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Science Target Prioritization Framework for Remote Sensing

Behind the scenes of a remote sensing mission there are complex decision making and planning operations. Streamlining these operations, with a quantitative scientific value framework, aids efficient and optimized science data collection.While there have been previous efforts to quantify the science value for specific science scenarios, our work aims to develop a general framework which can be applied across different scenarios. We describe a pipeline of processes which combines model forecast and observation data, in computational forms, as dictated by the mission objectives set forth by subject matter experts. The framework is described with use cases involving the monitoring of nitrogen dioxide (NO2) concentrations over the Gulf of Mexico and methane concentrations over interior Alaska.

Remote Sensing↗

The application of remote sensing in geobotanical exploration for metal sulfides

A field study was conducted in Mineral, VA in 1980-82 to test the suitability of remote sensing techniques for geobotanical exploration. It was found that on trees growing over lead sulfide deposits, buds opened later and leaves were smaller than on trees growing on soils with background levels of lead and copper. This difference in leaf growth could be detected in remotely sensed data. In the spring, the smaller leaf size of metal-stressed trees resulted in a greater contribution from the soil and bark to the total reflectance imaged by the sensor. In the fall, the leaves of metal-stressed oaks sensed earlier than surrounding vegetation, which was also detected in remotely sensed data. It is concluded that vegetation growing on lead sulfide deposits has a shorter growing season than surrounding vegetation on unmineralized soil and that remotely sensed data collected at either end of the growing season can be used to locate geobotanical anomalies associated with these deposits.

Masuoka, E. J.↗

Present status of LANDSAT remote sensing

The state-of-the-practice of satellite remote sensing is examined. Emphasis is placed on the use of remote sensing to improve information gathering practices. Impediments to adopting this technology and opportunities to overcome these impediments are addressed.

Cressy, P. J.↗

The Future of Instrument Technology for Space-based Remote Sensing

The current paradigm for space-based remote sensing relies upon frequency-specific measurements in pre-defined orbits with fixed or narrowly variable apertures. The suites of Earth observing instruments currently deployed or planned for deployment within the next 3 years typify this paradigm. To enable NASA's Earth Science vision, the future paradigm of remote sensing must employ frequency-agile measurements capable of multi-scene observations. Real-time, autonomous adaptive sensing and taskability will be critical. Advanced capabilities will include: (1) Miniaturized observatories. (2) Robust, compact instrument architectures. (3) Miniaturized/programmable components. (4) Aperture synthesis. (5) Deployable apertures. (6) Low cost production.

Peri, Frank↗

Senteniel-6 Radio Occultation Product Released by NASA GES DISC to Supplement Satellite Remote Sensing Datasets for PBL Study

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates hyperspectral atmospheric sounder remote sensing and numerical model reanalysis datasets which have been utilized in the Planetary Boundary Layer (PBL) research and applications. The hyperspectral sounder remote-sensing datasets include the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite to the Cross-track Infrared Sounder (CrIS) on Suomi--National Polar- orbiting Partnership (NPP) and National Oceanic and Atmospheric Administration -20 (N NOAA-20)/ Joint Polar-orbiting Satellite System -1 (JPSS-1). The Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global reanalysis product provides a data record commencing in 1980. The sounder remote sensing and reanalysis datasets include temperature, water vapor, and trace gas profile down to the PBL, and also have a derived PBL height as well. A nearly 10-year (June 2006 to December 2015) seasonal and annual PBL height climatology dataset from COSMIC Global Navigation Satellite System (GNSS) radio occultation (RO) measurement is also available from the GES DISC. In collaboration with Sentinel-6 Project, the GES DISC is implementing curation activities for GNSS RO products from the Sentinel-6A/Sentinel-6 Michael Freilich satellite launched on November 21, 2020. Sentinel-6A RO products provide refractivity, temperature, and humidity profile with finer vertical resolution, leveraging PBL research and application as a supplement to the hyperspectral sounder remote sensing and reanalysis products. The public release of Sentinel- 6A RO products is scheduled for mid-October of 2021. In this presentation, we will introduce all Senitnel-6A products and services, and demonstrate use cases studying the PBL by combining these products with other GES DISC archived data products.

Feng Ding↗

Use of remote sensing for land use policy formulation

Uses of remote sensing imagery were investigated based on exploring and evaluating the capability and reliability of all kinds of imagery for improving decision making on issues of land use at all scales of governmental administration. Emphasis was placed on applications to solving immediate problems confronting public agencies and private organizations. Resulting applications of remote sensing use by public agencies, public organizations, and related private corporations are described.

