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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Remote Sensing of Suspended Sediments and Shallow Coastal Waters

Ocean color sensors were designed mainly for remote sensing of chlorophyll concentrations over the clear open oceanic areas (case 1 water) using channels between 0.4 and 0.86 micrometers. The Moderate Resolution Imaging Spectroradiometer (MODIS) launched on the NASA Terra and Aqua Spacecrafts is equipped with narrow channels located within a wider wavelength range between 0.4 and 2.5 micrometers for a variety of remote sensing applications. The wide spectral range can provide improved capabilities for remote sensing of the more complex and turbid coastal waters (case 2 water) and for improved atmospheric corrections for Ocean scenes. In this article, we describe an empirical algorithm that uses this wide spectral range to identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. The algorithm takes advantage of the strong water absorption at wavelengths longer than 1 micrometer that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

Li, Rong-Rong↗
NASA NTRS1976

The application of remote sensing to resource management and environmental quality programs in Kansas

Activities of the Kansas Applied Remote Sensing Program (KARS) designed to establish interactions on cooperative projects with decision makers in Kansas agencies in the development and application of remote sensing procedures are reported. Cooperative demonstration projects undertaken with several different agencies involved three principal areas of effort: Wildlife Habitat and Environmental Analysis; Urban and Regional Analysis; Agricultural and Rural Analysis. These projects were designed to concentrate remote sensing concepts and methodologies on existing agency problems to insure the continued relevancy of the program and maximize the possibility for immediate operational use. Completed projects are briefly discussed.

Barr, B. G.↗
NASA NTRS1983

The application of remote sensing to resource management and environmental quality programs in Kansas

The activities of the Kansas Applied Remote Sensing (KARS) Program during the period April 1, 1982 through Marsh 31, 1983 are described. The most important work revolved around the Kansas Interagency Task Force on Applied Remote Sensing and its efforts to establish an operational service oriented remote sensing program in Kansas state government. Concomitant with this work was the upgrading of KARS capabilities to process data for state agencies through the vehicle of a low cost digital data processing system. The KARS Program continued to take an active role in irrigation mapping. KARS is now integrating data acquired through analysis of LANDSAT into geographic information systems designed for evaluating groundwater resources. KARS also continues to work at the national level on the national inventory of state natural resources information systems.

Barr, B. G.↗
NASA NTRS1978

Relation of laboratory and remotely sensed spectral signatures of ocean-dumped acid waste

Results of laboratory transmission and remotely sensed ocean upwelled spectral signatures of acid waste ocean water solutions are presented. The studies were performed to establish ocean-dumped acid waste spectral signatures and to relate them to chemical and physical interactions occurring in the dump plume. The remotely sensed field measurements and the laboratory measurements were made using the same rapid-scanning spectrometer viewing a dump plume and with actual acid waste and ocean water samples, respectively. Laboratory studies showed that the signatures were produced by soluble ferric iron being precipitated in situ as ferric hydroxide upon dilution with ocean water. Sea-truth water samples were taken and analyzed for pertinent major components of the acid waste. Relationships were developed between the field and laboratory data both for spectral signatures and color changes with concentration. The relationships allow for the estimation of concentration of the indicator iron from remotely sensed spectral data and the laboratory transmission concentration data without sea-truth samples.

Lewis, B. W.↗
NASA NTRS1980

Investigation of the application of remote sensing technology to environmental monitoring

Activities and results are reported of a project to investigate the application of remote sensing technology developed for the LACIE, AgRISTARS, Forestry and other NASA remote sensing projects for the environmental monitoring of strip mining, industrial pollution, and acid rain. Following a remote sensing workshop for EPA personnel, the EOD clustering algorithm CLASSY was selected for evaluation by EPA as a possible candidate technology. LANDSAT data acquired for a North Dakota test sight was clustered in order to compare CLASSY with other algorithms.

Rader, M. L.↗
NASA NTRS1981

Remote sensing techniques for conservation and management of natural vegetation ecosystems

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

Parada, N. D. J.↗
NASA NTRS1998

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Soman, Vishwas V.↗
NASA NTRS1991

The application of geologic remote sensing to vertebrate biostratigraphy - General results from the Wind River Basin, Wyoming

Since 1986, remote sensing images derived from satellite and aircraft-borne sensor data have been used to study the stratigraphy and sedimentology of the vertebrate-bearing Wind River and Wagon Bed formations in the Wind River Basin (Wyoming). Landsat 5 TM and aircraft Thermal Infrared Multispectral Scanner data were combined with conventional geologic analyses. The remote sensing data have contributed significantly to: (1) geologic mapping at the formation, member, and bed levels; (2) stratigraphic correlation; (3) reconstruction of ancient depositional environments; and (4) identification of structural complexity. This information is critical to vertebrate paleontology in providing the stratigraphic, sedimentologic, and structural framework required for evolutionary and paleoecologic studies. Of primary importance is the ability to map at minimal cost the geology of large areas (20,000 sq km or greater) at a high level of precision. Remote sensing data can be especially useful in geologically and paleontologically unexplored or poorly understood regions.

