The Impact of Changes in Land Use on Green Open Space and Comfort Index in Semarang City, Indonesia

Dinda Penggayuh, Khursatul Munibah, Muhammad Ardiansyah

Abstract

Semarang City is one of the cities with the most dense population in Indonesia. The increase in the population of Semarang City causes land conversion which has an impact on increasing heat and can cause environmental problems. The results of the random classification of forests for land use in 2013-2022 are dominated by the built-up land class. Use of built-up land continues to increase from 2013-2022 by 8.84% or an area of 3410 ha. This causes a reduction in green open space by 7.59% or an area of 2928.49 Ha and is still sufficient by 30%. In the predicted use of land in 2032, the dominance of the built-up land class is 61% (23,575 ha). The availability of green open space (RTH) in Semarang City continues to decline from 2013-2032 by 9%. Where in 2032 the availability of green open space will be 29.62% or less than 30%. The relationship between green open space and comfort levels influences each other, where a reduction in green open space causes an increase in comfort levels. Directions need to be made for developing green open spaces consisting of priority 1 areas, namely adding green open spaces in each sub-district, maintaining existing green open spaces, and creating roof gardens and vertical gardens to reduce temperatures in densely populated areas. Meanwhile, priority area 2 is maintaining existing green open space in the form of urban forests and plantation areas.

References

Aryaguna PA, Gaffara GR, Sari DAK, Arianto A. 2022. Green Open Space Priority Modelling Using GIS

Analysis In West Jakarta. Indones. J. Geogr. 54(2):263–271.doi:10.22146/ijg.68184.

As-syakur AR, Adnyana IWS, Arthana IW, Nuarsa IW. 2012. Enhanced built-UP and bareness index (EBBI)

for mapping built-UP and bare land in an urban area. Remote Sens. 4(10):2957–

doi:10.3390/rs4102957.

Effendy S. 2009. Dampak Pengurangan Ruang Terbuka Hijau (RTH) Perkotaan Terhadap Peningkatan Suhu

Udara dengan Metode Penginderaan Jauh. J. Agromet. 23(2):169–181.

Fineschi S, Loreto F. 2020. A Survey of Multiple Interactions Between Plants and the Urban Environment.

Front. For. Glob. Chang. 3(March):1–19.doi:10.3389/ffgc.2020.00030.

Gong C, Hu C. 2022. Community Public Open Space Planning Based on Green Infrastructure with the

Priority of Biodiversity. IOP Conf. Ser. Earth Environ. Sci. 994(1).doi:10.1088/1755-1315/994/1/012002.

Highland N. 2022. Modeling and Prediction of Land use Land Cover Change using Land Change Modeler in

Suluh River. (August):1–27.doi:10.21203/rs.3.rs-1981572/v1.

J Wang YL. 2009. Land use and land cover change and its driving forces in Sanya. J. Nat. Resour.

(March):1458–1466.doi:10.20944/preprints202303.0526.v1.

Jana A, Jat MK, Saxena A, Choudhary M. 2022. Prediction of land use land cover changes of a river basin

using the CA-Markov model. Geocarto Int. 37(26):14127–

doi:10.1080/10106049.2022.2086634.

Kalfuadi Y, Geofisika D, Meteorologi DAN, Matematika F, Ilmu DAN, Alam P. 2009. Temperature heat

index.

Karyono TH. 2005. Fungsi Ruang Hijau Kota Ditinjau dari Aspek Keindahan, Kenyamanan, Kesehatan dan

Penghematan Energi. J. Tek. Lingkung. P3TL-BPPT.(3):452–457.

Koo KA, Park SU. 2022. Data on the predictions of plant redistribution under interplays among climate

change, land-use change, and dispersal capacity. Data Br.

:108667.doi:10.1016/j.dib.2022.108667.

Kusumaningrum KW, Saraswati R, Wibowo A. 2022. Green Open Space Development Based on Urban

Heat Island Phenomenon in Malang City. IOP Conf. Ser. Earth Environ. Sci.

(1).doi:10.1088/1755-1315/950/1/012066.

Kusumawardani D. 2011. Hubungan Ruang Terbuka Hijau ( Rth ) Dan Suhu Permukaan Menggunakan Citra

Landsat Tm / Etm + ( Studi Kasus : Dki Jakarta ).

Maduako I, Ebinne E, Zhang Y, Bassey P. 2016. Prediction of Land Surface Temperature (LST) Changes

within Ikom City in Nigeria Using Artificial Neural Network (ANN). Int. J. Remote Sens. Appl.

(0):96.doi:10.14355/ijrsa.2016.06.010.

Meikatama RC, Wibowo A, Putut I, Sidiq A, Sciences N. 2022. Spatial Distribution of Green Open Spaces

and Relation To Land Surface Temperature in Bandar Lampung City. 19(1):79–

doi:10.30536/j.ijreses.2022.v19.a3795.

