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Analysis of Land Use Spatial Pattern Change of Town Development Using Remote Sensing

Profile image of Dipo YudhatamaDipo Yudhatama

International Journal of Remote Sensing and Earth Sciences (IJReSES)

https://doi.org/10.30536/J.IJRESES.2018.V15.A2795
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10 pages

Abstract

The Assessment of the physical character of a city is considered relatively easier than the social-cultural aspects. It is important to recognize the type of city form and to predict the behavior of people in the city and its surrounding. Due to those characteristics, the study of the pattern of physical development of the city is required. The objective of research is to analyze the change of spatial pattern of the city due to the city growing by remote sensing. The multitemporal data of Landsat 5/7/8 year 2000, 2006 and 2015 in Jabodetabek area were used. The classification technique had been done and it produced five classes of land uses. Those are water, built-up area, vegetation, other land use and no data. The results of the analysis in Jabodetabek area (Jakarta, Bogor, Depok, Tangerang and Bekasi) show that there was land use changes from vegetation and other land use area to built-up area with an average accuracy of 78% in each year. The pattern of physical development of th...

Key takeaways
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  1. The research analyzes urban land use changes in Jabodetabek using multitemporal Landsat satellite data.
  2. Built-up areas increased by approximately 47 km² from 2000 to 2015, indicating urban expansion.
  3. Average classification accuracy of land use was 78% across the studied years due to cloud cover issues.
  4. Five land use classes identified: water, built-up, vegetation, other land use, and no data.
  5. Urban development patterns include concentric, ribbon, and leapfrog types, affecting planning strategies.
Figures (10)
Figure 2-1: Study location of research activities (Jabodetabek) network, and data from field surveys. of very large accessible data (Figure 2:1).
Figure 2-1: Study location of research activities (Jabodetabek) network, and data from field surveys. of very large accessible data (Figure 2:1).
Figure 2-2: Landsat Image 5/7 Jabodetabek Area Years of: (a) 2000, (b) 2006, (c) 2013 and (d) 2015.
Figure 2-2: Landsat Image 5/7 Jabodetabek Area Years of: (a) 2000, (b) 2006, (c) 2013 and (d) 2015.
Table 3-1: Land Cover Area of Jabodetabek Year 2000, 2006 and 2015 in units of Hectares (Ha). Jakarta, Bogor, Depok, Bekasi and
Table 3-1: Land Cover Area of Jabodetabek Year 2000, 2006 and 2015 in units of Hectares (Ha). Jakarta, Bogor, Depok, Bekasi and
Table 3-3: Land Cover Area of Jabodetabek Year 2000 (Ha)
Table 3-3: Land Cover Area of Jabodetabek Year 2000 (Ha)
Table 3-2: Accuracy Test of Land Built in Jabodetabek 78% in each year. The accuracy test can
Table 3-2: Accuracy Test of Land Built in Jabodetabek 78% in each year. The accuracy test can
Figure 3-2: The Built-Up Area in Jabodetabek Year 2000, 2006 and 2015
Figure 3-2: The Built-Up Area in Jabodetabek Year 2000, 2006 and 2015
Table 3-5: Land Cover Area of Jabodetabek Year 2015 (Ha) Table 3-4: Land Cover Area of Jabodetabek Year 2006 (Ha)
Table 3-5: Land Cover Area of Jabodetabek Year 2015 (Ha) Table 3-4: Land Cover Area of Jabodetabek Year 2006 (Ha)
Figure 3-3: Physical Development Pattern of Jabodetabek Year 2000, 2006, and 2015
Figure 3-3: Physical Development Pattern of Jabodetabek Year 2000, 2006, and 2015

