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Pengaruh Jumlah Kelas dan Skema Klasifikasi terhadap Akurasi Informasi Penggunaan Lahan Hasil Klasifikasi Berbasis Objek dengan Teknik Support Vector Machine di Sebagian Kabupaten Kebumen Provinsi Jawa Tengah Aria Jaka Dwiputra; R. Suharyadi; Projo Danoedoro
Majalah Geografi Indonesia Vol 30, No 2 (2016): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4772.844 KB) | DOI: 10.22146/mgi.15632

Abstract

Pemodelan Spasial Erosi Kualitatif Berbasis Raster (Studi Kasus di DAS Serang, Kabupaten Kulonprogo) Nursida Arif; Projo Danoedoro; Hartono Hartono
Jurnal Ilmu Lingkungan Vol 15, No 2 (2017): Oktober 2017
Publisher : School of Postgraduate Studies, Diponegoro Univer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1965.297 KB) | DOI: 10.14710/jil.15.2.127-134

Abstract

Erosi merupakan salah satu fenomena alam yang banyak dikaji karena melibatkan banyak faktor yaitu vegetasi, tanah, iklim, topografi dan manusia.  Kompleksitas faktor-faktor yang mempengaruhi erosi disederhanakan melalui pemodelan untuk memprediksi tingkat erosi pada suatu wilayah dengan memanfaatkan data penginderaan jauh dan sistem informasi geografis. Faktor yang digunakan dalam menyusun model hanya melibatkan tiga faktor yaitu vegetasi, tanah dan lereng. Penelitian ini dilakukan di DAS Serang karena termasuk salah satu DAS yang berada dalam kondisi kritis yang dapat memicu terjadinya degradasi lahan, erosi dan longsor. Tujuan penelitian ini adalah mengetahui distribusi spasial tingkat erosi kualitatif di DAS Serang. Pendekatan yang digunakan adalah integrasi peginderaan jauh dan sistem informasi geografis berbasis raster. Validasi model dilakukan dengan melihat faktor topografi dan indikator erosi kualitatif di lapangan yaitu armour layer, singkapan akar, pedestal, erosi alur dan gully. Hasil penelitian menunjukan model yang dihasilkan sangat efektif sebagai solusi cepat prediksi erosi. Berdasarkan hasil analisis tingkat erosi sangat berat mendominasi di wilayah kajian yaitu sebagian besar di kecamatan Kokap, Girimulyo dan sebagian Pengasih.Kata kunci: Erosi, Model, Kualitatif, DAS SerangEnglish Title: Spatial Modeling of Raster Based  Qualitative ErosionABSTRACTErosion is one of the natural phenomena that's studied by many because it involves many factors, namely vegetation, soil, climate, topography and humans. The complexity of the factors affecting erosion is simplified through modeling to predict of erosion rates in a region by utilizing remote sensing data and geographic information systems. The erosion control factor used in this research fewer parameters, namely vegetation, soil and topography only. This research was conducted in Serang watershed because it is one of the watersheds which are in critical conditions which can trigger land degradation, erosion and landslides. The purpose of this research was to know the spatial distribution of erosion susceptibility levels in Serang watershed. The approach used was the integration of remote sensing and raster-based geographic information system. Model validation was undertaken based on topograhy factor and observation of qualitative erosion indicators in the field. The indicators used were pedestals, armor layers, root exposure, or other erosion featuress such as rill and gullies. The results show that the resulting model is more effective as a quick solution to the prediction of erosion. Based on the results of the analysis, the spatial distribution of erosion rates is very dominant in the study area, mostly in Kokap, Girimulyo and some of the sub-districts.Keywords: Erosion, Modeling, Qualitative, Serang watershedCitation: Arif, N., Danoedoro, P., dan Hartono. (2017). Pemodelan Spasial Erosi Kualitatif Berbasis Raster Studi Kasus di DAS Serang, Kabupaten Kulonprogo. Jurnal Ilmu Lingkungan, 15(2),127-134, doi:10.14710/jil.15.2.127-134
Kajian Transformasi Indeks Vegetasi Citra Satelit Sentinel-2A untuk Estimasi Produksi Daun Kayu Putih Menggunakan Linear Spectral Mixture Analysis Lilik Norvi Purhartanto; Projo Danoedoro; Pramaditya Wicaksono
Jurnal Nasional Teknologi Terapan (JNTT) Vol 3, No 1 (2019): JULI
Publisher : Penelitian dan Pengabdian Kepada Masyarakat Sekolah Vokasi Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1066.098 KB) | DOI: 10.22146/jntt.56618

Abstract

A forest plantation area of Melaleuca cajuputi at BDH Karangmojo, BKPH Yogyakarta are 2,325.20 ha. One of the efforts to keep its sustainability is to plan the target and realization of cajuputi leaf production considerwith forest condition. Advances in remote sensing technology can be an alternative in estimating the cajuputi leaf production on large areas with an efficient time and high accuracy and able to analyze the quality of cajuputi. This study aims to examine Sentinel-2A capabilities through a relationship model of some vegetation indices integrated with vegetative factors on the production to obtain estimates of leaf production, map and test the estimation model accuracy. The method used is to classify objects in pixels with Linear Spectral Mixture Analysis and build relationship between age, number of plants and vegetation index with cajuputi leaf production. The results showed that the unmixing method has 99,66% accuracy in classifying pixels into the fraction of cajuputi. MERIS Terrestrial Chlorophyll Index of unmixing cajuputi fraction simultaneously with age and number of plants has the highest correlation with value of r = 0,668 to the production and modeled in mapping the estimated cajuputi leaf production at the research location with Standard Error of Estimate is 0,183.