Dede Dirgahayu
Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, Sekolah Pascasarjana Institut Pertanian Bogor

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MODEL BAHAYA BANJIR MENGGUNAKAN DATA PENGINDERAAN JAUH DI KABUPATEN SAMPANG (FLOOD HAZARD MODEL USING REMOTE SENSING DATA IN SAMPANG DISTRICT) Haryani, Nanik Suryo; Zubaidah, Any; Dirgahayu, Dede; Yulianto, Hidayat Fajar; Pasaribu, Junita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 9 No.1 Juni 2012
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Flood is the first biggest disaster in Indonesia, as stated by the National Disaster Management Agency (BNPB) in the BNPB’s natural disaster data of year 2000 to 2009. Considering the flood has the significant impact of causing the casualties and material losses, it is necessary to study on it. One of useful data for studying the flood is remote sensing data. The advantage of good historical data makes it possible to see the changes of cover/land use from year to year in a region. The extensive area coverage of remote sensing data allows it to view and analyze in a comprehensive manner. The method of the study of flood hazard models is using multiple variables, where each variable has a class of criteria. Determination of the weight of each flood variable by using the Composite Mapping Analysis. The results of this study shows the main cause of flooding in the District of Sampang is that most of the land system in the cities are the combined estuary and swamp plain, forming a low land and is triggered by the torrential rain. The model of flood hazard maps produced by variable weighting floods with a multi criteria analysis method which is function of rainfall, landuse, slope, land system and elevation. Key words: Flood hazard, Composite Mapping Analysis, Remote sensing
VERIFICATION OF LAND MOISTURE ESTIMATION MODEL BASED ON MODIS REFLECTANCES IN AGRICULTURAL LAND Dirgahayu, Dede; Sofan, Parwati
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 4,(2007)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (292.832 KB) | DOI: 10.30536/j.ijreses.2007.v4.a1216

Abstract

From this research, it is found that reflectances in the first, second, and sixth channels (R1, R2, R6) of MODIS have high correlations with surface soil moisture (percent weight) at 0-20 cm depth. An index called Land Moisture INdex (LMI) was created from the linier combination of R1 (percent), R2(percent), and R6 (percent). The MODIS reflectances and field soil moisture in paddy field taken from the Central and East Java during Juli-September 2005 are applied into the previous model which have been generated from data during July-September 2004. The result showed that there was a high correlation between Land/Soil Moisture (SM) which was measured from field survey, and LMI which was generated from the MODIS refectances. The best model equation between SM and LMI is the power regression model, which has the coeficient of determination of 88 percent. It is implied that soil moisture condition can be obtained from the MODIS data using LAnd Moisture Index. Therefore, the spatial information of drouht condition analysed throught the soil moisture in the agricultural land can be provided from the MODIS data. Keywords: Land Moisture Index, Soil Moisture Estimation, Spatial information, drought.
PEMANTAUAN KEJADIAN BANJIR LAHAN SAWAH MENGGUNAKAN DATA PENGINDERAAN JAUH Moderate Resolution Imaging Spectroradiometer (MODIS) DI PROVINSI JAWA TIMUR DAN BALI Zubaidah, Any; Dirgahayu, Dede; Pasaribu, Junita Monika
Jurnal Ilmiah Widya Vol 1 No 1 (2013)
Publisher : Jurnal Ilmiah Widya

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Abstract

Paper ini membahas tentang pemanfaatan data Satelit MODIS dan TRMM untuk memantau kejadian banjir di lahan sawah. Penelitian ini bertujuan untuk meningkatkan kualitas penyediaan informasi spasial tingkat rawan banjir pada lahan padi sawah di propinsi Jawa Timur dan Bali yang dapat dilakukan secara periodik (bulanan) berbasis data  penginderaan jauh. Data yang digunakan dalam penelitian ini adalah data satelit Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) bulan November dan Desember 2011 periode 8 harian, data curah hujan yang diperoleh dari TRMM pada periode yang sama di bulan November dan Desember 2011, luas baku sawah dan peta administrasi wilayah provinsi Jawa Timur dan Bali. Metode yang digunakan adalah mengkombinasi antara Enhance Vegetation Index (EVI) dengan curah hujan pada periode yang sama sehingga diperoleh tingkat rawan banjir yang diklasifikasikan menjadi 5 kelas yaitu kelas tidak banjir, ringan, sedang, berat, dan sangat berat.
PENGINDERAAN JAUH UNTUK PEMANTAUAN KEKERINGAN LAHAN SAWAH Zubaidah, Any; Dirgahayu, Dede; Pasaribu, Junita Monika
Jurnal Ilmiah Widya Vol 2 No 1 (2014)
Publisher : Jurnal Ilmiah Widya

