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a-beginner-guide-to-carry-out-extreme-value-analysis-with-codes-in-python

A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.

agrochain

Agricultural Supply Chain Dapp With Micro-Finance

ams-ml-python-course

Machine Learning in Python for Environmental Science Problems AMS Short Course Material

angulardemo

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

atmopsheric_physics_class_codes

automation_wrf_run

awesome-agriculture

Open source technology for agriculture, farming, and gardening

awesome-precision-agriculture

Advancement of UAV, deep Learning and cutting edged technologies and papers in Precision Agriculture.

bias_correction

python library for bias correction

btc_trading

calculate-precipitation-based-agricultural-drought-indices-with-python

Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).

climate

climate-change-risk-analysis

Weighted overlay of climate change risk factors

climate-risk-insurances

The world's poor are being encouraged to take out insurance against climate-related disasters. But as the logic of some schemes unravels, those who profited least from fossil fuels are left paying for their damage.

climate_learn

Deep learning for climate modeling.

downscale

Simple Delta-Downscaling for SNAP Climate Data

dreamhouse-mobile-ionic

dsen2

Super-Resolution of Sentinel-2 Images: Learning a Globally Applicable Deep Neural Network

edx_machine_learning_dse220x

eo-learn

Earth observation processing framework for machine learning in Python

eomaps

A library to create interactive maps of geographical datasets

esmvaltool

ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP

farmos

farmOS: A web-based farm record keeping application.

fossil_fuel_policy_nlp

This repo contains the NLP pipeline to run a Binder app for climate change policy classification

fun_projects

hydrodl

idv

The Integrated Data Viewer (IDV) from Unidata is a framework for analyzing and displaying geoscience data.

instancesegmentation_sentinel2

🌱 Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis

kate1