Land Cover Projection of Jember Irrigation Area Using MOLUSCE QGIS

Penulis

  • Adelia Nur Isna Kartikasari Universitas Jember
  • Sri Irawan Laras Prasojo Dinas Pekerjaan Umum Bina Marga dan Sumber Daya Air Jember
  • Hilma Wasilah Robbani Universitas Jember
  • Niswah Selmi Kaffa Universitas Jember

DOI:

https://doi.org/10.12962/geoid.v20i2.8071

Kata Kunci:

Land Cover Change, Projection, Sentinel-2, MOLUSCE

Abstrak

Jember Regency has the third largest agricultural area in East Java Province. However, the agricultural area has decreased due to the expansion of built-up areas in line with population growth. This indicates the need for special attention to controlling the expansion of built-up land in Jember Regency. This study focuses on predicting agricultural land loss and the increase in built-up land in Jember Regency. It examines land cover changes in the regency from 2017 to 2021. Sentinel-2 imagery was used to obtain land cover data for Jember Regency in 2017 and 2021. The 2017 and 2021 land cover maps will serve as reference maps to determine the 2025 land cover using the MOLUSCE plugin in QGIS. The obtained 2025 land cover map will be used to validate the model's accuracy by comparing it with the actual 2025 land cover using Kappa Accuracy. This model's Kappa Accuracy is 91%. The validated model will then be used to predict land cover for 2045. The analysis indicates a predicted reduction in agricultural area of 5.675 hectares and a predicted increase in built-up area in irrigated areas of 6.348 hectares during the 2025–2045 period. Over the next 20 years, irrigation areas under the authority of the regency are predicted to experience the highest growth in built-up land, at 46.1%. This is followed by areas under provincial authority, which are predicted to grow by 34.6%, and areas under central authority, which are predicted to grow by 110% of the total agricultural area in Jember Regency. These findings are important for local governments and stakeholders in land management and urban planning. They also contribute to the monitoring of agricultural land use and the development of effective policy strategies.

Referensi

Bill Donatien, L. M., Biona Clobite, B., & Lemvo Meris Midel, M. (2024). Comparing Sentinel-2 and Landsat 9 for land

use and land cover mapping assessment in the north of Congo Republic: a case study in Sangha region. International

Journal of Remote Sensing, 45(22), 8015–8036. https://doi.org/10.1080/01431161.2024.2394238

Cheng, X., Xiao, Z., Dai, L., Hu, X., Min, J., & Li, D. (2025). Policy-oriented framework for multi-tiered urban

development boundaries in the Tibetan-Qiang-Yi corridor. Environmental and Sustainability Indicators, 27,

100735. https://doi.org/10.1016/J.INDIC.2025.100735

Darshan Dash, P. (2024). High-Rise Living: A Sustainable Approach to Land Demand in Rampura, Dhaka.

https://doi.org/10.47772/IJRISS

De Raadt, A., Warrens, M. J., Bosker, R. J., & Kiers, H. A. L. (2019). Kappa Coefficients for Missing Data. Educational

and Psychological Measurement, 79(3), 558–576. https://doi.org/10.1177/0013164418823249

Değermenci, A. S. (2023). Spatio-temporal change analysis and prediction of land use and land cover changes using CAANN

model. Environmental Monitoring and Assessment, 195(10), 1229. https://doi.org/10.1007/s10661-023-

11848-9

Feizizadeh, B., Darabi, S., Blaschke, T., & Lakes, T. (2022). QADI as a New Method and Alternative to Kappa for

Accuracy Assessment of Remote Sensing‐Based Image Classification. Sensors, 22(12).

https://doi.org/10.3390/s22124506

Gabisa, M., kabite, G., & Mammo, S. (2025). Land use and land cover change trends, drivers and its impacts on ecosystem

services in burayu sub city, Ethiopia. Frontiers in Environmental Science, 13.

https://doi.org/10.3389/fenvs.2025.1557000

Indarto, I., Hidayah, E., & Setiawan, E. B. (2023). Water Balance Assessment, Land Use Land Cover Change and

Increasing Water Demand in Three Major Watersheds in Jember, East Java, Indonesia. Geosfera Indonesia, 8(2),

170. https://doi.org/10.19184/geosi.v8i2.39131

Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., & Brumby, S. P. (2021). Global land use / land

cover with Sentinel 2 and deep learning. 2021 IEEE International Geoscience and Remote Sensing Symposium

