jihconghan Goto Github PK

gee-ccdc-tools

Tools and Earth Engine apps to interact with the outputs from the CCDC algorithm

gee-user-summit-2018-hackathon

PumpIT - a Hackathon project of Google Earth Engine User Summit 2018

gee_packages

Google Earth Engine personal packages

gee_pkgs

Document of GEE JavaScript Packages

gee_s1_ard

Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.

gee_s1_sar_wetlands

Supplementary Material to my Remote Sensing publication 'Sentinel-1-Imagery-Based High-Resolution Water Cover Detection on Wetlands, Aided by Google Earth Engine'

geebfastmonitor

Google Earth Engine implementation of the popular R bfast package

geegprphenodemos

Google Earth Engine demo codes from the article "Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression"

geeguide

Harmonization of Landsat and Sentinel 2 in Google Earth Engine, documentation and scripts

geemap

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

geesharp.js

A library for pan-sharpening multispectral imagery and assessing image quality in Google Earth Engine

geet

Google Earth Engine Toolbox - Library to write small EE apps or big/complex apps with a lot less code.

geetools

Remote sensing and spatial analysis tools for Google Earth Engine

geetools-code-editor

A set of tools to use in Google Earth Engine Code Editor (JavaScript)

google-earth-engine-forest-fire-supervised

google-earth-engine-javascript-examples

Various examples for Google Earth Engine in Javascript

googleearthengine

googleearthengine-global-forest-change

Results from time-series analysis of Landsat images characterizing forest extent and change. Trees are defined as vegetation taller than 5m in height and are expressed as a percentage per output grid cell as ‘2000 Percent Tree Cover’. ‘Forest Cover Loss’ is defined as a stand-replacement disturbance, or a change from a forest to non-forest state, during the period 2000–2016. ‘Forest Cover Gain’ is defined as the inverse of loss, or a non-forest to forest change entirely within the period 2000–2012. ‘Forest Loss Year’ is a disaggregation of total ‘Forest Loss’ to annual time scales. Reference 2000 and 2016 imagery are median observations from a set of quality assessment-passed growing season observations.

googleearthengine-side-projects

Google Earth Engine side projects and tutorial scripts

heatwavetracker

hlj_soybean_map

A 30-m dataset that mapped the areas of soybean planting in Heilongjiang Province was produced, for the period of 1984~2020, based on Landsat-5/7/8 images and the Google Earth Engine (GEE) platform. Maps were made with a random forest classifier and phenological features extracted by a double-logistic model and a linear harmonic model. Here share our codes about how to use GEE platform to generate soybean maps and to verify accuracy of the map.

india-flood-inventory

The data repository for India Flood Inventory

jihconghan.github.io

个人主页

lala

lalala

landsat_smw_lst

Land Surface Temperature from Landsat on Google Earth Engine

landsurfacephenology_sentinel2

libsvm

lt-gee

Google Earth Engine implementation of the LandTrendr spectral-temporal segmentation algorithm. For documentation see:

machine-learning-using-r

Source code for 'Machine Learning Using R' by Karthik Ramasubramanian and Abhishek Singh

math_model

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