Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal AGRIVITA, Journal of Agricultural Science Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) MAJALAH ILMIAH GLOBE International Journal of Remote Sensing and Earth Sciences (IJReSES) Makara Journal of Technology Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Sayidah Sulma, Sayidah
Lembaga Penerbangan dan Antariksa Nasional, Jakarta 13710, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
Analysis of Agricultural Drought in East Java Using Vegetation Health Index Amalo, Luisa Febrina; Hidayat, Rahmat; Sulma, Sayidah
AGRIVITA, Journal of Agricultural Science Vol 40, No 1 (2018): FEBRUARY
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v40i1.1080

Abstract

Drought is a natural hazard indicated by the decreasing of rainfall and water storage and impacting agricultural sector. Agricultural drought assessment has been used to monitor agricultural sustainability, particularly in East Java as national agricultural production center. Identification of drought characteristics –correlated with El Niño-Southern Oscillation, and agricultural impact on paddy fields and rice production using VHI (Vegetation Health Index) were conducted. VHI is produced by TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The results showed agricultural drought usually started in June, maximum in October and ended in November. Onset and end time drought tends to follow monsoonal rainfall pattern. El Niño 2015 showed long duration of agricultural drought (i.e. ± 5 months), high severity (i.e. mild-extreme drought; VHI 0-40) and areal extent of drought approx. 197,343 km2, while during La Niña 2010 the areal extent was approx. 28,685 km2 with mild-severe drought (VHI 10-40). Impact of agricultural drought on paddy fields showed wider (smaller) areal extent in sub-round 3 (sub-round 1) from September-December (January-April). Areal extent of drought was negatively correlated with rice production (r=-0.79) which significant in 99 % confidence level.
DETEKSI TUMPAHAN MINYAK MENGGUNAKAN METODE ADAPTIVE THRESHOLD DAN ANALISIS TEKSTUR PADA DATA SAR Sulma, Sayidah; Rahmi, Khalifah Insan Nur; Febrianti, Nur; Sitorus, Jansen
MAJALAH ILMIAH GLOBE Vol 21, No 1 (2019)
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1426.618 KB) | DOI: 10.24895/MIG.2019.21-1.925

Abstract

Metode untuk deteksi tumpahan minyak menggunakan data SAR telah berkembang dari metode manual hingga metode otomatis. Penelitian ini bertujuan untuk membandingkan metode analisis tekstur dan adaptive threshold untuk deteksi tumpahan minyak menggunakan citra SAR Sentinel 1. Wilayah kajian meliputi perairan utara Bintan yang hampir rutin terjadi kasus tumpahan minyak khususnya pada musim barat/utara, serta perairan Teluk Balikpapan yang mengalami kejadian tumpahan minyak yang cukup besar pada akhir Maret 2018. Tahap awal dilakukan koreksi data meliputi koreksi atau kalibrasi radiometrik, filtering dan land masking. Tahap selanjutnya adalah deteksi dark spot yang dilakukan menggunakan dua pendekatan dan dibandingkan metode yang memberikan hasil terbaik. Metode pertama adalah analisis tekstur menggunakan Grey Level co-occurrence matrix (GLCM) dengan perhitungan homogenity, entropi dan Angular Second Moment (ASM), kemudian dilakukan klasifikasi menggunakan Maximum Likelihood, sedangkan pendekatan kedua adalah menggunakan adaptive threshold. Hasil kajian menunjukkan bahwa metode tekstur analisis GLCM dan adaptive threshold pada citra SAR Sentinel 1 memberikan hasil yang cukup baik untuk area tumpahan minyak yang cukup tebal. Namun untuk area tumpahan minyak yang tipis atau pada wilayah pencampuran air, metode adaptive threshold memberikan hasil yang lebih baik. Modifikasi berupa masking kapal (atau objek dengan backscatter tinggi) sebelum diterapkan metode adaptive threshold dapat mengurangi kesalahan seperti terdeteksinya objek minyak di sekitar kapal.
Coastal Physical Vulnerability of Surabaya and Its Surrounding Area to Sea Level Rise Sulma, Sayidah; Kusratmoko, Eko; Saraswati, Ratna
Makara Journal of Technology Vol. 16, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The study for coastal vulnerability to sea level rise was carried out in Surabaya and its surrounding area, it has focused on calculations of the physical vulnerability index were used coastal vulnerability index (CVI) methods. It was standardized by the multi criteria analysis (MCA) approach according to the study area. The score of each physical variable derived from remote sensing satellite data and the results of studies that have been done, such as modeling results and thematic maps, and then integrated into geographic information systems (GIS). Result of this study shows that the coastal areas of Gresik, Surabaya, and Sidoarjo in the very low to very high vulnerability level. Physically, the low land areas with open and slightly open coastal have a high vulnerability category. The high level vulnerability was found located in the northern of Madura Strait (Gresik Regency) that overlooks to the Java Sea is about 28.81% from the entire of study areas. Meanwhile, the moderate, low and very low levels of vulnerability were located on Surabaya and Sidoarjo Regency that have more protected coastal area, relatively. According to the physical condition, the coastal elevation is the most variable that contributes to the high of vulnerability index in the coastal of Surabaya City and Sidoarjo Regency.
DETECTING SURFACE WATER AREAS AS ALTERNATIVE WATER RESOURCE LOCATIONS DURING THE DRY SEASON USING SENTINEL-2 IMAGERY (CASE STUDY: LOWLAND REGION OF BEKASI-KARAWANG, WEST JAVA PROVINCE) Nugroho, Jalu Tejo; Suwarsono, Suwarsono; Chulafak, Galdita Aruba; Julzarika, Atriyon; Manalu, Johannes; Harini, Sri; Suhadha, Argo; Sulma, Sayidah
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.a3626

