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Projects
Description:
Terrain parameters are essential in various applications, including agriculture, forestry, and hydrology. However, generating high-resolution terrain parameters is computationally intensive, making it challenging to provide these value-added products to communities in need. GEOtiled is a scalable workflow that leverages data partitioning to accelerate the computation of terrain parameters from digital elevation models, while preserving accuracy.
Web Page:
GEOtiled Website
Github Repository:
GEOtiled Github
Source of Support:
National Science Foundation (NSF) under grant numbers
#1724843,
#1854312,
#2103836,
#2103845,
#2138811, and
#2334945
Description:
SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of interest (i.e., gap-filling), analysis of generated fine-grained predictions, and visualization of both predictions and analyses.
Web Page:
SOMOSPIE Website
Github Repository:
SOMOSPIE Github
Source of Support:
National Science Foundation (NSF) under grant numbers
#1724843,
#1854312,
#2103836,
#2103845,
#2138811, and
#2334945
