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At least 127 records · Page 7

Multispectral geologic remote sensing of a suspected impact crater near Al Madafi, Saudi Arabia

A multispectral Landsat TM image of a 6-km-diameter circular formation at Al Madafi in NW Saudi Arabia is interpreted by means of color-band composites, band ratios, and principal-components analysis to determine the nature of this feature. The geological characteristics of impact craters are discussed, and the satellite-image analysis techniques are described. Disruptions in the pattern of spectral signatures are seen in the Al Madafi formation and shown to be consistent with an impact origin.

Garvin, J. B.↗

The use of spatial characteristics for the improvement of multispectral classification of remotely sensed data

Two techniques for the classification of multispectral remotely sensed data - the image processing technique of texture features, which is modeled after the human visual system, and the ECHO (Extraction and Classification of Homogeneous Objects) numerical technique - are examined. These two spatial analysis techniques are compared using Landsat imagery of an area of Indiana as an example, and it is found that the numerical approach is superior in classification accuracy and more efficient computationally.

Wiersma, D. J.↗

An algorithm for the estimation of water temperatures from thermal multispectral airborne remotely sensed data

A method for water temperature estimation on the basis of thermal data is presented and tested against NASA's Thermal IR Multispectral Scanner. Using realistic bounds on emissivities, temperature bounds are calculated and refined to estimate a tighter bound on the emissivity of the source. The method is useful only when a realistic set of bounds can be obtained for the emissivities of the data.

Jaggi, S.↗

Multispectral microwave imaging radar for remote sensing applications

A multispectral airborne microwave radar imaging system, capable of obtaining four images simultaneously is described. The system has been successfully demonstrated in several experiments and one example of results obtained, fresh water ice, is given. Consideration of the digitization of the imagery is given and an image digitizing system described briefly. Preliminary results of digitization experiments are included.

Larson, R. W.↗

Sensitivity of Multiangle, Multispectral Polarimetric Remote Sensing Over Open Oceans to Water-Leaving Radiance: Analyses of RSP Data Acquired During the MILAGRO Campaign

For remote sensing of aerosol over the ocean, there is a contribution from light scattered underwater. The brightness and spectrum of this light depends on the biomass content of the ocean, such that variations in the color of the ocean can be observed even from space. Rayleigh scattering by pure sea water, and Rayleigh-Gans type scattering by plankton, causes this light to be polarized with a distinctive angular distribution. To study the contribution of this underwater light polarization to multiangle, multispectral observations of polarized reflectance over ocean, we previously developed a hydrosol model for use in underwater light scattering computations that produces realistic variations of the ocean color and the underwater light polarization signature of pure sea water. In this work we review this hydrosol model, include a correction for the spectrum of the particulate scattering coefficient and backscattering efficiency, and discuss its sensitivity to variations in colored dissolved organic matter (CDOM) and in the scattering function of marine particulates. We then apply this model to measurements of total and polarized reflectance that were acquired over open ocean during the MILAGRO field campaign by the airborne Research Scanning Polarimeter (RSP). Analyses show that our hydrosol model faithfully reproduces the water-leaving contributions to RSP reflectance, and that the sensitivity of these contributions to Chlorophyll a concentration [Chl] in the ocean varies with the azimuth, height, and wavelength of observations. We also show that the impact of variations in CDOM on the polarized reflectance observed by the RSP at low altitude is comparable to or much less than the standard error of this reflectance whereas their effects in total reflectance may be substantial (i.e. up to >30%). Finally, we extend our study of polarized reflectance variations with [Chl] and CDOM to include results for simulated spaceborne observations.

Chowdhary, Jacek↗

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Quattrochi, Dale A.↗

International Geoscience and Remote Sensing Symposium, Universitaet Muenchen, Munich, West Germany, June 1-4, 1982, Proceedings

The present conference on geoscience and remote sensing considers the multispectral remote sensing of saline seeps, the augmentation of LANDSAT MSS data with topographic data, thematic mapping, the sampling problem in radiation budget studies, aerial conductivity measurements over geothermal areas, a comparison of multifrequency band radars for crop classification, the improved estimation of vegetation-covered soil by combined active/passive microwave remote sensing, and atmospheric water vapor profiling by ground-based radiometry. Also discussed are SAR imaging from an inclined geosynchronous orbit, the classification of agricultural crops in radar images, the Ocean Color Experiment on the second orbital flight test of the Space Shuttle, the dielectric properties of wet materials, remote sensing systems for the mm-wave region, and the simulation of spaceborne stereo radar imagery.

