Integrate Google Earth Engine(GEE), Pandas framework and Matplotlip - Spatial Data Mining

Published on Apr 04, 2020
Discovery Pattern in Spatial data, extract potentially useful information from data stored in images and visualize the result in dynamic charts.

Generate Slope Elevation data from SRTM - Python API

Published on Apr 11, 2020
Digital elevation data is an international research effort that obtained digital elevation models on a near-global scale. This SRTM V3 product (SRTM Plus) is provided by NASA JPL at a resolution of 1 arc-second (approximately 30m).

Normalized Difference Snow Index (NDSI)

Published on May 17, 2020
NDSI is a measure of the relative magnitude of the reflectance difference between visible (green) and shortwave infrared (SWIR).

Calculate NDVI and export

Published on May 19, 2020
Normalized Difference Vegetation Index (NDVI) quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs).

Topographic illumination correction for Sentinel 2 - Python API

Published on Apr 26, 2020
Variation in the reflectance within the same land cover type can be seen in mountain areas caused due to sun position, slope, and aspect of the landform.

Chirps Precipitation to Excel - GEE and Pandas

Published on Apr 29, 2020
Extract Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset using Google earth engine API and convert it into. Excel and charts using Python Pandas data frame.

Land Cover Mapping - Part 4 (Analyze Statistics)

Published on Jun 08, 2020
Statistics are simple tools that helps us for a better understanding of our images. Spatial statistics is one of the most rapidly growing areas of statistics.

Land Cover Mapping - Part 3 (Validation)

Published on Jun 04, 2020
The surface of the Earth is continuously changing at many levels; local, regional, national, and global scales. Changes in land use and land cover are pervasive, rapid, and can have significant impacts on people, the economy, and the environment.

Calculate NDVI from Sentinel-2 with Python API

Published on May 07, 2020
Normalized Difference Vegetation Index (NDVI) quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs).

20 year Time-series change of Mega projects

Published on Jun 09, 2020
20 year Time series analysis of megaproject using Landsat satellite.

Interactive web mapping with Django and Google Earth Engine

Published on May 03, 2020
There are several ways to use GEE and each one has its advantages and disadvantages. In this example, GEE is used for web mapping with python Django.

Calculate Zonal Statistics and export as CSV

Published on Jul 10, 2020
Get statistics in each zone of the image or image collection in google earth engine and export the data in CSV. Statistics are simple tools that help us for a better understanding of our images. Spatial statistics is one of the most rapidly growing areas of statistics.

Most used spectral Indices with free satellite data

Published on May 14, 2020
Today many different indices exist and each one has its own significance in the study. Here are the most popular indices that be calculated from free data satellites.

All you need to know about NDVI

Published on May 07, 2020
The Normalized Difference Vegetation Index is a simple indicator of photosynthetically active biomass or, in layman’s terms, a calculation of vegetation health.

Google earth engine with python

Published on May 07, 2020
In addition to the web-based IDE Google Earth Engine also provides a Python API that can be used on your local machine.