Green Open Space and Barren Land Mapping for Flood Mitigation in Jakarta, the Capital of Indonesia

https://doi.org/10.22146/ijg.76452

Retno Dammayatri(1), Tri Muji Susantoro(2*), Ketut Wikantika(3)

(1) Geodesy and Geomatics, Faculty of Earth Sciences and Technology, Bandung Institute of Technology, Indonesia.
(2) Research Centre for Remote Sensing, National Research and Innovation Agency, Indonesia
(3) Centre for Remote Sensing, Bandung Institute of Technology, Bandung, 40132, Indonesia
(*) Corresponding Author

Abstract


High levels of rainfall, tidal flooding, land subsidence, intensified urban development, scarce barren land and a shortage of green open spaces (GOS) are contributing factors to the persistent flooding in Jakarta. Therefore, this study was conducted to map the GOS, built-up, and barren land in the city in order to calculate the biopore infiltration hole (LRB) potential for water infiltration as part of Jakarta's flood mitigation efforts using the Landsat 8 operational land imager (OLI). The Landsat data acquired on September 11, 2019, with path/row 122/064 were processed using the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method for the radiometric correction, and geometric correction with a root mean square error (RMSE) of 7.57 meters. Moreover, the normalized difference vegetation index (NDVI) was applied to classify the GOS, the normalized difference built-up index (NDBI) for the built-up areas, and the normalized difference barren land index (NDBaI) for barren land areas which were further confirmed using NDBI to distinguish them from the built-up areas. It is also important to note that the LRB potential was calculated by adding the GOS and barren land, dividing the result by the ideal land area multiplied by the ideal number of holes. The results showed that the GOS, built-up area, and barren land were 8.34%, 85.29%, and 2.48%, respectively. Furthermore, the LRB potential through the optimization of GOS and barren land was found to be 70.06 km2 and produced 16,816,248 LRB (18.27% of total needed). The realization of this value is expected to reduce the potential inundation in Jakarta by 15.6%.

Keywords


green open space; Landsat 8 OLI; NDVI; NDBI; NDBaI; biopore infiltration

Full Text:

PDF


References

Abidin, H. S., Andreas, H., Gumilar, I., & Brinkman, J. J. (2015). Study on the risk and impacts of land subsidence in Jakarta. Proc. IAHS, 115–120. https://doi.org/10.5194/piahs-372-115-2015

Ajrina, H., & Kustiwan, I. (2019). From green open space to green infrastructure: The potential of green open space optimization towards sustainable cities in Bekasi City & Regency, Indonesia. IOP Conference Series: Earth and Environmental Science, 399(1), 12130. https://doi.org/10.1088/1755-1315/399/1/012130

Angelia, T. (2017). Green open space developmnet concept as an ecological function to absorb rain water in Rungkut District Surabaya City. Institut Teknologi Sepuluh November.

Asdak, C., Supian, S., & Subiyanto. (2018). Watershed management strategies for flood mitigation: A case study of Jakarta’s flooding. Weather and Climate Extremes, 21, 117–122. https://doi.org/10.1016/j.wace.2018.08.002

Biopore Team of IPB. (2020). Absorb rainwater into groundwater (Resapkan air hujan menjadi air tanah).

BPDASHL Citarum - Ciliwung. (2018). Peta batas DAS BPDASHL Citarum - Ciliwung. Bogor.

Brata, K. R. R., & Nelistya, A. (2008). Biopori Infiltration hole (1st ed.). Jakarta, Indonesia, Indonesia: Penebar Swadaya.

Brenda Chandrawati, T., Ratna, A. A. P., & Sari, R. F. (2020). Implementing Bio-Inspired Algorithm for Pathfinding in Flood Disaster Prevention Game. In R. Alfred, Y. Lim, H. Haviluddin, & C. K. On (Eds.), Computational Science and Technology (pp. 23–31). Singapore: Springer Singapore. https://doi.org/10.1007/978-981-15-0058-9_3

Budiman, A., Sulistyantara, B., & Zain, A. F. F. (2014). Detection of greenery open space change of 5 major cities in Java Island (Case study: DKI Jakarta, Bandung City, Semarang City, Jogjakarta City, and Surabaya City). Jurnal Lanskap Indonesia, 6(1), 7–15. https://doi.org/10.29244/jli.2014.6.1.7-15

Chen, X. L., Zhao, H.-M., Li, P.-X., Yin, J., & Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133–146. https://doi.org/10.1016/j.rse.2005.11.016