Boylan, M.↗

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

Introduction to this Special Issue on Geostatistics and Scaling of Remote Sensing

The germination of this special PE&RS issue began at the Royal Geographical Society (with the Institute of British Geographers)(RCS-IBC) annual meeting in January, 1997 held at the University of Exeter in Exeter, England. The cold and snow of an England winter were greatly tempered by the friendly and cordial discussions that ensued at the meeting on possible ways to foster both dialog and research across "the Big Pond" between geographers in the US and the UK on the use of geostatistics and geospatial techniques for remote sensing of land surface processes. It was decided that one way to stimulate and enhance cooperation on the application of geostatistics and geospatial methods in remote sensing was to hold parallel sessions on these topics at appropriate meeting venues in 1998 in both the US and the UK Selected papers given at these sessions would be published as a special issue of PE&RS on the US side, and as a special issue of Computers and Geosciences (C&G) on the UK side, to highlight the commonality in research on geostatistics and geospatial methods in remote sensing and spatial data analysis on both sides of the Atlantic Ocean. As a consequence, a session on "Ceostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March, 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). A similar session was held at the RGS-IBG annual meeting in Guildford, Surrey, England in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). The six papers that in part, comprise this issue of PE&RS, are the US complement to such a dual journal publication effort. Both of us are co-editors of each of the journal special issues, with the lead editor of each journal being from their respective side of the Atlantic where the journals are published. The special issue of C&G that constitutes the other half of this co-edited journal series will be published in early 1999, with 3 papers by US authors being published along with 6 papers authored by individuals from the UK and other places in Europe.

Quattrochi, Dale A.↗

Microwave remote sensing from space

Spaceborne microwave remote sensors provide perspectives of the earth surface and atmosphere which are of unique value in scientific studies of geomorphology, oceanic waves and topography, atmospheric water vapor and temperatures, vegetation classification and stress, ice types and dynamics, and hydrological characteristics. Microwave radars and radiometers offer enhanced sensitivities to the geometrical characteristics of the earth's surface and its cover, to water in all its forms - soil and vegetation moisture, ice, wetlands, oceans, and atmospheric water vapor, and can provide high-resolution imagery of the earth's surface independent of cloud cover or sun angle. A brief review of the historical development and principles of active and passive microwave remote sensing is presented, with emphasis on the unique characteristics of the information obtainable in the microwave spectrum and the value of this information to global geoscientific studies. Various spaceborne microwave remote sensors are described, with applications to geology, planetology, oceanography, glaciology, land biology, meteorology, and hydrology. A discussion of future microwave remote sensor technological developments and challenges is presented, along with a summary of future missions being planned by several countries.

Carver, K. R.↗

Introducing remote sensing to county-level agencies in Michigan through the Cooperative Extension Service

State and regional planning agencies in Michigan are aware of remote sensing technology, however, many agencies at the county and township level have not been introduced to its potential. This paper describes an educational effort undertaken by the MSU Remote Sensing Project and the Michigan Cooperative Extension Service aimed at reaching local decision makers. Remote sensing materials and a questionnaire were used to elicit interest and aid in planning the program. A series of seven workshops were held throughout Michigan for governmental officials and the staff of public agencies from 38 counties. Emphasis was placed on the characteristics, availability and usefulness of remotely-sensed data through a series of successful applications conducted in the state. The workshops were highly successful and many local decision makers are not aware of a new tool to call upon in their responses to land use and natural resource concerns.

Enslin, W. R.↗

Radiometric remote sensing of mesospheric and stratospheric water vapor

The remote sensing of stratospheric and mesospheric water vapor by microwave and millimeter radiometry is described. The received radiation is emitted by and interacts with all levels of the atmosphere. The pressure dependence of the linewidth for the absorption cross section of water vapor permits retrieval of vapor mixing ratios. The 183.31-GHz line of water vapor can also be used for remote sensing of the water vapor concentration in the upper atmosphere, but due to the much stronger absorption cross section for this line, ground-based observations are difficult. To date all measurements at 183 GHz have been made from platforms above the troposphere.

