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Census Cities Project and atlas of urban and regional change
The research design and imagery utilization for urban applications of remote sensing are reviewed, including the combined use of sensor and census data and aircraft and spacecraft sensor platforms. The related purposes of the Census Cities Project are elucidated: (1) to assess the role of remote sensors on high altitude platforms for comparative study of urban areas; (2) to detect changes in selected U.S. urban areas between the 1970 census and the time of launching of an earth-orbiting sensor platform prior to next census; (3) to test the satellite sensor platform utility to monitor urban change and serve as a control for sensor image interpretation; (4) to design an information system for incorporating graphic sensor data with census-type data gathered by traditional techniques; (5) to identify and to design user-oriented end-products or information services; and (6) to ascertain what organizational capability would be needed to provide such services on a continuing basis. A need to develop not only a spatial data information system, but also a methodology for detecting and interpreting change is implied.
Surface truth measurements of optical properties of the waters in the northern Gulf of California
Gemini and Apollo flight photographs of the southwestern United States and northwestern Mexico, and especially of the Colorado River delta and the northwestern Gulf of California, are considered. The clearly discernible water coloration in the imagery led to the suggestion that remote sensing techniques may be usefully applied in such areas to determine bathymetric information. Measurements of the optical properties of the water in this region obtained in March 1971 showed that generally low transmissivities prevailed and at no station did the beam transmittance for the total water column exceed 2.5 x 10 to the -8th power. It was concluded that any correlation between water depth and spectral radiance at the surface must result from secondarily related phenomena.
The application of remote sensing techniques to inter and intra urban analysis
This is an effort to assess the applicability of air and spaceborne photography toward providing data inputs to urban and regional planning, management, and research. Through evaluation of remote sensing inputs to urban change detection systems, analyzing an effort to replicate an existing urban land use data file using remotely sensed data, estimating population and dwelling units from imagery, and by identifying and evaluating a system of urban places ultilizing space photography, it was determined that remote sensing can provide data concerning land use, changes in commercial structure, data for transportation planning, housing quality, residential dynamics, and population density.
Satellite Geological and Geophysical Remote Sensing of Iceland. Vatnajoekull Area, Iceland: New Volcanic and Structural Features on ERTS-1 Imagery
There are no author-identified significant results in this report.
Applied Remote Sensing Program (ARSP)
Descriptions of projects engaged by the Applied Remote Sensors Program in the state of Arizona are contained in an annual report for the fiscal year 1976-1977. Remote sensing techniques included thermal infrared imagery in analog and digital form and conversion of data into thermograms. Delineation of geologic areas, surveys of vegetation and inventory of resources were also presented.
Land utilization and ecological aspects in the Sylhet-Mymensingh Haor Region of Bangladesh: An analysis of LANDSAT data
The use of remote sensing data from LANDSAT (ERTS) imageries in identifying, evaluating and mapping land use patterns of the Haor area in Bangladesh was investigated. Selected cloud free imageries of the area for the period 1972-75 were studied. Imageries in bands 4, 5 and 7 were mostly used. The method of analysis involved utilization of both human and computer services of information from ground, aerial photographs taken during this period and space imageries.
A study of Minnesota land and water resources using remote sensing
The author has identified the following significant results. Both LANDSAT imagery and digital data were studied for usefulness in surveying water conditions of Minnesota lakes. Initial consideration was given to analysis of LANDSAT image densities because of the low technologic and cost requirements. The techniques employed, however, yield inconsistent and unreliable results. A set of criteria are given for using LANDSAT data in identification of three categories of particulate contaminants in Lake Superior. A linear transformation giving the relationship between the residual LANDSAT intensities and concentrations of three contaminants was obtained from correlation of remote sensing data with insitu measurements. LANDSAT imagery was found useful in placing peat bogs and fens in their respective geologic settings. Artificial disturbances and drainageways in peatlands could be recognized and classified.
HCMM hydrological analysis in Utah
The feasibility of applying a linear model to HCMM data in hopes of obtaining an accurate linear correlation was investigated. The relationship among HCMM sensed data surface temperature and red reflectivity on Utah Lake and water quality factors including algae concentrations, algae type, and nutrient and turbidity concentrations was established and evaluated. Correlation (composite) images of day infrared and reflectance imagery were assessed to determine if remote sensing offers the capability of using masses of accurate and comprehensive data in calculating evaporation. The effects of algae on temperature and evaporation were studied and the possibility of using satellite thermal data to locate areas within Utah Lake where significant thermal sources exist and areas of near surface groundwater was examined.
Methodology of remote sensing data interpretation and geological applications
Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.
Processing Digital Imagery Data
Earth Resources Laboratory Applications Software (ELAS) is geobased information system designed for analyzing and processing digital imagery data. ELAS offers user of remotely sensed data wide range of easy to use capabilities in areas of land cover analysis. ELAS system written in FORTRAN and Assembler for batch or interactive processing.
The absolute radiometric calibration of the advanced very high resolution radiometer
An increasing number of remote sensing investigations require radiometrically calibrated imagery from NOAA Advanced Very High Resolution Radiation (AVHRR) sensors. Although a prelaunch calibration is done for these sensors, there is no capability for monitoring any changes in the in-flight absolute calibration for the visible and near infrared spectral channels. Hence, the possibility of using the reflectance-based method developed at White Sands for in-orbit calibration of LANDSAT Thematic Mapper (TM) and SPOT Haute Resolution Visible (HVR) data to calibrate the AVHRR sensor was investigated. Three diffrent approaches were considered: Method 1 - ground and atmospheric measurements and reference to another calibrated satellite sensor; Method 2 - ground and atmospheric measurements with no reference to another sensor; and Method 3 - no ground and atmospheric measurements but reference to another satellite sensor. The purpose is to describe an investigation on the use of Method 2 to calibrate NOAA-9 AVHRR channels 1 and 2 with the help of ground and atmospheric measurements at Rogers (dry) Lake, Edwards Air Force Base (EAFB) in the Mojave desert of California.
