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Category: Google Earth Engine Page 1 of 3

Land cover Mapping in Data Scarce Environments: Challenges and Opportunities. Another paper on Land Cover

Land cover maps are a critical component to make informed policy, development, planning, and resource management decisions. However, technical, capacity and institutional challenges inhibit the creation of consistent and relevant land cover maps for use in developing regions. Many developing regions lack coordinated capacity, infrastructure, and technologies to produce a robust land cover monitoring system … CONTINUE READING

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

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

Machine Learning and Artificial Intelligence Exploring the Google TensorFlow Ecosystem

With the recent release of TensorFlow 2.0, showcased at GEO for Good 2019, there is increased interest in employing an array of neural net approaches to solve various Remote Sensing research questions. A dedicated group from NASA SERVIR has spent the last 5 days exploring the Google Earth Engine, Google Colaboratory, and Google … CONTINUE READING

Thresholding the primitives to generate the Land Cover Maps: a UI application in Google Earth Engine

This simple UI interface is built on the Google Earth Engine. It uses the primitives as percentage layers to assemble them to derive land cover maps. Here we are using the Random Forest algorithm to generate the land cover maps.
You can use the sliders to change the threshold input for the tree node structure … CONTINUE READING

Animation of the Amazon Fires 2019 using Google Earth Engine

Let’s use Google Earth Engine and satellite data to visualize the time-series of the Amazon Fires 2019. In this post, I will be using FIRMS (Fire Information for Resource Management System). FIRMS disseminates Near-Real-Time active fire from the NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) satellite. This data … CONTINUE READING

Making forest map using GLAD TCC and TCH Layers

Use the following code or follow the linkCONTINUE READING

Make a simple landcover classification map using Regression Tree

The full code for classification after obtaining sample points is here. The full code for classification with sample points generated on the fly is here.

Note: This is a very simple method for generating Landcover maps meant for showing the basic workflow for generating Landcover maps. You can use more sophisticated algorithms like CONTINUE READING

Point sampling in Google Earth Engine

In this exercise, we will try to sample a composite image of the Landsat with the landcover feature collection that we have. The full code can be found here.
The Feature Collection has the following integer assigned for ‘landcover’ column.

0 -> urban
1 -> vegetation
2 -> water

  1. We will use Landsat.simpleComposite method
CONTINUE READING

Filter a Feature Collection by attribute in Google Earth Engine

The full source code for the same can be found here.

  1. If you do not have the data yet, you can download it from here. I downloaded the Admin 1 boundary, but this method is generic, so applies to any shapefile that you have.
  2. Open up the QGIS or any other GIS software
CONTINUE READING

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