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The classification technique had been done and it produced five classes of land uses. Those are water, built-up area, vegetation, other land use and no data. The results of the analysis in Jabodetabek area (Jakarta, Bogor, Depok, Tangerang and Bekasi) show that there was land use changes from vegetation and other land use area to built-up area with an average accuracy of 78% in each year. The pattern of physical development of the city looks linear from year 2000 until year 2006, which is confirmed as concentric pattern from year 2006 to 2015. Based on those analysis, it confirmed that the city development in Jakarta as the center was influenced by the spatial land development of the surrounding cities of Depok, Bogor, Bekasi and Tangerang. The pattern of spatial development from 2000 to 2006 in Bogor, Bekasi and Depok areas is Linear pattern, whereas from 2006 - 2015 the pattern of spatial development shows Propagation Concentric pattern. For Tangerang Region in 2000-2015 its development is patterned Propagation Concentric. Keywords: Analysis, Spatial, Remote Sensing, Pattern, Development. 1 INTRODUCTION with a wide range of human settled in A city is a system of human life vast urban areas, sometimes the network characterized by high physical visual analysis of the city will population density, heterogeneous and be very different from the actual materialistic social economic strata. The situation (Rifai 2011) city is also a magnet of great attraction Remote sensing technology is a to human beings, due to the high level technology that can provide better of urban facilities service, the dream of information without direct contact with the number of jobs and the ease of the object or area to be observed and in reach (Birtanto 2016) some time imaging (Lillesand et al. Assessing the physical character of 2015). The use of remote sensing a city is considered easier because the technology in forestry sector is physical form is easier to "see" and "feel" considered to be a proper choice for than the socio - cultural aspects. Yet the detecting dynamics of land cover and reality is that although it is easy to see, land use changes, cheaply and relatively cheaper (Syam et al. 2012). 93 http://dx.doi.org/10.30536/j.ijreses.2018.v15.a2795 @National Institute of Aeronautics and Space of Indonesia (LAPAN) Samsul Arifin et al. A research had been conducted on horizontally. In addition, it is also need measuring the accuracy of data to be observed vertically, so it can including its interpretation as well as to observe the development of alteration of study the pattern of physical buildings. The appearance of the development of Surakarta city using pattern of urban physical development remote sensing image (Arminah 2002). can be seen visually at a particular “The increasing of urban population location or point, but on a very wide growth, caused the increases demand in area of course required a technology the economic, social, cultural, political that able to observe widely with effective and technological aspects which lead to and efficient. Using Landsat imagery an increasing need of a bigger urban along with socio-economic data in post- space. On the other hand, the city space classification analysis can mapped the is fixed and limited, resulted in the dynamics of spatial changes and increase needs for space and the land identify urbanization processes. Land functions which will always take up use/land cover statistics, taken from space in the suburbs (fringe area).” This Landsat in 1976, 1988 and 2000, phenomenon of urban sprawl is referred revealed that the built-up area had as "invasion" and the process of grown about 47 km2. The road network physical exposure to the outer city is has influenced urban spatial design and referred as "urban sprawl" (Yunus 1994). development patterns, so that the In accordance to the expansion of built areas has vertical characteristics of a city with its detailed growth and horizontal growth, linear and comprehensive, a study of the along main roads (Mundia et al. 2005). physical development patterns of the The remote sensing satellite