Dinas Komunikasi Informatika dan Statistiks. (2015). All data of green open space in DKI Jakarta Province (Data seluruh ruang terbuka hijau di Provinsi DKI Jakarta). Retrieved January 20, 2023, from Portal Data Terpadu Pemrpov DKI Jakarta website: https://data.jakarta.go.id/dataset/ruangterbukahijaudkijakarta/resource/716b64ee-eaab-4094-8226-67e445d287bf

Fuchs, R., Conran, M., & Louis, E. (2011). Climate Change and Asia’s Coastal Urban Cities: Can they Meet the Challenge? Environment and Urbanization ASIA, 2(1), 13–28. https://doi.org/10.1177/097542531000200103

Galderisi, A., & Treccozzi, E. (2017). Green Strategies for Flood Resilient Cities: The Benevento Case Study. Procedia Environmental Sciences, 37, 655–666. https://doi.org/10.1016/j.proenv.2017.03.052

Guo, G., Wu, Z., Xiao, R., Chen, Y., Liu, X., & Zhang, X. (2015). Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape and Urban Planning, 135, 1–10. https://doi.org/10.1016/j.landurbplan.2014.11.007

Harsoyo, B. (2013). Reviewing flooding in the DKI Jakarta from the angles of geology, geomorphology and river morphometry (Mengulas banjir di Wilayah DKI Jakarta dari sudut geologi, geomorfologi dan morfometri sungai). Jurnal Sains & Teknologi Modifikasi Cuaca, 14(1), 37–43.

Hutabarat, L. E., & Simanjuntak, I. V. (2022). Using bio-pore infiltration hole to reduce flooding in densely population communities of Jakarta and surrounding area. IOSR Journal of Engineering (IOSRJEN), 12(8), 2278–8719. Retrieved from www.iosrjen.org

Kagabu, M., Delinom, R. M., Lubis, R. F., Shimada, J., & Taniguchi, M. (2010). Groundwater characteristics in Jakarta Area, Indonesia. Indonesian Journal of Geology and Mining, 20(2), 69–79. https://doi.org/10.14203/risetgeotam2010.v20.35

Kamil, I. M., & Willis, R. (2013). Optimization models for the control of saltwater intrusion. Journal of Mathematical and Fundamental Sciences, 45(2), 124–143. https://doi.org/10.5614/j.math.fund.sci.2013.45.2.3

Khusna, N. I., Amin, S., & Sekarrini, C. E. (2020). The effect of using biopore on flood reduction in district of Besuki, Tulungagung Regency. Sumatra Journal of Disaster, Geography and Geography Education, 4(1), 100–104. https://doi.org/10.24036/sjdgge.v4i1.316

Latief. (2012, June). We, in the middle of poor green open space (Kita, di tengah miskinnya ruang terbuka hijau). Kompas.

Nugraha, G. U., Handayani, L., Lubis, R. F., Wardhana, D. D., & Gaol, K. L. (2020). Basement characteristics of Jakarta groundwater basin based on satellite gravimetry data. Indonesian Journal of Geography, 52(1), 42–52. https://doi.org/10.22146/ijg.46672

Nursyirwan, I., Bisri, M., Montarcih, L., & Suhartanto, E. (2019). Prediction numerical modeling of groundwater drawdow impact in Jakarta. Indonesian Journal of Geography, 51(2), 231–241. https://doi.org/10.22146/ijg.44914

Perkins-Kirkpatrick, S. E., & Gibson, P. B. (2017). Changes in regional heatwave characteristics as a function of increasing global temperature. Scientific Reports, 7(1), 1–12. https://doi.org/10.1038/s41598-017-12520-2

Reddy, V. R. (2019). Chapter 3 - Watershed management in Afghanistan: Lessons from South Asia. In M. D. Kumar, V. R. Reddy, & A. J. James (Eds.), From Catchment Management to Managing River Basins (pp. 55–85). Elsevier. https://doi.org/10.1016/B978-0-12-814851-8.00003-3

Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W., & Deering, J. A. S. D. W. (1974). Monitoring vegetation systems in the great plains with ERTS. In S. C. Becker, Freden E P, & Mercanti M A (Eds.), Third Earth Resources Technology Satellite-1 Symposium (Vol. 1, pp. 309–317). Washington, DC, USA: NASA. Goddard Space Flight Center 3d ERTS-1.

Safarina, A. B., Karnisah, I., Permana, A. S., & Sufianto, D. (2019). Green Cimahi watershed for balancing water supply and flood control. {IOP} Conference Series: Materials Science and Engineering, 669(1), 12040. https://doi.org/10.1088/1757-899x/669/1/012040

Sarbidi. (2012). Research on srain water subreservoir is in the green orpened space to educe the flooded water. Jurnal Permukiman, 7(3), 176–184.