Abstract

In Indonesia, drought is a type of disaster that often occurs, especially during the dry season. What is most needed at such times is the availability of sufficient water sources to meet shortages. Therefore, water source locations are vital during the dry season in order to meet needs. To meet this information need, remote sensing data offer a precise solution.  This research proposes a rapid method of detecting surface water areas based on remote sensing image data. It focuses on the use of remote sensing satellite imagery to detect objects and the location of surface water sources. The purpose of the study is to rapidly identify objects and locate surface water sources using Sentinel-2 MSI (MultiSpectral Instrument), one of the latest types of remote sensing satellite data. Several water index (WI) methods were applied before deciding which was most suitable for detecting surface water objects. The lowland region of Bekasi-Karawang, a drought prone area, was designated as the research location. The results of the research show that by using Sentinel-2 MSI imagery, MNDWI (Modified Normalized Water Index) is the appropriate parameter to detect surface water areas in the lowland region of Bekasi-Karawang, West Java Province, Indonesia, during times of drought. The method can be employed as an alternative approach based on remote sensing data for the rapid detection of surface water areas as alternative sources of water during the dry season. The existence of natural water sources (swamps, marshes, ponds) that remain during this time can be used as alternative water resources. Further research is still needed which focuses on different geographical conditions and other regions in Indonesia.
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 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.
PENGEMBANGAN METODE PENENTUAN INDEKS LUAS DAUN PADA PENUTUP LAHAN HUTAN DARI DATA SATELIT PENGINDERAAN JAUH SPOT-2 Suwarsono, Suwarsono; Arief, Muchlisin; Hidayat, Hidayat; Sulma, Sayidah; Suryo H, Nanik; Sulyantoro, Heri; Setiawan, Kuncoro Teguh
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 8 No. 1 (2011)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v8i1.3250

Abstract

It is necessary to develop the methods of Leaf Area Index (LAI) estimation based on satellite remote sensing data as first step to study the carbon storage and carbon emission which affect to global climate change. Direct measurements of Leaf Area Index in the field are expensive, take a long time, and so inefficient. The application of remote sensing data may gives an appropriate solution for Leaf Area Index estimation by more efficient and effective. Objective of the research is to develop the method of Leaf Area Index estimation by using remote sensing data. The method of Leaf Area Index estimation will be developed by using the reference method taken from back up algorithm of the Algorithm Theoretical Basis Document (ATBD) MOD15. The research will try to develop the model and applicate it for another remote sensing data, especially those of acquired or distributed by Indonesian National Institute of Aeronautics and Space (LAPAN) such as SPOT-2. Results of the research show that the LAI based on MOD 15 has low correlation with the measured LAI, but the measured LAI has good correlation with NDVI from SPOT-2 for forest area.
DETEKSI DAERAH TERCEMAR LUMPUR ASAM MENGGUNAKAN DATA LANDSAT 7 ETM BERDASARKAN SUHU PERMUKAAN TANAH Sulma, Sayidah; Pasaribu, Junita Monika; Haryani, Nanik Suryo
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 11 No. 2 (2014)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v11i2.3301

