The background for the Global Forest Watch and Forest Watcher training is the rampant deforestation in Indonesia’s primary forests. The use of remote sensing technology has long been used in forest monitoring and protection activities, but early detection of deforestation is still a challenge for forest protection activists. Global Forest Watch is a platform that makes monitoring forests easier because of the GLAD alert feature (GLAD Alerts) developed by the University of Maryland with WRI (World Resources Institute). GLAD alerts are able to indicate rapid loss of trees in an area. Based on the capabilities of the Global Forest Watch platform, it can be seen that there is a close link between the need for data on rapid tree loss and forest monitoring activities that are accelerating with rapid deforestation.
The training activities were carried out from 19 – 21 December 2022. The participants who attended were JPIK members in West Sumatra, Jambi, and the JPIK National Secretariat as well as instructors from WRI with a total of 23 people. The training was divided into 3 days, where the first day was used to introduce the Global Forest Watch and Forest Watcher applications. The second day was used for simulation experiments on how to process Global Forest Watch and Forest Watcher data using ArcMap and QGIS. The latest GLAD alert data (GLAD Alerts) from Global Forest Watch is processed using Arcmap or QGIS by utilizing forest area data to see deforestation points that occur in forest areas without concession permits. On the last day, the participants headed to the monitoring location they had obtained the previous day to carry out a direct monitoring simulation in the field. After being at the location, it was seen that there was indeed a new land clearing in accordance with the GLAD warning data that had been obtained. Overall, the participants understood how to use the Global Forest Watch platform, starting from selecting monitoring locations, utilizing GLAD warning data, to determining priority locations for direct monitoring. This training can assist monitors in carrying out their duties as forest monitors and protectors.