International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 07 | July 2024
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p-ISSN: 2395-0072
Application of the NDBI Method For Determining of Built-Up Land (A Case Study For Surabaya City, Indonesia) Wayan Suparta1,*, Hill Gendoet Hartono2 1Department of Electrical Engineering, Institut Teknologi Nasional Yogyakarta,
Jalan Babarsari, Caturtunggal, Depok, Sleman, Yogyakarta 55281, Indonesia
2Study Program of Magister of Geological Engineering, Institut Teknologi Nasional Yogyakarta,
Jalan Babarsari, Caturtunggal, Depok, Sleman, Yogyakarta 55281, Indonesia ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - To determine the built-up areas within a region or city for land use planning, map interpretation is one of the effective techniques. This paper utilizes the Normalized Difference Built-Up Index (NDBI) method for built-up city in Surabaya, Indonesia as a case study. Analyzing NDBI parameters from Landsat optical data reveals that Surabaya City saw a 21% increase in built-up land from 2002 to 2022. These findings highlight significant urban development in the city during this period and offer valuable insights for future spatial planning and land use policy formulation.
of NDBI. NDBI is one of the image processing methods aimed at identifying and analyzing built-up and non-builtup land in a region or city. The NDBI index highlights urban or built-up areas where there is usually higher reflectance in the Shortwave Infrared (SWIR) region compared to the Near-Infrared (NIR) region. SWIR is typically defined as light with a wavelength range of 0.9 – 1.7 µm [3]. The NDBI has advantages in identifying built-up areas because it utilizes the unique reflectance properties of building materials compared to vegetation and soil [3]. Using NDBI in land change analysis enables quicker and more efficient detection of urban expansion [4]. Combining NDBI with other indices like NDVI can improve the accuracy of land use classification [5]. Research shows that NDBI has a strong correlation with population density and economic activity in urban areas [6]. The NDBI method is highly effective in identifying changes in builtup land in tropical regions that frequently undergo rapid development [7] and it is also a low-cost but robust.
Keywords: NDBI, Built up land, Urbanization, Surabaya City
1. INTRODUCTION In terms of its potential utilization, physical environmental factors that influence land use include soil condition, climate, geological relief, topography, hydrology, and vegetation. Nearly every year, the population increases, leading to a rise in built-up land and a decrease in nonbuilt-up land. According to Sajow et al. [1], built-up land includes residential areas, commercial goods and services, social facilities, and public facilities, while non-built-up land encompasses green open spaces (GOS) such as plantations and rice fields, and non-green open spaces (NGOS) such as open land and fields. Lillesand and Kiefer [2] define land use as related to human activities on a plot of land, whereas land cover is more about the physical manifestation of objects covering the land, regardless of human activities associated with those objects.
2. RESEARCH METHODS 2.1 Study Area The study area for analyzing changes in built-up is in Surabaya City located in East Java of Indonesia, geographically located between 7°9′- 7°21′ South Latitude and 112° 36′ – 112° 54′ East Longitude. Surabaya was chosen as the study area due to its rapid infrastructure development linked to efforts to increase local revenue. According to the Central Statistics Agency (BPS), Surabaya is the second largest city in Indonesia after Jakarta, both in terms of area and population, with a population reaching 2,893,698 people. This density is driven by rapid urbanization, fast economic growth, and its role as a hub for trade and industry in East Java, Indonesia. Figure 1 shows the Surabaya City map with a free vector (https://www.vecteezy.com/free-vector/surabaya-map).
Urban land cover tends to change drastically within a short period due to urbanization. These changes are ideally monitored and detected using remote sensing imagery because such images are relatively current and provide thematic views. Remote sensing materials such as aerial photographs and satellite imagery are typically converted into useful information. To identify the built-up areas of a region or city, maps can be interpreted. Various image processing methods can be used to create maps of built-up land, such as Maximum Likelihood Classification (MLC), Normalized Difference Built-Up Index (NDBI), and others. This paper discusses the image processing method
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