IGARSS, 4704–4707. https://doi.org/10.1109/IGARSS47720.2021.9553499

Kholik, saeful, Nurlinda, I., Muttaqin, Z., & Priyanta, M. (2024). Reformulation of Policies to Prevent Land Conversion

of Rice Fields In Achieving Indonesia’s National Food Security. F1000Research, 13, 945.

https://doi.org/10.12688/f1000research.151364.1

Kumari, S., & Roy, A. (2025). Simulation of Land Use and Land Cover Using the MOLUSCE Plugin Integrated with

QGIS for the Western Himalayan Region of India. International Archives of the Photogrammetry, Remote Sensing

and Spatial Information Sciences - ISPRS Archives, 48(5), 81–85. https://doi.org/10.5194/isprs-archives-XLVIIIM-

5-2024-81-2025

Lukas, P., Melesse, A., & Kenea, T. (2023). Prediction of Future Land Use/Land Cover Changes Using a Coupled CAANN

Model in the Upper Omo-Gibe River Basin, Ethiopia. Remote. Sens., 15, 1148.

https://doi.org/10.3390/rs15041148

Mahmud Hanafi, W. (2025). Agricultural Land Control Based on the Regulation of the Minister of Agrarian and Spatial

Planning/ Head of the National Land Agency of the Republic of Indonesia Number 18 of 2016 Concerning Control

of Agricultural Land Tenure. https://doi.org/10.38035/jlph.v5i4

Muhammad, R., Zhang, W., Abbas, Z., Guo, F., & Gwiazdzinski, L. (2022). Spatiotemporal Change Analysis and

Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big

Data: A Case Study of Linyi, China. Land, 11(3). https://doi.org/10.3390/land11030419

Phiri, D., Simwanda, M., Salekin, S., Nyirenda, V. R., Murayama, Y., & Ranagalage, M. (2020). Sentinel-2 data for land

cover/use mapping: A review. In Remote Sensing (Vol. 12, Issue 14). MDPI AG.

https://doi.org/10.3390/rs12142291

Santoso, M. I. S., & Fitri, I. C. (2023). Alih Fungsi Lahan Persawahan Menjadi Perumahan di Kabupaten Jember

Berdasarkan Peraturan Daerah Kabupaten Jember Nomor 1 Tahun 2015 Tentang Rencana Tata Ruang Wilayah

Kabupaten Jember Tahun 2015-2035. Journal of Contemporary Law Studies, 1(1).

https://doi.org/10.47134/lawstudies.v1i1.1945

Shiri, Z., Frija, A., Rejeb, H., Ouerghemmi, H., & Le, Q. B. (2024). Data on the Land Cover Transition, Subsequent

Landscape Degradation, and Improvement in Semi-Arid Rainfed Agricultural Land in North–West Tunisia. Data,

9(8). https://doi.org/10.3390/data9080096

Tran Tuan, N. (2021). Shrinking agricultural land and changing livelihoods after land acquisition in Vietnam. Bulletin of

Geography. Socio-Economic Series, 53(53), 17–32. https://doi.org/10.2478/bog-2021-0020

Tuslaela, T., Rusdiansyah, R., Supendar, H., & Suharyanti, N. (2024). Implementation of K-Means Clustering in Food

Security by Regency in East Java Province in 2022. Sinkron, 9(1), 54–60.

https://doi.org/10.33395/sinkron.v9i1.13169

Wu, S., Cao, J. M., & Zhao, X. Y. (2025). Land cover classification of high-resolution remote sensing images based on

improved spectral clustering. PLoS ONE, 20(2 February). https://doi.org/10.1371/journal.pone.0316830

Yadav, A., & Singh, R. M. (2024). Spatio-Temporal Analysis and Prediction of Land Use and Land Cover in Jagdalpur

Sub-Division of Bastar District in State of Chhattisgarh, India from 2012 to 2037. Journal of The Institution of

Engineers (India): Series A. https://doi.org/10.1007/s40030-024-00849-7

Ye, J. (2015). Land Transfer and the Pursuit of Agricultural Modernization in China. Journal of Agrarian Change, 15(3),

314–337. https://doi.org/10.1111/joac.12117

Diterbitkan

2025-10-06

Cara Mengutip

Kartikasari, A. N. I., Prasojo, S. I. L., Robbani, H. W., & Kaffa, N. S. (2025). Land Cover Projection of Jember Irrigation Area Using MOLUSCE QGIS. GEOID, 20(2), 35–44. https://doi.org/10.12962/geoid.v20i2.8071

Terbitan

Bagian

Articles