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apsimregions

ApsimRegions is a one-way nested climate-crop modeling framework that links gridded weather data (rain, temperature, radiation, etc.) with the point-specific Agricultural Production Systems sIMulator (APSIM) crop model.

apsimx

R package for APSIM-X

aquacrop

AquaCrop-OSPy: Python implementation of AquaCrop-OS

aquacrop-irrig.designer

An aquacrop-based simulation tool make you plan your irrigation scheduling

aquacrop-r

Tools for crop simulations with Aquacrop V6

aquacrop_py

Python implementation of AquaCropOS

biome-bgc

Biome-BGC ecophysiological model

cesm

The Community Earth System Model

clm_ide_analyses

pre- and post-processing tools for International Drought Experiment simulations using Community Land Model

contextily

Context geo-tiles in Python

crop_yield_prediction

:corn: Machine learning model for crop yield prediction

ctsm

Community Terrestrial Systems Model (includes the Community Land Model of CESM)

dgvm_rs_dm_norway

We evaluate the performance of three methods for spatial representation of vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DM), one that uses a remote sensing (RS) dataset and a dynamic global vegetation model (DGVM).

dssat-csm-os

DSSAT Cropping System Model

ecosys

The ECOSYS model for terrestrial ecosystem biogeochemistry

et-demands

Dual crop coefficient crop water demand model

gee-scripts-repo

learning GEE

gee_pml

Penman-Monteith-Leuning Evapotranspiration in GEE

geemap

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets

get_rain_data_meteodata

NOAA气象站数据获得与处理

hrldasnoahmp

HRLDAS (High Resolution Land Data Assimilation System)

machinelearning-deeplearning-nlp-leetcode-statisticallearningmethod-tensorflow

最近在学习机器学习，深度学习，自然语言处理，统计学习方法等知识，理论学习主要根据readme的链接，在学习理论的同时，决定自己将学习的相关算法用Python实现一遍，并结合GitHub上相关大牛的代码进行改进，本项目会不断的更新相关算法，欢迎star，fork和关注。 主要包括： 1.吴恩达Andrew Ng老师的机器学习课程作业个人笔记 Python实现， 2.deeplearning.ai（吴恩达老师的深度学习课程笔记及资源） Python实现， 3.李航《统计学习方法》 Python代码实现， 4.自然语言处理NLP 牛津大学xDeepMind Python代码实现， 5.LeetCode刷题，题析，分析心得笔记 Java和Python代码实现， 6.TensorFlow人工智能实践代码笔记 北京大学曹健老师课程和TensorFlow：实战Google深度学习框架（第二版） Python代码实现， 附带一些个人心得和笔记。GitHub上有很多机器学习课程的代码资源，我也准备自己实现一下，后续会更新笔记，代码和百度云网盘链接。 这个项目主要是学习算法的，并且会不断更新相关资源和代码，欢迎关注，star，fork！ Min's blog 欢迎访问我的博客主页！ (Welcome to my blog website !)https://liweimin1996.github.io/

mapplet

Functional_Structural Plant Model of Apple Tree

mc2

MC2 Dynamic Global Vegetation Model

netcdf4-python

netcdf4-python: python/numpy interface to the netCDF C library

noahmp

Noah-MP Community Repository

nsga-ii_python_for_swat_model

Multi-Site and -Objective calibration method for SWAT model

optimal_vcmax_r

calculate optimal vcmax in R as in Smith et al. Photosynthetic capacity is optimized to the environment. Ecology Letters.

pasture

pcse

Repository for the Python Crop Simulation Environment