A Stanford writing course to learn how to write scientific articles in a clear, concise, and effective way

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

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

计算机经典书籍推荐 部分书籍提供PDF下载

收藏一些电子书

ggplot2: elegant graphics for data analysis

R package: A state-of-the-art Vegetation Phenology extraction package, phenofit

Find, Download and Process Sentinel-2 Data

📈 An exceptionally fast, tiny time series & line chart

Code used to create NDVI change detection maps from Sentinel-2 imagery on the Google Earth Engine platform.

Breaks For Additive Season and Trend

Deep Learning Book Chinese Translation

Deep Learning Classification, Clustering, LSTM Time Series and Regression with Tensorflow

Enhancements to the CGLOPS workflow via land cover change detection

The source codes of Time-series-based Reflectance Adjustment (TRA) approach (Windows C/C++ and MATLAB version)

A fork of the R package strucchange

A set of tools to understand what is happening inside a Random Forest

An R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.

My custom Google Earth Engine scripts for work with Landsat, Sentinel and other satellite data.

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

Interactive visualizations of time series using JavaScript and the HTML canvas tag

Materials for 2018 Tanintharyi land cover change analysis paper (De Alban et al. 2018. Remote Sensing).

Deep Learning for Time Series Forecasting

Landsat NDVI variability. Code archive

R package: Extract Remote Sensing Vegetation Phenology by TIMESAT Fortran library

scripts and snippets for Google Earth Engine