Classification of Land Cover by Using Aerial Photo At CV. Alaska Prima Coal, Cooling Village, Sanga-Sanga Sub-district, Kutai Kartanegara District, East Kalimantan Province

Agus Sofyan


Remote sensing can be done visually and digitally. one of the advantages of airborne photography data generated by drone (phantom-3) compared to satellite imagery with optical sensitivity is its ability to obtain cloud-free images and freedom of recording time and the displayed area shows clearly defined objects corresponding to land cover. characteristics. To limit the object-based area of this research method applied is Object Based Image Analysis (OBIA).

This study aims to classify land cover using highly resolved aerial photography with the help of Object Based Image Analysis (OBIA) technique and calculate the accuracy and accuracy, land cover classification by using Objeck Based Image (OBIA) analysis through examination of field conditions.

classifying land cover, the classification includes shrubs, young shrubs, plantations (oil palms), shrubs, mines, open land, roads and water bodies with Accuracy of Overcome 0.86.


Land Cover, Aerial Photo, accuracy

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Lillesand and Kiefer, 1989. Penginderaan jauh dan Interpretasi Citra, Gajah Mada University, Yogyakarta.

Riswanto, E., 2009. Evaluasi Akurasi Klasifikasi Penutupan Lahan Menggunakan Citra Alos Palsar Resolusi Rendah Studi Kasus di Pulau Kalimantan, Departemen Manajemen Hutan Fakultas Kehutanan Institut Pertanian, Bogor

Shofiyanti. 2011 Teknologi pesawat tanpa awak untuk pemetaan dan pemantauan tanaman dan lahan pertanian, Informatika Pertanian, Vol. 20 No.2, Desember 2011 : 58 – 64

Wahyunto, Sofyan Ritung dan Widagdo. 2003. Teknologi Penginderaan Jauh Untuk Monitoring Sumberdaya Lahan di Daerah Lampung. Laporan Akhir, Bagian Proyek Penelitian Sumberdaya Tanah. Balai Penelitian Tanah. Bogor (tidak dipublikasikan).


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