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All Journal Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Geoid - Journal of Geodesy and Geomatics
Indah Prasasti, Indah
Pusat Pemanfaatan Penginderaan Jauh Lembaga Penerbangan dan Antariksa Nasional
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Environmental Science

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HIGH RISE BUILDING IDENTIFICATION FROM SPOT 6 MULTISPECTRAL AND DIGITAL SURFACE MODEL (DSM) USING OBJECT BASED IMAGE ANALYSIS Zylshal, Zylshal; Nugroho, Jalu Tejo; Prasasti, Indah
Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Vol 14, No 2 (2017): July 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jg.v14i2.11583

Abstract

This study focuses on one aspect of urban geometry called urban canyon. Urban canyon defined by a relatively narrow street lined by tall buildings. The initial step to extract the urban canyon is to identify the tall buildings. This study aims to discuss the potential use of the SPOT-6 multispectral data and its digital surface model (DSM), using object-based image analysis methods and terrain analysis, to identify the high-rise buildings in some part of Jakarta, Indonesia. Using slope and elevation percentile from the DSM as well as the spectral information of the SPOT-6 image, we then processed using the Object Image Analysis (OBIA) method and decision tree algorithm (crisp classification), we are able to obtained the identification rate of 78% with mean location accuracy of 30 meter (5 pixels).
COMPARISON OF THE RADIOMETRIC CORRECTION LANDSAT-8 IMAGE BASED ON OBJECT SPECTRAL RESPONSE AND VEGETATION INDEX Muchsin, Fadila; Supriatna, .; Harmoko, Adhi; Prasasti, Indah; Rahayu, Mulia Inda; Fibriawati, Liana; Pradhono, Kuncoro Adi
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 18, No 2 (2021)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3632

Abstract

Landsat-8 standard level (level 1T) data received by users still in digital form can be used directly for land cover/land use mapping. These data have low radiometric accuracy when used to produce information such as vegetation indices, biomass, and land cover/land use classification. In this study, radiometric/atmospheric correction was conducted using FLAASH, 6S, DOS, TOA+BRDF and TOA method to eliminate atmospheric disturbances and compare the results with field measurements based on object spectral response and NDVI values. The results of the spectral measurements of objects in paddy fields at harvest time in the Cirebon Regency, West Java, Indonesia show that the FLAASH and 6S method have spectral responses that are close to those of objects in the field compared to the DOS, TOA and TOA+BRDF methods. For the NDVI value, the 6S method has the same tendency as the object's NDVI value in the field.  
HOTSPOT VALIDATION OF THE HIMAWARI-8 SATELLITE BASED ON MULTISOURCE DATA FOR CENTRAL KALIMANTAN Rahmi, Khalifah Insan Nur; Sulma, Sayidah; Prasasti, Indah
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 16, No 2 (2019)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1112.862 KB) | DOI: 10.30536/j.ijreses.2019.v16.a3293

Abstract

The Advanced Himawari Imager (AHI) is the sensor aboard the remote-sensing satellite Himawari-8 which records the Earth’s weather and land conditions every 10 minutes from a geostationary orbit. The imagery produced known as Himawari-8 has 16 bands which cover visible, near infrared, middle infrared and thermal infrared wavelength potentials to monitor forestry phenomena. One of these is forest/land fires, which frequently occur in Indonesia in the dry season. Himawari-8 can detect hotspots in thermal bands 5 and band 7 using absolute fire pixel (AFP) and possible fire pixel (PFP) algorithms. However, validation has not yet been conducted to assess the accuracy of this information. This study aims to validate hotspots identified from Himawari images based on information from Landsat 8 images, field surveys and burnout data. The methodology used to validate hotspots comprises AFP and PFP extraction, determining firespots from Landsat 8, buffering at 2 km from firespots, field surveys, burnout data, and calculation of accuracy. AFP and PFP hotspot validation of firespots from Landsat-8 is found to have higher accuracy than the other options. In using Himawari-8 hotspots to detect land/forest fires in Central Kalimantan, the AFP algorithm with 2km radius has accuracy of 51.33% while the PFP algorithm has accuracy of 27.62%.
PEMANFAATAN DATA PENGINDERAAN JAUH DAN SIG UNTUK ANALISA BANJIR (STUDI KASUS : BANJIR PROVINSI DKI JAKARTA) Ariyora, Yuan Karisma Sang Ariyora; Budisusanto, Yanto; Prasasti, Indah
GEOID Vol. 10 No. 2 (2015)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v10i2.1451

