Indah Prasasti, Indah
Pusat Pemanfaatan Penginderaan Jauh Lembaga Penerbangan dan Antariksa Nasional

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PENENTUAN POTENSI LAHAN UNTUK TANAMAN KEDELAI DAN CENGKIH DARI DATA LANDSAT TM DAN IKLIM DI KABUPATEN BANYUWANGI DENGAN SISTEM INFORMASI GEOGRAFIS Parwati, Ety; Prasasti, Indah; Effendy, Iskandar
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 1, No.1 Juni (2004)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.535 KB)

Abstract

Clove and soybean are plantations that have high enough economic pontetial. Both of these commodities need suitable land climate condition to grow in optimum. The process of Remote Sensing and climate data with Geographic Information System can determine a suitable land for clove and soybean plantations. Land potential evaluation uses Land Use data that is extracted from Landsat-TM data. The land suitability level is then determined based on climate parameter (rainfall and draught period) and land physical properties for sorbean and clove in Banyuwangi Regency.
THE EFFECT OF ENVIRONMENTAL CONDITION CHANGES ON DISTRIBUTION OF URBAN HEAT ISLAND IN JAKARTA BASED ON REMOTE SENSING DATA Prasasti, Indah; Suwarsono, .; Sari, Nurwita Mustika
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 12, No 1 (2015)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (777.162 KB) | DOI: 10.30536/j.ijreses.2015.v12.a2670

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Anthropogenic activities of urban growth and development in the area of Jakarta has caused increasingly uncomfortable climatic conditions and tended to be warmer and potentially cause the urban heat island (UHI). This phenomenon can be monitored by observing the air temperature measured by climatological station, but the scope is relatively limited. Therefore, the utilization of remote sensing data is very important in monitoring the UHI with wider coverage and effective. In addition, the remote sensing data can also be used to map the pattern of changes in environmental conditions (microclimate). This study aimed to analyze the effect of changes in environmental conditions (land use/cover, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Build-up Index (NDBI)) toward the spread of the urban heat island (UHI). In this case, the UHI was identified from pattern changes of Land Surface Temperature (LST) in Jakarta based on data from remote sensing. The data used was Landsat 7 in 2007 and Landsat 8 in 2013 for parameter extraction environmental conditions, namely: land use cover, NDVI, NDBI, and LST. The analysis showed that during the period 2007 to 2013, there has been a change in the condition of the land use/cover, impairment NDVI, and expansion NDBI that trigger an increase in LST and the formation of heat islands in Jakarta, especially in the area of business centers, main street and surrounding area, as well as in residential areas.
DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH Vetrita, Yenni; Prasasti, Indah; Haryani, Nanik Suryo; Priyatna, M; Khomarudin, M Rokhis
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 2 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.146 KB) | 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.
DETECTING THE LAVA FLOW DEPOSITS FROM 2018 ANAK KRAKATAU ERUPTION USING DATA FUSION LANDSAT-8 OPTIC AND SENTINEL-1 SAR Suwarsono, NFn; Prasasti, Indah; Nugroho, Jalu Tejo; Sitorus, Jansen; Triyono, Djoko
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (817.489 KB) | DOI: 10.30536/j.ijreses.2018.v15.a3078

Abstract

The increasing volcanic activity of Anak Krakatau volcano has raised concerns about a major disaster in the area around the Sunda Strait. The objective of the research is to fuse Landsat-8 OLI (Operational Land Imager) and Sentinel-1 TOPS (Terrain Observation with Progressive Scans), an integration of SAR and optic remote sensing data, in observing the lava flow deposits resulted from Anak Krakatau eruption during the middle 2018 eruption. RGBI and the Brovey transformation were conducted to merge (fuse) the optical and SAR data.  The results showed that optical and SAR data fusion sharpened the appearance of volcano morphology and lava flow deposits. The regions are often constrained by cloud cover and volcanic ash, which occurs at the time of the volcanic eruption.  The RGBI-VV and Brovey RGB-VV methods provide better display quality results in revealing the morphology of volcanic cone and lava deposits. The entire slopes of Anak Krakatau Volcano, with a radius of about 1 km from the crater is an area prone to incandescent lava and pyroclastic falls. The direction of the lava flow has the potential to spread in all directions. The fusion method of optical Landsat-8 and Sentinel-1 SAR data can be used continuously in monitoring the activity of Anak Krakatau volcano and other volcanoes in Indonesia both in cloudy and clear weather conditions.
DETEKSI AREA BEKAS KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN DATA CITRA RESOLUSI MENENGAH MODIS DENGAN PENDEKATAN INDEKS KEBAKARAN Hanifah, Mirzha; Syaufina, Lailan; Prasasti, Indah
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 | Full PDF (627.081 KB) | 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.
PENGKAJIAN PEMANFAATAN DATA TERRA-MODIS UNTUK EKSTRAKSI DATA SUHU PERMUKAAN LAHAN (SPL) BERDASARKAN BEBERAPA ALGORITMA Prasasti, Indah; Ari Sambodo, Katmoko; Carolita, Ita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 4, No.1 Juni (2007)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (251.149 KB)

