Identification Of Critical Areas For Mangroves Species In Spcw Using Geographic
Macalino, Kyle Emmanuel D.
Identification Of Critical Areas For Mangroves Species In Spcw Using Geographic [manuscript] / Macalino, Kyle Emmanuel D. - Magalang, Pampanga : Pampanga State Agricultural University, June 2023. - xv, 83 leaves ; 28 cm + 1computer disc (4 3/4 inch)
ABSTRACT Macalino, Kyle Emmanuel D. May 2023. IDENTIFICATION OF CRITICAL AREAS FOR MANGROVES SPECIES IN SPCW USING GEOGRAPHIC INFORMATION SYSTEM. Pampanga State Agricultural University. Adviser: Gerald M. Salas, Ph. D. Mangroves are vital in coastal areas because they provide protection from storm surges and provide ecosystem services in the livelihood. However, they are at risk due to threats and lack of conservation and management. Five barangays (Malusac, Sebitanan, Mabuanbuan, Batang 1, Batang 2nd and Sasmuan Bangkung Malapad Critical Habitat Ecotourism Area) in Sasmuan Pampanga Coastal Wetlands (SPCW) was assessed to determine the species diversity through Shannon Wiener Index, the assessment showed that the species diversity of the mangrove species is low with the score of 142. The identification of critical areas for the Rhizophora species was done by habitat suitability analysis through QGIS. The criteria identified were weighted by experts using Analytical Hierarchy Process, then the weights were converted into percentages. The points for each criterium were interpolated to produce raster layers and they were given the corresponding attributes then the raster layers were overlayed by raster calculator. The results showed that there is a total area of 14019322.23 m2 "fairly suitable" areas followed by, 2995568,62 m2 of highly suitable areas" and with the least of 21 16895.94 m2 "not suitable" areas. The land classification was done through QGIS, the landsat images were downloaded in USGS earth explorer. The date ranges from 1993, 2004, 2014 and 2021, the raster data were rectified using DOSI atmospheric correction. The study used unsupervised classification to input region of interests. The results showed in the duration from 1993 to 2014 when built-up areas expand the vegetation area decreases.
Identification Of Critical Areas For Mangroves Species In Spcw Using Geographic [manuscript] / Macalino, Kyle Emmanuel D. - Magalang, Pampanga : Pampanga State Agricultural University, June 2023. - xv, 83 leaves ; 28 cm + 1computer disc (4 3/4 inch)
ABSTRACT Macalino, Kyle Emmanuel D. May 2023. IDENTIFICATION OF CRITICAL AREAS FOR MANGROVES SPECIES IN SPCW USING GEOGRAPHIC INFORMATION SYSTEM. Pampanga State Agricultural University. Adviser: Gerald M. Salas, Ph. D. Mangroves are vital in coastal areas because they provide protection from storm surges and provide ecosystem services in the livelihood. However, they are at risk due to threats and lack of conservation and management. Five barangays (Malusac, Sebitanan, Mabuanbuan, Batang 1, Batang 2nd and Sasmuan Bangkung Malapad Critical Habitat Ecotourism Area) in Sasmuan Pampanga Coastal Wetlands (SPCW) was assessed to determine the species diversity through Shannon Wiener Index, the assessment showed that the species diversity of the mangrove species is low with the score of 142. The identification of critical areas for the Rhizophora species was done by habitat suitability analysis through QGIS. The criteria identified were weighted by experts using Analytical Hierarchy Process, then the weights were converted into percentages. The points for each criterium were interpolated to produce raster layers and they were given the corresponding attributes then the raster layers were overlayed by raster calculator. The results showed that there is a total area of 14019322.23 m2 "fairly suitable" areas followed by, 2995568,62 m2 of highly suitable areas" and with the least of 21 16895.94 m2 "not suitable" areas. The land classification was done through QGIS, the landsat images were downloaded in USGS earth explorer. The date ranges from 1993, 2004, 2014 and 2021, the raster data were rectified using DOSI atmospheric correction. The study used unsupervised classification to input region of interests. The results showed in the duration from 1993 to 2014 when built-up areas expand the vegetation area decreases.