No 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

Malaysia has a significant amount of biodiversity and has developed protected areas to conserve and sustain this tremendous degree of biodiversity. A protected area is known for its recognized natural, ecological or cultural values. However, the protected areas confront many obstacles, including poor or non-existent management plans. Remote sensing and Geographic Information Systems (GIS) can help with the speedy and cost-effective identification of biodiversity and environmentally sensitive areas. WebGIS (Web-based GIS) is useful for simplifying complicated geographical and temporal data on biodiversity such as the existence of threatened species, protected areas, and as well as on socially and environmentally significant ecosystem services. This study aimed to produce a WebGIS platform for Krau Wildlife Reserve (KWR) protected area using geospatial remote sensing and GIS data. The developed WebGIS played an important role in evaluating human activities near KWR that may impact the ecology and result in the extinction of natural habitats.