This study investigated the drivers of degradation in Southeast Asian mangroves through multi-source remote sensing data products. The degradation drivers that affect approximately half of this area are unidentified; therefore, naturogenic and anthropogenic impacts on these mangroves were studied. Various global land cover (GLC) products were harmonized and examined to identify major anthropogenic changes affecting mangrove habitats. To investigate the naturogenic factors, the impact of the water balance was evaluated using the Normalized Difference Vegetation Index (NDVI), and evapotranspiration and precipitation data. Vegetation indices’ response in deforested mangrove regions depends significantly on the type of drivers. A trend analysis and break point detection of percentage of tree cover (PTC), percentage of non-tree vegetation (PNTV), and percentage of non-vegetation (PNV) datasets can aid in measuring, estimating, and tracing the drivers of change. The assimilation of GLC products suggests that agriculture and fisheries are the predominant drivers of mangrove degradation. The relationship between water balance and degradation shows that naturogenic drivers have a wider impact than anthropogenic drivers, and degradation in particular regions is likely to be a result of the accumulation of various drivers. In large-scale studies, remote sensing data products could be integrated as a remarkably powerful instrument in assisting evidence-based policy making.

Mangrove has an important role not only for ecosystem services such as erosion control and water purification but also for human life. For instance, mangrove has been satisfactorily saving people from the ocean such as storm surge or tsunami. However, mangrove population has fallen for about a fifth over these 25 years. Therefore, rehabilitation and restoration of mangrove are essential to be taken to overcome mangrove loss. Nonetheless, in several areas, while doing the rehabilitation mangrove, some species of mangroves failed to survive due to several parameters that were not suitable for them to grow. Hence, this research aimed to determine suitable sites for mangrove life in Indonesia globally. This research used several parameters which were: elevation, slope, air temperature, and precipitation, to measure the suitable sites. The result shows that 62% from the total area (99,773 ha) of coastline in Indonesia are suitable for mangrove to grow included 59% is suitable class (95,347 ha) and 3% is perfectly suitable class (4,427 ha), while the unsuitable class has 38% (61,616 ha) from the total area. Furthermore, in some areas, the decreasing number of suitable land for mangrove was related to the increasing number of mangrove deforestation.

As natural drivers of mangrove forests’ degradation and depletion, mangrove forests’ water balance, as the ability of them to absorb and release water, which is related to mangrove’s coefficient growth, also makes an impact to those circumstances. The intention of this research is to identify the mangrove growth coefficient that used to analyze mangrove’s water balance and to identify the influence of mangrove’s water balance from mangrove’s depletion and degradation. The research is situated at Southeast Asia in 2000 and 2012. As a proxy for mangrove coefficient growth, MOD13A1 V6 satellite imagery that provides vegetation index values were used and will be multiplied by using the linear regression model that establishes the relationship between vegetation index and mangrove coefficient growth. The procedure for quantifying the mangrove’s water balance is carried out by multiplying the mangrove coefficient growth with evapotranspiration data derived from MOD16A2 V5 and then deducting it by precipitation data from CHIRPS V2. The results presented will confirm how these parameters influence the mangrove’s water balance and influential or not against the mangrove’s lost.