Model Perencanaan Penggunaan Lahan Berbasis Jasa Ekosistem Pangan Padi dan Stok Karbon (Studi Kasus Kabupaten Sukabumi)

Abstract

Kabupaten Sukabumi menghadapi tekanan perubahan penggunaan lahan akibat pertumbuhan penduduk, perkembangan wilayah, pembangunan infrastruktur, dan meningkatnya kebutuhan ruang terbangun. Tekanan tersebut berpotensi mengurangi lahan sawah dan hutan, sehingga menimbulkan trade-off antara kebutuhan pembangunan, penyediaan pangan padi, dan pemeliharaan stok karbon. Penelitian ini bertujuan: (1) menganalisis pola perubahan penutupan/penggunaan lahan; (2) mengidentifikasi faktor pendorong perubahan; (3) membangun model dinamik penggunaan lahan; (4) menganalisis dinamika keruangan hingga 2043; (5) menilai dampak perubahan lahan terhadap jasa ekosistem pangan padi dan stok karbon; serta (6) menyusun arahan perencanaan penggunaan lahan berbasis jasa ekosistem. Metode penelitian mengintegrasikan penginderaan jauh, Sistem Informasi Geografis, Sistem Dinamik, CLUE-S, dan InVEST. Peta penggunaan lahan 2000, 2010, dan 2020 disusun dari citra Landsat menggunakan Object-Based Image Analysis dengan Multiresolution Segmentation dan Random Forest. Faktor pendorong dianalisis dengan regresi logistik biner. Sistem Dinamik digunakan untuk memproyeksikan kebutuhan penggunaan lahan, produksi padi, kebutuhan beras, dan stok karbon pada empat skenario: BAU, moderat, optimis, dan progresif. CLUE-S mengalokasikan kebutuhan tersebut secara spasial pada grid 100 x 100 m, sedangkan InVEST mengevaluasi jasa ekosistem pangan padi dan stok karbon. Arahan akhir disusun melalui evaluasi skenario dan tumpang susun dengan pola ruang RTRW Kabupaten Sukabumi 2023-2043. Hasil menunjukkan bahwa selama 2000-2020 lahan terbangun meningkat 10.664 ha atau 47,78%, sedangkan hutan berkurang 774 ha, lahan kering 7.748 ha, perkebunan 440 ha, sawah 1.600 ha, dan lahan terbuka 102 ha. Kombinasi klasifikasi terbaik menggunakan scale 50, shape 0,1, dan compactness 0,5 dengan overall accuracy 90,55% dan Kappa 88,85%. Perubahan hutan menjadi pertanian terutama dipengaruhi jarak ke kota terdekat, sedangkan perubahan pertanian menjadi lahan terbangun terutama dipengaruhi kepadatan penduduk. Model Sistem Dinamik menunjukkan bahwa skenario progresif memberikan kinerja terbaik pada 2043: luas sawah 66.997 ha, produksi padi 983.113,98 ton, produksi beras 616.805,71 ton, kebutuhan beras 311.338,52 ton, surplus 305.467,19 ton, luas hutan/fungsi lindung 87.776 ha, dan stok karbon 17.110.157,34 ton C. Dibandingkan kondisi 2020, skenario progresif meningkatkan stok karbon 335.788,40 ton C. Model CLUE-S memiliki Kappa 88,01% dan overall accuracy 91,69%. Arahan perencanaan menempatkan perlindungan/penyediaan sawah 66.997 ha dan hutan atau kawasan berfungsi lindung 87.776 ha sebagai target spasial 2043, disertai produktivitas padi 5,80 ton/ha, indeks pertanaman 2,53, laju pertumbuhan penduduk 1,27% per tahun, dan konsumsi beras 0,0930 ton/kapita/tahun. Manfaat utama penelitian adalah menyediakan kerangka ilmiah yang menghubungkan dinamika penggunaan lahan, jasa ekosistem, dan tata ruang untuk mendukung pengambilan keputusan adaptif berbasis bukti di Kabupaten Sukabumi. Kebaruan penelitian bukan terletak pada penggunaan individual atau sekadar penggabungan Sistem Dinamik, CLUE-S, dan InVEST, tetapi pada pengembangan feedback-based dynamic-spatial ecosystem-service land-use planning framework. Kerangka tersebut membentuk siklus keputusan dari faktor pendorong dan kebutuhan lahan temporal, alokasi spasial, evaluasi kinerja jasa ekosistem, respons kebijakan, hingga arahan spasial. Kinerja pangan padi dan stok karbon diperlakukan sebagai sinyal untuk mengevaluasi kombinasi kebijakan. Umpan balik yang dimaksud adalah policy/decision feedback, bukan kopling numerik dua arah otomatis antarperangkat lunak.

