U.S. Drought Monitor gif-maker (for the Western region)
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Updated
Jan 27, 2017 - Ruby
U.S. Drought Monitor gif-maker (for the Western region)
Apresentação feita em R do meu estudo chamado "Are coexisting biomes in a heterogeneous tropical landscape alternative stable states?".
Geospatial data visualization project: Examining poverty, conflict, and climate change in Ethiopia with ACLED, World Climate, and MPI data. Using map algebra to generate a simplified Palmer Drought Severity Index to examine climate change.
Effects of drought and habitat fragmentation on Heliconia acuminata.
Quantifying drought sensitivity in coconut agriculture
Zylstra, E. R., D. E. Swann, and R. J. Steidl. 2019. Surface-water availability governs survival of an amphibian in arid mountain streams. Freshwater Biology 64:164-174.
This is the data and code to reproduce the results for the paper "Meta-analysis reveals that the effects of precipitation change on soil and litter fauna in forests depend on body size."
Summer Project at CCRC, investigating flash droughts in Australia
Application of the ETS model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahwalnagar District, Punjab, Pakistan.
Code repository for the article "Trait-based response of deadwood and tree-related microhabitats to decline in temperate lowland and montane forests"
Application of the ARIMA model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.
Collect, manipulate, and generate variables related to climatic shocks on AMC (Comparable Minimum Areas) in Brazil.
This is a repository with codebase and results of the publication: "Characterization of Bias During Meteorological Drought Calculation in Time Series Out-of-Sample Validation"
An API for serving up data on the California drought.
Application of the ARIMA model to forecast PET patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.
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