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At least 1,279 records · Page 71

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of wildlife areas in eastern South Dakota

A soils map for land evaluation in Potter County (Eastern South Dakota) was developed to demonstrate the use of remote sensing technology in the area of diverse parent materials and topography. General land use and soils maps have also been developed for land planning LANDSAT, RB-57 imagery, and USGS photographs are being evaluated for making soils and land use maps. LANDSAT fulfilled the requirements for general land use and a general soils map. RB-57 imagery supplemented by large scale black and white stereo coverage was required to provide the detail needed for the final soils map for land evaluation. Color infrared prints excelled black and white coverage for this soil mapping effort. An identification and classification key for wetland types in the Lake Dakota Plain was developed for June 1975 using color infrared imagery. Wetland types in the region are now being mapped via remote sensing techniques to provide a current inventory for development of mitigation measures.

Source record↗

A Multi-Band Analytical Algorithm for Deriving Absorption and Backscattering Coefficients from Remote-Sensing Reflectance of Optically Deep Waters

A multi-band analytical (MBA) algorithm is developed to retrieve absorption and backscattering coefficients for optically deep waters, which can be applied to data from past and current satellite sensors, as well as data from hyperspectral sensors. This MBA algorithm applies a remote-sensing reflectance model derived from the Radiative Transfer Equation, and values of absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. There are only limited empirical relationships involved in the algorithm, which implies that this MBA algorithm could be applied to a wide dynamic range of waters. Applying the algorithm to a simulated non-"Case 1" data set, which has no relation to the development of the algorithm, the percentage error for the total absorption coefficient at 440 nm a (sub 440) is approximately 12% for a range of 0.012 - 2.1 per meter (approximately 6% for a (sub 440) less than approximately 0.3 per meter), while a traditional band-ratio approach returns a percentage error of approximately 30%. Applying it to a field data set ranging from 0.025 to 2.0 per meter, the result for a (sub 440) is very close to that using a full spectrum optimization technique (9.6% difference). Compared to the optimization approach, the MBA algorithm cuts the computation time dramatically with only a small sacrifice in accuracy, making it suitable for processing large data sets such as satellite images. Significant improvements over empirical algorithms have also been achieved in retrieving the optical properties of optically deep waters.

Lee, Zhong-Ping↗

Remote Sensing Reflectance and Inherent Optical Properties in the Mid-mesohaline Chesapeake Bay

We used an extensive set of bio-optical data and radiative transfer (RT) model simulations of radiation fields to investigate relationships between inherent optical properties and remotely sensed quantities in the optically complex, mid-mesohaline Chesapeake Bay waters. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, when applied to waters with high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue-green wavelength remote sensing reflectance (Rrs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. Stronger correlation was observed between chlorophyll concentration and Rrs ratios in the red (i.e. Rrs(677)/Rrs(554)) where dissolved and non-algal particulate absorption become exponentially smaller. Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Good optical closure was obtained between independently measured Rrs spectra and the optical properties of backscattering, b(sub b), and absorption, a, over the wide range of in-water conditions observed in the Chesapeake Bay. Observed variability in the quantity f/Q (proportionality factor in the relationship between Rrs and the water inherent optical properties ratio b(sub b)/(a+b(sub b)) was consistent with RT model calculations for the specific measurement geometry and water bio-optical characteristics. Data and model results showed that f/Q values in these Case 2 coastal waters are not considerably different from those estimated in previous studies for Case 1 waters. Variation in surface backscattering significantly affected Rrs magnitude across the visible spectrum and was most strongly correlated (R(sup 2)=0.88) with observed variability in Rrs at 670 nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a(sub nap), in the blue wavelengths (R(sup 2)=0.83). These results, along with the measured values of backscattering fraction magnitude and non-algal particulate absorption spectral slope, suggest that suspended non-algal particles with high inorganic content are the major water constituents regulating b(sub b) variability in the mid-mesohaline Chesapeake Bay. Remote retrieval of surface b(sub b) and (a(sub nap), from Rrs(670) can be used in regionally-specific satellite algorithms to separate contribution by non-algal particles and dissolved organic matter to total light absorption in the blue, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters.

Tzortziou, Maria↗

Remote sensing of biomass of salt marsh vegetation in France

Spectral data (gathered using a hand-held radiometer) and harvest data were collected from four salt marsh vegetation types in Brittany, France, to develop equations predicting live aerial biomass from spectral measurements. Remote sensing estimates of biomass of the general salt marsh community (GSM) and of Spartina alterniflora can be obtained throughout the growing season if separate biomass prediction equations are formulated for different species mixtures (for the GSM) and for different canopy types (for S. alterniflora). Results suggest that remote sensing will not be useful for predicting Halimione portulacoides biomass, but can be used to estimate Puccinellia maritima biomass early in the growing season.