Stucky, Richard K.↗
NASA NTRS1998

The Application of Aperture Synthesis to the Remote Sensing of Sea Surface Salinity From Space

Sea surface salinity is measured optimally at the long wavelength end of the microwave spectrum in order to maximize radiometric sensitivity to changes in salinity. Long wavelengths (e.g. L-band) mean large antennas in space, and because of the technological challenge associated with putting large scanning antennas in orbit, no system currently exists to measure salinity. Aperture synthesis is an interferometric technique to make deployment of large antenna apertures in space feasible. It uses pairs of small antennas and signal processing to achieve the resolution of a single large aperture. Aperture synthesis has been demonstrated successfully for remote sensing by the aircraft prototype radiometer, ESTAR. ESTAR is an L-band instrument which employs aperture synthesis in the cross track dimension. Recent measurements with ESTAR of the fresh water outflow from the Delaware River are in good agreement (about 1 psu) with shipboard thermosalinograph measurements. Synthetic aperture radiometers are currently being developed for remote sensing from space. HYDROSTAR is an instrument for remote sensing from space based on the design of ESTAR. It employs aperture synthesis in one dimension and is being proposed as a pathfinder instrument to make global maps of soil moisture and sea surface salinity and to demonstrate the feasibility of aperture synthesis for remote sensing from space. Instruments which use remote sensing in two dimensions are currently being developed by the European Space Agency. These instruments include additional channels (frequencies and polarizations) and may be able to achieve radiometric sensitivity and spatial resolution to meet the diverse needs of the coastal zone and open ocean oceanographic communities.

LeVine, David M.↗
NASA NTRS1996

Geomorphic Processes and Remote Sensing Signatures of Alluvial Fans in the Kun Lun Mountains, China

Remote sensing techniques may be used to assist in regional mapping of geomorphic units related to past climate changes through their sensitivity to roughness and composition. Radar images from the Spaceborne Radar Laboratory and visible-wavelength images from the French SPOT satellite were used to determine remote sensing signatures of alluvial fan units for an area in the Kun Lun Mountains of northwestern China.

remote↗
NASA NTRS1991

Commercial remote sensing small satellite feasibility study

The Stennis Space Center acts as the program office for remote sensing activities on behalf of the NASA Office of Commercial Programs. Stennis is supplying systems engineering support to determine the technical and economic feasibility of a commercial remote sensing small satellite. Study efforts focus on the systems design of launch vehicle, sensor system, communications, attitude control, power, computational processing, and ground station capabilities. Results reveal that an example small satellite system, with a limited capability remote sensing payload, could be deployed for less than $20M. Technological advances and overall cost reductions in space systems may enable industry to develop new and expanded information service markets.

Birk, Ronald J.↗
NASA NTRS1998

Environmental Remote Sensing: New Development and Applications

The term 'scale', both in space and time, is central to remote sensing and geographic information systems (GIS). The emergency and widespread use of GIS technologies, including remote sensing, has generated interest in addressing scale as generic Issue, and in the development and implementation of techniques for dealing explicitly with the vicissitudes of scale as a multidisciplinary issue. Traditionally, the paper map has been used as the primary conveyor of 'scale', represented by the ratio between the distance as measured between pairs of points on the map and distance as measured between the same pairs of points on the Earth's surface. GIS and remote sensing, however, have expanded upon the paper map and now provide opportunities for representing multiscale representations; that is databases or models that contain spatial and temporal data that have been obtained and stored at different scales.

Quattrochi, Dale A.↗
NASA NTRS2011

Current NASA Earth Remote Sensing Observations

This slide presentation reviews current NASA Earth Remote Sensing observations in specific reference to improving public health information in view of pollen sensing. While pollen sampling has instrumentation, there are limitations, such as lack of stations, and reporting lag time. Therefore it is desirable use remote sensing to act as early warning system for public health reasons. The use of Juniper Pollen was chosen to test the possibility of using MODIS data and a dust transport model, Dust REgional Atmospheric Model (DREAM) to act as an early warning system.

Luvall, Jeffrey C.↗
NASA NTRS2010

Using Remotely Sensed Data to Map Urban Vulnerability to Heat

This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.

Stefanov, William L.↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗
NASA NTRS2013

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters : Synthetic Sensor Radiance Formulation - Pt. 1

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Simulations↗