Abstract

Land surface temperature (LST) is one primary parameters energy balance on the surface and also as primary climatology variable that controlling long-wave energy flux through atmosphere. The LST data is needed for drought estimating models which based on calculating of soil moisture lavel and/or evapotranspiration. TERRA satellite that brings sensor MODIS (Moderate Resolution Imaging Spectroradiometer) is an evironmental. Observation satellite that can be used for extracting LST data regionally. The MODIS relatively has width coverage; 2330 Km, and spatial resolution 250 m (1 and 2 channel) with high spectral resolution (36 channels), and temporal resolution that almost similar to the previous generation satellite called NOAA.
DETECTING THE AREA DAMAGE DUE TO COAL MINING ACTIVITIES USING LANDSAT MULTITEMPORAL (Case Study: Kutai Kartanegara, East Kalimantan) suwarsono, nFn; Haryani, Nanik Suryo; Prasasti, Indah; Fitriana, Hana Listi; Priyatna, M.; Khomarudin, M. Rokhis
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 2 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.505 KB) | DOI: 10.30536/j.ijreses.2017.v14.a2851

Abstract

Coal is one of the most mining commodities to date, especially to supply both national and international energy needs. Coal mining activities that are not well managed will have an impact on the occurrence of environmental damage. This research tried to utilize the multitemporal Landsat data to analyze the land damage caused by coal mining activities. The research took place at several coal mine sites in East Kalimantan Province. The method developed in this research is the method of change detection. The study tried to know the land damage caused by mining activities using NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), NDWI (Normalized Difference Water Index) and GEMI (Global Environment Monitoring Index) parameter based change detection method. The results showed that coal mine area along with the damage that occurred in it can be detected from multitemporal Landsat data using NDSI value-based change detection method. The area damage due to coal mining activities  can be classified into high, moderate, and low classes based on the mean and standard deviation of NDSI changes (ΔNDSI). The results of this study are expected to be used to support government efforts and mining managers in post-mining land reclamation activities.
Analisis Pemanfaatan Data CMORPH-IRI untuk Estimasi Curah Hujan Wilayah di Palangka Raya, Kalimantan Tengah dan Pekanbaru, Riau Prasasti, Indah; Suciantini, Suciantini
Jurnal Tanah dan Iklim (Indonesian Soil and Climate Journal) Vol 37, No 1 (2013)
Publisher : Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1087.553 KB) | DOI: 10.2017/jti.v37i1.6318