Abstract

Banjir merupakan salah satu fenomena alam yang sering terjadi di berbagai wilayah. Banjir dalam dua pengertian, yaitu : 1) meluapnya air sungai yang disebabkan oleh debit sungai yang melebihi daya tampung sungai pada keadaan curah hujan tinggi, 2) genangan pada daerah dataran rendah yang datar yang biasanya tidak tergenang. Banjir merupakan salah satu bencana yang sering terjadi di Indonesia, khususnya kota-kota besar seperti Jakarta.Daerah bahaya banjir dapat diidentifikasi secara cepat dengan menggunakan memanfaatkan data Penginderaan Jauh yaitu tumpang susun/overlay terhadap parameter-parameter banjir, seperti : curah hujan, bentuk penggunaan lahan (landuse), tekstur tanah, dan kemiringan lereng. Serta perpaduan visualisasi persebaran banjir dengan SIG (Sistem Informasi Geografi). Pembagian kelas dari setiap parameter yang digunakan secara umum disesuaikan dengan kelas parameter yang dimiliki oleh daerah yang diamati.Nilai bobot dan skor juga menyesuaikan dengan daerah penelitian yang diamati. Dalam penelitian ini, nilai bobot dan skor yang digunakan merupakan modifikasi dari nilai bobot dan skor. Dari hasil bobot dan skoring lalu menghitung Nilai potensi suatu daerah terhadap genangan ditentukan dari total penjumlahan skor masing-masing parameter genangan. Daerah yang sangat berpotensi terhadap genangan akan memiliki skor total dengan jumlah paling besar dan sebaliknya daerah yang tidak berpotensi terhadap genangan akan mempunyai total skor yang rendah. Tabel berikut menunjukkan tingkat potensi genangan berdasarkan nilai penjumlahan skor masing-masing parameter genangan.Hasil yang didapatkan penetapan kawasan bahaya banjir, ternyata daerah bahaya banjir yang dibuat Pemerintah Provinsi DKI 100% semuanya masuk dalam daerah sangat bahaya banjir berdasarkan hasil penelitian.Hal ini terjadi karena memang setiap musim penghujan daerah-daerah bahaya tersebut selalu mengalami banjir atau langganan banjir.
Pemanfaatan Citra VIIRS untuk Deteksi Asap Kebakaran Hutan dan Lahan di Indonesia Zubaidah, Any; Sulma, Sayidah; Suwarsono, Suwarsono; Prasasti, Indah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 9 No 4 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.9.4.929-945

Abstract

The observation of smoke because of land and forest fires in some regions in Indonesia mostly use the composite image visually. This study aims to develop the detection model of forest and land fire smoke using a digital analysis, which will be faster in supporting spatial information on emergency response in monitoring forest and land fire smoke. The method used is multi-threshold method and compare it with the existing model that is by modification of method Li et al. (2015). The data used is Suomi NPP-VIIRS satellite imagery. The results concluded that the VIIRS image can be used to detect the smoke and smoke distribution of forest fire and digital smoke. The multi-threshold model uses reflectance data obtained from the M4 visible channel, and the brightness temperature data obtained from the LWIR VIIRS M14 channel, with an average accuracy of 82.2% with a Commision error of 9.8% and an Ommision error of 10%. While the model of modification Li is based only on reflectance of visible-channel data i.e. channel M1, M2, M3, and SWIR VIIRS M11 channel, which has an average accuracy of 72.3% with a Commision error of 0.3% and an Ommision error of 27.4%. The multi-threshold model is a model that has the potential to be applied to detect forest and land fire smoke.
PENGKAJIAN NILAI VEGETASI DATA MODIS DENGAN MENERAPKAN BEBERAPA ALGORITMA PENGOLAHAN DATA INDEKS VEGETASI Prasasti, Indah; Sambodo, Kaimoko Ari
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 1 No. 1 (2004)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v1i1.3088