data is very city requires relatively detailed data. To useful for monitoring the pattern of obtain this data, several ways have been physical development of the city developed, from a very traditional way (Mundhe 2016). Based on the remote using terrestrial surveys to the use of sensing data in four different years satellite technology which completed (1999, 2004, 2010 and 2014) and based with high precision of GPS networking on the temperature retrieval method, systems and good imaging systems. the results show that the expansion of Satellite imagery and aerial photographs built-up area in Jingzhou has not a can produce a large-scale of building correlation with the speed of population maps that ultimately can help to design growth (Wang et al. 2018). the city in high-precision designs. The objectives of this research aim These needs spur the development of to analysis the land use spatial pattern remote sensing imagery capabilities. using change of town development using The method of Enhanced Built-Up remote sensing. and Bareness Index (EBBI), Soil Adjusted Vegetation Index (SAVI) and 2 MATERIAL AND METHODOLOGY Modified Normalized Difference Air In this study, the method consists Index (MNDWI) was effective and simple of several steps, namely: determining to be implemented and can be used for the location, data used, data processing, extraction built-up area in other areas classification, pattern of physical (Sinha et al. 2016) development of the city, and analysis of Monitoring the physical pattern of the phenomenon of the research area. urban development is usually observed 94 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 Analysis of Land Use Spatial Pattern Change…. 2.1 Location 2.2 Data Research location is in The data used in this study consist Jabodetabek (Jakarta, Bogor, Depok, of primary and secondary data. Primary Tangerang, Bekasi), a megapolitan area data consists of multispectral of Landsat in Indonesia. This location was chosen 5 and Landsat 7, year of 2000, 2006, due to its relatively short time 2013 and 2015 (Figure 2-2). Secondary experiencing of rapid changes or data used in the form of administrative settlement developments and availability boundaries, infrastructure and river of very large accessible data (Figure 2:1). network, and data from field surveys. Figure 2-1: Study location of research activities (Jabodetabek) (a) (b) (c) (d) Figure 2-2: Landsat Image 5/7 Jabodetabek Area Years of: (a) 2000, (b) 2006, (c) 2013 and (d) 2015. International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 95 Samsul Arifin et al. 2.3 Image Processing Landsat classification result at the The data used in this research specific location from the five regions consist of Landsat 5/7/8 which with reference from Ikonos image processed radiometric correction and retrieved from Google Earth. geometric correction, mosaic between scenes and data path contiguously 2.5 Determination of Physical Town because Jabodetabek area consists of 2 Patterns path/row. Data of 2000, 2006, 2013 Determination of urban physical and 2015 imageries, then classified into pattern in this study is followed the several classes as needed. model according to Northam in Yunus (1994), that urban physical distribution 2.4 Classification is divided into three kinds, namely the There are five land cover classes concentric development pattern, (Figure namely blue as for water class, red as 2-3): cleared land use, magenta as for land, a. The concentric development pattern green as vegetation and white as for no (concentric development) is the data. Water class is used to classify physical propagation of the city that some classes of water surface objects, has a flat nature on the outside, such as sea, lake/reservoir and river. tend to be slow and shows the Land classes referred as group of some morphology of a compact city. non-vegetation objects such as ponds b. The pattern of physical development and open lands. Vegetation is a group of is linear/linear (ribbon/linear/axial forest, plantations, fields, mixed garden development) that is the physical and paddy fields for rice or intercrop spreading of the city that follows the