The Geo-ICT Blog

Tutorials/Post – ICT, GIS, Remote Sensing, Earth System, Humanitarian, Disaster Management, Travel

Month: October 2019

Primitives as building blocks for constructing landcover maps – New paper out on RLCMS and Google Earth Engine

Land cover maps play an integral role in environmental management. However, countries and institutes encounter many challenges with producing timely, efficient, and temporally harmonized updates to their land cover maps. To address these issues we present a modular Regional Land Cover Monitoring System (RLCMS) architecture that is easily customized to create land cover products using … CONTINUE READING

Downloading 12.5 m ALOS PALSAR High-Resolution DEM

NASA’s Earth Observing System Data and Information System (EOSDIS) is the data distribution system facilitated with NASA’s Distributed Active Archive Centers (DAACs). Alaska Satellite Facility (ASF) is one of the DAAC providing various data sources to the public for free. We will use the ASF website (as of 28th October 2019) to download the 12.5 … CONTINUE READING

Changing the size of the rectangle in Google Earth Engine

After the Geo for Good Summit 2019, all my focus has been geared toward integrating Machine Learning Models using Tensorflow with the Satellite data.  One of the issues for exporting the training and testing data especially with a large number of features or huge areas for the neighborhood pixels if you are using the Fully … CONTINUE READING

Connected Pixel Counts in Google Earth Engine

Connected Pixel Count is one of the ways where the concept of the Minimum Mapping Unit (MMU) can be applied. Basically, the connected pixel count gives the image with every pixel containing the information on the number of the connected neighbors including the pixel in context. The neighbors can be 4- or 8-connected neighbors, and … CONTINUE READING

Area Calculation using Google Earth Engine

There are a couple of ways to calculate the area of the image in the Google Earth Engine. The full implementation of both method can be accessed using this link.

  1. Pixel Count Method
    We can calculate the area of the image by counting the total number of unmasked pixels in that image. Then, multiply
CONTINUE READING

Powered by WordPress & Theme by Anders Norén