Paddy field classification with MODIS-terra multi-temporal image transformation using phenological approach in Java Island

This paper presents the paddy field classification model using the approach based on periodic plant life cycle events and how these elevations in climate as well as habitat factors, such as elevation. The data used are MODIS-Terra two tiles of H28v09 and H29v09 of 2016, consist of 46 series of 8-daily data, with 500 meter resolution in Java region. The paddy field classification method based on the phenological model is done by Maximum Likelihood on the transformed annual multi-temporal image of the reflectance data, index data, and the combination of reflectance and index data. The results of the study showed that, with the reference of the Paddy Field Map from the Ministry of Agriculture (MoA), the overall accuracies of the paddy field classification results using the combination of reflectance and index data provide the highest (85.4%) among the reflectance data (83.5%) and index data (81.7%). The accuracy levels were varied; these depend on the slope and the types of paddy fields. Paddy fields on the slopes of 0-2% could be well identified by MODIS-Terra data, whereas it was difficult to identify the paddy fields on the slope >2%. Rain-fed lowland paddy field type has a lower user accuracy than irrigated paddy fields. This study also performed correlation (r2) between the analysis results and the statistical data based on district and provincial boundaries were >0.85 and >0.99 respectively. These correlations were much higher than the previous study results, which reached 0.49-0.65 (hilly-flat areas of county-level), and 0.80-0.88 (hilly-flat areas of provincial level) for China, and reached 0.44 for Indonesia

Digital Interpretability of Annual Tile-based Mosaic of Landsat-8 OLI for Time-series Land Cover Analysis in the Central Part of Sumatra

This paper presents an interoperability of annual tile-based mosaic (MTB) images, as well as a verification of the validity of the model for the time series land cover analysis purposes. The primary data used are MTB image of Landsat-8 of the central part of Sumatra, acquired from January 2015 to June 2017. The method used for the interoperability validation is the digital analysis of three-years time series land cover. The classification was performed with four band spectral groups. Training samples are taken from the image of 2016. The results are then reclassified to improve the overall accuracy score based on Jefferies Matusita (JM) distance. The interoperability can be measured by the average of overall accuracy (AOA) score, namely Good (scores > 80%), Fair (70.0% -79.9%), and Bad ( 80% for six and four classes object. Thus the most efficient for interoperability is the use of Bands 6-5 to analyze four class object of land cover.

A Minimum Cloud Cover Mosaic Image Model of the Operational Land Imager Landsat-8 Multitemporal Data using Tile based

The need for remote sensing minimum cloud cover or cloud free mosaic images is now increasing in line with the increased of national development activities based on one map policy. However, the continuity and availability of cloud and haze free remote sensing data for the purpose of monitoring the natural resources are still low. This paper presents a model of medium resolution remote sensing data processing of Landsat-8 uses a new approach called mosaic tile based model (MTB), which is developed from the mosaic pixel based model (MPB) algorithm, to obtain an annual multitemporal mosaic image with minimum cloud cover mosaic imageries. The MTB model is an approach constructed from a set of pixels (called tiles) considering the image quality that is extracted from cloud and haze free areas, vegetation coverage, and open land coverage of multitemporal imageries. The data used in the model are from Landsat-8 Operational Land Imager (OLI) covering 10 scenes area, with 2.5 years recording period from June 2015 to June 2017; covered Riau, West Sumatra and North Sumatra Provinces. The MTB model is examined with tile size of 0.1 degrees (11x11 km2), 0.05 degrees (5.5x5.5 km2), and 0.02 degrees (2.2x2.2 km2). The result of the analysis shows that the smallest tile size 0.02 gives the best result in terms of minimum cloud cover and haze (or named clear area). The comparison of clear area values to cloud cover and haze for three years (2015, 2016 and 2017) for the three mosaic images of MTB are 68.2%, 78.8%, and 86.4%, respectively

Assessing the Reliability of Satellite-Derived Evapotranspiration Data Using Numerical Modified Penman Method at Citarum Watershed

