Pemerintah Indonesia mencanangkan swasembada gula nasional sejak tahun 2015. Di sisi lain luas areal lahan pertanian di Jawa terutama Jawa Timur semakin menurun sedangkan konsumsi gula nasional meningkat 1,51 % per tahun. Peningkatan konsumsi tidak diimbangi dengan peningkatan produksi tebu dilahan, rata-rata produksi tebu di lahan di bawah 60 ton/ha menurun 50% dari 15 tahun terakhir. Tujuan dari kegiatan penelitian yaitu evaluasi kesesuaian lahan aktual dan potensial guna meningkatkan produktifitas tanaman tebu. Penelitian dilaksanakan pada bulan Agustus-September 2021 di Kecamatan Sumberbaru Kabupaten Jember. Metode penelitian yang digunakan untuk menyelesaikan masalah yaitu metode diskriptif eksploratif dengan memachingkan data karakteristik tanah & lingkungan dengan diskripsi lingkungan tumbuh ideal bagi tanaman tebu. Hasil penelitian menunjukkan bahwa di Kecamatan Sumberbaru Kabupaten Jember luas kelas kesesuaian lahan aktual tidak sesuai (N) seluas 7517,53 hektar (48,26%), sesuai marginal (S3) seluas 5392,60 hektar (35,62%), cukup sesuai (S2) seluas 2666,03 hektar (17,12%). Kesesuaian lahan potensial untuk tanaman tebu tidak sesuai (N) seluas 401,62 hektar (2,58%) turun 94,66%, sesuai marginal (S3) luas 745,85 hektar (4,79%) turun sebesar 86,17%, cukup sesuai (S2) luas 7747,86 hektar (49,74%) meningkat 190,61%, sesuai (s1) luas 6680,83 hektar (42,89%).
Erosion is an event of eroding soil that occurs naturally. However, human activities that change land use from natural (forestry, plantation, rural areas) to urban features can alter the erosion processes. Rapid calculation of erosion level for the wide area is necessary for the management and conservation planning. This research aims to analyze the erosion level in East Java area using USLE (Universal Soil Loss Equation) and GIS. The erosivity factor (R) is calculated from rainfall data. Vegetation factor (C) and the conservation factor (P) estimated from land use map. The length and slope factor (LS) are calculated from the ASTER GDEM2, and the erodibility factor (K) is obtained from interpretation of soil map. Furthermore, all factors were analysed to calculate erosion rate. The result shows that the average erosion rate in East Java regions is 10,30 tons/ha/year. The result also show that 78,71% area of East Java is classified as very low erosion rate (0-15 tons/ha/year); 10,75% classified as low erosion rate (15-60 tons/ha/year); 6,39% classified as moderate erosion rate (60-180 tons/ha/year); and 2,83% is severe type (180-480 tons/ha/year). Only 1,31% from the total area is classified as very severe erosion rate (>480 tons/ha/year). The result also shows that USLE can be used to facilitate rapid erosion prediction for wide area.
The regencies of Probolinggo, Lumajang, Jember, Bondowoso, Situbondo, and Banyuwangi are located in the Eastern part of East Java and called as Tapal Kuda. These regions are actually on fast development. The development to service human settlement generates land use change from natural into urban or developed areas. The change in land use will generate more runoff, erosion, and sedimentation from the watersheds. This study examined the effect of land use types and their percentage areas on erosion rates. The Universal Soil Loss Equation (USLE) was used to predict the erosion rate. The erosion rate of four land uses, which were forests, paddy fields, plantations and settlements, were calculated and compared. The values of the erosion rate were obtained by the statistical value per pixel in the watershed. Fifteen watersheds in the Tapal Kuda area were used as the samples. The results showed that the relationship (r 2) between forests, rice fields, plantations, settlements and the erosion rate:
Sentine-2 menjanjikan citra yang gratis, pada ketelitian spasial sedang dan ketelitian spektral tinggi. Data citra ini mungkin dapat digunakan sebagai dasar pemetaan tutupan lahan (land cover) dan pruntukan lahan (land use) sampai dengan level Desa. Artikel ini bertujuan untuk membandingkan dan mengevaluasi peta tematik yang dihasilkan dari: (1) Klasifikasi dari citra Sentinel-2A, (b) digitasi manual dari Google Earth Image, (c) dan peta RBI (Rupa Bumi Indonesia). Citra Sentinel-2A, citra google earth dan peta RBI digital digunakan sebagai input utama. Pengolahan citra Sentinel-2A mencakup: atmosferic correction, image composite, klasifikasi terbimbing, koleksi training area, dan uji-akurasi. Selanjutnya, ke tiga jenis peta tematik yang dihasilkan digunakan untuk membandingkan luasan per jenis tutupan lahan yang dipetakan dan interpretasi perubahan peruntukan lahan yang terjadi. Selanjutnya, wilayah empat desa digunakan sebagai sampel pengukuran. Penelitian menghasilkan peta tematik tutupan dan peruntukan lahan pada level Desa. Perbandingan peta tematik menunjukkan bahwa citra Sentinel mampu untuk menangkap fitur tutupan lahan yang utama (yaitu: Lahan-sub-optimal kering, lahan irigasi, lahan non-irigasi, area terbangun, hutan-perkebunan, dan badan air) pada level desa. Lebih lanjut peta yang dihasilkan dari citra Sentinel dapat digunakan untuk memperbaharui, perencanaan dan evaluasi kegiatan pembangunan di Desa. Kata Kunci: Sentinel-2A, Pemetaan, Tutupan Lahan, peruntukan lahan, desa.Sentinel-2 provide a free of cost imagery in medium spatial and high spectral resolutions. These data promise a rapid, low-cost and easy to apply imagery for the end-user. These free data may produce a rationale thematic land cover and land use (LCLU) map at the village level. This paper aims to compare and to evaluate the thematics maps created by (a) Sentinel-2, (b) digitalisation from Google Earth and (c) RBI (Rupa Bumi Indonesia) Digital Map. Sentinel-2 image, google earth image, and RBI digital map used as the primary input. The treatment of sentinel 2A imagery consists of atmospheric correction, image composite, supervised classification, collecting training areas, and accuracy assessment. The three types of maps use to compare area extent mapped for each type of land cover (LC), and the interpretation of land-use change occurred. Four villages used as samples of measurement. The research produces thematic LCLU maps at the village level. Comparison of maps shows that Sentinel capable of capturing major LC (i.e., Dry-marginal land, non-irrigated area, irrigated area, pavement areas, forest - plantation, and water body) at the village level. Moreover, Sentinel-2A produce more detail of land cover type. Finally, the maps derived from Sentinel data provide data for up-dating, planning and evaluation of village development.Keywords : Sentinel-2A, mapping, land cover, land use, village.
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