dongjwOU/CongoAnalysis
Congo Rain Forest Analysis
Ecosystem Production in Space and Time (ePiSaT) models Gross Primary Production (GPP) across the Australian continent from OzFlux flux tower data, gridded climate and satellite (MODIS) data. ePiSaT can be used to estimate ecosystem variables by partitioning OzFlux eddy covariance data to estimate GPP, light use efficiency (LUE), the maximum rate of carboxylation (Amax) etc. Once determined, the ePiSaT-modelled variables can be used in the well-founded and tested LUE approach to estimate GPP. Sample OzFlux data from Howard Springs is provided; ePiSaT requires the user to provide fAPAR, observed radiation, temperature and humidity data.
Public repository record indexed from GitHub. Explore verified star velocity metrics, source code repositories, and curated developer tool directories across the GitHubRepo ecosystem.
Congo Rain Forest Analysis
Work on: extraction of bands and creation of indices from Landsat image, cloud QA, creation of seasonal model and plotting cusum charts
A project to schedule and control the download and processing of Landsat 8 Imagery
Post-disturbance regrowth monitoring using Landsat Time Series (LTS)