Sukabumi Regency is experiencing land-use pressure driven by population growth, regional development, infrastructure expansion, and increasing demand for built-up land. These pressures may reduce paddy fields and forest cover, creating trade-offs among development needs, rice-food provisioning, and carbon-stock maintenance. This study aimed to: (1) analyze land-cover/use change patterns; (2) identify the driving factors of change; (3) develop a dynamic land-use model; (4) analyze spatial dynamics up to 2043; (5) assess impacts on rice-food provisioning and carbon stock; and (6) formulate ecosystem-service-based land-use planning directions. The research integrated remote sensing, GIS, System Dynamics, CLUE-S, and InVEST. Land-use maps for 2000, 2010, and 2020 were derived from Landsat imagery using Object-Based Image Analysis with Multiresolution Segmentation and Random Forest. Binary logistic regression was used to identify land-use change drivers. System Dynamics projected land demand, rice production, rice demand, and carbon stocks under four scenarios: BAU, moderate, optimistic, and progressive. CLUE-S spatially allocated land demand on a 100 x 100 m grid, while InVEST evaluated rice-food provisioning and carbon-stock ecosystem services. The preferred scenario was then evaluated against the 2023-2043 Sukabumi spatial plan. Between 2000 and 2020, built-up land increased by 10,664 ha or 47.78%, while forest declined by 774 ha, dry land by 7,748 ha, plantations by 440 ha, paddy fields by 1,600 ha, and open land by 102 ha. The best classification configuration used scale 50, shape 0.1, and compactness 0.5, producing an overall accuracy of 90.55% and Kappa accuracy of 88.85%. Forest-to-agriculture conversion was most strongly associated with distance to the nearest town, whereas agriculture-to-built-up conversion was most strongly associated with population density. The progressive scenario provided the best 2043 performance: 66,997 ha of paddy fields, 983,113.98 tons of paddy production, 616,805.71 tons of rice production, 311,338.52 tons of rice demand, a surplus of 305,467.19 tons, 87,776 ha of forest/protection-function land, and 17,110,157.34 tons C of carbon stock. Relative to 2020, carbon stock increased by 335,788.40 tons C. CLUE-S validation yielded a Kappa coefficient of 88.01% and overall accuracy of 91.69%. The novelty does not lie in the individual use or simple coupling of System Dynamics, CLUE-S, and InVEST, but in a feedback-based dynamic-spatial ecosystem-service land-use planning framework. The framework closes the planning decision cycle from drivers and temporal land demand, through spatial allocation and ecosystem-service assessment, to policy response and spatial planning directions. Rice-food and carbon-stock performance are treated as decision signals for evaluating policy packages. The feedback is operationalized as policy/decision feedback, not as automated two-way numerical recoupling among software platforms. The planning direction sets 2043 spatial targets of 66,997 ha of protected/provided paddy fields and 87,776 ha of forest or protection-function land, combined with a rice productivity target of 5.80 tons/ha, a cropping index of 2.53, population growth of 1.27% per year, and rice consumption of 0.0930 tons/capita/year. The study provides a scientific decision-support framework linking land-use dynamics, ecosystem-service performance, and spatial planning for adaptive, evidence-based land-use governance in Sukabumi Regency.