Use of remote sensing for land use policy formulation
There are no author-identified significant results in this report.
Boylan, M.↗
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Use of remote sensing for land use policy formulation
The author has identified the following significant results. By utilizing remote sensing techniques, it was possible to accurately inventory a relatively large area for sand mining impact on protection and management of shoreland dunes within a limited time period and at a relatively low cost. Analysis of two sample areas selected from the Grand Mere area after prohibition of off-road-vehicle use indicated an increase in vegetation regrowth of 8.52% for sample area 1 and of 4.44% for sample area 2.
Boylan, M.↗
Use of remote sensing for land use policy formulation
There are no author-identified significant results in this report.
Boylan, M.↗
Use of remote sensing for land use policy formulation
There are no author-identified significant results in this report.
Boylan, M.↗
Use of remote sensing for land use policy formulation
Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.
Source record↗
A Framework for the Cross-Sectoral Integration of Multi-Model Impact Projections: Land Use Decisions Under Climate Impacts Uncertainties
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making
farmlands↗
Land Use Planning
Computer technology, aerial photography and space imagery are being combined in a NASA community services program designed to help solve land use and natural resource planning problems. As urban areas grow, so grows the need for comprehensive, up-to-date information on which to base intelligent decisions regarding land use. State and local planners need information such as the nature of urban change, where the changes are occurring, how they affect public safety, transportation, the economy, tax assessment, sewer systems, water quality, flood hazard, noise impact and a great variety of other considerations. Most importantly they need continually updated maps. Preparing timely maps, gathering the essential data and maintaining it in orderly fashion are becoming matters of increasing difficulty. The NASA project, which has nationwide potential for improving efficiency in the planning process, is a pilot program focused on Tacoma, Washington and surrounding Pierce County. Its key element, developed by Jet Propulsion Laboratory (JPL), is a computerized Land Use Management Information System (LUMIS).
Source record↗
Testing the accuracy of remote sensing land use maps
Some of the main aspects that need to be considered in a remote sensing sampling design are: (1) the frequency that any one land use type (on the ground) is erroneously attributed to another class by the interpreter; (2) the frequency that the wrong land use (as observed on the ground) is erroneously included in any one class by the remote sensing interpreter; (3) the proportion of all land (as determined in the field) that is mistakenly attributed by the interpreter; and (4) the determination of whether the mistakes are random (so that the overall proportions are approximately correct) or subject to a persistent bias. A sampling and statistical testing procedure is presented which allows an approximate answer to each of these aspects. The concept developed and described incorporates the probability of making incorrect interpretations at particular prescribed accuracy levels, for a certain number of errors, for a particular sample size. It is considered that this approach offers a meaningful explanation of the interpretation accuracy level of an entire remote sensing land use survey.
Vangenderen, J. L.↗
Land use classification in Bolivia
The Bolivian LANDSAT Program is an integrated, multidisciplinary project designed to provide thematic analysis of LANDSAT, Skylab, and other remotely sensed data for natural resource management and development in Bolivia, is discussed. Among the first requirements in the program is the development of a legend, and appropriate methodologies, for the analysis and classification of present land use based on landscape cover. The land use legend for Bolivia consists of approximately 80 categories in a hierarchical organization which may be collapsed for generalization, or expanded for greater detail. The categories, and their definitions, provide for both a graphic and textual description of the complex and diverse landscapes found in Bolivia, and are designed for analysis from LANDSAT and other remotely sensed data at scales of 1:1,000,000 and 1:250,000. Procedures and example products developed are described and illustrated, for the systematic analysis and mapping of present land use for all of Bolivia.
Brockmann, C. E.↗
A preliminary evaluation of land use mapping and change detection capabilities using an ERTS image covering a portion of the CARETS region
The author has identified the following significant results. A preliminary study on the capabilities of ERTS data in land use mapping and change detection was carried out in the area around Frederick County, Maryland, which lies in the northwest corner of the Central Atlantic Regional Ecological Test Site. The investigation has revealed that Level 1 (of the Anderson classification system) land use mapping can be performed and that, in some cases, land undergoing change can be identified. Results to date suggest that more work should be done in areas where land use changes are known to exist, in order to establish some form of base for recognizing the spectral signature indicative of change areas.
Fitzpatrick, K. A.↗
A Web Architecture to Geographically Interrogate CHIRPS Rainfall and eMODIS NDVI for Land Use Change
Monitoring of rainfall and vegetation over the continent of Africa is important for assessing the status of crop health and agriculture, along with long‐term changes in land use change. These issues can be addressed through examination of long‐term precipitation (rainfall) data sets and remote sensing of land surface vegetation and land use types. Two products have been used previously to address these goals: the Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) rainfall data, and multi‐day composites of Normalized Difference Vegetation Index (NDVI) from the USGS eMODIS product. Combined, these are very large data sets that require unique tools and architecture to facilitate a variety of data analysis methods or data exploration by the end user community. To address these needs, a web‐enabled system has been developed to allow end‐users to interrogate CHIRPS rainfall and eMODIS NDVI data over the continent of Africa. The architecture allows end‐users to use custom defined geometries, or the use of predefined political boundaries in their interrogation of the data. The massive amount of data interrogated by the system allows the end‐users with only a web browser to extract vital information in order to investigate land use change and its causes. The system can be used to generate daily, monthly and yearly averages over a geographical area and range of dates of interest to the user. It also provides analysis of trends in precipitation or vegetation change for times of interest. The data provided back to the end‐user is displayed in graphical form and can be exported for use in other, external tools. The development of this tool has significantly decreased the investment and requirements for end‐users to use these two important datasets, while also allowing the flexibility to the end‐user to limit the search to the area of interest.
