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At least 1,513 records · Page 84

Remote sensing of forest canopy and leaf biochemical contents

Recent research on the remote sensing of forest leaf and canopy biochemical contents suggests that the shortwave IR region contains this information; laboratory analyses of dry ground leaves have yielded reliable predictive relationships between both leaf nitrogen and lignin with near-IR spectra. Attention is given to the application of these laboratory techniques to a limited set of spectra from fresh, whole leaves of conifer species. The analysis of Airborne Imaging Spectrometer data reveals that total water content variations in deciduous forest canopies appear as overall shifts in the brightness of raw spectra.

Peterson, David L.↗

Semiconductor laser technology for remote sensing experiments

Semiconductor injection lasers are required for implementing virtually all spaceborne remote sensing systems. Their main advantages are high reliability and efficiency, and their main roles are envisioned in pumping and injection locking of solid state lasers. In some shorter range applications they may even be utilized directly as the sources.

Katz, Joseph↗

Submillimeter heterodyne remote sensing of upper atmospheric gases

Technology now becoming available for submillimeter heterodyne remote sensing of upper atmospheric gases is discussed. The general features of microwave limb sounding are reviewed, and the UARS Microwave Limb Sounder, a NASA mission dedicated to the comprehensive and integrated study of earth's upper atmosphere, is briefly described. The EOS Microwave Limb Sounder is briefly examined, showing its expected measurement capability for various gases.

Waters, Joe W.↗

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

Ground support for Space Shuttle earth observations by the NASA environment remote sensing analysis facility (ERSAF)

The functions and capabilities of the NASA Environment Remote Sensing Analysis Facility (ERSAF) located at the Johnson Space Center are described. ERSAF provides dedicated support to earth-observation activities and Earth-looking payloads conducted aboard the Space Shuttle. This support merges environmental satellite imagery with high-resolution film products and digital imagery acquired aboard the Space Shuttle. ERSAF utilizes several computer systems with specialized software to process and analyze environmental information as well as data acquired from the Space Shuttle. These computer systems and the image analysis capabilities are discussed.

Chambers, M. A.↗

Remote Sensing and Information Technology for Large Farms

A method of applying of remote sensing (RS) and information management technology to help large farms produce at maximum efficiency is undergoing development. The novelty of the method does not lie in the concept of "precision agriculture," which involves variation of seeding, of application of chemicals, and of irrigation according to the spatially and temporally local variations in the growth stages and health of crops and in the chemical and physical conditions of soils. The novelty also does not lie in the use of RS data registered with other data in a geographic information system (GIS) to guide the use of precise agricultural techniques. Instead, the novelty lies in a systematic approach to overcoming obstacles that, heretofore, have impeded the timely distribution of reliable, relevant, and sufficient GIS data to support day-to-day, acre-to-acre decisions concerning the application of precise agricultural techniques to increase production and decrease cost. The development and promotion of the method are inspired in part by a vision of equipping farm machinery to accept GIS (including RS) data and using the data for automated or semiautomated implementation of precise agricultural techniques. Primary examples of relevant GIS data include information on plant stress, soil moisture, and effects of applied chemicals, all derived by automated computational analysis of measurements taken by one or more airborne spectroradiometers. Proper management and timeliness of the large amount of GIS information are of paramount concern in agriculture. Information on stresses and changes in crops is especially perishable and important to farmers. The need for timeliness and management of information is satisfied by use of computing hardware and software capable of (1) rapid georectification and other processing of RS data, (2) packaging the output data in the form of GIS plots, and (3) making the data available to farmers and other subscribers by Internet password access. It is a goal of this development program to make RS data available no later than the data after an aerial survey. In addition, data from prior surveys are kept in the data base. Farmers can, for example, use current and prior data to analyze changes.

Williams, John E.↗

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regional cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.

54 ENVIRONMENTAL SCIENCES↗

Remote sensing of directional wave spectra using the surface contour radar

A unique radio-oceanographic remote sensing instrument was developed. The 36 GHz airborne Surface Contour Radar (SCR) remotely produces a real-time topographical map of the sea surface beneath the aircraft. It can routinely produce ocean directional wave spectra with off-line data processing. The transmitter is a coherent dual-frequency device that uses pulse compression to compensate for the limited available power at Ka band. The radar has selectable pulse widths of 1, 2, 4, and 10 nanoseconds. The transmitting antenna is a 58 lambda horn fed dielectric lens whose axis is parallel to the longitudinal axis of the aircraft. It illuminates an elliptical mirror which is oriented 45 deg to the lens' longitudinal axis to deflect the beam towards the region beneath the aircraft. The mirror is oscillated in a sinusoidal fashion through mechanical linkages driven to a variable speed motor to scan the transmitter beam (1.2 deg X 1.2 deg) with + or - 16 deg of the perpendicular to the aircraft wings in the plane perpendicular to the aircraft flight direction.

