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Current references were surveyed for the application of remote sensing to traffic and transportation studies. The major problems are presented that concern traffic engineers and transportation managers, and the literature references that discuss remote sensing applications are summarized.
This review covers the optical design of passive remote sensing optical instruments. The review concentrates on the design of spaceborne multispectral cameras and imaging spectometers. The major designs that have been produced over the past ten years are discussed, and new designs for future imaging spectrometers are presented.
Advantages and disadvantages of traditional methods of obtaining required information for land and resources management and the possibilities of remote sensing are discussed. The services available, organization and objectives of the pilot operation are presented. Emphasis is placed on multidisciplinary dialog among designers, builders, operators, interpreters and users in all phases. The principles, operation and practical applications of remote sensing systems and processing systems under the pilot operation are presented.
A portion of the highlands terrain northwest of the Humorum basin, a large multiringed impact structure on the southwestern portion of the lunar nearside, exhibits anomalous characteristics in several remote sensing data sets. A variety of remote sensing studies of the terrain northwest of Humorum basin were performed in order to determine the composition and origin of the anomalous unit as well as the composition of the highland material exposed by the Humorum impact event. It was found that at least a portion of the mare-bounding ring of Humorum is composed of pure anorthosite. Other details of the study are reported.
Pennsylvania Abandoned Mine Land Inventory demonstrated the effective use of remote sensing techniques within the context of the Surface Mining Control and Reclamation Act of 1977. The inventory combined data from field work, a literature search, and photointerpretation to fulfill both State and Federal requirements. A primary project objective was to accurately identify and map all surface features and disturbances from abandoned surface and underground mining. Black-and-white aerial photographs were used to record pits, contour benches, highwalls, spoil material, graded and recontoured areas, impounded water, and serious erosion and slide prone areas. In addition, vegetation cover estimates and surrounding land uses were noted. The inventory data base provides Pennsylvania with a valuable resource management tool that should be systematically updated. The utilization of remotely sensed data from SPOT or LANDSAT-D satellites may prove valuable in the anticipated updating and monitoring of the Pennsylvania AML inventory over the next several years.
The concept of integrating ecological perspectives on early man's settlement patterns with advanced remote sensing technologies shows promise for predictive site modeling. Early work with aerial imagery and ecosystem analysis is discussed with respect to the development of a major project in Maya archaeology supported by NASA and the National Geographic Society with technical support from the Mississippi State Remote Sensing Center. A preliminary site reconnaissance model will be developed for testing during the 1991 field season.
The Arctic is home to many indigenous peoples, including those who depend on reindeer herding for their livelihood, in one of the harshest environments in the world. For the largely nomadic peoples, reindeer not only form a substantial part of the Arctic food base and economy, but they are also culturally important, shaping their way of life, mythologies, festivals and ceremonies. Reindeer pastoralism or husbandry has been practiced by numerous peoples all across Eurasia for thousands of years and involves moving herds of reindeer, which are very docile animals, from pasture to pasture depending on the season. Thus, herders must adapt on a daily basis to find optimal conditions for their herds according to the constantly changing conditions. Climate change and variability plus rapid development are increasingly creating major changes in the physical environment, ecology, and cultures of these indigenous reindeer herder communities in the North, and climate changes are occurring significantly faster in the Arctic than the rest of the globe, with correspondingly dramatic impacts (Oskal, 2008). In response to these changes, Eurasian reindeer herders have created the EALAT project, a comprehensive new initiative to study these impacts and to develop local adaptation strategies based upon their traditional knowledge of the land and its uses - in targeted partnership with the science and remote sensing community - involving extensive collaborations and coproduction of knowledge to minimize the impacts of the various changes. This chapter provides background on climate and development challenges to reindeer husbandry across the Arctic and an overview of the EALAT initiative, with an emphasis on indigenous knowledge, remote sensing, Geographic Information Systems (GIS), and other scientific data to 'co-produce' datasets for use by herders for improved decision-making and herd management. It also provides a description of the EALAT monitoring data integration and sharing system and portal being developed for reindeer pastoralism. In addition, the chapter provides some preliminary results from the EALAT Project, including some early remote sensing research results.
The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS Aqua Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and MODIS in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for MODIS.
