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Google Earth Engine
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.
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.
Google Earth Engine Image Pre-processing : Background and methods Part I
Published on Apr 19, 2020
While using remote sensing data several pre-processing steps can be applied that aim at removing artifacts from the images that are not related to the actual reflectance of the land cover such as sensor effects, atmospheric, and illumination conditions.
Google Earth Engine: Disadvantages and Limitation
Published on Apr 27, 2022
As Google Earth Engine is getting popular in geoscience and data computation, there are a few things that need to consider before you deep dive. This blog will highlight some of the GEE's limitations and disadvantages. Importantly, Google Earth Engine is free only for non-commercial, non-production use, This means its sole purpose is to serve the educational professional, students, and the nonprofit organization.
Learn Google Earth Engine from Scratch
Published on Sep 18, 2020
Google Earth Engine is a geospatial processing service with the motto "To organize the world's information and make it universally accessible and useful."
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).
Google earth engine Detail comparison between Python and JavaScript
Published on Apr 13, 2020
Both the Python and JavaScript APIs access the same server-side functionality, but it is different in the syntax and the way we digest.
Introduction to the Google Earth Engine Python API
Published on Apr 13, 2020
This tutorial will go over how to set up the API on your local machine as well as some basic Python scripts utilizing the Google Earth Engine Python API
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).
Google Earth Engine as WMS Layer - Using Python API
Published on Apr 02, 2020
The Python API provides a programmatic and flexible interface to Earth Engine for automating batch processing tasks, and leveraging the power of the command line.
Google Earth Engine tip 2 (Cyclone Thumnail)
Published on May 27, 2021
The Indian Ocean cyclone season has no official bounds, but cyclones tend to form between April and December, with the peak from May to November. With Google Earth Engine you can create and visualize the cyclone in the video for a particular day.
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.
Geo-pandas data frame to GEE feature collection using Python
Published on Apr 27, 2020
The simplest way to convert shapefile, CSV it into ee.FeatureCollection is to infuse the Geopandas data frame with GEE python API.
Land Cover Mapping - Part 2
Published on May 31, 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.