Abstract

The high human activity in the mining and industrial areas increases the potency for hazardous and toxic waste pollution. One form of hazardous and toxic waste is acid sludge, a mixture of hydrocarbons and sulfuric acid derived from the disposal of plant wax. This study aims to detect and monitor the acid sludge contaminated area based on the Land Surface Temperature (LST) derived from Landsat 7 ETM multi-temporal data. The steps included data collection, development of LST algorithms for Landsat 7 ETM resulted from regression of Terra-MODIS LSTand Tb of Landsat data, calculation of LST using Landsat 7 ETM multi temporal data and monitoring LST in polluted areas. The distribution of the MODIS LST value can be used as a reference in determining the LST from Landsat 7 ETM by performing linear regression models with a coefficient determination of 0.84. Based on the analysis of LST, the contaminated areas have a higher temperature compare to the uncontaminated area. There is no significant relationship pattern to the land and land recovery process. This may indicate that the recovery process in that area did not significantly affect the temperature.
DETEKSI LIMBAH ACID SLUDGE MENGGUNAKAN METODE RED EDGE BERBASIS DATA PENGINDERAAN JAUH Haryani, Nanik Suryo; Hidayat, Hidayat; Sulma, Sayidah; Pasaribu, Junita Monika
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 11 No. 2 (2014)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v11i2.3303

Abstract

In line with the growing industry and population, the contamination of hazardous and toxic waste material increased. The increases is triggered by inappropriate handling of household and industry sector. The monitoring or detection of contaminated area or zone is very crucial to identify the areas of dispersion of the hazardous waste material. Remote sensing is one of applicable tool for detecting purposes. Several research has utilized remote sensing data to detect the contaminated areas by vegetation index, surface temperature as well as other indexes. This research proposes the red edge method from Landsat TM data to detect the hazardous waste material contamination in Pertamina RU-V Balikpapan. Based on the executed review, it is acknowledged that red edge method has a potential to detect the existence of hazardous and toxic waste, in the case where the acid sludge waste detection is correlated with the land rehabilitation such as neutralization, bioremediation, solidification and non-activation of acid sludge in the contaminated area which can be observed from its spectral displacement. The detection is related to bioremediation implementation and the indication of acid sludge in contaminated area. Based on the executed review, the red edge method is potentially applicable for this activity. The red edge pattern has defined the contaminated area in Pertamina RU-V Balikpapan. Based on the obtained and reviewed data, this research concluded that the monitoring of condition of hazardous waste could be implemented to identify which hazardous waste has been treated.
KLASIFIKASI DAERAH TERCEMAR LIMBAH ACID SLUDGE MENGGUNAKAN METODE SPECTRAL MIXTURE ANALYSIS BERBASIS DATA LANDSAT 8 Haryani, Nanik Suryo; Sulma, Sayidah; Pasaribu, Junita Monika; Fitriana, Hana Listi
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i1.3307

Abstract

The existence waste materials in an area potentially triggers the contamination, and in turns will damages the environment particularly in the vicinity of waste disposal location. This research is aimed to analyze the acid sludge waste contaminated area using the remote sensing satellite Landsat 8. The applied methodology for analyzing the spectral of contaminated area is using spectral mixture analysis method. The result shows that the spectral analysis using this method with spectral reference based on endmember images convey the better output. This is caused by the availability of the SWIR wave length in Landsat 8. The SWIR wave length is sensitive against a highly contaminated substance like as sand and sludge, and contributes to non land contaminated substance like vegetation. Further the index classification based on images endmember shows the result which matching better to the field condition. Based on accuracy review, the result shows the classification accuracy based on this index as 62.5 %.
Co-Authors Amalo, Luisa Febrina Any Zubaidah Atriyon Julzarika Chulafak, Galdita Aruba Eko Kusratmoko Febrianti, Nur Hana Listi Fitriana, Hana Listi Hidayat Hidayat Indah Prasasti, Indah Jalu Tejo Nugroho, Jalu Tejo Johannes Manalu, Johannes Junita Monika Pasaribu Kuncoro Teguh Setiawan, Kuncoro Teguh Muchlisin Arief Nanik Suryo Haryani Rahmat Hidayat Rahmi, Khalifah Insan Nur Rahmi, Khalifah Insan Nur Ratna Saraswati, Ratna Sitorus, Jansen Sri Harini Suhadha, Argo Sulyantoro, Heri Suryo H, Nanik Suwarsono Suwarsono