Model A, Penggunaan P, Artificial M, Network N, Kota DI. 2019. Pemodelan Perubahan Penggunaan Lahan

Dengan Artificial Neural Network (Ann) Di Kota Semarang. J. Geod. Undip. 9(1):197–206.

Mushore TD, Odindi J, Dube T, Mutanga O. 2017. Prediction of future urban surface temperatures using

medium resolution satellite data in Harare metropolitan city, Zimbabwe. Build. Environ.

(June):397–410.doi:10.1016/j.buildenv.2017.06.033.

Nopianto D, Nugradi A. 2009. Identifikasi Ruang Terbuka Hijau Kota Semarang. Identifikasi Ruang Terbuka

Hijau Kota Semarang. 11(1):61–70.doi:10.15294/jtsp.v11i1.6967.

Prakoso P, Herdiansyah H. 2019. Analisis Implementasi 30% Ruang Terbuka Hijau Di Dki Jakarta. Maj. Ilm.

Globe. 21(1):17.doi:10.24895/mig.2019.21-1.869.

Ramdani AP. 2015. Analisis Ruang Terbuka Hijau Dan Keterkaitannya Dengan Kenyamanan Kota

Samarinda.

Ranjan AK, Anand A, Kumar PBS, Verma SK, Murmu L. 2017. Prediction of Land Surface Temperature

Using Artificial Neural Network in Conjunction with Geoinformatics Technology Within Sun City

Jodhpur ( Rajasthan ), India. Asian J. Geoinformatics. 17(3):14–23.

Rilatupa J, 2008. No Title.

Rushayati SB, Hermawan R. 2013. Characteristics of Urban Heat Island Condition in DKI Jakarta. Forum

Geogr. 27(2):111.doi:10.23917/forgeo.v27i2.2370.

Ruslisan. 2015. Prediksi Perubahan Penggunaan Lahan Terbangun Terhadap Kesesuaian Rancangan Tata

Ruang Wilayah Menggunakan Regresi Logistic Binner Berdasar Data Spasial dan Penginderaan

Jauh di Kota Semarang. Pembang. Inklusif Menuju ruang dan Lahan Perkota. yang

Berkeadilan.:51–67.

Samsudi. 2010. Ruang Terbuka Hijau Kebutuhan Tata Ruang Perkotaan Kota Surakarta. J. Rural Dev. Vol.

(No. 1):Hal. 11-19.

Santhosh Baboo D, Devi Mr, Baboo L, Doss Vaishnav College G. 2010. Integrations of Remote Sensing and

GIS to Land Use and Land Cover Change Detection of Coimbatore District. IJCSE) Int. J.

Comput. Sci. Eng. 02(09):3085–3088.

Schneider LC, Gil Pontius R. 2001. Modeling land-use change in the Ipswich watershed, Massachusetts,

USA. Agric. Ecosyst. Environ. 85(1–3):83–94.doi:10.1016/S0167-8809(01)00189-X.

Selamat, Napitupulu DM, Muchlis F, Adriansyah E. 2022. Analysis of Provision of Green Open Space in

Jambi City. Int. J. Res. Vocat. Stud. 2(3):78–82.doi:10.53893/ijrvocas.v2i3.148.

Selanno FM, Sitanala MR, Santoso P, Arinah H. 2022. Optimization of green open space in Ambon City.

IOP Conf. Ser. Earth Environ. Sci. 1115(1).doi:10.1088/1755-1315/1115/1/012020.

Shooshtari SJ, Shayesteh K, Gholamalifard M, Azari M, López-Moreno JI. 2018. Land cover change

modelling in hyrcanian forests, northern iran: A landscape pattern and transformation analysis

perspective. Geogr. Res. Lett. 44(2):743–761.doi:10.18172/cig.3279.

Sun C, Bao Yulong, Vandansambuu B, Bao Yuhai. 2022. Simulation and Prediction of Land Use/Cover

Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in

Mongolia. Sustain. 14(23).doi:10.3390/su142315707.

Supratiwi S. 2019. Studi ruang terbuka hijau dalam kebijakan pengelolaan lingkungan hidup Pemerintah

Kota Semarang. J. Ilm. Ilmu Pemerintah. 3(2):89.doi:10.14710/jiip.v3i2.3878.

Verburg PH, Schot PP, Dijst MJ, Veldkamp A. 2004. Land use change modelling: Current practice and

research priorities. GeoJournal. 61(4):309–324.doi:10.1007/s10708-004-4946-y.

Yusof M, Johari M. 2012. Identifying Green Spaces in Kuala Lumpur Using Higher Resolution Satellite

Imagery. Alam Cipta. 5(2):93–106.

Authors

Dinda Penggayuh
penggayuh@gmail.com (Primary Contact)
Khursatul Munibah
Muhammad Ardiansyah
PenggayuhD., MunibahK. and ArdiansyahM. (2023) “The Impact of Changes in Land Use on Green Open Space and Comfort Index in Semarang City, Indonesia”, Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management). Bogor, ID, 13(4), pp. 683-693. doi: 10.29244/jpsl.13.4.683-693.

Article Details