fields (palawija). Land of built-up area is pattern of the road network and a cluster of objects for settlements, shows unequal distribution in each markets, shops, offices, industries, part of urban development. ports, terminals, airports and roads. No c. The leap-frog/cheche pattern of data is identify as a class of cloud- physical propagation of a city that covered object. The accuracy analysis of does not follow a particular pattern the land classification was assessed is called a springing development. using 35 points sampling on the Centre of City Concentric Propagation Concentric Linier Leap Concentric Figure 2-3: Physical of Propagation Models Source: Northam in Yunus (1994) 96 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 Analysis of Land Use Spatial Pattern Change…. 2.6 Analysis ribbon/linear/axial development and The analysis was conducted to leap frog/checher board development. monitor changes in land cover and urban physical development pattern in 3 RESULT AND DISCUSSION Jabodetabek area both quantitatively 3.1 Classification of Land Cover. and qualitatively referring to the model developed by Northam. Analysis is The result of land cover working to see the pattern of city classification using Landsat-5, Landsat- development in the case of study area 7 and Landsat-8 data for Jabodetabek that is Jabodetabek. Determination of area can be seen in Figure 3-1. From classification area conducted using the results of the classification of the quantitative calculation analysis, while data of 2000, 2006, 2013 and 2015, the the determination of land development image of 2013 is not sufficient to be pattern was built using qualitative analyzed. Therefore, for next analysis analysis based on literature review to data 2013 will be ignored. So that determine the pattern of development of spatial pattern of development city form Jakarta, Bogor, Depok, Bekasi and will only be used data of 2000, 2006, Tangerang. The physical development and 2015 (Figure 3-1). pattern of the city consists of 3 types, they are: concentric development, Jabodetabek 2000 Jabodetabek 2006 Jabodetabek 2015 Legend: Water Other Landuse Built Land Vegetation No Data Figure 3-1: Image Classification of Land Use / Land Coverage of Greater Jakarta Jabodetabek Table 3-1: Land Cover Area of Jabodetabek Year 2000, 2006 and 2015 in units of Hectares (Ha). Year 2000 (Ha) 2006 (Ha) 2015 (Ha) Water 18,198.8 16,789.5 19,355.6 Usage of others 19,714.7 32,110.2 89,501.7 Built-up Area 85,203.4 106,518.0 208,768.0 Vegetation 522,713.0 513,586.0 347,915.0 No data 47,441.7 22,994.9 30,760.8 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 97 Samsul Arifin et al. Table 3-2: Accuracy Test of Land Built in Jabodetabek Regency Sample Point IKONOS Data (Google Earth) Accuracy Built up Area True False Year 2015 Jakarta 7 7 0 100% Depok 7 6 1 85% Bogor 7 6 1 85% Bekasi 7 4 3 71% Tangerang 7 4 3 71% Average 78% Statistically, land cover area in of water has decreased from 2000 to Jabodetabek in each year can be seen in 2006 while the increasing number Table 3-1, with an average accuracy of occurred from 2006 to 2015 because 78% in each year. The accuracy test can there are cloud and shadow which be seen in Table 3-2. The lack of resulted in the classification accuracy maximum accuracy is due to the rate at only about 78%. The considering presence of cloud cover data and cloud condition that the land built-up area in shadows in the research area. Jabodetabek will continue to increase, The data in Table 3-1, shows that will result in the reduce of land there was a very significant development availability due to accommodate from 2000, 2006 until 2015, where the humans needs. Therefore it is land cover of vegetation area decreased. recommended to develop the city in The addition of others land use area vertically rather than in horizontally. from 2000, 2006 to 2015 was 19,714.7 The analysis of land cover changes Ha, 32,110.2 Ha, to 89,501.7 Ha, while in various areas of Jabodetabek which the built-up area was 85,203.4 Ha, is located in Jakarta, Bekasi Regency, 106,518.0 Ha and 208,768.0. The Bogor Regency, Bekasi City, Bogor City, addition of the area of built up area Depok City, Tangerang City, South largely derived from the cover of Tangerang City and Tangerang Regency vegetation land and another land from from 2000, 2006 and 2015 can be seen derived cover vegetation land into open in Table 3-3, 3-4 and 3-5. In general, land. This resulted in the decreased of changes in the built-up area in every vegetation land cover from 2000, 2006 regency or city in Jabodetabek to 2015 that is from 522.713.0 Ha, increased as shown in (Figure 3-2). 