Abstract

Abstract. Land Surface Temperature (LST) is said to be affected by frequent changes in the land cover. Over the years, the immediate environs of Mount Makiling Forest Reserve (MMFR) have experienced such kind of change due to rapid economic growth of the area that also led to the expansion of urban centers. The study utilized Landsat imageries to determine the possible effects of land cover change on surface temperature using the integration of remote sensing and GIS technologies. Initially, the multispectral bands were radiometrically corrected using Dark Object Subtraction (DOS) while the thermal bands were corrected using Land Surface Emissivity (LSE). After these corrections were applied, the images were classified using supervised image classification technique where seven land cover types have been identified. The classified images were then validated using 200 reference data and this revealed an overall accuracy of 87.5% and 86.0% for the May 2003 and July 2015 images, respectively. Results showed that changes in land cover resulted to a significant change in Land Surface Temperature (LST). The LST in 2003 (16.49°C – 40.44°C) was found higher than that of 2015 which was observed between 13.35°C and 33.83°C only. The reason behind this is the increase in green spaces from 2003 to 2015. Among the major land cover types, forest lands exhibited the lowest mean surface temperature for both years having 27.27°C in 2003 and 21.35°C in 2015 while built-up areas had the highest surface temperature having 32.60°C in 2003 and 26.00°C in 2015.

Highlights

  • Population growth and economic expansion are some of the major causes of land cover changes worldwide, especially in developing countries

  • The green spaces around the world increasingly turns into buildings and other infrastructures that have been brought by the population growth

  • Geographic Information Systems (GIS) is a powerful tool in analyzing and presenting information obtained from satellite images

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Summary

INTRODUCTION

Population growth and economic expansion are some of the major causes of land cover changes worldwide, especially in developing countries. Its land is converted from forest to agriculture to built-up area for only a short period of time to accommodate the increase in population This is primarily because of its proximity to Metro Manila and the economic and industrial opportunities that exist in the region. As of the year 2000, 67 percent of Calabarzon’s population is in urban areas (Lusterio-Berja, et al, 2008) With this massive population growth in the said region, environmental issues such as forest degradation, pollution, climate change, and global warming increasingly became a major concern. Geographic Information Systems (GIS) is a powerful tool in analyzing and presenting information obtained from satellite images Utilizing these effective and efficient tools helps researchers, the government, and urban planners to understand and monitor the possible effects of land cover in the land surface temperature

Data Collection
Study Area
Image Pre-processing
Accuracy Assessment
Supervised image classification
Supervised Image Classification
Change Detection Statistics of Land Cover
CONCLUSIONS
Findings
A Statistic Correlation Analysis Algorithm between
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