Integrasi GEE dan Citra Optik Sentinel untuk Pemetaan Tutupan dan Penggunaan lahan di Jawa Timur
Abstract
Informasi Tata Guna Lahan dan Tutupan Lahan (LULC) sangat penting untuk pemantauan lanskap dan pengembangan kebijakan pengelolaan lahan yang efektif. Penelitian ini bertujuan untuk memetakan LULC di Provinsi Jawa Timur. Dalam hal ini, citra Optik (sentinel 2) dikumpulkan dan diproses menggunakan Google Eatth Engine (GEE) untuk menghasilkan peta LULC terkini. Penggunaan citra diambil antara tahun 2020 hingga 2022. Algoritma Random Forest digunakan untuk mengklasifikasikan piksel untuk membentuk kelas LULC. Dalam studi ini, delapan kelas LULC signifikan dikategorikan, yaitu, area terbangun (BU), lahan pertanian heterogen (HAL), lahan kosong (BS), sawah (PF), badan air (OW), vegetasi (VG ), semak belukar (SH), dan lahan basah (WL). Selanjutnya, sampel pelatihan diinterpretasikan dari Google Earth Pro, peta dasar satelit GEE, dan titik kendali tanah (GCP) yang dikumpulkan. GCP yang dikumpulkan dibagi menjadi 70% data pelatihan dan 30% data validasi. Hasilnya peta LULC mencakup seluruh wilayah provinsi Jawa Timur. Seluruh wilayah provinsi terdiri dari lahan terbangun (BU = 6,65 %), lahan pertanian heterogen (HAL = 7,99%), lahan kosong (BS = 1,92%), sawah (PF=46,11 %), perairan terbuka (OW=0.21%), vegetasi (VG= 23.56%), semak belukar (SH= 12.17%), dan badan air (WL= 1.39%). Studi menunjukkan bahwa kombinasi citra optik dan GEE menghasilkan peta tematik yang baik yang menggambarkan kelayakan kelas LULC di Jawa Timur.
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