Gross, M. F.↗

Recent Advances in Maya Studies Using Remotely Sensed Data

The Peten region of northern Guatemala is one of the last places on earth where major archeological sites remain to be discovered. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper and IKONOS satellite and airborne Star3i radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as cities, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. The use of baJos for farming has been a source of debate within the professional community for many years. But the recent detection and verification of cultural features within the baJo system by our research team are providing conclusive evidence that the ancient Maya had adapted well to wetland environments from the earliest times and utilized them until the time of the Maya collapse. The combination of water management and baJo farming is an important resource for the future of the current inhabitants who are experiencing rapid population growth. Remote sensing imagery is also demonstrating that in the Preclassic period (600 BC- AD 250), the Maya had already achieved a high organizational level as evidenced by the construction of massive temples and an elaborate inter-connecting roadway system. Although they experienced several setbacks such as droughts and hurricanes, the Maya nevertheless managed the delicate forest ecosystem successfully for several centuries. However, around AD 800, something happened to the Maya to cause their rapid decline and eventual disappearance from the region. The evidence indicates that at this time there was increased climatic dryness, extensive deforestation, overpopulation, and widespread warfare. This raises a relevant question today-namely, how severe do internal stresses in a civilization have to become before relatively minor climate shifts can cause a widespread cultural collapse?

Sever, Tom↗

Recent Advances in Maya Studies Using Remotely Sensed Data

The Peten region of northern Guatemala is one of the last places on earth where major archeological sites remain to be discovered. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper and IKONOS satellite and airborne Star3i radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as cities, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the baJos, which are seasonally flooded swamps that cover over 40% of the land surface. The use of bajos for farming has been a source of debate within the professional community for many years. But the recent detection and verification of cultural features within the bajo system by our research team are providing conclusive evidence that the ancient Maya had adapted well to wetland environments from the earliest times and utilized them until the time of the Maya collapse. The combination of water management and bajo farming is an important resource for the future of the current inhabitants who are experiencing rapid population growth. Remote sensing imagery is also demonstrating that in the Preclassic period (600 BC- AD 250), the Maya had already achieved a high organizational level as evidenced by the construction of massive temples and an elaborate inter-connecting roadway system. Although they experienced several setbacks such as droughts and hurricanes, the Maya nevertheless managed the delicate forest ecosystem successfully for several centuries. However, around AD 800, something happened to the Maya to cause their rapid decline and eventual disappearance from the region. The evidence indicates that at this time there was increased climatic dryness, extensive deforestation, overpopulation, and widespread warfare. This raises a relevant question today-namely, how severe do internal stresses in a civilization have to become before relatively minor climate shifts can cause a widespread cultural collapse?

Sever, Tom↗

Marketing Remote Sensing Data for North Pacific Fisheries Development and Management

Fish poaching, drug trafficking, ocean dumping, and other illegal activities are important problems on the high seas and in national economic zones. The primary thrust of the EOCAP II project, "Marketing Remote Sensing Data for North Pacific Fisheries Development and Management", was to use space-based sensors to improve the effectiveness of marine monitoring, control, and surveillance (MCS). Our initial objectives were to concentrate on the development of MCS tools using Advanced Very High Resolution Radiometry (AVHRR) and Synthetic Aperture Radar (SAR) data. Although we have successfully completed development of an initial version of our SAR-based monitoring tool (OmniVision), project activity has resulted in a much broader application of space-based assets to marine applications. Based in part on work commenced within EOCAP II, a new company, Ocean and Coastal Environmental Sensing, Inc. (OCENS), has been launched and the development of several new software products outside of the MCS arena initiated. One of those products, SeaStation, is near completion with a Fall, 1995 release date. Equity investment in OCENS now totals $70,000-with an additional amount being sought in the first round of financing. One of the pre-eminent objectives of EOCAP II is to make contributions to the US economy and job growth through the expansion of commercial uses of remotely sensed data. OCENS and the software products it is introducing into marine and coastal zone markets responds to this primary object*e. EOCAP II funding leveraged the market and technical know-how of OCENS founders into smart products that benefit marine and coastal zone users. Although technical difficulties and geopolitical shifts damaged the commercial feasibility of initial project objectives, the flexibility of the EOCAP II program now permits long-term business success. This in no small part stems from the fact that the EOCAP program recognizes the realities of small and start-up businesses and does not attempt to force these conditions to fit the apparent needs of big government. Instead, EOCAP works with those who know their market best in order to produce successful products and expanding businesses.

Source record↗

Possible lunar source areas of meteorite ALHA 81005 Geochemical remote sensing information

Antarctic meteorite ALHA 81005 is a regolith breccia apparently sent to earth by an impact event in the lunar highlands. Laboratory studies of this sample provide information that is used to understand the source region on the moon using remote sensing data. The meteorites low thorium content is inconsistent with thorium values measured for the central lunar nearside from orbit with Apollo gamma-ray spectrometers. Similarly, the mineral assemblages inferred from near-IR spectra of small impact craters on the lunar nearside do not exhibit the significant component of olivine and Fe-bearing feldspar that is observed in the meteorite spectra. The existing remote sensing data suggest the most probable source region for ALHA 81005 is the nearside limb or the lunar farside and that the composition of ALHA 81005 represents a surface unit that has not previously been extensively sampled.

