ywg0212

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

causalml

Uplift modeling and causal inference with machine learning algorithms

mlens

ML-Ensemble – high performance ensemble learning

Free-shared-Spatiotemporal-method-of-remote-sensing-

spatiotemporal fusion method

Landsat_SMW_LST

Land Surface Temperature from Landsat on Google Earth Engine

sun-position

Python code for computing sun position

Landsat-LAI

Employing a data-driven approach to generate Leaf Area Index (LAI) maps from Landsat images over CONUS

REddyProc

Processing data from micrometeorological Eddy-Covariance systems

iMetaPlot

iMeta teaches you to plot

LEAF-Toolbox

ee_BioNet

The Google Earth Engine implementation of the BioNet algorithm to estimate biophysical parameters along with their uncertainties.

BEPS_hourly_site

Bioshpere-atmosphere Exchange Process Simulator, hourly version for site.

OEEex

A chrome extension to enhance Google Earth Engine code editor

geedataextract

dual_pol_descriptors

sentinel2_crop_traits

Sentinel-2 Crop Trait Retrieval Using Physiological and Phenological Priors from Field Phenotyping (Graf et al., 2023, RSE)

GEE_GPR_mapping_vegetation

Mapping vegetation properties in Google Earth Engine using GPR models and the Sentinel-2 L1C product.

GlobalSolarPosition

Global computation of the solar position at a given time in Google Earth Engine

GEE_xtract

GEE code for extracting high-quality remotely sensed data at multiple scales

ETES

[doi: 10.1016/j.agrformet.2023.109337] Wenquan Zhu, Cenliang Zhao*, Zhiying Xie. An end-to-end satellite-based GPP estimation model devoid of meteorological and land cover data. Agricultural and Forest Meteorology, 2023

Global-EVT-maps

Global temporally reconstructed maps of essential vegetation traits processed from the TOA Sentinel-3 catalogue in Google Earth Engine

GEE-scripts

GEE scripts

Spatiotemporal-fusion-data

Data for evaluation of remote sensing spatiotemporal fusion algorithm

S3_TOA_GPR_1

Scaling

Resampling satellite images using Wavelets and PCA

get-phenometrics

ARTMOtoGEE

Short tutorial to import ARTMO GPR models into GEE

gee-biopar

Implementation of Sentinel-2 biophysical parameters in Google Earth Engine

SEBALIGEEv2

spotpy

A Statistical Parameter Optimization Tool