Walsh, E. J.↗

Microwave Interferometric Radiometry in Remote Sensing: an Invited Historical Review

The launch of the Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009 marked a milestone in remote sensing for it was the first time a radiometer capable of acquiring wide field of view images at every single snapshot, a unique feature of the synthetic aperture technique, made it to space. The technology behind such an achievement was developed, thanks to the effort of a community of researchers and engineers in different groups around the world. It was only because of their joint work that SMOS finally became a reality. The fact that the European Space Agency, together with CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnológico e Industrial), managed to get the project through should be considered a merit and a reward for that entire community. This paper is an invited historical review that, within a very limited number of pages, tries to provide insight into some of the developments which, one way or another, are imprinted in the name of SMOS.

Microwave↗

The SuperCam remote sensing instrument suite for the Mars 2020 rover mission: A preview

We present that the SuperCam remote sensing instrument suite under development for the National Aeronautics and Space Administration’s (NASA) Mars 2020 rover performs laser-induced breakdown spectroscopy (LIBS), remote Raman spectroscopy, visible and infrared (VISIR) reflectance spectroscopy, acoustic sensing, and high-resolution color imaging. The instrument builds on the successful architecture of the ChemCam instrument, which provides LIBS and panchromatic images on the Curiosity rover, adding remote Raman spectroscopy by frequency doubling the laser and using a gated intensified detector to obtain Raman signals at distances to 12 m. To the visible reflectance spectroscopy used by ChemCam, an acousto-optic tunable filter (AOTF)-based IR spectrometer is added to cover the 1.3–2.6 µm range that contains important mineral signatures. A complementary metal-oxide semiconductor (CMOS) detector provides color (Bayer filter) images at a pixel resolution of 19 µrad and an optical resolution of 30 µrad. Sounds are recorded via a Knowles Electret microphone, which is the same one that was included but not used on two earlier missions. The acoustic signals of the LIBS plasmas will provide information on the hardness of the targets, while other sounds (wind, rover sounds) will also be recorded. The laser, telescope, IR spectrometer, and camera reside on the rover’s mast and are provided by the Centre national d’etudes spatiales (CNES), while the LIBS, Raman, and VIS spectrometers and data processing unit are built by Los Alamos National Laboratory (LANL) and reside in the rover body. A calibration target assembly provided by the University of Valladolid, Spain, resides on the back of the rover. Lastly, the overall mass of the instrument suite is 10.7 kg.

47 OTHER INSTRUMENTATION↗

Imaging spectrometry for earth remote sensing

Initial results of the novel remote earth sensing technique of imaging spectrometry, which is technically feasible from both spacecraft and aircraft platforms, indicate that the direct identification of surface materials on a picture-element basis is possible through proper sampling of absorption features in the reflectance spectrum. Sensors of this type are able to acquire images simultaneously in 100-200 contiguous spectral bands. Computerized data reduction and storage techniques are available for the large data sets thus generated, and novel analytic techniques are under development to maximize information content extraction.

Goetz, A. F. H.↗

Remote sensing of coastal fronts and their effects on oil dispersion

The use of remote sensing techniques to determine the properties of coastal and estuarine fronts, which represent regions of discontinuities and high gradients in ocean physical parameters such as velocity and density, and to assess the influence of such fronts on oil pollutants is discussed. Results of an aircraft and boat verification study of an oil drift and spread model in Delaware Bay are indicated which illustrate the tendency of oil slicks to be attracted to frontal regions, where a denser fluid underlies a lighter fluid giving rise to an inclined interface with convergence zones. Landsat imagery of the bay acquired in order to incorporate frontal information into the interactive computer model is then presented which allows the locations of coastal fronts to be charted throughout a tidal cycle. It is noted that satellite observations of flood-associated fronts on the New Jersey side of the bay and ebb-associated fronts on the Delaware side agree with boat measurements and model predictions, and that the remote tracking of fronts by aircraft and satellites will aid in oil slick clean-up operations.

Klemas, V.↗

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

The review of optical instrumentation, forward modeling, and inverse problem solution for the polarimetric aerosol remote sensing from space is presented. The special emphasis is given to the description of current airborne and satellite imaging polarimeters and also to modern satellite aerosol retrieval algorithms based on the measurements of the Stokes vector of reflected solar light as detected on a satellite. Various underlying surface reflectance models are discussed and evaluated.

polarimetry↗

Vision Foundation Models in Remote Sensing: A survey

Artificial intelligence (AI) technologies have profoundly transformed the field of remote sensing (RS), revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, RS research has been significantly enhanced by the advent of foundation models (FMs)—large-scale pretrained AI models capable of performing a wide array of tasks with unprecedented accuracy and efficiency. This article provides a comprehensive survey of FMs in the RS domain. We categorize these models based on their architectures, pretraining datasets, and methodologies. Through detailed performance comparisons, we highlight emerging trends and the significant advancements achieved by those FMs. Additionally, we discuss technical challenges, practical implications, and future research directions, addressing the need for high-quality data, computational resources, and improved model generalization. Our research also finds that pretraining methods, particularly self-supervised learning (SSL) techniques like contrastive learning (CL) and masked autoencoders (MAEs), remarkably enhance the performance and robustness of FMs. This survey aims to serve as a resource for researchers and practitioners by providing a panorama of advances and promising pathways for the continued development and application of FMs in RS.

data models↗