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Remote sensing research in geographic education: An alternative view

It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

Wilson, H.↗

NASA’s NextGen Remote Sensing Instruments Have Arrived: Data Products For Studying Disease Vectors

Remote sensing can be used to measure, evaluate or estimate both the environment (state functions) and interfaces (processfunctions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equationsto significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remotesensing instruments which have become recently operational will provide a significant enhancement in our ability to studydisease vector’s life cycles and habitats. These instruments are on the International Space Station (ISS) and includeECOSTRESS, DESIS, and GEDI. ECOSTRESS is a 5 channel, thermal IR instrument with 70 m resolution and approximately1-5 day repeat cycle of day/night pairs. DESIS jointly developed by German Aerospace Center and Teledyne Brown Engineeringis a hyperspectral sensor system of 235 channels and 30 m resolution. DESIS data is only being acquired on demand. GEDI is ahigh-resolution laser ranger used for observing Earth’s forests and topography. NASA’s current ISS instrument configuration provides measurements of the critical environmental measures of environmentalstate functions important to vector & disease life cycles. Remote sensing data provide a spatial context and time series oflandscape scale process functions represented by land use mapping and measurements of ecological functions. Global publichealth is entering a new information age through the use of spatial models of disease vector/host ecologies driven by the use ofremotely sensed data to measure environmental and structural factors critical in determining disease vector habitats. In 2018, NASA initiated a new study for the Surface Biology and Geology (SBG) Designated Observable, identified in the 2018National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observationfrom Space.” (https://www.nap.edu/catalog/24938/thriving-on-our-changing-planet-a-decadal-strategy-for-earth) . The SBG isplanned to collect global remote sensing measurements using a hyperspectral spectrometer and multispectral thermal data. Thesedata sets will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats globally. The 3sensors on the ISS provide precursor data to prepare the community for the application of future SBG data toward diseasestudies.

Disease Vectors↗

Remote Sensing of Earth Terrain

Theoretical models that are useful and practical in relating remote sensing data to the important physical parameters characterizing Earth terrain are developed. The development of models that are useful in data analysis and interpretation, scene simulation, and developing new remote sensing approaches and techniques is discussed. Numerous theoretical models that are applicable to the active and passive remote sensing of plowed fields, atmospheric precipitation, vegetation, and snow fields were developed. The radiative transfer theory is used to interpret the active and passive data as a function of rain rate. Both the random medium model and the discrete scatterer model is used to study the remote sensing of vegetation fields. Due to the non-spherical geometry of the scatterers there is strong azimuthal dependence in the observed data. Thus, the anisotropic random medium model and the discrete scatterer model with nonspherical particles was developed. In order to relate the remote sensing data to the actual physical parameters, the scattering of electromagnetic waves from randomly distributed dielectric scatterers was studied. Both the rigorous random discrete scatterer theory and the strong fluctuation theory are used to derive the backscattering cross section in terms of the actual physical parameters and the results agree well with the data obtained from the snow fields.

Kong, J. A.↗

Earth and atmospheric remote sensing; Proceedings of the Meeting, Orlando, FL, Apr. 2-4, 1991

The papers presented in this volume address the technical aspects of earth and atmospheric remote sensing. Topics discussed include spaceborne and ground-based applications of laser remote sensing, advanced applications of lasers in remote sensing, laser ranging applications, data analysis and systems for biospheric processes, measurements for biospheric processes, and remote sensing for geology and geophysics. Papers are presented on a space-qualified laser transmitter for lidar applications, solid state lasers for planetary exploration, automated band selection for multispectral meteorological applications, aerospace remote sensing of natural water organics, and remote sensing of volcanic ash hazards to aircraft.

Curran, Robert J.↗

Quantitative interpretation of Great Lakes remote sensing data

The paper discusses the quantitative interpretation of Great Lakes remote sensing water quality data. Remote sensing using color information must take into account (1) the existence of many different organic and inorganic species throughout the Great Lakes, (2) the occurrence of a mixture of species in most locations, and (3) spatial variations in types and concentration of species. The radiative transfer model provides a potential method for an orderly analysis of remote sensing data and a physical basis for developing quantitative algorithms. Predictions and field measurements of volume reflectances are presented which show the advantage of using a radiative transfer model. Spectral absorptance and backscattering coefficients for two inorganic sediments are reported.

