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All Journal Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Tanah dan Iklim The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Indah Prasasti
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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DETEKSI AREA BEKAS KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN DATA CITRA RESOLUSI MENENGAH MODIS DENGAN PENDEKATAN INDEKS KEBAKARAN Mirzha Hanifah; Lailan Syaufina; Indah Prasasti
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 6 No. 1 (2016): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.6.1.77

Abstract

This research examined the use of fire index algorithms to detect and recognize the burnt area in West Kalimantan by applying the pre-fire and post-fire image comparison technique.  The main data used were derived from remotely sensed data MODIS acquired from Januari to April 2014.  The examined algorithms utilized the near-infrared (NIR) and short-infrared (SWIR) wavelength spectrums.  in the case of forest and land fires, occured the value of NIR decreases as the amount of chlorophyll decrease, while the pixel values and the inceasing value of SWIR will increase due to the rising temperature.  The research objective was to the capability of the algorithms in detecting burnt forest and land areas in several selected areas in West Kalimantan, using few indices generated from MODIS data.  The examined indices were NDFI (Normalized Difference Fire Index) and MNDFI (Modified Normalized Difference Fire Index), which utilize the reflectance values of band 2 (NIR) and band 7 (SWIR) from MODIS.  The study results show that both the NDFI and MNDFI were applicable in detecting burnt area having good performance with the Normalize Distance (D) values larger than 1.  Based on D-Value and accuracy assessment, MNDFI algorithm gave better index than the NDFI in detecting both forest and land areas.
Co-Authors . Suwarsono Adhi Harmoko Andi Ibrahim Any Zubaidah Dandy Aditya Novresiandi Dianovita Djoko Triyono Fadila Muchsin Hana Listi Fitriana Jalu Tejo Nugroho Jansen Sitorus Khalifah Insan Nur Rahmi Kiki Winda Veronica Kuncoro Adi Pradhono Kuncoro Adi Pradono Kurnia Ulfa Lailan Syaufina Liana Fibriawati M. Priyatna M. Rokhis Khomarudin Mirzha Hanifah Mulia Inda Rahayu Nanik Suryo Haryani Nanik Suryo. Haryani nFn suwarsono nFN suwarsono Nurwita Mustika Sari Rahmat Arief Rizaldi Boer Sayidah Sulma Suciantini Suciantini Supriatna Suwarsono Yenni Vetrita