Evapotranspiration is an essential part of water availability analysis and crop water needs that are useful to estimate irrigation water demand. Since discharge measurement stations are limited, the analysis of water availability is the most important part of water management planning. Citarum watershed is the biggest watershed in West Java, supplies raw water to Jakarta, the capital city of Indonesia. Modified Penman is the common equation to analyze evapotranspiration, which was developed by Food and Agriculture Organization (FAO) and modified for tropical areas. Evapotranspiration is one term of the water balance equation. To determine water losses, it is necessary to solve this equation. Another source of evapotranspiration data is provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite's standard product, MOD16A2. In order to used the evapotranspiration satelilite data to fullfill the lack of groud station data, the reliability of satelite data is needed. The objective of this study is to compares and analyzes the reliability of satellite evapotranspiration potential images with the numerical Modified Penman method at Citarum Watershed. Modified Penman is one of several methods that calculate the evapotranspiration potential based on climate data. MOD16A2 was used for simulation data, and Modified Penman was used for baseline data. The reliability of the two simulations was analyzed by the skewness percentage of each pixel and period. The distribution of percent skewness indicates the performance of satellite evapotranspiration on the Modified Penman that represents the actual condition. The sensitivity of satellites is greatly affected by local weather conditions

Remote sensing dan sistem informasi geografis : untuk perencanaan

Vii, 165 hal. : ilus. ; 24 c

Penentuan Ambang Batas Temperatur untuk Pendeteksian Sumber Asap Kebakaran Hutan/Lahan dari Data Landsat-8 (Studi Kasus Wilayah P. Kalimantan pada MusimKemarau 2015)

kebakaran hutan/lahan. Begitu pula pada musim kemarau 2015, terutama pada bulan-bulan Agustus September2015 terjadi kebakaran hutan/lahan yang cukup besar melebihi kejadian di musim kemarau pada tahun-tahunsebelumnya khususnya terjadi di 6 propinsi yakni Kalbar, Kalteng, Kalsel, Riau, Jambi, dan Sumsel. Bahkan beberapapihak mengusulkan agar dinyatakan sebagai bencana Nasional. Selama ini, data penginderaan jauh resolusi rendah telahbanyak digunakan untuk pemantauan terjadinya kebakaran hutan/lahan yakni pendeteksian titik api (hotspot), danpemetaan wilayah terbakar (burnt scar). Pendeteksian hotspot tersebut dilakuan dengan memanfaatkan data NOAAAVHRRdan MODIS yang mempunyai resolusi spasial lebih rendah (1 km). Penelitian penentuan ambang batastemperatur dalam pendeteksian hotspot ini dilakukan menggunakan data Landsat-8 TIRS (Thermal Infrared Sensor)dengan resolusi spasial lebih besar yakni 100 m guna peningkatan kedetilan informasi dan tingkat akurasi. Tujuanpenelitian ini yakni mencari dan menentukan nilai ambang batas temperatur kecerahan (brighness temperature) darisensor TIRS untuk identifikasi adanya sumber asap kebakaran. Data yang digunakan yakni Landsat-8 perekamanLAPAN periode 24 Agustus sampai 18 September 2015 di sebagian wilayah P. Kalimantan. Data Landsat-8 kanal TIRSdikonversi menjadi temperatur kecerahan dalam satuan derajat celsius, selanjutnya titik-titik di wilayah yang dianggapmerupakan sumber asap jika suhu setiap pixel pada wilayah tersebut >43oC, dan diberi atribut dengan suhu paling tinggidari pixel di wilayah tersebut. Kebenaran adanya sumber asap pada area tersebut diperoleh melalui analisis visualkenampakan pada citra multispektral Natural Color Composite (NCC) dan True Color Composite (TCC) . Analisiskesalahan (error comission) diperoleh dengan membandingkan suhu yang terdeteksi oleh kanal TIRS dengankenampakan sumber asap secara visual. Hasil penelitian menunjukkan bahwa dari 27 data Landsat-8 di wilayah P.Kalimantan yang diolah, terdeteksi 9 scene dengan suhu tinggi, yang meliputi 153 lokasi. Ketelian identifikasi untuknilai batas suhu ?51oC adalah 0% (comission error), nilai batas suhu ?47oC adalah 10%( comission error), nilai batassuhu ?43oC adalah 30.5% ( comission error).Hal.755-76

Study of Short Mackerel Cath, Sea Surface Temperature, and Chlorophyll -A in The Makassar Strait

