Arizona Water Resources II: Utilizing Aerial Imagery and NASA Earth Observations to Assess Pinyon-Juniper Tree Mortality near Flagstaff, AZ
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Arina Morozova↗
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Hurricane Ike Deposits on the Bolivar Peninsula, Galveston Bay, Texas
In September 2008, Hurricane Ike made landfall on Galveston Bay, close to the NASA Johnson Space Center (JSC). The storm flooded much of the area with a storm surge ranging from 11 -20 feet. The Bolivar peninsula, the southeastern coast of Galveston Bay, experienced the brunt of the surge. Several agencies collected excellent imagery baselines before the storm and complementary data a few days afterward that helped define the impacts of the storm. In April of 2011, a team of scientists and astronauts from JSC conducted field mapping exercises along the Bolivar Peninsula, the section of the Galveston Bay coast most impacted by the storm. Astronauts routinely observe and document coastal changes from orbit aboard the International Space Station. As part of their basic Earth Science training, scientists at the Johnson Space Center take astronauts out for field mapping exercises so that they can better recognize and understand features and processes that they will later observe from the International Space Station. Using pre -storm baseline images of the Bolivar Peninsula near Rollover Pass and Gilchrist (NOAA/Google Earth Imagery and USGS aerial imagery and lidar data), the astronauts mapped current coastline positions at defined locations, and related their findings to specific coastal characteristics, including channel, jetties, and other developments. In addition to mapping, we dug trenches along both the Gulf of Mexico coast as well as the Galveston Bay coast of the Bolivar peninsula to determine the depth of the scouring from the storm on the Gulf side, and the amount of deposition of the storm surge deposits on the Bay side of the peninsula. The storm signature was easy to identify by sharp sediment transitions and, in the case of storm deposits, a layer of storm debris (roof shingles, PVC pipes, etc) and black, organic rich layers containing buried sea grasses in areas that were marshes before the storm. The amount of deposition was generally about 20 -25 cm; the local areas experiencing obvious deposition are readily obvious in post -Ike imagery of the region. We used a March 2010 aerial photograph from the NOAA -Google Earth collection because construction and vegetation recovery was minimal. Based on the before and after aerial imagery and the trenching data collected over two days, we can begin to characterize the material transported and deposited by Hurricane Ike along one stretch of the Bolivar peninsula. We summarize the results from our mapping and trenching data. The basic data collected 2.5 years after the storm are ephemeral as the storm deposits become reworked and overprinted by coastal processes, vegetation regrowth and reconstruction.
Evans, Cynthia A.↗
Spatial Resolution Characterization for Aerial Digital Imagery
The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration have jointly conducted characterizations of aerial digital imagery from commercial data providers. In a typical scenario, a vendor acquired imagery over the Stennis Space Center test range and provided a common data package to SSC. SSC personnel analyzed the geopositional accuracy and spatial resolution of the images, then documented the characterization results in a report and delivered the report to the USGS. Spatial resolution characterization was based on edge response measurements using one of the SSC edge targets and the tilted-edge technique. Relative Edge Response (RER) has been estimated for aerial digital imagery from several commercial data providers. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale.
Blonski, Slawomir↗
Spatial Resolution Characterization for Aerial Digital Imagery
This viewgraph presentation reviews NASA and the U.S. Geological Survey (USGS)'s analysis of spatial characterization resolution for Aerial Digital Imagery.
Blonski, Slawomir↗
Forest and land inventory using ERTS imagery and aerial photography in the boreal forest region of Alberta, Canada
Satellite imagery and small-scale (1:120,000) infrared ektachrome aerial photography for the development of improved forest and land inventory techniques in the boreal forest region are presented to demonstrate spectral signatures and their application. The forest is predominately mixed, stands of white spruce and poplar, with some pure stands of black spruce, pine and large areas of poorly drained land with peat and sedge type muskegs. This work is part of coordinated program to evaluate ERTS imagery by the Canadian Forestry Service.
Kirby, C. L.↗
EROS main image file - A picture perfect database for Landsat imagery and aerial photography
The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.