Burks, Jason E.↗
Land use in the Northern Coachella Valley
Land use in Northern Coachella Valley, California
Bale, J. B.↗
Land Use Classification and Change Analysis Using ERTS-1 Imagery in CARETS
Land use classification and change analysis using ERTS-1 imagery in Central Atlantic Research Test Site
Alexander, R. H.↗
Utilizing LANDSAT imagery to monitor land-use change - A case study in Ohio
A study, performed in Ohio, of the nature and extent of interpretation errors in the application of Landsat imagery to land-use planning and modeling is reported. Potential errors associated with the misalignment of pixels after geometric correction and with misclassification of land cover or land use due to spectral similarities were identified on interpreted computer-compatible tapes of a portion of Franklin County for two adjacent days of 1975 and one day of 1973, and the extents of these errors were quantified by comparison with a ground-checked set of aerial-photograph interpretations. The open-space and agricultural categories are found to be the most consistently classified, while the more urban areas were classified correctly only from about 43 to 8% of the time. It is thus recommended that the direct application of Landsat data to land-use planning must await improvements in classification techniques and accuracy.
Gordon, S. I.↗
Study of application of remote sensing data to land use planning on the Mississippi Gulf Coast
There are no author-identified significant results in this report. Comparisons are being developed for ERTS-1 imagery and data from existing land use studies of the four county area of the Mississippi Gulf Coast. ERTS-1 data will be analyzed by computer programs and land use maps will be produced which delineate categories of interest. These computer produced products will be analyzed to determine accuracy and suitability of the data for land use planning compared to the present means of data collection for such studies.
Ingels, F. M.↗
Investigating the Impacts of Land Use Change on Urban Heat and Vulnerability in Cali, Columbia
The urban heat island effect (UHI) is an environmental phenomenon where cities experience higher temperatures than rural areas due to increased pavement and decreased cooling from vegetation. Approximately 76% of people in Colombia live in urban areas, and the city of Santiago de Cali is facing UHI challenges exacerbated by land use change. Wetlands and forests formerly surrounded the city but were replaced by development and agriculture. The Colombian municipal government agency Departamento Administrativo de Gestión del Medio Ambiente and the community organization Fundacion Dinamizadores Ambientales partnered with NASA DEVELOP to evaluate communities in Cali most vulnerable to urban heat. This project illustrated the utility of using NASA Earth observations to evaluate the relationship between land use, temperature, and social factors in Cali, Colombia between 2013 and 2023. The team used Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), and Landsat 9 OLI-2/TIRS-2 to generate land surface temperature (LST), normalized difference vegetation index (NDVI), and albedo maps in Google Earth Engine. Heavy cloud cover limited the accuracy of the LST but incorporating up to three satellites for a median image reduced potential errors. Through further analysis in ArcGIS Pro, the team classified land use change using a deep learning model and found that LST was significantly higher in urban areas than in wetlands or forests. Using R studio, the team ran a principal component analysis to determine which social factors had the strongest correlation with LST. The team found that health care and green space access were negatively correlated, and Afro-Colombian ethnicity was positively correlated with LST. With awareness of the most impacted and vulnerable regions, the partner organizations can work to prioritize green space establishment in those areas to reduce the impacts of urban heat. Addressing the urban heat island effect will reduce environmental justice concerns within the city and improve overall health, air, and water quality for those who live there.
Brenna Bruffey↗
Land use studies with Skylab data, August 1974
The author has identified the following significant results. Capabilities of Skylab photographic data suggest significant applications for: (1) identification and mapping of all primary, most secondary, and many tertiary land use classes; (2) stratification of the landscape for more detailed sampling; and (3) rapid updating of existing land use and vegetation maps subscaled at 1:25,000 and smaller with manual interpretation techniques. Automated thematic mapping of land use categories with electronic data processing techniques is feasible with the S-192 multispectral scanner, despite the high noise levels in many channels.
Simonett, D. S.↗
Skylab and ERTS-1 investigations of coastal land use and water properties
The author has identified the following significant results. ERTS-1 multispectral scanner and Skylab's S190A, S190B, and S192 data products were evaluated for their utility in studying current circulation, suspended sediment concentrations and pollution dispersal in Delaware Bay and in mapping coastal vegetation and land use. Imagery from the ERTS-1 MSS, S190A and S190B cameras shows considerable detail in water structure, circulation, suspended sediment distribution and within waste disposal plumes in shelf waters. These data products were also used in differentiating and mapping twelve coastal vegetation and land use classes. The spatial resolution of the S190A multispectral facility appears to be about 30 to 70 meters while that of the S190B earth terrain camera is about 10 to 30 meters. Such resolution, along with good cartographic quality, indicates a considerable potential for mapping coastal land use and monitoring water properties in estuaries and on the continental shelf. The ERTS-1 MSS has a resolution of about 70-100 meters. Moreover, its regular 18-day cycle permits observation of important changes, including the environmental impact of coastal zone development on coastal vegetation and ecology.
Klemas, V.↗