Tutorials

Loading data in Jupyter notebooks

Loading data in Jupyter notebooks

A Jupyter notebook is a document that allows one to write code, notes and explanations as well as visualize the output of the code all in a single page. Its uses include data cleaning and transformations, data visualization, machine learning, simulations among others. Its numerous uses allow for working with multiple and varied data-sets from…

Display WMS Layer from GeoServer on Leaflet using Vue.js

Display WMS Layer from GeoServer on Leaflet using Vue.js

The Web Map Service (WMS) is an Open Geospatial Consortium (OGC) specification that defines an HTTP interface used to request a georeferenced map in an image format from a server. GeoServer supports WMS 1.1.1, the most widely used version of WMS, as well as WMS 1.3.0. WMS provides a standard interface for requesting a geospatial…

How to Apply Styled Layer Descriptor (SLD) in GeoServer

How to Apply Styled Layer Descriptor (SLD) in GeoServer

This tutorial will focus on outlining step by step process of applying a style on layer in GeoServer. A Style Layer Descriptor (SLD) file from QGIS will be used to style the layers. Launch QGIS and Export the Styled Layer Descriptor. Firstly, open QGIS and load the vector layer that you want to style. Apply…

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…

Computation of Principal Components Analysis in GEE

Computation of Principal Components Analysis in GEE

Principal components analysis (PCA) is a technique applied to hyperspectral and multispectral data acquired through remote sensing. PCA converts an original correlated image into a smaller image with uncorrelated variables. These variables represent most of the information existing in the original image or dataset. PCA reduces the dimensions of data. When PCA is done on…

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….

Shapefile Conditional Columns in GeoPandas and Numpy

Shapefile Conditional Columns in GeoPandas and Numpy

While most shapefiles acquired from various sources are fairly ready to use with little or no edits, other uses may dictate that changes are made to a shapefile. One such instance is the need to add a column to a shapefile based on some condition. In most instances, the conditions may be too complicated such…

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,…

Plotting a Digital Elevation Model Profile in GEE

Plotting a Digital Elevation Model Profile in GEE

A digital elevation model is a representation of the bare ground topographic surface of the earth exclusive of trees, buildings and other objects on the earth’s surface. Digital elevation models are extracted from sources such as topographic maps, high resolution LiDAR (Light Detection and Ranging) or IfSAR (interferometric Synthetic Aperture Radar). However, LiDAR and IfSAR…

Using Landsat 8 Image To Perform Cloud Masking on GEE

Using Landsat 8 Image To Perform Cloud Masking on GEE

Landsat 8 images are widely used for a variety of applications. However, cloud and cloud shadow cover issues are still a challenge. Clouds and cloud shadow decrease accuracy of remote sensing application results because they obscure the land surface, and the brightening effect of clouds and the darkening effect of cloud-shadow’s influence the reflectance capability…

Computation of NDBI in Google Earth Engine

Computation of NDBI in Google Earth Engine

What is NDBI? Normalized Difference Built-up Index (NDBI) is a spectral index used to analyze built-up areas. This index uses two bands: the short-wave infrared (SWIR) and the near infrared (NIR). Areas with more built-up structures reflect shortwave-infrared (SWIR) more while areas with less built-up have a low Near-Infrared (NIR) reflectance. NDBI values range from…