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Category: Google Earth Engine Page 2 of 3

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

Uploading a shapefile to Google Earth Engine

  1. In Code Editor, shapefiles can be uploaded to the assets. In the code editor, on the left side panel, go to Assets.
  2. Click NEW and Table upload.shape-file-upload
  3. In the popup screen. Make sure you have the correct path for the asset. Click SELECT. Point to the directory that has your shapefile. Earth Engine

An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale

In this study, we develop a vegetation monitoring framework which is applicable at a planetary scale and is based on the BACI (Before-After, Control-Impact) design. This approach utilizes Google Earth Engine, a state-of-the-art cloud computing platform. A web-based application for users named EcoDash was developed. EcoDash maps vegetation using Enhanced Vegetation Index(EVI) from Moderate Resolution … CONTINUE READING

Classifying the dynamics of the forest using the time-series

In this post, we will use the datasets from UMD (Tree Canopy Cover [TCC] and LOSS layers) to calculate and classify the dynamics of the forest. The TCC is available from 1988 and LOSS layers are available from 1989. Here we will be calculating different forest dynamics. Use the final assemblage using this link or … CONTINUE READING

Assessment of time since forest disturbance

In the assessment of time since forest disturbance, we define disturbance as the drop of TCC from =10% to 0%. Use following code or the link here.

Happy Earth Science 🙂… CONTINUE READING

Making Forest Rotation Map

Rotation of the forest is defined as the number of forest disturbance events for the year range, with disturbance defined as a drop of Tree Canopy Cover from >=10% to 0%, or the loss from 1 to 0.

The pseudo-code for the rotation map can be written as:

We travel time for 3 years and … CONTINUE READING

Calculate the amplitude of datasets over a time-series

With the Google Earth Engine, it’s very easy to calculate the amplitude of any time-series datasets. The amplitude in wave physics is defined as the distance between the high and the low peak as shown in the picture below. Similarly, for any raster datasets for a time series, the amplitude is the difference of the … CONTINUE READING

Get Primary Forest Map using the Tree Canopy Cover

The primary forest can be mapped in a number of ways. One of them is described here, where the base year 2000 map for the primary forest is used in relation with the forest definitions on tree canopy cover (tcc) and tree canopy height (tch) to calculate the primary forest in each year. Turns … CONTINUE READING

Mapping Primary Forest using UMD datasets

GLAD at UMD provides the primary forest for 2000 which is the base map for most of their analysis. This primary forest consists of natural long-lived forest extent. The mapping and definition for the primary forest are based on the methodology as described in the paper for humid tropical forests and modified to include dry … CONTINUE READING

SERVIR releases Synthetic Aperture Radar (SAR) Handbook

SERVIR released the Synthetic Aperture Radar (SAR) Handbook which includes the comprehensive methodologies for Forest Monitoring and Biomass Estimation. This handbook contains a collection of state-of-the-art methods and theoretical background to facilitate the use of SAR data for forest monitoring and biomass estimation.

Subject Matter Expert (SME) in SAR, in collaboration with SERVIR, conducted five … CONTINUE READING

Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000‐2017 Landsat time-series – A paper with GLAD at UMD

As a SERVIR-Mekong, we have been working closely with our Applied Science Team (AST)  at The Global Land Analysis and Discovery (GLAD) laboratory in the Department of Geographical Sciences at the University of Maryland led by Dr. Peter Potapov. The annual product on the Tree Cover Canopy (TCC), Tree Cover Height (TCH) and Primary Forest … CONTINUE READING

Change Detection in Google Earth Engine using Sentinel 1 images

In this tutorial, we will try to perform the change detection using the SAR images from the Sentinel-1 satellite images in the Google Earth Engine. As the SAR images are acquired in different polarisation medium namely VV, HH, VH, and HV, we will focus on dual polarisation medium VV and VH. Also, we will be … CONTINUE READING

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