Pieters, C. M.↗

Deep learning models map rapid plant species changes from citizen science and remote sensing data

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model— Deepbiosphere— not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Gillespie, Lauren E.↗

A Summary of Microwave Remote Sensing Investigations Planned for Boreas

The Boreal Ecosystem - Atmosphere Study (BOREAS) is a multidisciplinary field and remote sensing study that will be implemented jointly by the United States and Canada. The Goal of Boreas is to obtain an improved understanding of the interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change.

Microwave↗

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Menzel, W. Paul↗

Annual Sea Level Variability Induced by Changes in Sea Ice Extent and Accumulation on Ice Sheets: An Assessment Based on Remotely Sensed Data

Changes of mean annual net accumulation at the surface on the grounded ice sheets of East Antarctica, West Antarctica, and Greenland in response to variations in sea ice extent are estimated using grid-point values 100 km apart. The data bases are assembled principally by bilinear interpolation of remotely sensed brightness temperature (Nimbus-5 ESMR, Nimbus-7 SMMR), surface temperature (Nimbus-7 THIR), and surface elevation (ERS-1 radar altimeter). These data, complemented by field data where remotely sensed data are not available, are used in multivariate analyses in which mean annual accumulation (derived from firn emissivity) is the dependent variable; the independent variables are latitude, surface elevation, mean annual surface temperature, and mean annual distance to open ocean (as a source of energy and moisture). The last is the shortest distance measured between a grid point and the mean annual position of the 10% sea ice concentration boundary, and is used as an index of changes in sea ice extent as well as of mean concentration. Stepwise correlation analyses indicate that variations in sea ice extent of +/-50 km would lead to changes in accumulation inversely of +/-4% on East Antarctica, +/- 10% on West Antarctica, and +4% on Greenland. These results are compared with those obtained in a previous study using visually interpolated values from contoured compilations of field data; they substantiate the findings for the Antarctic ice sheets (+/-4% on East Antarctica, +/-9% in West Antarctica), and suggest a reduction by one half of the probable change of accumulation on Greenland (from +/-8%). The results also suggest a reduction of the combined contribution to sea level variability to +/- 0.19 mm/a (from +/- 0.22 mm/a).

Zwally, H. J.↗

Variograms and spatial variation in remotely sensed images

Research is presented that is aimed at developing a link or connection between ground scenes and spatial variation in images. The link is established through the use of models of scenes and a measure of spatial variation - the variogram. The approach used to explore the nature of spatial variation in remotely sensed images can be thought of as a 'bottom up' approach because it starts with a model of the scene and works toward the characteristics of a remotely sensed image derived from the scene. To date, observed images at two resolutions for each of three kinds of environment have been used to evaluate the use of variograms in real images. The images are from forests, residential, and agricultural environments. One resolution used is 30 m from the Thematic Mapper or Thematic Mapper Simulator. For each environment also there is fine resolution data from the range of 0.15-2.5 m. It is noted that variograms from these images show considerable structure. Work continues on checking the validity of the disk model (a way of representing trees and their shadows).

Woodcock, C.↗

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.↗

Testing an Energy Balance Model for Estimating Actual Evapotranspiration Using Remotely Sensed Data

An energy-balance model is used to estimate daily evapotranspiration for 3 days for a barley field and a wheat field near Hannover, Federal Republic of Germany. The model was calibrated using once-daily estimates of surface temperatures, which may be remotely sensed. The evaporation estimates were within the 95% error bounds of independent eddy correlation estimates for the daytime periods for all three days for both sites, but the energy-balance estimates are generally higher; it is unclear which estimate is biassed. Soil moisture in the top 2 cm of soil, which may be remotely sensed, may be used to improve these evaporation estimates under partial ground cover. Sensitivity studies indicate the amount of ground data required is not excessive.

Gurney, R. J.↗

Remote Sensing of Terrestrial Snow and Ice for Global Change Studies

Snow and ice play a significant role in the Earth's water cycle and are sensitive and informative indicators climate change. Significant changes in terrestrial snow and ice water storage are forecast, and while evidence of large-scale changes is emerging, in situ measurements alone are insufficient to help us understand and explain these changes. Imaging remote sensing systems are capable of successfully observing snow and ice in the cryosphere. This chapter examines how those remote sensing sensors, that now have more than 35 years of observation records, are capable of providing information about snow cover, snow water equivalent, snow melt, ice sheet temperature and ice sheet albedo. While significant progress has been made, especially in the last five years, a better understanding is required of the records of satellite observations of these cryospheric variables.

Kelly, Richard↗

Survey of university programs in remote sensing funded under grants from the NASA University-Space Applications program

NASA's Office of Space and Terrestrial Applications (OSTA) is currently assessing approaches to transferring NASA technology to both the public and private sectors. As part of this assessment, NASA is evaluating the effectiveness of an ongoing program in remote sensing technology transfer conducted by 20 university contractors/grantees, each supported totally or partially by NASA funds. The University-Space Applications program has as its objective the demonstration of practical benefits from the use of remote sensing technology to a broad spectrum of new users, principally in state and local governments. To evaluate the University-Space Applications program, NASA has a near-term requirement for data on each university effort including total funding, funding sources, length of program, program description, and effectiveness measures.

Madigan, J. A.↗