Measurements of forest cover and change are vital to understanding the global carbon cycle and the contribution of forests to carbon sequestration. Many nations are engaged in international agreements, such as the Reducing Emissions from Deforestation and Degradation (REDD+) initiative, which includes tracking annual deforestation rates and developing early warning systems of forest loss. Remote sensing data are integral to data collection for these metrics, however, the use of optical remote sensing for monitoring forest health can be challenging in tropical, cloud-prone regions.
Radar remote sensing overcomes these challenges because of its ability to “see” the surface through clouds or regardless of day or night conditions. In addition, the radar signal can penetrate through the vegetation canopy and provide information relevant to structure and density.
Although the capabilities and benefits of SAR data for forest mapping and monitoring are known, it is underutilized operationally due to data complexities and limited user-friendly tutorials.
This advanced webinar series will introduce participants to 1.) SAR time series analysis of forest change using Google Earth Engine (GEE), 2.) land cover classification with radar and optical data with GEE, 3.) mapping mangroves with SAR, and 4.) forest stand height estimation with SAR. Each training will include a theoretical portion describing the use of SAR for landcover mapping as related to the focus of the session followed by a demonstration that will show participants how to access, download, and analyze SAR data for forest mapping and monitoring. These demonstrations will use freely-available, open-source data and software.
By the end of this training, attendees will be able to:
Attendees who have not completed the following may not be prepared for the pace of this training:
You can follow along with the demonstrations by using the software listed below. Recordings of each Part will be made available on YouTube within 48 hours after each demonstration for you to go through at your own pace.
Part One: Time Series Analysis of Forest Change
Part Two: Land Cover Classification with Radar and Optical Data
– Google Earth Engine
Part Three: Mangrove Mapping
– Sentinel-1 Toolbox
Local, regional, state, federal, and non-governmental forest and environmental managers already working with satellite remote sensing datasets for forest monitoring.