ANALYSIS OF URBAN GREEN SPACE CLASSIFICATION USING LANDSCAPE PATTERN ANALYSIS BASED ON GIS AND REMOTE SENSING IN PATTAYA, THAILAND.

Abstract

Thailand is a country located in Southeast Asia. The Thai government wants to become the economic leader of Association of Southeast Asian Nations (ASEAN), so there is an economic development plan named Eastern Economic Corridor (EEC), a megaproject with a huge investment budget. Pattaya is a part of ECC in Chonburi, Thailand. This project will make Pattaya more accessible and be the center of the East. Most of the land use of Pattaya is urban and built-up land, and forest and water are low. During the process of populations, urbanization reduce the availability of space in the city, created artificial and impervious surfaces to replace natural areas. The green space should be developed along with the ECC project for the good quality of life of the people in Pattaya. However, despite efforts to increase green areas. Which had begun a long time ago, but there has not been found a suitable measure to lead to factual action.

The purpose of this research are 1) to explore the urban green space (UGS) classification that represent the structure and 2) to analyze the quantity and distribution of UGS using landscape pattern analysis in Pattaya, Thailand. In order to implement the map provided as a guide for the optimization of green space patterns, increasing the benefits of green space, and planning green spaces in Pattaya City.

The usage of the classification for UGS are processed through landscape pattern analysis. In this research, use satellite image interpretation with high-resolution (Pléiades). The base is a map of Pattaya's land use. Digitization for six criteria: (1) natural green space, (2) amenity green space, (3) function green space, (4) linear green space, (5) economy green space and (6) abandoned green space were identified to explore the classification. The field survey provided information to validate the interpretations. Landscape pattern was based on landscape metrics analyzed using FRAGSTAT 4.2. Six landscape metrics were chosen and they were (1) the number of patches (NP), (2) the total area of each patch type (CA), (3) patch density (PD), (4) mean patch area (Area_MN), (5) Shannon’s Diversity Index (SHDI) and (6) Shannon’s Evenness Index (SHEI).

The result show that the study area in Pattaya have total area of 50.19 square kilometers and the total area covered by urban green space is 8.3174 square kilometer or 16.57% of the total area in Pattaya. The proportion of abandoned green space (AB) is the highest (63.69%), followed by functional green space (FS) (19.84%), natural green space (NS) (8.44%), Linear green space (LS) (4.96), Amenity green space (AS) (2.43) and economy green space (ES) (0.64%). If not counting the abandoned green spaces because it is an area that cannot be accessible and useless. There will be only 3.0198 square kilometers (6.02%) of green space that people can use. That means in Pattaya only have 5.81 square meters for per person (or less).

Landscape pattern analysis revealed that abandoned green space has the highest number of patches and patch density followed by functional green space, natural green space, linear green space and amenity green space while economy green space is the lowest. Abandoned green space has the highest mean patch area, followed by natural green space, economy green space, functional green space and amenity green space while the lowest is linear green space.

The result show that the landscape pattern of the Pattaya city is irrational, the amenity green space is severely lost and the distribution is not balanced. The proportion of abandoned green space is high but useless and the landscape diversity index is low. The analysis of landscape patterns allows interpretations of which types need interest to improve quality and quantity. Furthermore, to protect UGS from developing urbanization and to guide sustainable green space management in Pattaya.

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