Abstract

The vegetation index (VI) that is extracted from MODIS data using several algorithms still needs to develop and to study. It is due to MODIS (Moderate Resolution Imaging Spectroradiometer) data that is relatively new in the operation and data application. The study aims to compare sensitivity application of 3 algorithms for extraction of vegetation index data. The simulation in this research is using MODIS data level 1B with all resolution (250m, 500m, and 1000m) for Kalimantan Island dated May 17, 2002 by applying NDVI algorithm (Normalized Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index),and SARVI (Soil and Atmosphere Resistant Vegetation Index). The result of this research shows that the application of SAVI and SARVI algorithms in cloud-dominated location will have higher vegetation index value as much as 0.001 - 0.04 unit with SAVI model, if compared with SAVI and can be higher or lower compared with SARVI value, depending on the condition of how much influential factor of atmospheric water vapor, aerosol content and canopy background that can be reduced and corrected by applying the SARVI model. In the meanwhile, in urban area, the applying of SAVI model will be lower as much as 0.14-0.15 unit, and about 0.1-0.15 unit with SARVI model if compared with NDVI.
KAJIAN PEMANFAATAN DATA ALOSPALSAR DALAM PEMETAAN KELEMBABAN TANAH Prasasti, Indah; Carolita, Ita; Ramdani, A. E.; Risdiyanto, Idung
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v9i2.3263

Abstract

ESTIMASI LIMPAHAN PERMUKAAN DARI DATA SATELIT UNTUK MENDUKUNG PERINGATAN DINI BAHAYA BANJIR DI WILAYAH JABODETABEK Sofyan, Parwati; Febrianti, Nur; Prasasti, Indah
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 11 No. 1 (2014)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v11i1.3299

Abstract

The study about runoff estimation based on soil moisture conditions was conducted using remote sensing data i.e., Landsat and Tropical Rainfall Measurement Mission during flood period January – February 2013 in Jakarta and its souroundings area. The Landsat data used to analyze the landcover/landuse which one of the basin characteristics. In this study, the TRMM has ability for representing the regional rainfall as 62.5 %. The Curve Number-Soil Conservation Service (CN-SCS) method was used in this study to estimate the runoff. The results of runoff estimation was shown in hydrograph unit in order to know when the flood will occur. The antecedent soil moisture condition in wet condition showed the best hydrograph unit. It had the peak point in January 17th 2013 exactly same with the time flood occurred in Jakarta and the souroundings area. This model has a good potential to be used as a flood early warning system. Spatially, the overall accuracy of the flood identification in Jakarta region compared with the flood map produced by Disaster Management Berau was 43 % with the producer’s accuracy 96 %, and user’s accuracy 42 %.
Co-Authors Any Zubaidah Ariyora, Yuan Karisma Sang Ariyora Febrianti, Nur Harmoko, Adhi Idung Risdiyanto Ita Carolita, Ita Jalu Tejo Nugroho, Jalu Tejo Liana Fibriawati, Liana Muchsin, Fadila Mulia Inda Rahayu, Mulia Inda Pradhono, Kuncoro Adi Rahmi, Khalifah Insan Nur Ramdani, A. E. Sambodo, Kaimoko Ari Sayidah Sulma, Sayidah Sofyan, Parwati Supriatna, . Suwarsono Suwarsono Yanto Budisusanto, Yanto Zylshal, Zylshal