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Full-Text Articles in Physical Sciences and Mathematics
An Automated Approach To Map Winter Cropped Area Of Smallholder Farms Across Large Scales Using Modis Imagery, Meha Jain, Pinki Mondal, Gillian L. Galford, Greg Fiske, Ruth S. Defries
An Automated Approach To Map Winter Cropped Area Of Smallholder Farms Across Large Scales Using Modis Imagery, Meha Jain, Pinki Mondal, Gillian L. Galford, Greg Fiske, Ruth S. Defries
Rubenstein School of Environment and Natural Resources Faculty Publications
Fine-scale agricultural statistics are an important tool for understanding trends in food production and their associated drivers, yet these data are rarely collected in smallholder systems. These statistics are particularly important for smallholder systems given the large amount of fine-scale heterogeneity in production that occurs in these regions. To overcome the lack of ground data, satellite data are often used to map fine-scale agricultural statistics. However, doing so is challenging for smallholder systems because of (1) complex sub-pixel heterogeneity; (2) little to no available calibration data; and (3) high amounts of cloud cover as most smallholder systems occur in the …
Evaluation Of Modis Land Surface Temperature Data To Estimate Near-Surface Air Temperature In Northeast China, Yuan Z. Yang, Wen H. Cai, Jian Yang
Evaluation Of Modis Land Surface Temperature Data To Estimate Near-Surface Air Temperature In Northeast China, Yuan Z. Yang, Wen H. Cai, Jian Yang
Forestry and Natural Resources Faculty Publications
Air temperature (Tair) near the ground surface is a fundamental descriptor of terrestrial environment conditions and one of the most widely used climatic variables in global change studies. The main objective of this study was to explore the possibility of retrieving high-resolution Tair from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products, covering complex terrain in Northeast China. The All Subsets Regression (ASR) method was adopted to select the predictors and build optimal multiple linear regression models for estimating maximum (Tmax), minimum (Tmin), and mean (Tmean) air temperatures. …
Using Remote Sensing To Estimate Crop Water Use To Improve Irrigation Water Management, Arturo Reyes-Gonzalez
Using Remote Sensing To Estimate Crop Water Use To Improve Irrigation Water Management, Arturo Reyes-Gonzalez
Electronic Theses and Dissertations
Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently. Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to …
A Method For Reflectance Index Wavelength Selection From Moisture-Controlled Soil And Crop Residue Samples, Ali Hamidisepehr, Michael P. Sama, Aaron P. Turner, Ole O. Wendroth
A Method For Reflectance Index Wavelength Selection From Moisture-Controlled Soil And Crop Residue Samples, Ali Hamidisepehr, Michael P. Sama, Aaron P. Turner, Ole O. Wendroth
Biosystems and Agricultural Engineering Faculty Publications
Reflectance indices are a method for reducing the dimensionality of spectral measurements used to quantify material properties. Choosing the optimal wavelengths for developing an index based on a given material and property of interest is made difficult by the large number of wavelengths typically available to choose from and the lack of homogeneity when remotely sensing agricultural materials. This study aimed to determine the feasibility of using a low-cost method for sensing the moisture content of background materials in traditional crop remote sensing. Moisture-controlled soil and wheat stalk residue samples were measured at varying heights using a reflectance probe connected …
Fit To Predict? Ecoinformatics For Predicting The Catchability Of A Pelagic Fish In Near Real-Time, Kylie L. Scales, Elliot L. Hazen, Sara M. Maxwell, Heidi Dewar, Suzanne Kohin, Michael G. Jacox, Christopher A. Edwards, Dana K. Briscoe, Larry B. Crowder, Rebecca L. Lewison, Steven J. Bograd
Fit To Predict? Ecoinformatics For Predicting The Catchability Of A Pelagic Fish In Near Real-Time, Kylie L. Scales, Elliot L. Hazen, Sara M. Maxwell, Heidi Dewar, Suzanne Kohin, Michael G. Jacox, Christopher A. Edwards, Dana K. Briscoe, Larry B. Crowder, Rebecca L. Lewison, Steven J. Bograd
Biological Sciences Faculty Publications
The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of …