A Landsat-Based Assessment of Mobile Bay Land Use and Land Cover Change from 1974 to 2008
The Mobile Bay region has experienced noteworthy land use and land cover (LULC) change in the latter half of the 20th century. Accompanying this change has been urban expansion and a reduction of rural land uses. Much of this LULC change has reportedly occurred since the landfall of Hurricane Frederic in 1979. The Mobile Bay region provides great economic and ecologic benefits to the Nation, including important coastal habitat for a broad diversity of fisheries and wildlife. Regional urbanization threatens the estuary s water quality and aquatic-habitat dependent biota, including commercial fisheries and avian wildlife. Coastal conservation and urban land use planners require additional information on historical LULC change to support coastal habitat restoration and resiliency management efforts. This presentation discusses results of a Gulf of Mexico Application Pilot project that was conducted in 2008 to quantify and assess LULC change from 1974 to 2008. This project was led by NASA Stennis Space Center and involved multiple Gulf of Mexico Alliance (GOMA) partners, including the Mobile Bay National Estuary Program (NEP), the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration s (NOAA s) National Coastal Data Development Center (NCDDC), and the NOAA Coastal Services Center. Nine Landsat images were employed to compute LULC products because of their availability and suitability for the application. The project also used Landsat-based national LULC products, including coastal LULC products from NOAA s Coastal Change & Analysis Program (C-CAP), available at 5-year intervals since 1995. Our study was initiated in part because C-CAP LULC products were not available to assess the region s urbanization prior to 1995 and subsequent to post Hurricane Katrina in 2006. This project assessed LULC change across the 34-year time frame and at decadal and middecadal scales. The study area included the majority of Mobile and Baldwin counties that encompass Mobile Bay. In doing so, each date of Landsat data was classified using an end-user defined modified Anderson level 1 classification scheme. LULC classifications were refined using a decision rule approach in conjunction with available C-CAP products. Individual dates of LULC classifications were validated by image interpretation of stratified random locations on raw Landsat color composite imagery in combination with higher resolution remote sensing and in-situ reference data. The results indicate that during the 34-year study period, urban areas increased from 96,688 to 150,227 acres, representing a 55.37% increase, or 1.63% per annum. Most of the identified urban expansion results from conversion of rural forest and agriculture to urban cover types. Final LULC mapping and metadata products were produced for the entire study area as well as watersheds of concern within the study area. Final project products, including LULC trend information, were incorporated into the Mobile Bay NEP State of the Bay report. Products and metadata were transferred to NOAA NCDDC to allow free online accessibility and use by GOMA partners and by the public.
Reducing Tick-Borne Disease in Alabama: Linking Health Risk Perception with Spatial Analysis Using the NASA Earth Observing System
Lyme disease (LD) accounts for most vector-borne disease reports in the U.S., and although its existence in Alabama remains controversial, other tick-borne illnesses (TBI) such as Southern Tick-Associated Rash Illness (STARI) pose a health concern in the state. Phase One of the Marshall Space Flight Center-UAB DEVELOP study of TBI identified the presence of the chain of infection for LD (Ixodes scapularis ticks carrying Borrelia burgdorferi bacteria) and STARI (Amblyomma americanum ticks and an as-yet-unconfirmed agent) in Alabama. Both LD and STARI are associated with the development of erythema migrans rashes around an infected tick bite, and while treatable with oral antibiotics, a review of educational resources available to state residents revealed low levels of prevention information. To improve prevention, recognition, and treatment of TBI in Alabama, Phase Two builds a health communication campaign based on vector habitat mapping and risk perception assessment. NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery identified likely tick habitats using remotely sensed measurements of vegetation vigor (Normalized Difference Vegetation Index) and soil moisture. Likely tick habitats, identified as those containing both high vegetation density and soil moisture, included Oak Mountain State Park, Bankhead National Forest, and Talladega National Forest. To target a high-risk group -- outdoor recreation program participants at Alabama universities -- the study developed a behavior survey instrument based on existing studies of LD risk factors and theoretical constructs from the Social Ecological Model and Health Belief Model. The survey instrument was amended to include geographic variables in the assessment of TBI knowledge, attitudes, and prevention behaviors, and the vector habitat model will be expanded to incorporate additional environmental variables and in situ data. Remotely sensed environmental data combined with risk perception assessments inform an ongoing outreach campaign consisting of stakeholder meetings and educational seminars.
Modeling and Simulation for DAVINCI Entry, Descent, and Landing
The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission will launch in June 2029 and explore Venus via two flybys and a probe landing currently scheduled for June 2031. DAVINCI is the 16th selection of the NASA Discovery Class program and its objectives include quantifying the chemical composition of the Venusian atmosphere, taking infrared descent imagery of the surface, and conducting remote observations of the dynamic atmosphere and cloud-deck. The goals are to study the origin, evolution, and current state of Venus, to understand if it was habitable at a point in the past, and to create an analog to hot terrestrial exo-planets similar to Venus.
Using AI/ML to Address Satellite Cloud Remote Sensing Challenges
Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.
NASA SCIFLI’s Calibrated Mission Portfolio
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WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring
Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management.