 and 142 Pg C of global carbon emissions and removals, respectively, resulting in average net emissions (E LUC ) of 1.21 Pg C year −1 . Latin America, Southeast Asia, and Sub-Saharan Africa dominated global E LUC with 69% of 60-year cumulative emissions, or about 86% between 2001 and 2020. Forest-related LUC activities (e.g., deforestation, reforestation) contributed largely to both regional and global carbon fluxes. Our findings shed new light on identifying LUC-induced emissions hotspots and managing land for climate mitigation and conservation.

bookkeeping model↗
DOE OSTI2021

Past agricultural land use affects multiple facets of ungulate antipredator behavior

Antipredator behavior affects prey fitness, prey demography, and the strength of ecological interactions. Although predator-prey interactions increasingly occur in habitats that experience multiple forms of human-generated disturbance, it is unclear how different forms of disturbance might affect antipredator behavior. Fire is a contemporary disturbance that has dramatic effects on terrestrial habitats. Such habitats may have also experienced past disturbances, like agricultural land use, that leave lasting legacies on habitat structure (e.g., overstory and understory composition). It is unclear how these past and present disturbances affect the use of different antipredator behaviors, like temporal avoidance and vigilance. We examined whether variation in disturbance regimes generates differences in ungulate antipredator behavior by using cameras to measure white-tailed deer vigilance and activity time across 24 longleaf pine woodlands that vary in past land use and contemporary fire regime. Regardless of land-use history, woodlands with high fire frequencies had 4 times less vegetation cover than low-fire woodlands, generating riskier habitats for deer; however, deer responded to fire with different antipredator strategies depending on land-use history. In nonagricultural woodlands, fire affected deer activity time such that activity was nocturnal in low-fire woodlands and crepuscular in high-fire woodlands. In post-agricultural woodlands, fire affected vigilance and not activity time such that deer were more vigilant in high-fire woodlands than in low-fire woodlands. Furthermore, these results suggest that ungulate antipredator behavior may vary spatially depending on past land use and contemporary fire regime, and such disturbances may generate “landscapes of fear” that persist for decades after agricultural use.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1983

Urban land use of the Sao Paulo metropolitan area by automatic analysis of LANDSAT data

The separability of urban land use classes in the metropolitan area of Sao Paulo was studied by means of automatic analysis of MSS/LANDSAT digital data. The data were analyzed using the media K and MAXVER classification algorithms. The land use classes obtained were: CBD/vertical growth area, residential area, mixed area, industrial area, embankment area type 1, embankment area type 2, dense vegetation area and sparse vegetation area. The spectral analysis of representative samples of urban land use classes was done using the "Single Cell" analysis option. The classes CBD/vertical growth area, residential area and embankment area type 2 showed better spectral separability when compared to the other classes.

Parada, N. D. J.↗
DOE OSTI2021

Assessing Marginal Land Availability Based on Land Use Change Information in the Contiguous United States

Utilization of marginal land for growing dedicated bioenergy crops for second-generation biofuels is appealing to avoid conflicts with food production. This study develops a novel framework to quantify marginal land for the Contiguous United States (CONUS) based on a history of satellite-observed land use change (LUC) over the 2008–2015 period. Frequent LUC between crop and noncrop is assumed to be an indicator of economically marginal land; this land is also likely to have a lower opportunity cost of conversion from food crop to bioenergy crop production. We first present an approach to identify cropland in transition using the time series of Cropland Data Layer (CDL) land cover product and determine the amount of land that can be considered marginal with a high degree of confidence vs with uncertainty across the CONUS. We find that the biophysical characteristics of this land and its productivity and environmental vulnerability vary across the land and lie in between that of permanent cropland and permanent natural vegetation/bare areas; this land also has relatively low intrinsic value and agricultural profit but a high financial burden and economic risk. We find that the total area of marginal land with confidence vs with uncertainty is 10.2 and 58.4 million hectares, respectively, and mainly located along the 100th meridian. Only a portion of this marginal land (1.4–2.2 million hectares with confidence and 14.8–19.4 million hectares with uncertainty) is in the rainfed region and not in crop production and, thus, suitable for producing energy crops without diverting land from food crops in 2016. These estimates are much smaller than the estimates obtained by previous studies, which consider all biophysically low-quality land to be marginal without considering economical marginality. The estimate of marginal land for bioenergy crops obtained in this study is an indicator of the availability of economically marginal land that is suitable for bioenergy crop production; whether this land is actually converted to bioenergy crops will depend on the market conditions. Here, we note the inability to conduct field-level validation of cropland in transition and leave it to future advances in technology to ground-truth land use change and its relationship to economically marginal land.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

2023 Land Use Control Inspections Report

2023 Land Use Control (LUC) Inspections Report for John F. Kennedy Space Center (KSC), Florida. This letter report documents the quarterly LUC inspections the KSC Remediation Group conducts at Remediation Sites. No LUC findings occurred in 2023. A Corrective Action to address arsenic-impacted soil at the KSC Child Development Center was performed in July 2023. This letter report provides a summary and documents the field activities for that Corrective Action. Copies of the formal LUC Implementation Plans (LUCIPs) for 71 Remediation Sites at KSC are presented in this letter report. For the Remediation Sites that do not have formal LUCIPs, the report documents that informal LUCs that the Remediation Group has implemented at these sites.

Christopher Adkison↗