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At least 667 records · Page 37

Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual variability in the observations, although reasons for persistent discrepancies in northern hemisphere vegetation uptake are examined. At this time, we do not find any serious shortcomings in the model transport representation, but this is still the subject of close scrutiny. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in CO2 fluxes and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

Agricultural applications of remote sensing: A true life adventure

A study of agricultural applications of remote sensing with a major US agricultural firm was undertaken in mid-1973. The study continued for eighteen months, and covered the areas of crop monitoring and management as well as large scale crop inventories. Pilot programs in the application of aircraft remote sensing and LANDSAT data were conducted. An operational aircraft survey program for ranch management has subsequently been implemented by the agricultural firm. LANDSAT data was successfully used to produce a ninety-seven percent accurate inventory of cotton over 4.8 million acres of California's San Joaquin Valley.

Schaller, E. S.↗

Remote sensing of wet lands in irrigated areas

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Ham, H. H.↗

Remote sensing of tropical forests - An overview of research and applications using non-photographic sensors

A comprehensive overview is presented on how remote sensing technology has been applied to tropical forest monitoring over the past 20 years. Research needs for monitoring the condition and extent of tropical forests are suggested. The discussion focuses on nonphotographic sensors, especially those on orbiting satellites. Several remote sensing approaches to tropical forest monitoring are outlined, including NOAA AVHRR, Landsat MSS, the Landsat Thematic Mapper, SPOT-1, and Synthetic Aperture Radar. Suggested research needs are addressed, along with discussions on the use of Geographic Information Systems, and multistage and multisensor approaches in data analysis and acquisition. It is concluded that additional research and technique development is urgently needed to advance the utility of remotely sensed data for tropical forest monitoring. However, there is sufficient information available now to prototype a global tropical forest monitoring system that would utilize current satellite sensors complemented with airborne sensors for detailed measurements on sample locations.

Sader, Steven A.↗

Remote sensing R&D planning

A NASA method is described for forecasting remote sensing needs in the last decade of this century and for planning the necessary space system technology R&D. Five- and ten-year plans for earth observations in various disciplines are extrapolated forward to circa 1995 via a scenario which envisions major advances in remote sensing and information management. Space system studies identify the 'technology drivers', and development programs are initiated to develop the enabling technology. An example is given for a multipurpose large-aperture microwave radiometer spacecraft.

Keafer, L. S., Jr.↗

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

58 GEOSCIENCES↗

A review of future remote sensing satellite capabilities

Existing, planned and future NASA capabilities in the field of remote sensing satellites are reviewed in relation to the use of remote sensing techniques for the identification of irrigated lands. The status of the currently operational Landsat 2 and 3 satellites is indicated, and it is noted that Landsat D is scheduled to be in operation in two years. The orbital configuration and instrumentation of Landsat D are discussed, with particular attention given to the thematic mapper, which is expected to improve capabilities for small field identification and crop discrimination and classification. Future possibilities are then considered, including a multi-spectral resource sampler supplying high spatial and temporal resolution data possibly based on push-broom scanning, Shuttle-maintained Landsat follow-on missions, a satellite to obtain high-resolution stereoscopic data, further satellites providing all-weather radar capability and the Large Format Camera.

Calabrese, M. A.↗

Survey of instructional material for remote sensing

The contents of 17 major textbooks and reference guides on remote sensing technology are listed and compared. As a group, these books concentrate more on principles of the electromagnetic spectrum, sensors and data processing, than on applications. Secondly, it appears that basic photointerpretation receives considerable attention, but that photogrammetry does not. Four texts which provide well-rounded treatments of the systematics of remote sensing are suggested.

Morain, S. A.↗

Beaufort/Bering 1979 microwave remote sensing data catalog report, 14-24 March 1979

The airborne microwave remote sending measurements obtained by the Langley Research Center in support of the 1979 Sea-Ice Radar Experiment (SIRE) in the Beaufort and Bering Seas are discussed. The remote sensing objective of SIRE was to define correlations between both active and passive microwave signatures and ice phenomena assocated with practical applications in the Arctic. The instruments used by Langley during SIRE include the stepped frequency microwave radiometer (SFMR), the airborne microwave scatterometer (AMSCAT), the precision radiation thermometer (PRT-5), and metric aerial photography. Remote sensing data are inventoried and cataloged in a user-friendly format. The data catalog is presented as time-history plots when and where data were obtained as well as the sensor configuration.

Hirstein, W. S.↗

The potential of expert systems for remote sensing

The use of expert systems for the interpretation of remote-sensing data is discussed. Expert-system architectures are described; the systems in use, under development, or proposed in various scientific and industrial fields are listed in a table; and three image-interpretation systems are briefly characterized. It is found that expert systems have the potential to perform repetitive interpretation of image data compiled from various remote-sensing satellites, especially to detect changes over time as in the case of deforestation. A system comprising an image interpreter, change interpreter, a cause interpreter, and a global data base is outlined and illustrated with a diagram.

Mooneyhan, D. W.↗

Development of satellite remote sensing techniques as an economic tool for forestry industry

A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?

Sader, Steven A.↗

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗

Thermal infrared remote sensing of crude oil slicks

Unambiguous detection of oil slicks by remote sensing techniques has proven an elusive goal. This article presents new thermal infrared spectra of oil slicks made from five different crude oil samples with a wide range of API gravities and compositions. After a brief outgassing phase, all oil slick spectra are quite similar and little affected by thickness, extended exposure to air or sunlight, and even by emulsification with seawater (mousse formation). Thus, oil slicks provide a remarkably unvarying spectral signature as remote sensing targets in the thermal infrared compared to other regions of the spectrum. This spectral signature in the 8-14 micron atmospheric window is flat, with an average reflectance of 4 percent. Seawater, on the other hand, has a spectrum that varies in reflectance with wavelength in the 8-14 micron window from 0.90 to 3.65 percent. In addition, we show that sea foam displays a reflectance spectrum quite similar to that of seawater in the 8-14 micron region. This results in a relatively uniform spectral background, against which oil slicks can be detected, based on their different spectral signature.

Salisbury, John W.↗

Research Issues in Image Registration for Remote Sensing

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

Eastman, Roger D.↗

Modeling the Effect of Vegetation on Passive Microwave Remote Sensing of Soil Moisture

The effect of vegetation on passive microwave remote sensing of soil moisture is studied. The radiative transfer modeling work of Njoku and Kong is applied to a stratified medium of which the upper layer is treated as a layer of vegetation. An effective dielectric constant for this vegetation layer is computed using estimates of the dielectric constant of individual components of the vegetation layer. The horizontally-polarized brightness temperature is then computed as a function of the incidence angle. Model predictions are used to compare with the data obtained in the Huntsville '96, remote sensing of soil moisture experiment, and with predictions obtained using a correction procedure of Jackson and Schmugge.

Liu, Y. P.↗

Remote sensing: Snow monitoring tool for today and tomorrow

Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

Rango, A.↗

The NASA Icing Remote Sensing System

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data are post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Although the comparison data set is quite small, the cases examined indicate that the remote sensing technique appears to be an acceptable approach.

Reehorst, Andrew L.↗