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Abstract

Information of drough condition, especially in the paddy field is much needed in order to manage food availability in a certain area. Drough monitoring in paddy field can be generated by using MODIS and TRMM data. The purpose of this paper is to show spatial information of drough prone condition in the paddy field in East Java Province especially on July – September 2011. Data used in this paper is Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) and TRMM data in the same period on July – September 2011, standard extensive field and administration map of East Java Province. The method which is used in this paper is combining EVI (Enhance Vegetation Index) with LST (Land Surface Temperature) to obtain ETP (Potential Evapotranspiration) and make Meteorologist and Agronomist Drough parameter. Furthermore, processing of reflectance data was done to calculate Hydrologist Drough parameter. After that, this drough condition was classified into five class, namely non dry, mild, moderate, heavy and puso (crop failure).
MULTITEMPORAL LANDSAT DATA TO QUICK MAPPING OF PADDY FIELD BASED ON STATISTICAL PARAMETERS OF VEGETATION INDEX (CASE STUDY: TANGGAMUS, LAMPUNG) Parsa, I Made; Dirgahayu, Dede
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 1 (2013)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.578 KB) | DOI: 10.30536/j.ijreses.2013.v10.a1838

Abstract

Paddy  field  has  unique  characteristics  that  distinguish  it  from  other  plants.  Before it planting, paddy field is always flooded so that the appearance is dominated by water (aqueous phase). Within the  growth  of rice, field  conditions  will  be  increasingly  dominated  by  greenish rice  plants.While at the end, the rice plants will turn yellow indicating for harvesting. During flooding stage, the normalized difference vegetation index (NDVI) of pady field is negative. The negative value of NDVI of paddy field will ultimately increase to the maximum value at the maximum vegetative growth. TheNDVI of paddy field will decrease from generative phase until harvest and after harvest. The objective of  this  study  was  to  perform  the vegetation  index  analyses for multitemporal  Landsat  imagery of paddy field. The results showed that the difference of vegetation index values (maximum - minimum)of  paddy  field  were greater than the  difference  of vegetation index  values of  other land  uses.  Such differences values can be used as indicator to map land for rice. The evaluation results with reference data showed that the mapping accuracy (overall accuracy) was of 87.4 percent.
COMPARISON OF MODEL ACCURACY IN TREE CANOPY DENSITY ESTIMATION USING SINGLE BAND, VEGETATION INDICES AND FOREST CANOPY DENSITY (FCD) BASED ON LANDSAT-8 IMAGERY (CASE STUDY: PEAT SWAMP FOREST IN RIAU PROVINCE) Ashaari, Faisal; Kamal, Muhammad; Dirgahayu, Dede
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 1 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (779.58 KB) | DOI: 10.30536/j.ijreses.2018.v15.a2845

Abstract

Identification of a tree canopy density information may use remote sensing data such as Landsat-8 imagery. Remote sensing technology such as digital image processing methods could be used to estimate the tree canopy density. The purpose of this research was to compare the results of accuracy of each method for estimating the tree canopy density and determine the best method for mapping the tree canopy density at the site of research. The methods used in the estimation of the tree canopy density are Single band (green, red, and near-infrared band), vegetation indices (NDVI, SAVI, and MSARVI), and Forest Canopy Density (FCD) model. The test results showed that the accuracy of each method: green 73.66%, red 75.63%, near-infrared 75.26%, NDVI 79.42%, SAVI 82.01%, MSARVI 82.65%, and FCD model 81.27%. Comparison of the accuracy results from the seventh methods indicated that MSARVI is the best method to estimate tree canopy density based on Landsat-8 at the site of research. Estimation tree canopy density with MSARVI method showed that the canopy density at the site of research predominantly 60-70% which spread evenly.
DETEKSI KONDISI KETAHANAN PANGAN BERAS MENGGUNAKAN PEMODELAN SPASIAL KERENTANAN PANGAN Dirgahayu, Dede; Jaya, I Nengah Surati; Purwadhi, Florentina Sri Hardiyanti; Ardiansyah, Muhammad; Triwidodo, Hermanu
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 2, No 2 (2012): 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 | Full PDF (434.412 KB) | DOI: 10.29244/jpsl.2.2.85