Jack, R. F.↗
The application of airborne imaging radars (L and X-band) to earth resources problems
A multiplexed synthetic aperture Side-Looking Airborne Radar (SLAR) that simultaneously images the terrain with X-band (3.2 cm) and L-band (23.0 cm) radar wavelengths was developed. The Feasibility of using multiplexed SLAR to obtain useful information for earth resources purposes. The SLAR imagery, aerial photographs, and infrared imagery are examined to determine the qualitative tone and texture of many rural land-use features imaged. The results show that: (1) Neither X- nor L-band SLAR at moderate and low depression angles can directly or indirectly detect pools of water under standing vegetation. (2) Many of the urban and rural land-use categories present in the test areas can be identified and mapped on the multiplexed SLAR imagery. (3) Water resources management can be done using multiplexed SLAR. (4) Drainage patterns can be determined on both the X- and L-band imagery.
Drake, B.↗
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.↗
Normalizing shadows in multi-temporal aerial frame imagery using relative radiometric adjustments to support near-real-time change detection
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Emanuel Arnal Storey↗
Photographic image enhancement and processing
Scientists using aerial imagery frequently desire image processing or enhancement of that imagery to aid them in data analysis. Sophisticated digital image processing techniques are currently employed in many applications where the data is recorded in digital format, where processing hardware and programs are available. Aerial photographic imagery poses a problem in the magnitude of the digitization processing. Photographic image processing analogous to many available digital techniques is being employed by scientific investigators. Those techniques which may be applied in a cost effective manner to processing of aerial photographic imagery are described here.
Lockwood, H. E.↗
Utilizing Airborne and Space-Based Remote Sensing Imagery to Implement the Unvegetated-Vegetated Ratio to Assess Salt Marsh Vulnerability in South Carolina
Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region and can be used to determine the life span of the marsh. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR), developed by researchers at USGS, is a scalable and efficient method to assess vulnerability. The NASA DEVELOP National Program collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center to apply the UVVR method within Google Earth Engine. Marsh vulnerability was analyzed using UVVR derived from clustering and manual interpretation of National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. NAIP derived UVVR was aggregated to Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) resolution and projection. A Random Forest Regression between Landsat derived data and UVVR was modeled to estimate a potential relationship. The estimation of this relationship was used to produce temporal change analysis maps of salt marsh vulnerability back to 1984. The NAIP imagery processed through Google Earth Engine allowed us to make detailed UVVR maps for 2009, 2015, 2017, and 2019 for decision making within South Carolina. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh regions and easily calculate marsh vulnerability without external data downloading. These results were used to understand what areas of the marsh need most resource allocation in the future.
NASA DEVELOP↗
South Carolina Water Resources Project Summary - Implementing the Unvegetated-Vegetated Ratio to Assess Salt Marsh Vulnerability in South Carolina Using Airborne and Space-Based Remote Sensing Imagery
Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR) is a scalable and efficient method to assess vulnerability. This NASA DEVELOP project collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center. Marsh vulnerability was analyzed using UVVR derived from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) in conjunction with National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. A Landsat random forest regression showed a low correlation (r2 = 0.247) between Landsat 7 ETM+ bands and NAIP aggregated UVVR suggesting the need for a more complex model and higher resolution sensors. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh areas and easily calculate UVVR without external data downloading.
DEVELOP Project Summary↗
Multiple RGB ortho-mosaics and digital surface models in 2017 and 2018 across the Lower Montane site in the East River Watershed, Colorado
Aerial imagery was collected at the Lower Montane site (Pumphouse) in the East River Watershed, Colorado during the spring, summer, and fall seasons of 2017 and 2018 to improve the understanding of seasonal vegetation dynamics and their drivers. The datasets include Red-Green-Blue (RGB) ortho-mosaics and digital surface models (DSMs) inferred from the Unoccupied Aerial System (UAS) acquired aerial RGB imagery for June 3, June 19, July 7, and August 14, 2017, and for March 14, April 26, June 1, June 18, July 6, and August 7, 2018. Real-Time Kinematic Global Positioning System (RTK-GPS) surveyed Ground control points (GCPs) were used to increase the reconstruction accuracy. The reconstructed RGB mosaics and DSMs have been trimmed to cover a similar spatial domain. The accuracy of the RGB mosaics is considered high (~10 cm). DSM accuracy is highest (~10 cm) where sufficient GCPS are available, and more difficult to assess elsewhere (see reconstruction reports for uncertainty estimates). The dataset includes a total of 20 GeoTIFF (.tif) files, 10 PDF (.pdf) files, 3 data CSV (.csv) files, and 2 metadata CSV (.csv) files. Feel free to contact the authors with any questions or collaboration interests.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
54 ENVIRONMENTAL SCIENCES↗
A semi-automated system for plotting and computer cataloging of remote sensing imagery
Description of a computer-assisted system for plotting and descriptor-cataloging of aerial imagery - an ingredient of the aerial image data handling system of the NASA Earth Resources Aircraft Project (ERAP). The system under consideration uses two graphic tablets linked interactively with a digital computer as input devices for deriving frame coordinates by correlating image points to map points. The various software programs and operating modes facilitate a semiautomatic plotting of an image by selecting two or more points within the image for matching with map details. The computer performs the scaling and orientation transformations for the calculation of the center and corner coordinates of the frame. Twenty five other descriptors for each frame are fed into a computerized data base requiring a minimum operator's time for verification and correction.
