An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

Abstract

Time series of satellite sensor data have been used to quantify mangrove cover changes at regional and global levels. Although mangrove forests have been monitored using remote sensing techniques, the use of time series to quantify the regeneration of these forests still remains limited. In this study, we focus on the Matang Mangrove Forest Reserve (MMFR) located in Peninsular Malaysia, which has been under silvicultural management since 1902 and provided the opportunity to investigate the use of Landsat annual time series (1988–2015) for (i) detecting clear-felling events that take place in the reserve as part of the local management, and (ii) tracing back and quantifying the early regeneration of mangrove forest patches after clear-felling. Clear-felling events were detected for each year using the Normalized Difference Moisture Index (NDMI) derived from single date (cloud-free) or multi-date composites of Landsat sensor data. From this series, we found that the average period for the NDMI to recover to values observed prior to the clear-felling event between 1988 and 2015 was 5.9 ± 2.7 years. The maps created in this study can be used to guide the replantation strategies, the clear-felling planning, and the management and monitoring activities of the MMFR.

Eleven Years of Mangrove–Mudflat Dynamics on the Mud Volcano-Induced Prograding Delta in East Java, Indonesia: Integrating UAV and Satellite Imagery

“…We assessed the mangrove vegetation cover by way of four optical-related vegetation indices that are widely used in land cover characterisation [14,78,81,82], i.e., NDVI (Normalised Difference Vegetation Index) [83], NDMI (Normalised Difference Moisture Index) [15], EVI (Enhanced Vegetation Index) [84], and SAVI (Soil-Adjusted Vegetation Index) [85]. The S1 images were first pre-processed with a speckle filter (Lee refined) at a window size of 7 × 7 pixels [81,86].…”

Distribution of mercury in sediments, plant and animal tissues in Matang Mangrove Forest Reserve, Malaysia

“…Sundarbans in India (Muller, 1979), could be due to prevailing interspecies, regional, individual and tissue differences (Ding et al, 2009). The canopy structure at managed mangrove sites in MMFR is quite uniform as all trees have the same age and the forest gets a closed canopy after 6 years on average (Otero et al, 2019), while in the Sundarban mangroves the forest structure is much more variable and therefore stems are more exposed to the atmosphere and to Hg deposition. Moreover, Chowdhury et al (2017) have linked the accumulation of Hg in R. apiculata bark with the atmospheric deposition due to burning of fossil fuel and garbage by local people along with agricultural and chemical run-off.…”

Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tree Models

“…The most common method for mapping vegetation are the vegetation indices such as the Simple Ratio Index (SRI) of Birth and McVey (1968), Normalized Difference Vegetation Index (NDVI) of Edwards and Richardson (2004), and the Normalized Difference Moisture Index (NDMI) is the oldest and most well known and most frequently used by several researchers (Fang and Liang, 2003;Huete et al, 2010). These indices were designed to enhance the sensitivity of the spectral reflectance contribution of vegetation while minimizing the soil background reflectance or atmospheric effects (Fang and Liang, 2008;Huete et al, 2010) and widely used in the literature (Díaz and Blackburn, 2003;Ishil and Tateda, 2004;Jean-Baptiste and Jensen, 2006;Kovacs et al, 2009;Rodríguez-Romero et al, 2011;Laongmanee et al, 2013;Nascimento et al, 2013;Pereira et al, 2018;Otero et al, 2019;Liu et al, 2020). These indices sometimes cannot discriminate between mangrove and non-mangroves areas such as grass and algae (Howari et al, 2009;Elmahdy and Mostafa Mohamed, 2013a,b).…”