513,586.0 Ha to 347,915.0 Ha. The area Table 3-3: Land Cover Area of Jabodetabek Year 2000 (Ha) South DKI Bekasi Bogor Bekasi Bogor Depok Tangerang Tangerang Tangerang Year 2000 Jakarta Regency Regency City City City City City Regency Water 1,360.88 1,250.64 594.96 235.88 96.14 22.38 171.98 46.32 553.43 Usage of others 2,114.24 7,055.35 4,642.73 402.13 146.55 212.13 231.99 47.60 4,498.08 Built Land 38,481.27 11,910.24 4,668.53 5,385.67 2,613.17 3,264.19 7,531.26 3,798.06 7,278.46 Vegetation 19,291.68 111,708.29 247,978.92 7,961.08 7,719.23 16,479.64 9,598.51 12,408.94 89,023.86 No data 3.069,91 1,410.41 40,032.87 479.39 674.06 82.64 606.58 105.75 948.74 98 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 Analysis of Land Use Spatial Pattern Change…. Table 3-4: Land Cover Area of Jabodetabek Year 2006 (Ha) South DKI Bekasi Bogor Bekasi Bogor Depok Tangerang Tangerang Tangerang Year 2006 Jakarta Regency Regency City City City City City Regency Water 229.36 800.79 519.60 26.67 0.69 122.14 161.57 147.17 294.37 Usage of others 4,448.47 15,696.12 4,110.79 318.31 72.96 76.75 697.84 103.31 5,934.63 Built Land 40,540.72 14,366.71 11,477.20 6,998.05 2,846.97 4,959.65 9,646.26 5,627.59 9,929.31 Vegetation 16,311.85 101,259.88 264,197.66 6,962.67 8,226.08 14,647.58 6,739.74 10,374.43 84,275.97 No data 2,614.46 807.91 17,541.69 71.69 63.02 232.42 375.76 78.58 1,106.97 Table 3-5: Land Cover Area of Jabodetabek Year 2015 (Ha) South DKI Bekasi Bogor Bekasi Bogor Depok Tangerang Tangerang Tangerang Year 2015 Jakarta Regency Regency City City City City City Regency Water 198.27 2,351.40 3,697.47 3.90 22.11 25.52 19.51 11.91 710.28 Usage of others 2,732.42 31,450.10 19,145.96 739.39 234.88 953.35 2,265.79 728.95 29.661.39 Built Land 49,336.60 38,712.45 40,635.61 10,763.56 6,956.07 11,111.21 11,855.72 9,881.33 28,634.18 Vegetation 11,654.54 59,940.09 210,095.02 2,900.36 3.961.13 7,887.46 3,755.97 5,707.96 40,996.42 No data 399.42 1,717.53 25,315.70 57.45 75,52 84.05 243.44 76.11 2,733.04 DE VE LO PME NT O F BUI LT UP JA BO DE TA BE K Year 2000 Year 2006 Year 2015 49,336.60 40,635.61 40,540.72 38,712.45 38,481.27 28,634.18 14,366.71 11,910.24 11,855.72 11,477.20 11,111.21 10,763.56 9,929.31 9,881.33 9,646.26 7,531.26 7,278.46 6,998.05 6,956.07 5,627.59 5,385.67 4,959.65 4,668.53 3,798.06 3,264.19 2,846.97 2,613.17 Figure 3-2: The Built-Up Area in Jabodetabek Year 2000, 2006 and 2015 Year 2000 Year 2006 Year 2015 Figure 3-3: Physical Development Pattern of Jabodetabek Year 2000, 2006, and 2015 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 99 Samsul Arifin et al. 3.2 Analysis Development of Built- was 85,203.4 Ha, 106,518.0 Ha and Up Pattern 208,768.0 Ha, and vegetation decreased The pattern of physical from 2000, 2006 to 2015 that is development of built-up area in 522,713.0 Ha, 513,586.0 Ha to Jabodetabek is very different in every 347,915.0 Ha, with an average accuracy regency or city. Jakarta City from 2000 of 78% in each year. The pattern of to 2015 was concentrated in the urban development of Jakarta from 2000-2015 areas, thus forming a pattern of is in the form of Propagation Concentric propagation concentrations, because Pattern. Within 5 years Jakarta became Jakarta has no additional land for a new center as the main city of the constructed land development, so small towns of Bogor, Depok, Bekasi Jakarta is the new center of spatial and Tengerang. Year 2000-2006 Depok, development of the Depok city, Bogor, Bogor and Bekasi formed a Linear Bekasi and Tangerang and its Concentric pattern, while from 2006 surrounding. This illustrates that and 2015 shows patterned of Jakarta is the main city that exists with Propagation Concentric. Tangerang