Gnauck, G. E.↗
Dronebase Photovoltaic (PV) Fleet Imagery Quantitative Evaluation (CRADA CRD-22-22941 Final Report)
Combine the Dronebase aerial imagery with corresponding sites in the NLR Photovoltaic (PV) Fleets database. By combining these two data sources in an aggregated, anonymized fashion, we can perform the following analyses: quantifying power loss due to outages caused by stuck trackers, string outages, and shading/snow, validate site metadata, including tilt and azimuth, and correlate.
14 SOLAR ENERGY↗
DMSP-SSM/1 NASA algorithm validation using primarily LANDSAT and secondarily DMSP and/or AVHRR visible and thermal infrared satellite imagery
The approach to the DMSP SSMI (Defense Meteorological Satellite Program; Special Sensor Microwave Imager) sea-ice validation effort is to demonstrate a quantitative relationship between the SSMI-derived sea ice parameters and those same parameters derived from other data sets including visible and infrared satellite imagery, aerial photographic and high-resolution microwave aircraft imagery. The question to be addressed is to what accuracy (relative to these other observations) can the following ice parameters be determined: (1) position of the ice boundary; (2) total sea ice concentration; and (3) multiyear sea ice concentration. Specific tasks include: (1) a study of the interrelationship of surface information content and sensor spatial and spectral resolution in order to establish relationships between ice surface features and the manner in which they are expressed in the satellite observations; and (2) apply these relationships to map the sea ice features which can be used to evaluate NASA's proposed SSM/1 sea ice algorithms. Other key points to be addressed include the accuracy to which these parameters can be determined in different regions (marginal ice zone such as Bering Sea, Arctic ocean, such as Beaufort Sea); the accuracy of these parameters for different seasons; the accuracy of the algorithms weather filter under different weather conditions; and the effectiveness of the 85.5 GHz channels to locate the ice edge.
Steffen, K.↗
A survey of users of earth resources remote sensing data
The use of Landsat imagery and digital data, Skylab data and high-altitude aerial imagery by industry, government, academic and foreign analysts was surveyed. The study indicated that while most users are satisfied with current Landsat product quality and spectral coverage, there does exist a significant demand for extension of the spectral coverage to thermal and microwave regions, for resolutions in the 20 to 40 and 10 to 20 meter range, and for more rapid data delivery. Problems involving the acceptance of digital processing techniques by some users are also mentioned.
Wukelic, G. E.↗
Boundaries of ERTS and aircraft data within which useful water quality information can be obtained
Calibration procedures have been devised and applied to ERTS-1, multispectral, true color, and false color imagery. The results indicate that the ERTS and multispectral imagery are correlated with optical in situ measurements of the harbor water. Correlation is extended to true and false color imagery through in situ optical measurements of the harbor water. The best photometric accuracy is achieved with multispectral aerial imagery and the use of bulk MSS tape. The aircraft green photographic and ERTS-1 MSS-4 bands have been found most suitable for monitoring the scattered light levels under the conditions of this investigation. The application of satellite or aircraft for optical remote sensing depends upon the physical scale and frequency of sensing since both sensor systems generally have sufficient photometric sensitivity. The chemical parameters of the harbor water were found to be correlated to the optical properties for two stations investigated in detail.
Egan, W. G.↗