The Makassar Strait is the major fishing ground for Short Mackerel (Rastrelliger spp) fisheries in South Sulawesi, Indonesia using both commercial fishing vessels and boats with traditional fishing gear. Though Short Mackerel is one of dominant commercial food fishes in South Sulawesi, the annual Cath per Unit Effort (CPUE) has been decreasing from year to year. In 2000, the total of annual CPUE was 22,117 tons and in 2007, it was 17,596 tons. The purpose of this research was to forecast the fishing ground of Short Mackerel employing Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images in Makassar Strait territory with the study interest of 3 S and to 5 S and 118 E to 120 E. This research was conductade from September 15 to October 20, 2007. Fishing data were collected from the fishermen including fishing locations, catch, sea surface temperature, and chlorophyll concentrations. To determine the relationship between cacth and oceanographic parameters, linear regression was employed. We also examined sea surface temperature (SST) and Chlorophyll-a concentration field data vs. MODIS satellite data. The result showed that SST andChlorophyll distributions have close relationship with the distribution of fishing location of Short Mackerel. The fishing location tends to spread on the waters with the SST ranged from 26 degree of celcius to 29 degree of celcius and Chlorophyll concentration from 1.19 mg per m to 1.25 mg per m.p.77-84 : ilus. ; 30 c

Food Security Monitoring Using Remote Sensing Data

Food seCurily refers to the everialuthy of food and ono's access to if Remotely sensed environmental conditions play a key rote to food Seaway. The appacabon of remote sensing to food insocurify is relatively mature. Indonesian National lastAtee of Aeronautics and Spaco (LAPAN) as the national provider of remote sensing safenfe data has way important roles to the cRuololknolk related to emnronmental monitoring as well as food Security information in Indonesia. Some apiohcations of remote sensing conducted by LAPAN fo support the information needed for food sootinly policy making have been presented in This paperHlm. 29-3

Interpretability Evaluation of Annual Mosaic Image of MTB Model for Land Cover Changes Analysis

To verify whether the annual mosaic image of MTB model is acceptable for further digital analysis, it is necessary to evaluate the visual interpretability. The MTB model is an effort to integrate multi-scene and multi-temporal data, to obtain a minimum cloud cover mosaic image in locations that are often covered by clouds and haze. This study is to evaluate the interpretability of the annual mosaic image for analysis of the land cover changes. The data used are the images of 2015, 2016, and 2017 covers a part of central Sumatra. Visual interpretations with a series of steps are used, starting with identification of the objects using interpretation keys, followed by spectral band correlations, scattergram analysis, and ended by consistency assessment. The consistency assessment step is performed to determine the level of clearness and easiness of the object recognition in the annual mosaic images. The results showed that the most optimal spectral bands used for RGB combinations for visual interpretation were Band SWIR-1, Band NIR, and Band Red. Based on the evaluation results, the annual mosaic image of MTB model performed the consistent results of the clearness objects and the easiness of the object recognition. Thus the annual mosaic image of MTB model of 0.02x0.02 degree tile is acceptable for further digital processing as well as digital land cover analysis

Tsunami Effect in Nanggroe Aceh Darussalam and North Sumatra Provinces, Indonesia

In relation to identifying the destructed area in Nanggroe Aceh Darusslam (NAD) and North Sumatra, as the result of quake and Tsunami on 26 December 2004, LAPAN - the National Institute of Aeronautics and Space of Indonesia - and other institutions in Indonesia, such as Indonesian Soil Research Institute (ISORI), and Agency for Assessment and Application of Technology (BPPT), have conducted damage assessment of affected area. Remote sensing data, field observation, and CS techniques have been combined to identify the destructed area. Visual interpretation of Landsat TM and IKONOS and simulation using DEM has been exercised for the activities. The result shows that a total length of coastline corridors destructed by tsunami in NAD and North Sumatra is about 600 km to at least 1 km inland. Total area destructed is 120,295 ha, 21.5 % of which is settlement and 272% is agricultural lands with various level of damages and several types of causes. Field observation indicated that a dense coconut trees or. and palm oil trees corridor of 100-200 m width is the potential of vegetation belts to reduce devastating effect of tsunami occurred along coastline.Hlm. 1-1