Patience Kori

A GIS enthusiast keen to use location analytics, web mapping, web design, and web development to find solutions to the day-to-day challenges in the world. An avid reader especially in the growing trends of machine learning, the internet of things, and artificial intelligence.
Creating a chart in Google Earth Engine

Creating a chart in Google Earth Engine

Charts are used to represent data. They can be in different forms; such as pie charts, bar charts, column charts, line charts, scatter plots, and histograms. This blog will show a simple code for the creation of a bar chart in GEE. The result when the code is run is a bar chart as shown…

Exporting vector data in GEE

Exporting vector data in GEE

This blog shows how to export images from the google earth engine. The blog on supervised classification is used, and we will be exporting the classified image to Google Drive as shown below. The code for exporting the image is as follows: Once the code is run, the exportation process is visible on the task…

Adding a Legend in GEE

Adding a Legend in GEE

A legend is a quick guide and easy roadmap to enable the identification of the outputs of a particular analysis or study. In this blog, a legend is created for the supervised classification we did earlier. The following is a step-by-step guide for adding a legend in GEE. Create the legend title and style it….

Importing vector and raster data in the Google Earth Engine.

Importing vector and raster data in the Google Earth Engine.

Vector and raster data formats are used in analysis in the Google Earth Engine. Vector data can be in formats such as shapefile, which is the most commonly used, Digital Line Graph (DLG), Keyhole Markup Language (KML), GeoJSON (Geographic JavaScript Object Notation), among others. Raster data formats on the other hand can be in GeoTIFF,…

Accuracy Assessment in Image Classification on GEE

Accuracy Assessment in Image Classification on GEE

This post covers accuracy assessment on a sentinel image in the Google Earth Engine. Selection of the area of interest and the classification classes This is done using the geometry tool as shown below. One can use the point tool or the polygon tool in the selection of the classes. Selection of the Image collection…

Computation of NDVI using Google Earth Engine

Computation of NDVI using Google Earth Engine

Normalized Difference Vegetation Index (NDVI) is a spectral index used to quantify the greenness of vegetation. It is used to monitor the health of plants and understand vegetation density. Calculating NDVI is done using two bands: the red band and the near-infrared band. This computation can be easily adapted using the Google earth engine. This…

Unsupervised Classification in the Google Earth Engine

Unsupervised Classification in the Google Earth Engine

This blog covers unsupervised classification in the Google earth engine. Source: Google Earth Engine The process of unsupervised classification in GEE is carried out using¬† the ee.Clusterer package. The package has been adopted from Weka Loading of the image The image used in classification is from the landsat program. A landsat 7 image is used…