UTILIZATION OF SPOT 6/7 AND LANDSAT TO ANALYZE OPEN GREEN SPACE AND BUILT AREA IN SURABAYA CITY

Mohammad Ardha, Nurwita Mustika Sari, Mukhoriyah Mukhoriyah

Abstract

The migration of people from rural to urban areas is a common phenomenon nowadays. One of the goals of urbanization is in the city of Surabaya. The increase in population causes the need for housing and the need for life to increase. One of the many changes in land use is the change of land into built-up land. The increase in the area of built-up land currently raises a new phenomenon where the area of open space is reduced due to changes in land use, one of the changes in land use is from green open space to built-up land. This study aims to see the extent to which the growth trend of green open space and built-up land in the city of Surabaya by using the NDVI method to see the trend of changes in green open space in the city of Surabaya and NDBI for the land built in the city of Surabaya. The data used in this study are SPOT 7 images for green open space and Landsat 8 for built land. Based on this method, green open space in the city of Surabaya in 2015 was 29.19%, in 2016 it was 21.22%, then in 2017 it was 24.54 %, and in 2018 it was 27.60%. While for Built land in 2015, it was 26.43%, in 2016 it was 26.44%, in 2017 it was 30.99% and in 2018 it was 42.88%. Other results were also obtained for the change of green open space into the land. awakened has increased every year, namely from 2015 to 2016 by 2.67%, from 2016 to 2017 by 4.43%, and from 2017 to 2018 by 8.08%. As for the land built into green open space, namely 2015 to 2016 of 2.01%, 2016 to 2017 of 2.84%, 2017 to 2018 of 2.72%. The conclusion from this activity is that NDVI can be used to see the level of vegetation density which can indicate the existence of green open space in urban areas. And NDBI can show the existence of built-up land. The city of Surabaya, has stable green open space, while the built land continues to increase every year.

Keywords

: Open Green Space, NDVI, NDBI SPOT, Remote Sensing

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DOI: http://dx.doi.org/10.30536/j.ijreses.2024.v21.a3904

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