Difference between revisions of "Effects of Background variation on special Vegetation indices in Mangrove Forest"

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[[Category: Theses]]
 
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[[Category: Remote Sensing Thesis]]
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[[Category: Genetic Engineering Thesis]]
 
[[Category: College of Engineering Thesis]]
 
[[Category: College of Engineering Thesis]]

Revision as of 01:04, 7 September 2011

Beata D. Batadlan

Thesis (M.S. in Remote Sensing) - -University of the Philippines, Diliman. -2009

Abstract

Mangroves are biologically diverse and fragile coastal ecosystems that are severely threatened by human activities in the coastal zone. While there is an urgent need to manage restore and rehabilities remaining mangrove areas, these interventions are either severely constrained by insufficient information on the current biophysical conditions of mangrove ecosystems. The use of remote sensing in spatial prediction and modeling of vegetation biophysical properties are prominent in terrestrial forest but very limited in mangroves. Vegetation indices (VIs) derived from satellite data are one of the primary sources of information for operational monitoring of the Earth's vegetive cover. However, the underlying background is one of the sources of variation in VIs and adjusted indices are developed to minimized and reduce soil background effects partiicularly at sparse vegetation and low leaf area index. Mangrove environments are subject to a wider background variations caused by tidal cycle at a specific conditions. Therefore, it is important to systematically investigate the influence of variations in background reflectance properties, created by different background types and changes in moisture content or inundation, on the relationships between spectral indices and canopy biophysical properties in order to identify robust predictive approaches. This study investigated the effects of various background conditions typically found in mangrove communities on the relationships on various spectral vegetation indices and leaf area index. The study area is located in Guimaras province within the Taklong Island National Marine Reserve (TINMAR). Satellite remote sensing image data taken by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on April 2005 was used to identify/classify mangrove areas within the study area. Mangrove canopy spectral reflectance and leaf area index (LAI) were measured in the field using a spectrometer and Photosynthetically Active Radiation sensor. These data were then used to calculate Spectral Vegetation Indices such as RVI, NDVI, SAVI, SAVI2, PVI, OSAVI, TSAVI and DVI. Field measurements were conducted last January 28-31, 2009 and April 20-25, 2009. The relationships between several spectral vegetation indices measured from the field and LAI have been assessed particularly the effects of background variation typically found beneath mangrove canopies. As expected soil influences were found prevailing in partially vegetted canopies they are more significant in LAI below 1.5. Based on the regression correlation coefficients, the Vegetation Indices which consider soil parameter normalized the soil-background effects such as SAVI₂, OSAVI, TSAVI and SAVI with corresponding regression coefficient of 0.81, 0.74, 0.73 and 0.71 respectively.