Abstract

Abstrak. Ketersediaan data curah hujan observasi permukaan seringkali menjadi pembatas dalam pengembangan model, pemantauan dan kajian iklim.Oleh sebab itu, pemanfaatan data satelit menjadi salah satu alternatif solusi yang perlu dikembangkan, seperti pemanfaatan data CMORPH-IRI.Penelitian ini bertujuan menganalisis potensi pemanfaatan data curah hujan CMORPH-IRI dan mendapatkan model estimasi curah hujan dari data CMORPH-IRI di wilayah Pekanbaru, Riau dan Palangkaraya, Kalimantan Tengah. Analisis dilakukan menggunakan analisis regresi, sedangkan validasi model dengan teknik validasi silang. Keterandalan model dinilai dari nilai korelasi (r) dan RMSEP antara nilai dugaan model terhadap nilai observasi. Hasil penelitian menunjukkan bahwa data CMORPH-IRI mempunyai potensi cukup baik sebagai penduga curah hujan dengan nilai korelasi baik (r > 0,5), kecuali untuk musim hujan di Palangka Raya, dengan RMSE berkisar antara 36,4-58,4 mm. Model dugaan di masing-masing wilayah penelitian adalah sebagai berikut: Palangka Raya: Musim Kemarau: y = 0,003(CH MK)2 + 0,301(CH MK)(R2 = 54,2%); Musim Hujan: y = 0,824(CH MH) (R2 = 20,8%), sedangkan untuk Pekanbaru: Musim Kemarau: y = 0,867(CH MK) (R2 = 26,2%); Musim Hujan: y = 0,984(CH MH) (R2 = 37,9%). Hasil validasi silang menunjukkan model tidak konsisten antar tahun akibat adanya keragaman curah hujan yang tinggi. Abstract. Availability of rainfall data from surface observation is one of the limiting factors for model development, monitoring and studyof climate. Therefore, the application of satellite data is an important alternative to be developed, such as the application of CMORPH-IRI data. The objectives of this research were to analyze the potential application of CMORPH-IRI rainfall data and obtain the estimation model using data CMORPH-IRI in Pekanbaru, Riau and Palangkaraya, Central Kalimantan. Analysis was done using regression analysis, while the validation of the model was based on cross-validation techniques. Reliability of the model was based on the correlation coefficient and RMSEP value.The results showed that the CMORPH-IRI data has good potential to be developed as a predictor of rainfall and good correlation coefficient (r > 0.5), except for rainy season in Palangkaraya (r=0.47). RMSEP value ranged from 36.4 to 58.4 mm. The model of rainfall estimation in Palangkaraya was y = 0.003(CH-MK) 2+0.301(CH-MK) (R2=54.2%) andy = 0.824(CH-MH) (R2=20.8%)for dry and rainy seasons, respectively, while in Pekanbaru was y = 0.867(CH-MK) (R2=26.2%) and y = 0.984(CH-MH) (R2=37.9%)for dry and rainy seasons, respectively. Cross validation results indicate that the model was not consistent between years due to high rainfall variability.
ANALISIS HUBUNGAN KODE-KODE SPBK (SISTEM PERINGKAT BAHAYA KEBAKARAN) DAN HOTSPOT DENGAN KEBAKARAN HUTAN DAN LAHAN DI KALIMANTAN TENGAH Prasasti, Indah; Boer, Rizaldi; Ardiansyah, Muhammad; Buono, Agus; Syaufina, Lailan; Vetrita, Yenni
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 (698.01 KB) | DOI: 10.29244/jpsl.2.2.101

Abstract

Land and forest fire is one of causes ofland degradation in Central Kalimantan. Remote sensing dataapplications, especially READY-ARL NOAA and CMORPH data, are benefit forthe available climate observation data. The objectives of this research are: (1) to analyzis relationship between hotspots, FDRS and occurences of land and forest fire, and (2) to develop the estimation model of burned area from hotspot and FDRS codes. The result of this research showed that burned area can not be estimated by using number of hotspots. The drought code (DC) wich is one of FDRS codes has correlation with burned area. So, burned area can be estimated using drought code (DC) (R-sq = 58%) by using the following formula: Burned Area (Ha) = -62.9 + 5.14 (DC – 500).Keywords: land and forest fire, NOAA, CMORPH, hotspot
APPLICATION OF CMORPH DATA FOR FOREST/LAND FIRE RISK PREDICTION MODEL IN CENTRAL KALIMANTAN Prasasti, Indah; Boer, Rizaldi; Syaufina, Lailan
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 1 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (726.74 KB) | DOI: 10.30536/j.ijreses.2014.v11.a2600

Abstract

Central Kalimantan Province is a region with high level of forest/land fire, especially during dry season. Forest/land fire is a dangerous ecosystem destroyer factor, so it needs to be anticipated and prevented as early as possible. CMORPH rainfall data have good potential to overcome the limitations of rainfall data observation. This research is aimed to obtain relationship model between burned acreage and several variables of rainfall condition, as well as to develop risk prediction model of fire occurrence and burned acreage by using rainfall data. This research utilizes information on burned acreage (Ha) and CMORPH rainfall data. The method applied in this research is statistical analysis (finding correlation and regression of two phases), while risk prediction model is generated from the resulting empirical model from relationship of rainfall variables using Monte Carlo simulation based on stochastic spreadsheet. The result of this study shows that precipitation accumulation for two months prior to fire occurrence (CH2Bl) has correlation with burned acreage, and can be estimated by using following formula (if rainfall ≤ 93 mm): Burnt Acreage (Ha) = 5.13 – 21.7 (CH2bl – 93) (R2 = 67.2%). Forest fire forecasts can be determined by using a precipitation accumulation for two months prior to fire occurrence and Monte Carlo simulation. Efforts to anticipate and address fire risk should be carried out as early as possible, i.e. two months in advance if the probability of fire risk had exceeded the value of 40%.