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All Journal MAJALAH ILMIAH GLOBE The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Yenni Vetrita
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Earth & Planetary Sciences Education

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VARIABILITAS TINGKAT KEHIJAUAN VEGETASI BERDASARKAN ENHANCED VEGETATION INDEX SELAMA KEKERINGAN EKSTRIM TAHUN 2015 DI PULAU JAWA: (Variability of Vegetation Greenness Level based on Enhanced Vegetation Index during the 2015 Extreme Drought in Java Island) Sayidah Sulma; Jalu Tejo Nugroho; Yenni Vetrita; Sri Harini
Majalah Ilmiah Globe Vol. 24 No. 2 (2022): GLOBE VoL 24 No 2 TAHUN 2022
Publisher : Badan Informasi Geospasial

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Abstract

Bencana kekeringan memiliki dampak yang sangat besar terhadap sektor pertanian dan perekonomian, sehingga pemantauan kekeringan perlu dilakukan secara berkala. Pemantauan kekeringan berbasis indeks vegetasi dari data satelit semakin berkembang dan perlu dikaji lebih lanjut khususnya untuk wilayah Indonesia. Pada tahun 2015 terjadi fenomena El Niño yang menyebabkan kondisi kekeringan ekstrim khususnya di wilayah Indonesia. Kondisi ini berpotensi untuk menjadi bahan kajian dalam pemantauan kekeringan menggunakan data penginderaan jauh. Tujuan penelitian ini adalah untuk mengetahui kemampuan pengkelasan Tingkat Kehijauan Vegetasi (TKV) dalam menggambarkan kondisi kekeringan, serta untuk menganalisis keterkaitan waktu terjadinya kekeringan meteorolgis dengan kekeringan pertanian. Pemantauan kondisi kekeringan dilakukan menggunakan indikator TKV. Variabilitas TKV diperoleh dari pengkelasan indeks vegetasi yaitu Enhanced Vegetation Index (EVI) dari data MODIS (Moderate Resolution Imaging Spectroradiometer), yang dianalisis mewakili kondisi kekeringan ekstrim yaitu pada saat El Niño tahun 2015 di Pulau Jawa dan dibandingkan dengan kondisi TKV 2019 yang mewakilli kondisi netral. Hasil perbandingan menunjukkan bahwa TKV dapat digunakan untuk pemantauan kondisi kekeringan di suatu wilayah, dimana saat musim kemarau di kedua waktu tersebut sama-sama menunjukkan kondisi kering, namun pada tahun 2015 saat iklim ekstrim TKV menunjukkan tingkat kehijauan vegetasi yang rendah hingga sangat rendah di sebagian besar Pulau Jawa. Berdasarkan penelitian diketahui bahwa rendahnya tingkat kehijauan vegetasi dapat mengindikasikan terjadinya kekeringan pertanian, dimana terdapat jeda waktu sekitar 2 bulan, dampak dari kekeringan meteorologi terhadap menurunnya kondisi tutupan vegetasi secara alami.
DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH Yenni Vetrita; Indah Prasasti; Nanik Suryo. Haryani; M. Priyatna; M. Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1841

Abstract

This study evaluated two parameters of fire danger rating system (FDRS) using remote sensing data i.e. drought code (DC) and fine fuel moisture code (FFMC) as an early warning program for forest/land fire in Indonesia. Using the reference DC and FFMC from observation data, we calculated the accuracy, bias, and error. The results showed that FFMC from satellite data had a fairly good correlation with FFMC observations (r=0.68, bias=7.6, and RMSE=15.7), while DC from satellite data had a better correlation with FFMC observations (r=0.88, bias=49.91, and RMSE=80.22). Both FFMC and DC from satellite and observation were comparable. Nevertheless, FFMC and DC satellite data showed an overestimation values than that observation data, particularly during dry season. This study also indicated that DC and FFMC could describe fire occurrence within a period of 3 months before fire occur, particularly for DC. These results demonstrated that remote sensing data can be used for monitoring and early warning fire in Indonesia.
MANGROVE ABOVE GROUND BIOMASS ESTIMATION USING COMBINATION OF LANDSAT 8 AND ALOS PALSAR DATA Gathot Winarso; Yenni Vetrita; Anang D Purwanto; Nanin Anggraini; Soni Darmawan; Doddy M. Yuwono
International Journal of Remote Sensing and Earth Sciences Vol. 12 No. 2 (2015)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2015.v12.a2687

Abstract

Mangrove ecosystem is important coastal ecosystem, both ecologically and economically. Mangrove provides rich-carbon stock, most carbon-rich forest among ecosystems of tropical forest. It is very important for the country to have a large mangrove area in the context of global community of climate change policy related to emission trading in the Kyoto Protocol. Estimation of mangrove carbon-stock using remote sensing data plays an important role in emission trading in the future. Estimation models of above ground mangrove biomass are still limited and based on common forest biomass estimation models that already have been developed. Vegetation indices are commonly used in the biomass estimation models, but they have low correlation results according to several studies. Synthetic Aperture Radar (SAR) data with capability in detecting volume scattering has potential applications for biomass estimation with better correlation. This paper describes a new model which was developed using a combination of optical and SAR data. Biomass is volume dimension related to canopy and height of the trees. Vegetation indices could provide two dimensional information on biomass by recording the vegetation canopy density and could be well estimated using optical remote sensing data. One more dimension to be 3 dimensional feature is height of three which could be provided from SAR data. Vegetation Indices used in this research was NDVI extracted from Landsat 8 data and height of tree estimated from ALOS PALSAR data. Calculation of field biomass data was done using non-decstructive allometric based on biomass estimation at 2 different locations that are Segara Anakan Cilacap and Alas Purwo Banyuwangi, Indonesia. Correlation between vegetation indices and field biomass with ALOS PALSAR-based biomass estimation was low. However, multiplication of NDVI and tree height with field biomass correlation resulted R2 0.815 at Alas Purwo and R2 0.081 at Segara Anakan. Low correlation at Segara anakan was due to failed estimation of tree height. It seems that ALOS PALSAR height was not accurate for determination of areas dominated by relative short trees as we found at Segara Anakan Cilacap, but the result was quite good for areas dominated by high trees. To improve the accuracy of tree height estimation, this method still needs validation using more data.
Co-Authors Anang D Purwanto Doddy M. Yuwono Gathot Winarso Indah Prasasti Jalu Tejo Nugroho M. Priyatna M. Rokhis Khomarudin Nanik Suryo. Haryani Nanin Anggraini Sayidah Sulma Soni Darmawan Sri Harini