Setiowati, R., Hasibuan, H. S., & Koestoer, R. H. (2018). Green open space masterplan at Jakarta Capital City, Indonesia for climate change mitigation. {IOP} Conference Series: Earth and Environmental Science, 200, 12042. https://doi.org/10.1088/1755-1315/200/1/012042

Sitorus, S. R. P., Aurelia, W., & Panuju, D. R. (2011). Analysis of changing on greenery open apace area and its influencing factors in south Jakarta. Jurnal Lanskap Indonesia, 3(1), 15–20. https://doi.org/10.29244/jli.2011.3.1.%p

Solihin, & Sunarwan, B. (2010). Basic technical review of the efficiency of the infiltration system in the flood control effort case study: DKI Jakarta area (Tinjauan teknis dasar efisiensi sistem resapan dalam usaha pengendalian banjir studi kasus: kawasan DKI Jakarta). Jurnal Teknologi, 2(16), 76–91.

Sudiana, I. B., & Diasmara, E. (2008). Analysis of Vegetation Index Using Satellite Data NOAA/AVHRR and TERRA/AQUA-MODIS. Seminar on Intelligent Technology and Its Applications.

Sulma, S., Nugroho, J. T., Zubaidah, A., Fitriana, H. L., & Haryani, N. S. (2017). Detection of Green Open Space Using Combination Index of Landsat 8 Data (Case Study: Dki Jakarta). International Journal of Remote Sensing and Earth Sciences (IJReSES), 13(1), 1–8. https://doi.org/10.30536/j.ijreses.2016.v13.a2712

Susantoro, T. M., Wikantika, K., Puspitasari, A. S., & Saepuloh, A. (2017). Impact of oil and gas field in sugar cane condition using Landsat 8 in Indramayu area and its surrounding, West Java Province, Republic of Indonesia. IOP Conf. Series: Earth and Environmental Sciences, 54(012019), 1–10. Bogor: {IOP} Publishing. https://doi.org/10.1088/1755-1315/54/012019

Susantoro, T. M., Wikantika, K., Saepuloh, A., & Harsolumakso, H. A. (2018). Selection of Vegetation Indices for Mapping the Sugarcane Condition Around the Oil and Gas field of North West Java Basin, Indonesia. IOP Conf. Series: Earth and Environmental Sciences, 149(012001), 1–10. https://doi.org/10.1088/1755-1315/149/1/012001

Susantoro, T. M., Wikantika, K., Yayusman, L. F., Tan, A., & Ghozali, M. F. (2020). Monitoring of Mangrove Growth and Coastal Changes on the North Coast of Brebes, Central Java, Using Landsat Data. International Journal of Remote Sensing and Earth Sciences (IJReSES), 16(2), 197–214. https://doi.org/10.30536/j.ijreses.2019.v16.a3221

Tejada, J. J., Raymond, J., & Punzalan, B. (2012). On the Misuse of Slovin’s Formula. The Philippine Statistician, 61(1), 129–136.

Vermote, E. F., Saleous, N. E., & Justice, C. O. (2002). Atmospheric correction of MODIS data in visible to middle infrared: First Result. Remote Sensing of Environment, 83(1–2), 97–111. https://doi.org/10.1016/S0034-4257(02)00089-5

Verstraete, M. M., & Pinty, B. (1991). The potential contribution of satellite remote sensing to the understanding of arid lands processes The potential contribution of satellite remote sensing to the understanding of arid lands processes. Vegetation, 91(January), 59–72. https://doi.org/10.1007/BF00036048

Widodo, M. S. (2007). ground hole for earth guard (lubang tanah penjaga bumi). Gatra, p. 23.

Xu, H. (2007). Extraction of urban built-up land features from landsat imagery using a thematic-oriented index combination technique. Photogrammetric Engineering and Remote Sensing, 73(12), 1381–1391. https://doi.org/10.14358/PERS.73.12.1381

Yamashita, S., Watanabe, R., & Shimatani, Y. (2015). Smart Adaptation to Flooding in Urban Areas. Procedia Engineering, 118, 1096–1103. https://doi.org/10.1016/j.proeng.2015.08.449

Zha, Y., Guo, Y., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583–594. https://doi.org/10.1080/01431160304987

Zhao, H. H., & Chen, X. X. (2005). Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+. Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS ’05., 3, 1666–1668. Seoul, Koreal: IEEE International. https://doi.org/10.1109/IGARSS.2005.1526319





DOI: https://doi.org/10.22146/ijg.76452

Article Metrics

Abstract views : 1795 | views : 1215

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2023 Tri Muji Susantoro, Retno Dammayatri, Ketut Wikantika

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)

Web Analytics IJG STATISTIC