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All Journal JURNAL ITENAS REKAYASA REKA GEOMATIKA Indonesian Journal of Geospatial JURNAL BIOLOGI INDONESIA JURNAL ILMIAH GEOMATIKA
Agung Budi Harto
Institut Tekhnologi Bandung
Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Education Mathematics

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Journal : REKA GEOMATIKA

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Peningkatan Akurasi Interpretasi Foto Udara Menggunakan Metode Pembobotan Berbasis Objek untuk Pembuatan Peta Skala 1:5000 Lumbantobing, Marlonroi; Wikantika, Ketut; Harto, Agung Budi
REKA GEOMATIKA Vol 2017, No 1
Publisher : Institut Teknologi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (989.367 KB) | DOI: 10.26760/jrg.v2017i1.1459

Abstract

ABSTRAK Kebutuhan akan adanya pengembangan metode untuk meningkatkan akurasi dari interpretasi objek memerlukan kajian metodologi yang disebut analisis citra berbasis objek. Penelitian ini ditujukan untuk menentukan dan menganalisis akurasi dari interpretasi objek secara otomatis dengan metode berbasis objek dengan memberikan bobot yang berbeda untuk setiap kanal. Data yang digunakan adalah foto hasil pemotretan udara format menengah (medium format) dengan resolusi 16 cm. Ekstrak data menggunakan teknik object based image analysis (OBIA). Data diproses berdasarkan bobot yang yang berbeda untuk setiap kanal. Nilai akurasi ditentukan berdasarkan overall accuracy. Overall accuracy merupakan hasil validasi klasifikasi objek dengan ground truth yang diperoleh dari peta garis skala 1:5000 yang diinterpretasi secara visual. Hasil penelitian menunjukkan terjadi peningkatan nilai akurasi dengan pendekatan OBIA jika setiap kanal diberikan bobot yang berbeda dibandingkan dengan bobot yang sama. Peningkatan akurasi paling tinggi dengan bobot (Red=3, Green=4, Blue=3, IR=4, dan DEM= 3) menghasilkan akurasi 85,88%. Hasil akurasi meningkat sebesar 10,27 % dibandingkan dengan interpretasi tanpa pembobotan. Kata kunci: Interpretasi, Peta 1:5000, Klasifikasi, OBIA, Pembobotan, AkurasiABSTRACT Interpretation of imagery or aerial photo is an attempt to understand or interpret imagery to obtain accurate information and in accordance with the recorded object. The need for developing methods to improve the accuracy of the object interpretation requires assessment methodology which is called as object based image analysis. This study aimed at determining and analyzing the accuracy of the interpretation of the object automatically using object based method by giving different weights to each band. The data used were medium format aerial photos with a resolution of 16 cm. The method of data processing was object based image analysis (OBIA). Data were processed by different weights for each band. Accuracy value is determined based on the overall accuracy. Overall accuracy is the result of the validated object classification with ground truth obtained from the map of 1:5000 which were interpreted visually. The research results showed that the value of the accuracy with OBIA approach increased if each band is given different weights compared with the same weight. The highest accuracy was achieved with weights (Red=3, Green=4, Blue=3 , IR=4, and DEM=3), and resulted overall accuracy 85,88%. Results accuracy increased 10,27% compared with the interpretation without weighting. Keywords: Interpretation, Map 1:5000, Classification, OBIA, Weighting, Accuracy
Pemetaan Pola Tanam dan Kalender Tanam Padi Sawah menggunakan Teknik Pengindraan Jauh Hernawati, Rika; Harto, Agung Budi; Sari, Dewi Kania
REKA GEOMATIKA Vol 2017, No 2
Publisher : Institut Teknologi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1149.85 KB) | DOI: 10.26760/rg.v2017i2.1768

Abstract

ABSTRAKPemantauan dan prakiraan hasil tanam padi sawah penting untuk dilakukan antara lain dalam rangka menjaga ketahanan pangan nasional. Saat ini, pemantauan pertumbuhan tanaman padi sawah dapat dilakukan dengan mengaplikasikan teknologi pengindraan jauh, antara lain dengan mendeteksi fenologi tanaman padi sawah yang terekam pada setiap piksel citra yang selanjutnya dapat digunakan untuk pemetaan pola tanam dan kalender tanam padi sawah. Penelitian ini bertujuan untuk mengembangkan algoritma deteksi fenologi padi sawah dengan menggunakan indeks vegetasi Enhanced Vegetation Index (EVI) dan Land Surface Water Index (LSWI) berkala yang diturunkan dari data citra MODIS, dengan menerapkan proses penapisan Gaussian. Penerapan teknik penapisan Gaussian pada data indeks vegetasi tersebut diharapkan dapat meminimalisasi derau, sehingga akan meningkatkan ketelitian hasil pendeteksian fenologi tanaman padi sawah. Wilayah studi mencakup 3 Kabupaten di Provinsi Jawa Barat bagian utara, yaitu Kabupaten Subang, Kabupaten Karawang, dan Kabupaten Bekasi. Hasil penelitian menunjukkan bahwa penerapan penapisan Gaussian pada metode deteksi fenologi padi sawah berbasis indeks vegetasi EVI dan LSWI berkala telah dapat meningkatkan ketelitian hasil deteksi tanggal-tanggal fenologis padi sawah. Keakuratan hasil estimasi luas tanam dan luas panen padi sawah divalidasi menggunakan data statistik dari Dinas Pertanian Kabupaten.Kata Kunci: deteksi fenologi, EVI, LSWI, penapisan GaussianABSTRACTMonitoring and forecasting yields of paddy rice are important to do, in order to maintain national food security. The current paddy crop growth monitoring can be done by applying remote sensing technology by detecting paddy phenology to produce the date of planting and harvest dates, which were recorded at each pixel of the digital image of rice field and can then be used for cropping pattern and planting calendar mapping. This research aims to develop a detection algorithm phenology paddy using vegetation indices Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) periodic image data derived from MODIS, by applying a Gaussian filtering process. The application of Gaussian filtering techniques to the data of vegetation indeces, EVI and LSWI, are expected to minimize the noise, thereby increasing the precision of detection of paddy rice crop phenology. The study area covers three districts in the northern part of West Java Province, i.e. Subang, Karawang and Bekasi. The results showed that the application of Gaussian filtering on the detection method of paddy rice phenology based on multitemporal vegetation indices EVI and LSWI can improve the precision of the detection of paddy phenological dates. The accuracy of the estimation results of the planting and harvested area of paddy were validated using statistical data from the District Agricultural Office.Keywords: phenology detection, EVI, LSWI, Gaussian filtering
Co-Authors Akhmad Riqqi, Akhmad Armi, Ilham Deni Suwardhi Dewi Kania Sari Fahmi, Muhammad Nurul Hakim, Yofri Furqani Hernawati, Rika Ishak Hanafiah Ismullah Ketut Wikantika Lumbantobing, Marlonroi Matahelemual, Godfried Junio Sebastian Muhammad Mukhlisin Primajati,, Mahendra Primajati,, Mahendra Sulistyawati, Endah Sulistyawati, Endah Tri Muji Susantoro, Tri Muji Widyo Nugroho Sulasdi Wiwin Windupranata, Wiwin