One of the more fortunate outcomes of the capture and transformation of remote sensing data into applied information is their usefulness and impacts to better understanding climatological impacts on public health. Today, with petabytes of remote sensing data providing global coverage of climatological parameters, public health research and policy decision makers have an unprecedented (and growing) data record that relates the effects of climatic parameters, such as rainfall, heat, soil moisture, etc. to incidences and spread of disease, as well as predictive modeling. In addition, tools and services that specifically serve public health researchers and respondents have grown in response to needs of the these information users.
Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.
Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.
Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interference-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.
Project MEDSAT was proposed with the specific goal of designing a satellite to remotely sense pertinent information useful in establishing strategies to control malaria. The 340 kg MEDSAT satellite is to be inserted into circular earth orbit aboard the Pegasus Air-Launched Space Booster at an inclination of 21 degrees and an altitude of 473 km. It is equipped with a synthetic aperture radar and a visible thermal/infrared sensor to remotely sense conditions at the target area of Chiapas, Mexico. The orbit is designed so that MEDSAT will pass over the target site twice each day. The data from each scan will be downlinked to Hawaii for processing, resulting in maps indicating areas of high malaria risk. These will be distributed to health officials at the target site. A relatively inexpensive launch by Pegasus and a design using mainly proven, off-the-shelf technology permit a low mission cost, while innovations in the satellite controls and the scientific instruments allow a fairly complex mission.
An understanding of radiative transfer in the earth's atmosphere is a necessity for the remote sensing of surface reflectivity from satellites and aircraft. The range of the adjacency effect, which represents the effect of bright areas on the radiance above dark areas, is the main parameter that distinguishes atmospheric radiative transfer over a nonuniform surface from that over a uniform one. A radiative transfer model which expresses this range correctly is, therefore, critical for developing remote sensing methods for the case of an atmosphere over a nonuniform surface. The present investigation is concerned with the development of a new approximate solution of the radiative transfer (RT) equation. The solution is not limited to nonabsorbing atmospheres, but it will still be limited to nadir observations. The results compare favorably with Monte Carlo simulations.
Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.
Theoretical and experimental data which have defined and/or extended the effectiveness of remote sensing operations are explored, with consideration given to both scientific and commercial activities. The remote sensing of soil moisture, the sea surface, and oil slicks is discussed, as are programs using satellites for studying geodynamics and geodesy, currents and waves, and coastal zones. NASA, Canadian, and Japanese radar and microwave passive and active systems are described, together with algorithms and techniques for image processing and classification. The SAR-580 project is outlined, and attention is devoted to satellite applications in investigations of the structure of the atmosphere, agriculture and land use, and geology. Design and performance features of various optical scanner, radar, and multispectral data processing systems and procedures are detailed.
Understanding the relationship between remotely sensed snow disappearance and seasonal water supply may become vital in coming years to supplement limited ground based, in situ measurements of snow in a changing climate. For the period 2001–2019, we investigated the relationship between satellite derived Day of Snow Disappearance (DSD)—the date at which snow has completely disappeared—and the seasonal water supply, i.e., the April—July total streamflow volume, for 15 snow dominated basins across the western U.S. A Monte Carlo framework was applied, using linear regression models to evaluate the predictive skill—defined here as a model’s ability to accurately predict seasonal flow volumes—of varied predictors, including DSD and in situ snow water equivalent (SWE), across a range of spring forecast dates. In all basins there is a statistically significant relationship between mean DSD and seasonal water supply (p ≤ 0.05), with mean DSD explaining roughly half of the variance. Satellite-based model skill improves later in the forecast season, surpassing the skill of in-situ-based (SWE) models in skill in 10 of the 15 basins by the latest forecast date. We found little to no correlation between model error and basin characteristics such as elevation and the ratio of snow water equivalent to total precipitation. Despite a relatively short data record, this exploratory analysis shows promise for improving seasonal water supply prediction, in particular for snow dominated basins lacking in situ observations.
The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. The experimental design is a multi-sensor, multi-scale (1-ha to 160,000 km ^ {2}) approach to providing the comprehensive data set necessary to address several experiment objectives. A description focusing on the microwave remote sensing components (ground, airborne, and spaceborne) of the experiment will be presented.