Ho Chi Minh City, Vietnam, September 14-16, 2015

Monitoring deforestation and degradation is key to assessing change in carbon storage. Satellite remote sensing is the most cost effective way to monitor forest change over larger areas and most accurate for national reporting. Given the increased availability of remote sensing data, this workshop will familiarize scientists with the different existing time series methods. Each time series method will be applied in an area in the Lam Dong Province in Vietnam. These methods will use a time series of Landsat optical data for mapping and modelling forest cover and forest cover change.

Purpose of the training course/workshop:

This workshop is designated to expose partners to different processing methods, classifications, quality assessments, and derivation of time derived spectral features. Additionally, the workshop will help to improve the technical knowledge on mapping forest change using time series analysis systems; and help to coordinate the next steps for time series systems capacity transfer. The workshop will showcase all the technical and financial aspects for running several Landsat based time-series analyses for detecting cover forest change. The leading experts of these methodologies will be running their methods before the workshop in a Landsat scene in the Lâm Đồng province of Vietnam. An accuracy assessment will be conducted prior to the workshop, and it will be used as a base for discussing the differences among the change detection products produced by each method. Vietnam representatives will have the opportunity to discuss, verify, and explore the dynamics of forest cover change using Google Earth Engine and the TimeSync Landsat time-series Visualization tool. The overall goal of the workshop is to identify the method that will be more suitable for Vietnam to adapt in the future considering their resources and technical capacity. In the future, a second intensive workshop will be scheduled for hands on training in one of the methodologies if Vietnam considers them suitable.