city the surrounding small towns of Bogor, from 2000-2015 experienced a change Depok, Bekasi and Tangerang. City and pattern of pattern development of Regency of Bogor and Depok has similar propagation concentric pattern. pattern of physical development of the city patterned of Concentric Linear from ACKNOWLEDGEMENT year 2000 until year 2006. This can be The success of this research seen that there is a change of built-up cannot be separated from the support area along the road, whereas from year and advice of researchers in the 2006 to year 2015 pattern of physical environment Remote Sensing development of town shows a Applications Center. Therefore, the Propagation Concentric pattern, authors thank to all the researchers because the development of land who have provide support and advice, conversion was built by means of especially Dr. Bambang Trisakti and the propagation that is concentrated in the structural in Remote Sensing city center. The Bekasi city from 2000 to Applications Center -LAPAN. 2006 shows the Concentric Linear REFERENCES pattern of physical development of the Arminah, Valintina, (2002), Study of Physical city, but from 2006 until 2015 the Development Pattern of Surakarta City physical development pattern of the city with SPOT and Landsat TM Image. showed a Leap concentric. Meanwhile, Majalah Geografi Indonesia, Yogjakarta. for Tangerang city or Regency, the Birtanto, (2016), 24 Pengertian Kota Menurut pattern of physical development of the Para Ahli Terlengkap (Understanding the city has started from 2000 until 2015 City According to the Experts Complete). with the patterned of Concentric Seputar Pengetahuan, Buku Geografi. Propagation. This can be seen in Figure Lillesand T., Kiefer RW, Chipman JW, (2015), 3-3. Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN 0- 4 CONCLUSION 471-15227-7. Land cover changed of ponds and Mundhe N., (2016), Department of Geography, open lands area from 2000, 2006 to Sir Parashurambhau College, Pune - 30. 2015, was 19,714.7 Ha, 32,110.2 Ha, to Global Journal For Research Analysis. 89,501.7 Ha, while the built-up area 100 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 Analysis of Land Use Spatial Pattern Change…. Mundia CN, Aniya M., (2005), Analysis of Land Identifying of Land Cover Changes: Use/Cover Changes and Urban Case Study of Protected Forest of Expansion of Nairobi City using Remote Register 22 Way Waya Central Lampung. Sensing and GIS. International Journal Globe Journal, Bogor. of Remote Sensing Vol. 26. Li X.,, Yeh AGO, (2004), Analyzing Spatial Maktav D., Erbek FS, Jürgens C., (2005), Restructuring of Land Use Patterns in a Remote Sensing of Urban Areas. Fast-Growing Region using Remote International Journal of Remote Sensing. Sensing and GIS. Journal of Landscape Vol. 26. and Urban Planning. Vol. 69, Issue 4, Rifai, (2011), Analisis Perkembangan Fisik Pages 335-354 Kota Palu dengan Citra Landsat Ma Y., Xu R., (2010), Remote Sensing (Analysis of Physical Development of Monitoring and Driving Force Analysis of Palu City with Landsat Image). Jurnal Urban Expansion in Guangzhou City Ruang. Vol. 3 Nomor. Jurusan China. Journal of Habitat International. Arsitektur Fakultas Teknik Universitas Vol 34, Pages 228–235. Tadulako. Yunus, Sabari H., (1994), Theory and Model Sinha P., Verma NK, Ayele E., (2016), Urban Structure of City Damages. Fakultas Built-up Area Extraction and Change Geografi UGM, Yogyakarta. Detection of Adama Municipal Area Yunus, Sabari H., (2000), City Space using Time-Series Landsat Images. Structure. Penerbit Pustaka Pelajar, International Journal of Advanced Yogyakarta. Remote Sensing and GIS. Vol. 5 Issue 8, Wang L, Zhu J., Xu Y.,et al, (2018), Urban pp. 1886-1895. Article ID Tech-649, Built-Up Area Boundary Extraction and ISSN 2320-0243. Spatial-Temporal Characteristics Based Syam T., Darmawan A., Banuwa IS, et al, on Land Surface Temperature Retrieval. (2012), Utilization of Satellite Imagery in Journal of Remote Sensing, MDPI. International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018 101 Samsul Arifin et al. 102 International Journal of Remote Sensing and Earth Science Vol. 15 No. 1 June 2018

