DOI: https://doi.org/10.14710/geoplanning.5.1.17-34

MONITORING AND PREDICTING LAND USE-LAND COVER (LULC) CHANGES WITHIN AND AROUND KRAU WILDLIFE RESERVE (KWR) PROTECTED AREA IN MALAYSIA USING MULTI-TEMPORAL LANDSAT DATA

Jibrin Gambo  -  Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM) and School of General Studies, Binyaminu Usman Polytechnic, Hadejia P.M.B 013 Jigawa State, Nigeria, Nigeria
*Helmi Zulhaidi Mohd Shafri orcid  -  Universiti Putra Malaysia (UPM), Malaysia
Nur Shafira Nisa Shaharum  -  Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), 43400, Serdang, Malaysia, Malaysia
Fauzul Azim Zainal Abidin  -  Department of Wildlife and National Parks (DWNP), KM10 Jalan Cheras, 56100 Kuala Lumpur, Malaysia, Malaysia
Mohd Taufik Abdul Rahman  -  Department of Wildlife and National Parks (DWNP), KM10 Jalan Cheras, 56100 Kuala Lumpur, Malaysia, Malaysia

Citation Format:
Abstract
Natural and anthropogenic activities surrounding a Protected Area (PA) may cause its natural area to change in terms of Land Use-Land Cover (LULC). Thus, there is need of environmental change monitoring within and around PA because of its significant values to ecosystem at conservation scales. Effects and influences of local community within and around PA turn into the major problems for natural resource and conservations management as well as environmental impact assessment. Ascertaining the complex interface in relations to changes and its driving factors over period of time within and around PA is significant in order to predict future LULC changes, build alternative scenarios and serve as tools for decision making.  The main objective of this work was to evaluate temporal change detection and prediction of LULC as well as the trends of changes from 1989 to 2016 within and around Krau Wildlife Reserve (KWR).  The cloud issues were mitigated by producing cloud free image and object-based image analysis (OBIA) was adopted after a comparison with pixel-based analysis for overall accuracy and kappa statistics. The comparison of classified maps had produced a satisfactory results of overall accuracies of 91%, 86% and 90% for 1989, 2004 and 2016 respectively. The natural/dense forest between periods of 1989-2016 was decreased whereas built-up and agricultural/sparse forest were increased. The simulation model of Land Change Modeler (LCM) was utilized with digital elevation model (DEM) and past LULC maps to project future LULC pattern using Markov chain. The predicted map trend showed an increase of dense forest converted to agricultural/sparse forest in the north-western, and urban/built-up in east-southern part of KWR. The study is important for the conservation of habitat species and monitoring the current status of the KWR
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Keywords: LULC; OBIA; Protected Area; Krau Wildlife Reserve; Land Change Modeler

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Section: Original Research
Language : EN
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