Croskey, Charles L.↗

Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding

Deep learning has proven its effectiveness in numerous tasks for remote sensing scene understanding. However there is an increasing interest to explore fusion of domain-specific background information to the deep neural network to further improve its performance. Remote sensing researchers are also working towards developing models that generalize and adapt to multiple applications. Generalization challenges coupled with the scarcity of large corpora of high-quality noise-free labelled data, have together fueled an interest for leveraging background information. Knowledge graphs serve as excellent choice to represent domain-specific information in a structured, standardized and extensible manner. Integrating symbolic knowledge representations in the form of Knowledge Graph Embedding (KGE) to perform neuro-symbolic reasoning is an emerging research direction promising significant impacts. This vision paper seeks to position ideas and provoke early thoughts toward advancing neuro-symbolic artificial intelligence in the context of geospatial challenges. Specifically, it conceptualizes and elaborates on an architecture for infusing geospatial knowledge from knowledge graph in a deep neural network pipeline. As guiding case studies - land-use land-cover classification, object detection and instance segmentation can benefit from infusing spatio-contextual information with remote sensing imagery. The discussion further reflects on and articulates the challenges and explainable AI opportunities anticipated when scaling and maintaining large-scale geospatial knowledge graphs.

Potnis, Abhishek↗

Possible Near-IR Channels for Remote Sensing Precipitable Water Vapor from Geostationary Satellite Platforms

Remote sensing of tropospheric water vapor profiles from current geostationary weather satellites are made using a few broadband infrared (IR) channels in the 6 to 13- micrometers region. Uncertainties greater than 20 percent exist in derived water vapor values just above the surface from the IR emission measurements. In this paper, we propose three near-IR channels, one within the 0.94-micrometer water vapor band absorption region, and the other two in nearby atmospheric windows, for remote sensing of precipitable water vapor over land areas, excluding lakes and rivers, during daytime from future geostationary satellite platforms. The physical principles are as follows. The reflectance of most surface targets varies approximately linearly with wavelength near 1 micrometer. The solar radiation on the sun-surface-sensor ray path is attenuated by atmospheric water vapor...

Green, R. O.↗

Our national energy future - The role of remote sensing

An overview of problems and opportunities in remote sensing of resources. The need for independence from foreign and precarious energy sources, availability of fossil fuel materials for other purposes (petrochemicals, fertilizer), environmental conservation, and new energy sources are singled out as the main topics. Phases of response include: (1) crisis, with reduced use of petroleum and tapping of on-shore and off-shore resources combined; (2) a transition phase involving a shift from petroleum to coal and oil shale; and (3) exploitation of renewable (inexhaustible and clean) energy. Opportunities for remote sensing in fuel production and energy conservation are discussed along with problems in identifying the spectral signatures of productive and unproductive regions. Mapping of water resources, waste heat, byproducts, and wastes is considered in addition to opportunities for international collaboration.

Schmitt, H. H.↗

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.↗

Remote Sensing in Geography in the New Millennium: Prospects, Challenges and Opportunities

As noted in the first edition of Geography in America, the term remote sensing was coined in the early 1960's by geographers to describe the process of obtaining data by use of both photographic and nonphotographic instruments. Although this is still a working definition today, a more explicit and updated definition as it relates to geography can be phrased as: "remote sensing is the science, art, and technology of identifying, characterizing, measuring, and mapping of Earth surface, and near earth surface, phenomena from some position above using photographic or nonphotographic instruments." Both patterns and processes may be the object of investigation using remote sensing data. The science dimension of geographic remote sensing is rooted in the fact that: a) it is dealing with primary data, wherein the investigator must have an understanding of the environmental phenomena under scrutiny, and b) the investigator must understand something of the physics of the energy involved in the sensing instrument and the atmospheric pathway through which the energy passes from the energy source, to the Earth object to the sensor.

Quattrochi, Dale A.↗

Geometric representation methods for multi-type self-defining remote sensing data sets

Efficient and convenient representation of remote sensing data is highly important for an effective utilization. The task of merging different data types is currently dealt with by treating each case as an individual problem. A description is provided of work which is carried out to standardize the multidata merging process. The basic concept of the new approach is that of the self-defining data set (SDDS). The creation of a standard is proposed. This standard would be such that data which may be of interest in a large number of earth resources remote sensing applications would be in a format which allows convenient and automatic merging. Attention is given to details regarding the multidata merging problem, a geometric description of multitype data sets, image reconstruction from track-type data, a data set generation system, and an example multitype data set.

Anuta, P. E.↗

The application of remote sensing techniques to selected inter and intra urban data acquisition problems

The utility of remote sensing techniques to urban data acquisition problems in several distinct areas was identified. This endeavor included a comparison of remote sensing systems for urban data collection, the extraction of housing quality data from aerial photography, utilization of photographic sensors in urban transportation studies, urban change detection, space photography utilization, and an application of remote sensing techniques to the acquisition of data concerning intra-urban commercial centers. The systematic evaluation of variable extraction for urban modeling and planning at several different scales, and the model derivation for identifying and predicting economic growth and change within a regional system of cities are also studied.

Horton, F. E.↗