Shook, D. F.↗

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertainty that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.

54 ENVIRONMENTAL SCIENCES↗

Opportunities and problems in introducing or expanding the teaching of remote sensing in universities

The need for degree programs in remote sensing is considered. Any education program which claims to train remote sensing specialists must include expertise in the physical principles upon which remote sensing is based. These principles dictate the limits of engineering and design, computer analysis, photogrammetry, and photointerpretation. Faculty members must be hired to provide emphasis in those five areas.

Maxwell, E. L.↗

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Tsang, Leung↗

Remote sensing for vineyard management

Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.

Philipson, W. R.↗

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Sea surface spectrum↗

Application of remote sensing to state and regional problems

The primary purpose of the remote sensing applications program is for various members of the university community to participate in activities that improve the effective communication between the scientific community engaged in remote sensing research and development and the potential users of modern remote sensing technology. Activities of this program are assisting the State of Mississippi in recognizing and solving its environmental, resource and socio-economic problems through inventory, analysis, and monitoring by appropriate remote sensing systems. Objectives, accomplishments, and current status of the following individual projects are reported: (1) bark beetle project; (2) state park location planning; and (3) waste source location and stream channel geometry monitoring.

Miller, W. F.↗

Use of remote sensing for land use policy formulation

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Source record↗

Laboratory Measurements of Sea Ice: Connections to Microwave Remote Sensing

The connections between laboratory measurements and remote sensing observations of sea ice are explored. The focus of this paper is on thin ice which is more easily simulated in a laboratory environment. We summarize results of C-band scatterometer measurements and discuss how they may help in the interpretation of remote sensing data.

remote↗

Microwave remote sensing of snowpack properties

Topic concerning remote sensing capabilities for providing reliable snow cover data and measurement of snow water equivalents are discussed. Specific remote sensing technqiues discussed include those in the microwave region of the electromagnetic spectrum.

Rango, A.↗

Application of remote sensing to water resources problems

The following conclusions were reached concerning the applications of remote sensing to water resources problems: (1) Remote sensing methods provide the most practical method of obtaining data for many water resources problems; (2) the multi-disciplinary approach is essential to the effective application of remote sensing to water resource problems; (3) there is a correlation between the amount of suspended solids in an effluent discharged into a water body and reflected energy; (4) remote sensing provides for more effective and accurate monitoring, discovery and characterization of the mixing zone of effluent discharged into a receiving water body; and (5) it is possible to differentiate between blue and blue-green algae.

Clapp, J. L.↗

International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981, Digest. Volumes 1 & 2

Sensors used for the geophysical and remote sensing studies are reviewed; in particular, NIMBUS-7 Scanning Multichannel Microwave Radiometer results are given. Remote sensing analyses consider such areas as hydrology, soil moisture, and planetary surfaces. In addition, Shuttle remote sensing experiments and SAR systems, remote sensing in the thermal infrared, and microwave remote sensing of the earth are considered. Finally, attention is given to lithologic and geobotanical studies, and geophysical sensing techniques and inversion theory.

Source record↗

Mathematic modeling of the Earth's surface and the process of remote sensing

It is shown that real data from remote sensing of the Earth from outer space are not best suited to the search for optimal procedures with which to process such data. To work out the procedures, it was proposed that data synthesized with the help of mathematical modeling be used. A criterion for simularity to reality was formulated. The basic principles for constructing methods for modeling the data from remote sensing are recommended. A concrete method is formulated for modeling a complete cycle of radiation transformations in remote sensing. A computer program is described which realizes the proposed method. Some results from calculations are presented which show that the method satisfies the requirements imposed on it.

Balter, B. M.↗

Advances in the development of remote sensing technology for agricultural applications

The application of remote sensing technology to crop forecasting is discussed. The importance of crop forecasts to the world economy and agricultural management is explained, and the development of aerial and spaceborne remote sensing for global crop forecasting by the United States is outlined. The structure, goals and technical aspects of the Large Area Crop Inventory Experiment (LACIE) are presented, and main findings on the accuracy, efficiency, applicability and areas for further study of the LACIE procedure are reviewed. The current status of NASA crop forecasting activities in the United States and worldwide is discussed, and the objectives and organization of the newly created Agriculture and Resources Inventory Surveys through Aerospace Remote Sensing (AgRISTARS) program are presented.

Powers, J. E.↗