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Civil and Environmental Engineering Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Civil and Environmental Engineering
Sharpening Ecostress And Viirs Land Surface Temperature Using Harmonized Landsat-Sentinel Surface Reflectances, Jie Xue, Martha C. Anderson, Feng Gao, Christopher Hain, Liang Sun, Yun Yang, Kyle R. Knipper, William P. Kustas, Alfonso F. Torres-Rua, Mitch Schull
Sharpening Ecostress And Viirs Land Surface Temperature Using Harmonized Landsat-Sentinel Surface Reflectances, Jie Xue, Martha C. Anderson, Feng Gao, Christopher Hain, Liang Sun, Yun Yang, Kyle R. Knipper, William P. Kustas, Alfonso F. Torres-Rua, Mitch Schull
Civil and Environmental Engineering Faculty Publications
Land surface temperature (LST) is a key diagnostic indicator of agricultural water use and crop stress. LST data retrieved from thermal infrared (TIR) band imagery, however, tend to have a coarser spatial resolution (e.g., 100 m for Landsat 8) than surface reflectance (SR) data collected from shortwave bands on the same instrument (e.g., 30 m for Landsat). Spatial sharpening of LST data using the higher resolution multi-band SR data provides an important path for improved agricultural monitoring at sub-field scales. A previously developed Data Mining Sharpener (DMS) approach has shown great potential in the sharpening of Landsat LST using Landsat …
Hydrologic Observation, Model, And Theory Congruence On Evapotranspiration Variance: Diagnosis Of Multiple Observations And Land Surface Models, Ruijie Zeng, Ximing Cai
Hydrologic Observation, Model, And Theory Congruence On Evapotranspiration Variance: Diagnosis Of Multiple Observations And Land Surface Models, Ruijie Zeng, Ximing Cai
Civil and Environmental Engineering Faculty Publications
This paper reconciles the state-of-the-art observations and simulations of evapotranspiration (ET) temporal variability through a diagnostic framework composed of an observation-model-theory triplet. Specifically, a confirmed theoretical tool, Evapotranspiration Temporal VARiance Decomposition (EVARD), is used as a benchmark to estimate ET monthly variance (σ2ET) across the contiguous United States (CONUS) with inputs including hydroclimatic observations, Gravity Recovery and Climate Experiment-based terrestrial water storage, four observation-based products (ETRSUW by the University of Washington, ETRSMOD16 from MOD16 Global Terrestrial ET Data Set, ETFLUXNET upscaled from of fluxtower observations, and ETGLEAM from Global Land Evaporation Amsterdam Model), …
Mapping Annual Riparian Water Use Based On The Single-Satellite-Scene Approach, Kul Khand, Saleh Taghvaeian, Leila Hassan-Esfahani
Mapping Annual Riparian Water Use Based On The Single-Satellite-Scene Approach, Kul Khand, Saleh Taghvaeian, Leila Hassan-Esfahani
Civil and Environmental Engineering Faculty Publications
The accurate estimation of water use by groundwater-dependent riparian vegetation is of great importance to sustainable water resource management in arid/semi-arid regions. Remote sensing methods can be effective in this regard, as they capture the inherent spatial variability in riparian ecosystems. The single-satellite-scene (SSS) method uses a derivation of the Normalized Difference Vegetation Index (NDVI) from a single space-borne image during the peak growing season and minimal ground-based meteorological data to estimate the annual riparian water use on a distributed basis. This method was applied to a riparian ecosystem dominated by tamarisk along a section of the lower Colorado River …
Estimation Of Surface Soil Moisture In Irrigated Lands By Assimilation Of Landsat Vegetation Indices, Surface Energy Balance Products, And Relevance Vector Machines, Alfonso F. Torres-Rua, Andres M. Ticlavilca, Roula Bachour, Mac Mckee
Estimation Of Surface Soil Moisture In Irrigated Lands By Assimilation Of Landsat Vegetation Indices, Surface Energy Balance Products, And Relevance Vector Machines, Alfonso F. Torres-Rua, Andres M. Ticlavilca, Roula Bachour, Mac Mckee
Civil and Environmental Engineering Faculty Publications
Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices) has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and …