International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W11
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W11, 85–92, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W11-85-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W11, 85–92, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W11-85-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Feb 2020

14 Feb 2020

LAND COVER MONITORING OF LAGUNA LAKE WATERSHED USING MODIS NDVI DATA

J. M. Medina1, A. C. Blanco1,2, and C. G. Candido1 J. M. Medina et al.
  • 1Training Center for Applied Geodesy and Photogrammetry, University of the Philippines Diliman, 1101 Quezon City, Philippines
  • 2Department of Geodetic Engineering, University of the Philippines Diliman, 1101 Quezon City, Philippines

Keywords: LULC, vegetation index, ISODATA, spacetime cube, hot spot analysis, MAD, canonical correlation

Abstract. Land use and land cover monitoring is an important component in the management of Laguna Lake watershed due to its impacts on the lake’s water quality. Due to limitations caused by cloud cover, satellite systems with limited revisit capability fail to provide sufficient data to more effectively monitor the land surface. Normalized difference vegetation index (NDVI) derived from MODIS image data were used to generate land cover maps for the years 2001, 2005, 2009, 2013, and 2017. These were produced by classifying ISODATA classes using annual NDVI profiles, which resulted in land cover classes, namely, agricultural land, built-up, forest, rangeland, water, and wetland. The resulting maps were post-processed using multi-variate alteration detection (MAD), resulting in multi-temporal land cover maps with improved overall accuracies and kappa coefficients that indicate moderate agreement with ground truth data. Spatiotemporal hot spot analysis was also performed using NDVI data from 2001 to 2017 to identify vegetation hot spot areas, where clustering of low NDVI values were observed over the years. Results showed an increasing trend in built-up areas accompanied by decreasing trends in water and wetland areas, indicating impacts caused by land reclamation and expansion of residential subdivisions near the lakeshore. The decrease in total vegetation area from 2001 to 2017 could be attributed to conversion of land to built-up surface. Vegetated areas in identified hot spots decreased from 41% in 2001 to 19% in 2017. This suggests that vegetation cover in these hot spots was converted to non-vegetated surface during the time period studied.