An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Silvicultural Management
2.2. Methods
2.2.1. Satellite Imagery
2.2.2. Time Series Creation
2.2.3. Fieldwork
2.2.4. Time Series Analysis
- We detected clear-felling events based on two conditions:
- We first defined a reference year as the year when the NDMI was below 0.288. This threshold was determined through comparison of the NDMI series of pixels associated with clear-felled and non-clear-felled areas. Areas with dense vegetation (including pre-logged and mature mangroves) exhibited NDMI values around 0.5, which contrasted with areas that were clear-felled which exhibited NDMI values below 0.288.
- The difference between the NDMI of the reference year and the following year was at least 0.275. We defined this second threshold to guarantee that the drop in the NDMI value was sufficient to correspond to a true clear-felling event. This second threshold was also determined by comparing different series of pixels associated with clear-felled and non-clear-felled areas. The approach followed on from previous studies [30,50,51,52] that have also used thresholds to analyse time series.
- We determined the following values for each clear-felling event:
- The year of clear-felling
- The year of recovery. This value was determined as the year when the NDMI value returned to the state prior to clearing [26]. This previous state was defined as the median value of all the points in the series before the clear-felling event minus one standard deviation to account for normal fluctuations in the vegetation index.
- The recovery time. This time is defined as the number of years that the mangrove forest took to regenerate that is, the difference between the year of recovery and the year of the clear-felling occurrence. If this number was one, we considered this event as noise as mangrove regeneration is not possible in a single year.
- The drop in the NDMI value, calculated as the difference between the NDMI value before clear-felling and the lowest NDMI value in the time series.
2.2.5. Validation Time Series Analysis
- The time series of 135 randomly selected pixels from locations clear-felled between 1989 and 2015. For each pixel, we determined the year of clear-felling and the recovery time by visual interpretation of the NDMI time series. We selected these points such that we included five examples of clear-felling events per year in the time series (from 1988 to 2015).
- The management zone maps and the logging plans included in the management plans from 2000 to 2009, and 2010 to 2019 [8,40]. First, we compared the existing local management zone map against the results of our clear-felling map, on the assumption that clearing only occurs in the productive and restrictive productive areas (i.e., where wood extraction is officially approved). Second, we compared the clear-felling year calculated in this study against the logging plans outlined in those management plans. These logging plans contain the year when the coupes should be clear-felled.
3. Results
3.1. Time Series Creation
3.2. Reference to Field and UAV Data
3.3. Time series Analysis
3.4. Validation Time Series Analysis
4. Discussion
4.1. Time Series Analysis
4.2. Implication for the Local Management
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Optical Sensor | Year and Number of Images Per Year |
---|---|
Landsat Thematic Mapper (TM) - Landsat 4 | 1991 (1) |
Landsat Thematic Mapper (TM) - Landsat 5 | 1988 (2), 1989 (6), 1990 (2), 1991 (4), 1992 (2), 1993 (1), 1994 (5), 1995 (1), 1996 (1), 1997 (3), 1998 (4), 1999 (2), 2000 (3), 2003 (2), 2004 (4), 2005 (6), 2006 (3), 2007 (5), 2008 (6), 2009 (2), 2010 (3), 2011 (2) |
Enhanced Thematic Mapper Plus (ETM+) – Landsat 7 | 1999 (1), 2000 (1), 2001 (2), 2002 (4), 2003 (3), 2012 (6) |
Operational Land Imager (OLI) – Landsat 8 | 2013 (6), 2014 (3), 2015 (1) |
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Otero, V.; Van De Kerchove, R.; Satyanarayana, B.; Mohd-Lokman, H.; Lucas, R.; Dahdouh-Guebas, F. An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia. Remote Sens. 2019, 11, 774. https://doi.org/10.3390/rs11070774
Otero V, Van De Kerchove R, Satyanarayana B, Mohd-Lokman H, Lucas R, Dahdouh-Guebas F. An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia. Remote Sensing. 2019; 11(7):774. https://doi.org/10.3390/rs11070774
Chicago/Turabian StyleOtero, Viviana, Ruben Van De Kerchove, Behara Satyanarayana, Husain Mohd-Lokman, Richard Lucas, and Farid Dahdouh-Guebas. 2019. "An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia" Remote Sensing 11, no. 7: 774. https://doi.org/10.3390/rs11070774