Two Decades Mangroves Loss Monitoring Using Random Forest and Landsat Data in East Luwu, Indonesia (2000–2020)

Abstract

Mangroves grow in the tidal zone and have many benefits for the ecosystem and human life. Mangrove loss monitoring is important information to know the condition and status of mangrove forests. Along with the development of computer technology, machine learning and satellite imagery has widely used for mangrove mapping. The goal of this study is to monitor two decades (2000–2020) of mangrove loss using a random forest (RF) algorithm with Landsat-7 and Landsat-8 data in East Luwu, Indonesia. East Luwu has a high mangrove deforestation rate based on the previous study. More detailed mangrove loss monitoring in this area is needed to know the annual mangrove deforestation rate in this area. This study used an RF model to produce mangrove maps in the whole study area from 2000 to 2020. According to the large computing and storage capabilities of time-series satellite data, this study used Google Earth Engine (GEE) platform as the cloud computing process. A total of 2500 independent testing points were collected to calculate the evaluation assessment of produced mangrove maps. Based on the evaluation assessment, the average overall score of produced mangrove map is 0.966, while the average UA score of mangrove class is 0.936. In general, this study revealed the total area of mangroves in East Luwu from 2000 to 2020 has a decreased trend. The highest annual rate of mangrove loss happened from 2000 to 2005 with a loss rate of −14.11% (2477.39 Ha). The main factor of mangrove loss in this area is caused by the aquaculture ponds. In addition, we found an increase in mangrove areas from 2016 to 2020 by +1.04% (87.96 ha).

Keywords

• mangroves
• deforestation
• random forest
• Google Earth Engine
• East Luwu
• Landsat