References (21)

  1. Year 2000 (Ha) 2006 (Ha) 2015 (Ha) Water 18,198.8 16,789.5 19,355.6 Usage of others 19,714.7 32,110.2 89,501.7
  2. Built-up Area 85,203.4 106,518.0 208,768.0 Vegetation 522,713.0 513,586.0 347,915.0 No data 47,441.7 22,994.9 30,760.8
  3. Water 1,360.88 1,250.64
  4. Figure 3-2: The Built-Up Area in Jabodetabek Year 2000, 2006 and 2015
  5. Figure 3-3: Physical Development Pattern of Jabodetabek Year 2000, 2006, and 2015 38,481.27 11,910.24 4,668.53 5,385.67 2,613.17 3,264.19 7,531.26 3,798.06 7,278.46 40,540.72 14,366.71 11,477.20 6,998.05 2,846.97 4,959.65
  6. Arminah, Valintina, (2002), Study of Physical Development Pattern of Surakarta City with SPOT and Landsat TM Image. Majalah Geografi Indonesia, Yogjakarta.
  7. Birtanto, (2016), 24
  8. Pengertian Kota Menurut Para Ahli Terlengkap (Understanding the City According to the Experts Complete).
  9. Seputar Pengetahuan, Buku Geografi.
  10. Lillesand T., Kiefer RW, Chipman JW, (2015), Remote Sensing and Image Interpretation (7th ed.). Wiley. ISBN 0- 471-15227-7.
  11. Mundhe N., (2016), Department of Geography, Sir Parashurambhau College, Pune -30. Global Journal For Research Analysis.
  12. Mundia CN, Aniya M., (2005), Analysis of Land Use/Cover Changes and Urban Expansion of Nairobi City using Remote Sensing and GIS. International Journal of Remote Sensing Vol. 26.
  13. Maktav D., Erbek FS, Jürgens C., (2005), Remote Sensing of Urban Areas. International Journal of Remote Sensing. Vol. 26.
  14. Rifai, (2011), Analisis Perkembangan Fisik Kota Palu dengan Citra Landsat (Analysis of Physical Development of
  15. Sinha P., Verma NK, Ayele E., (2016), Urban Built-up Area Extraction and Change Detection of Adama Municipal Area using Time-Series Landsat Images. International Journal of Advanced Remote Sensing and GIS. Vol. 5 Issue 8, pp. 1886-1895. Article ID Tech-649, ISSN 2320-0243.
  16. Syam T., Darmawan A., Banuwa IS, et al, (2012), Utilization of Satellite Imagery in Identifying of Land Cover Changes: Case Study of Protected Forest of Register 22 Way Waya Central Lampung. Globe Journal, Bogor.
  17. Li X.,, Yeh AGO, (2004), Analyzing Spatial Restructuring of Land Use Patterns in a Fast-Growing Region using Remote Sensing and GIS. Journal of Landscape and Urban Planning. Vol. 69, Issue 4, Pages 335-354
  18. Ma Y., Xu R., (2010), Remote Sensing Monitoring and Driving Force Analysis of Urban Expansion in Guangzhou City China. Journal of Habitat International. Vol 34, Pages 228-235.
  19. Yunus, Sabari H., (1994), Theory and Model Structure of City Damages. Fakultas Geografi UGM, Yogyakarta.
  20. Yunus, Sabari H., (2000), City Space Structure. Penerbit Pustaka Pelajar, Yogyakarta.
  21. Wang L, Zhu J., Xu Y.,et al, (2018), Urban Built-Up Area Boundary Extraction and Spatial-Temporal Characteristics Based on Land Surface Temperature Retrieval. Journal of Remote Sensing, MDPI.

FAQs

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What specific remote sensing indices were employed to analyze land use changes?add

The research utilized Enhanced Built-Up and Bareness Index (EBBI), Soil Adjusted Vegetation Index (SAVI), and Modified Normalized Difference Water Index (MNDWI) for land use analysis.

How did urban sprawl manifest in Jabodetabek according to the study?add

The study observed built-up areas expanding approximately 47 km², predominantly influenced by linear growth along main roads.

What methodology was used to assess land cover classification accuracy?add

An accuracy analysis was conducted using 35 sampling points compared against Ikonos imagery, achieving an average accuracy of 78%.

When were the significant land cover changes in Jabodetabek recorded?add

Land cover changes were analyzed for the years 2000, 2006, and 2015, highlighting ongoing urban expansion.

What urban physical development patterns were identified in Jabodetabek?add

The identified patterns include concentric, ribbon/linear/axial, and leap frog/chequerboard developments.

About the author
Dipo Yudhatama
Tarumanagara University, Graduate Student
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