Abstract

In 2005 and 2009, BKP and WFP has provided food security conditions in Indonesia on Food Insecurity Map which were developed using food availability, food accessibility, food absorption and food vulnerability. There are 100 out of 265 districts in Indonesia or about 37,7%, which fall into the vulnerable to very vulnerable categories, where 11 districts were found in Java. The main objective of this research is to develope a spatial model of the rice production vulnerability (KPB) based on Remote Sensing and GIS technologies for estimating the food insecurity condition. Several criteria used to obtain food vulnerability information are percentage level of green vegetation (PV), rainfall anomaly (ACH), land degradation due to erosion (Deg), and paddy harvest failure due to drought and flood in paddy field (BK). Dynamic spatial information on the greenness level of land cover can be obtained from multitemporal EVI (Enhanced vegetation Index) of MODIS (Moderate Resolution Imaging Spectroradiometer) data. Spatial information of paddy harvest failure caused by drought and flood was estimated by using vegetation index, land surface temperature, rainfall and moisture parameters with advance image processing of multitemporal EVI MODIS data. The GIS technology were used to perform spatial modelling based on weighted overlay index (multicriteria analysis). The method for computing weight of factors in the vulnerability model was AHP (Analytical Hierarchy Process). The spatial model of production vulnerability (KPB) developed in this study is as follows: KPB = 0,102 PV + 0,179 Deg + 0,276 ACH + 0,443 BK. In this study, level of production vulnerability can be categorized into six classes, i.e.: (1) invulnerable; (2) very low vulnerability; (3) low vulnerability; (4) moderately vulnerable; (5) highly vulnerable; and (6) extremely vulnerable. The result of spatial modelling then was used to evaluate progress production vulnerability condition at several sub-districts in Indramayu Regency. According to the investigation results of WFP in 2005, this area fall into moderately vulnerable category. Only few sub-districts that fall into highly and extremely vulnerable during the period of May ~ August 2008, namely: Kandanghaur, Losarang, part of Lohbener, and Arahan.Keywords: remote sensing, GIS, food vulnerability, vegetation index, AHP
ANALIIS SPASIAL KONVERSI LAHAN SAWAH DI KABUPATEN BEKASI (STUDI KASUS DI KECAMATAN CIBITUNG DAN TAMBUN) Dirgahayu, Dede
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 1, No.1 Juni (2004)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

The result of spatial analysis indicates that there has been position sidetrack of paddy field concentration (SM=Spatial Mean)from the year 1996 until the year 2000 to the North East direction as far as 691 m in Cibitung district and 481 m in Tambun district. The SM movement is away from the center of social economic activity of the community whether in yhe local area (district) or the regional area (City, Regency). Land conversion of paddy field into non-agricultural land that mostly occur are as a residential and industrial area. Land conversion has also occured in Tambun of paddy - then more settlement type about 105.2 Ha and 154.6 Ha in Cibitung. Land conversion of paddy - then more industry type has occured in Cibitung about 486.1 Ha and 87.9 Ha in Tambun. Paddy field conversion that occurs in the research location has taken place in Highly Suitable (S1) land, and has high productivity because it taken place in the area High Accessibility towards main road and center of the district.
PENGEMBANGAN PENGGUNAAN PENGINDERAAN JAUH UNTUK ESTIMASI PRODUKSI PADI (STUDI KASUS KABUPATEN BEKASI) Rudiana, Eka; Rustiadi, Ernan; Firdaus, Muhammad; Dirgahayu, Dede
Jurnal Ilmu Tanah dan Lingkungan Vol 19, No 1 (2017): Jurnal Ilmu Tanah dan Lingkungan
Publisher : Departemen Ilmu Tanah dan Sumberdaya Lahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.575 KB) | DOI: 10.29244/jitl.19.1.6-12

