The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLVI-4/W6-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W6-2021, 295–301, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-295-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W6-2021, 295–301, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-295-2021

  18 Nov 2021

18 Nov 2021

MONITORING POST-DISASTER MANGROVE FOREST RECOVERIES IN LAWAAN-BALANGIGA, EASTERN SAMAR USING TIME SERIES ANALYSIS OF MOISTURE AND VEGETATION INDICES

K. V. Ticman1, S. G. Salmo III2, K. E. Cabello1, M. Q. Germentil1, D. M. Burgos1, and A. C. Blanco1,3 K. V. Ticman et al.
  • 1Department of Geodetic Engineering, College of Engineering, University of the Philippines Diliman, Philippines
  • 2Institute of Biology, College of Science, University of the Philippines Diliman, Philippines
  • 3Training Center for Applied Geodesy and Photogrammetry, University of the Philippines Diliman, Philippines

Keywords: Mangroves, Landsat 8, time series, NDVI, EVI, MSAVI, NDMI

Abstract. The mangrove forests of Lawaan-Balangiga in Eastern Samar lost significant cover due to the Typhoon Haiyan that struck the region in 2013. The mangroves in the area have since shown signs of recovery in terms of growth and spatial coverage, but these widely varied with locations. This study aims to further examine the status of recovery of mangroves across different locations by analysing the time series trends of selected vegetation and moisture indices: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Normalized Difference Moisture Index (NDMI). These indices were extracted from Landsat 8 surface reflectance images, spanning 2014 to 2020, using Google Earth Engine (GEE). The time series analyses showed similar NDVI, MSAVI and NDMI values and trends after the 2013 typhoon event. The trend slopes also indicated high correlation (0.91 – 1.00) between and among the indices, with NDVI having the highest correlation with MSAVI (∼1.00). The study was able to corroborate the previous study on mangroves in Lawaan-Balangiga, by presenting positive trend results in the identified recovered areas. These trends, however, would still have to be validated by collecting and comparing biophysical parameters in the field. The next step of the research would be to identify the factors that contribute to the varying rates of recovery in the areas and to evaluate how this can affect the carbon sequestration rates of recovering mangroves.