Seiber, A. J.↗

Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net

We highlight three emerging NASA optical technologies that enhance our ability to remotely sense, analyze, and explore ocean worlds–FluidCam and fluid lensing, MiDAR, and NeMO-Net. Fluid lensing is the first remote sensing technology capable of imaging through ocean waves without distortions in 3D at sub-cm resolutions. Fluid lensing and the purpose-built FluidCam CubeSat instruments have been used to provide refraction-corrected 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs). Results from repeat 2013 and 2016 airborne fluid lensing campaigns over coral reefs in American Samoa present a promising new tool for monitoring fine-scale ecological dynamics in shallow aquatic systems tens of square kilometers in area. MiDAR is a recently-patented active multispectral remote sensing and optical communications instrument which evolved from FluidCam. MiDAR is being tested on UAVs and autonomous underwater vehicles (AUVs) to remotely sense living and non-living structures in light-limited and analog planetary science environments. MiDAR illuminates targets with high-intensity narrowband structured optical radiation to measure an object’s spectral reflectance while simultaneously transmitting data. MiDAR is capable of remotely sensing reflectance at fine spatial and temporal scales, with a signal-to-noise ratio 10-10(exp 3) times higher than passive airborne and spaceborne remote sensing systems, enabling high-framerate multispectral sensing across the ultraviolet, visible, and near-infrared spectrum. Preliminary results from a 2018 mission to Guam show encouraging applications of MiDAR to imaging coral from airborne and underwater platforms whilst transmitting data across the air-water interface. Finally, we share NeMO-Net, the Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment. NeMO-Net is a machine learning technology under development that exploits high-resolution data from FluidCam and MiDAR for augmentation of low-resolution airborne and satellite remote sensing. NeMO-Net is intended to harmonize the growing diversity of 2D and 3D remote sensing with in situ data into a single open-source platform for assessing shallow marine ecosystems globally using active learning for citizen-science based training. Preliminary results from four-class Q17 coral classification have an accuracy of 94.4%. Together, these maturing technologies present promising scalable, practical, and cost-efficient innovations that address current observational and technological challenges in optical sensing of marine systems.

Ved Chirayath↗

High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used by government officials, urban planners, and other decision-makers, to make more informed decisions on how to mitigate the UHI and its subsequent impacts.

Quattrochi, Dale A.↗

Detection of southern corn leaf blight by remote sensing techniques.

Multispectral photographic and scanner data were collected over western Indiana in August and September 1970, to determine the detectability of southern corn leaf blight by remote sensing. Measurements were made at altitudes of 3000 to 7000 ft. Color, color IR, and multiband black and white photography were collected at altitudes from 3000 to 60,000 ft. Six levels of infection based on the amount of leaf damage were identified in the fields. Three levels of infection were detected with color IR photography by standard photo-interpretive techniques. Up to five levels of infection were distinguished by applying automatic pattern recognition techniques to the multispectral scanner data. The results illustrate the potential of remote sensing techniques in the detection of crop diseases.

Bauer, M. E.↗

Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques

Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.

Malila, W. A.↗

Remote sensing techniques applied to multispectral recognition of the Aranjuez pilot zone

A rectangular (7 x 14 km) area 40 km S of Madrid was remote-sensed with a three-stage recognition process. Ground truth was established in the first phase, airborne sensing with a multispectral scanner and photographic cameras were used in the second phase, and Landsat satellite data were obtained in the third phase. Agronomic and hydrological photointerpretation problems are discussed. Color, black/white, and labeled areas are displayed for crop recognition in the land-use survey; turbidity, concentrations of pollutants and natural chemicals, and densitometry of the water are considered in the evaluation of water resources.

Lemos, G. L.↗

Sensitivity of Multiangle Remote Sensing Observations to Aerosol Sphericity

Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), can distinguish spherical from nonspherical particles over calm ocean for mineral-dust-like particles with the range of sizes and column amounts expected under natural conditions. The ability to make such distinctions is critical if remote sensing of atmospheric aerosol properties is to provide significant new contributions to our understanding of the global-scale, clear-sky solar radiation balance. According to theoretical simulations the measurements can retrieve column optical depth for nonspherical particles to an accuracy of at least 0.05 or 10%, whichever is larger. In addition, three to four distinct size groups between 0.1 and 2.0 microns effective radius can be identified at most latitudes.

Kahn, Ralph↗

Multiangle Remote Sensing of Aerosols Over Ocean

Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multiangle Imaging SpectroRadiometer (MISR), can significantly improve our ability to constrain aerosol properties from space.

retrieve column optical depth calm ocean particle ↗

Recent comet impacts on the moon - The evidence from remote-sensing studies

Multispectral images and near-infrared reflectance spectra were obtained for the Reiner Gamma Formation, a swirllike albedo and magnetic anomaly in the western portion of the lunar near side, as well as for nearby geologic units in Oceanus Procellarum, using the University of Hawaii 2.24-m telescope at the Mauna Kea Observatory. The spectra of the high albedo swirl material are closely matched by models incorporating 90-95 percent fresh mare basalt with 5-10 percent highlands debris.

Bell, Jeffrey F.↗