Abstract

Pemanfaatan produk penginderaan jauh satelit Landsat-8 (OLI) untuk melakukan pendugaan luas area panen dan produktivitas tanaman padi dengan menggunakan parameter Enhanced Vegetation Index (EVI) merupakan salah satu pendekatan baru untuk menghasilkan data estimasi produksi padi wilayah. Berdasarkan hasil analisis citra satelit dengan tanggal akuisisi bulan Mei-Agustus 2015, diperoleh hasil perkiraan luas panen padi sawah di Kabupaten Bekasi periode bulan Juli-Oktober 2015 adalah seluas 15.86 ribu ha atau lebih kecil 7.74 (32.79 %) ribu ha dibandingkan angka BPS pada periode yang sama. Berdasarkan keeratan hubungan antara nilai produktivitas hasil ubinan BPS dengan nilai EVI maksimum, diperoleh model persamaan pendugaan produktivitas tanaman padi sawah sebagai berikut: Produktivitas (ku ha-1) = 36.818 + 44.965 EVI maksimum. Nilai Rsquare yang diperoleh sebesar 0.809. Berdasarkan model tersebut diperoleh pendugaan produktivitas padi sawah di Kabupaten bekasi periode bulan Juli-Oktober 2015 sebesar 47.40 ku ha-1 atau lebih kecil 12.66 ku ha-1 dibandingkan angka produktivitas subround I 2015, lebih kecil 6.77 ku ha-1 dibandingkan angka produktivitas subround II 2015, lebih kecil 10.15 ku ha-1 dibandingkan angka produktivitas subround III 2015, dan lebih kecil 6.62 ku ha-1 dibandingkan angka produktivitas periode Januari-Desember 2015 yang dipublikasikan BPS. Sementara itu, perkiraan produksi padi sawah periode panen bulan Juli- Oktober 2015 berdasarkan analisis citra satelit yakni sebanyak 75.16 ribu ton GKG atau lebih kecil 55.35 ribu ton GKG (42.41%) dibandingkan angka yang dipublikasikan BPS pada periode yang sama. Kata kunci: Enhanced Vegetation Index, Landsat-8 (OLI), estimasi produksi padi
PENGEMBANGAN PENGGUNAAN PENGINDERAAN JAUH UNTUK ESTIMASI PRODUKSI PADI (STUDI KASUS KABUPATEN BEKASI) Rudiana, Eka; Rustiadi, Ernan; Firdaus, Muhammad; Dirgahayu, Dede
Jurnal Ilmu Tanah dan Lingkungan Vol 19, No 1 (2017): Jurnal Ilmu Tanah dan Lingkungan
Publisher : Departemen Ilmu Tanah dan Sumberdaya Lahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.575 KB) | DOI: 10.29244/jitl.19.1.6-12

Abstract

The utilization of remote sensing imagery such Landsat-8 (OLI) to estimate harvested area and yield using Enhanced Vegetation Index (EVI) parameter is a new approach to estimate regional rice production. Based on the analysis of the satellite imagery acquisition during May-August 2015, the estimation of rice harvested area in Bekasi District during July-October 2015 is 15.86 thousand ha or 7.74 thousand ha (32.79%) lower than BPS figures in the same period. Based on the relationship between yield (from the crop cutting survei, BPS) and EVI maximum, the equation model for rice yield estimation is: Yield (qu ha-1) = 36.818 + 44.965 EVImax. R2 value is 0.809. Based on the model, the estimation of rice yield in Bekasi District during July-October 2015 is 47.40 qu ha-1. Compared to the data published by BPS, the result is 12.66 qu ha-1 lower than the yield figure in subround I 2015, 6.77 qu ha-1 lower than the one in subround II 2015, 10.15 qu ha-1 lower than the one subround III 2015, and 6.62 qu ha-1 lower than the one in January-December 2015. Meanwhile, based on satellite imagery analysis, the estimation of rice production in the period of July-October 2015 is 75.16 thousand tons of GKG or 55.35 thousand tons of GKG (42.41%) lower than BPS figures during the same period. Keywords: Enhanced Vegetation Index, Landsat-8 (OLI), rice production estimation