Bambang H. Trisasongko
Tim KKP3T-Padi, Departemen Ilmu Tanah dan Sumberdaya Lahan, Institut Pertanian Bogor, Bogor 16680

Published : 4 Documents
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Tropical Mangrove Mapping Using Fully-Polarimetric Radar Data

Journal of Mathematical and Fundamental Sciences Vol 41, No 2 (2009)
Publisher : ITB Journal Publisher, LPPM ITB

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Abstract

Although mangrove is one of important ecosystems in the world, it has been abused and exploited by human for various purposes. Monitoring mangrove is therefore required to maintain a balance between economy and conservation and provides up-to-date information for rehabilitation. Optical remote sensing data have delivered such information, however ever-changing atmospheric disturbance may significantly decrease thematic content. In this research, Synthetic Aperture Radar (SAR) fully polarimetric data were evaluated to present an alternative for mangrove mapping. Assessment using three statistical trees was performed on both tonal and textural data. It was noticeable that textural data delivered fairly good improvement which reduced the error rate to around 5-6% at L-band. This suggests that insertion of textural data is more important than any information derived from decomposition algorithm.

Simulation on the Use of LOSAT Data for Rice Field Mapping

Makara Journal of Technology Vol 14, No 2 (2010)
Publisher : Directorate of Research and Community Services, Universitas Indonesia

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Abstract

Since the launch of LAPAN-TUBSAT satellite in 2007, Indonesia has been developing mission on earth observation missions for various applications. The next generation mission, called LAPAN-ORARI Satellite (LOSAT), is currently under development and expected to be launched in 2011. In order to facilitate the applications, a thorough assessment of the sensor should be made. This paper presents an examination of simulated LOSAT data for rice monitoring and mapping purposes coupled with QUEST statistical tree. We found that three-band simulated LOSAT data were suitable for the task with reasonably high accuracy.

PEMANTAUAN LAHAN SAWAH MENGGUNAKAN CITRA ALOS AVNIR-2

GEOMATIKA Vol 15, No 2 (2009)
Publisher : Badan Informasi Geospasial in Partnership with MAPIN

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Abstract

Rice production has been one of important issues in food sufficiency and increasingly gains more attention to the government. Suitable monitoring scheme is then required to ensure proper data analysis. Remote sensing offers an efficient way to acquire such data, allowing rapid assessment on agricultural system. Many advances on sensor technology have been witnessed. Nonetheless, each sensor has to be evaluated for a specific task such as monitoring various stages in rice production. This paper discusses the performance of AVNIR-2 sensor combined with two statistical tree algorithms. Interestingly, the result shows the outstanding performance of the third band of the sensor. We obtained overall accuracy around 90%. The research indicates the applicability of sensors with limited bands coupled with suitable algorithms.Keywords: ALOS, AVNIR-2, rice , CRUISE, QUEST.ABSTRAKDalam menyusun kebijakan pemerintah yang terkait masalah swasembada pangan, data produksi pangan memegang peranan yang sangat penting. Selama proses produksi, mekanisme pemantauan sangat diperlukan, terutama menggunakan teknologi penginderaan jauh. Berbagai kemajuan dalam bidang sensor telah menunjang beragam aplikasi praktis seperti pemantauan padi. Namun demikian, berbagai percobaan masih relevan untuk dilakukan, mengingat sensitivitas suatu sensor masih perlu diuji dalam berbagai wilayah. Makalah ini mengkaji keragaan sensor pasif AVNIR-2 dalam memantau berbagai fase pertumbuhan padi, memanfaatkan dua algoritma pohon keputusan. Hasil yang diperoleh menunjukkan kinerja yang baik dari sensor tersebut, terutama pada kanal 3 dengan tingkat akurasi sekitar 90%. Hal tersebut mengindikasikan bahwa dengan pemanfaatan mekanisme analisis yang tepat, sensor dengan kanal terbatas masih dapat dimanfaatkan untuk tujuan yang spesifik.Kata kunci: ALOS, AVNIR-2, padi, CRUISE, QUEST.

VARIASI NILAI INDEKS VEGETASI MODIS PADA SIKLUS PERTUMBUHAN PADI

GEOMATIKA Vol 15, No 2 (2009)
Publisher : Badan Informasi Geospasial in Partnership with MAPIN

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Abstract

Remote sensing technology has been employed extensively for food crops mapping and monitoring. Despite its widespread utilization, analyses have been limited to single set of data. Rice monitoring, ideally, requires time series data and therefore needs high revisit satellite configuration. Nonetheless, very limited research has been dedicated to time series data. This paper presents a study on the use of MODIS time series data for understanding various stages of rice growth in Subang Regency. Two widely-recognized vegetation indices were compared, namely Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). It is shown that 8-day temporal compositing scheme was unable to provide a proper dataset for this application. This suggests that detailed rice growth could be monitored solely in dry season.Keywords: MODIS, paddy phenology, NDVI, EVI.ABSTRAKPerkembangan teknologi penginderaan jauh telah dimanfaatkan dalam berbagai bidang, termasuk diantaranya bidang pertanian pangan. Namun demikian, fokus utama pemanfaatan masih terbatas pada penggunaan data akuisisi tunggal. Aplikasi pemantauan tanaman pangan, terutama padi, yang memiliki siklus pertumbuhan sangat cepat sangat membutuhkan konfigurasi deret waktu. Telaah literatur menunjukkan bahwa analisis deret waktu sangat terbatas disajikan. Makalah ini menyajikan analisis data serial untuk memantau berbagai fase pertumbuhan padi di Kabupaten Subang memanfaatkan data MODIS yang tersedia secara gratis. Dua indeks kehijauan yaitu Normalized Difference Vegetation Index (NDVI) dan Enhanced Vegetation Index (EVI) dibandingkan dalam kajian ini. Makalah ini menunjukkan indikasi bahwa citra komposit multitemporal 8 hari belum mampu menyediakan data untuk tujuan pemantauan pertumbuhan padi. Dengan demikian, analisis data hanya dapat dimungkinkan pada musim kemarau.