scholarly journals Penggunaan Citra Satelit untuk Mengetahui Persebaran Dacrycarpus imbricatus (Blume) de Laub. di Bukit Tapak, Cagar Alam Batukahu Bali

2017 ◽  
Vol 11 (2) ◽  
pp. 130
Author(s):  
Rajif Iryadi ◽  
Arief Priyadi ◽  
I Dewa Putu Darma
Keyword(s):  
Satellite Imagery ◽  
Spatial Data ◽  
Satellite Image ◽  
Visual Interpretation ◽  
Site Characteristics ◽  
Natural Reserve ◽  
High Resolution Satellite Imagery ◽  
The One ◽  
Total Accuracy

Citra Pleaides merupakan aset penting untuk memperoleh data dan informasi tentang struktur vegetasi di hutan yang sulit untuk diukur langsung karena wilayah yang tidak dapat diakses dan memiliki cakupan luas. Dacrycarpus imbricatus (Blume) de Laub. merupakan salah satu tanaman khas di Bukit Tapak yang memiliki nilai konservasi dan nilai ekonomi. Penelitian ini bertujuan untuk mengetahui persebaran D. imbricatus menggunakan data citra satelit Pleaides yang memiliki resolusi spasial tinggi. Penelitian dilakukan dengan interpretasi visual pada citra satelit Pleaides tahun 2014 dan data spasial elevasi. Akurasi citra Pleaides dalam identifikasi tutupan D. imbricatus mencapai 96,83% dan ketelitian total pemetaan mencapai 93,38% dengan koefisien kappa 88,64%. Persebaran D. imbricatus di Bukit Tapak memiliki range habitat aktual lebih sempit dibandingkan dengan range potensialnya yakni pada elevasi 1.321-1.800 mdpl dengan persentase tutupan 89,52% dari total tutupannya. Lereng Bukit Tapak dengan kemiringan 25,1-55% memiliki lingkup tutupan D. imbricatus sebesar 79,29% dari total tutupannya dan sisanya pada lereng>25%. Informasi tersebut penting terkait dengan kelestarian dan usaha konservasi salah satu jenis tumbuhan berbiji terbuka ini di Bukit Tapak.Kata kunci: akurasi; interpretasi; kanopi; konservasi; pleaides Usage of Satellite Imagery to Determine Distribution of Dacrycarpus imbricatus (Blume) De Laub. on The Tapak Hill, Batukahu Natural Reserve BaliAbstractPleaides image is an important asset to obtain data and information with regard to the structure of the vegetation in the forest that are difficult to measure directly as the area is inaccessible and has a large coverage. Dacrycarpus imbricatus (Blume) de Laub. is the one of typical plants on the Tapak Hill which has the conservation and economic values. This study aimed to determine the location and distribution of D. imbricatus using Pleaides satellite image that had a high spatial resolution. The determination of site characteristics was conducted by visual interpretation of high resolution satellite imagery Pleiades 2014 and elevation spatial data. Pleaides accuracy in the identification cover of D. imbricatus reached 96.83% and total accuracy mapping reached 93.38% with kappa coefficient of 88.64%. The distribution of D. imbricatus in Tapak Hill showed actual habitat range narrower than of its potential, which was distributed on the elevation of 1,321 – 1,800 m asl with a percentage of 89,52% from its total cover. About 79.29% of the coverage laid on the slope of 25.1 to 55%, whereas the rest on the slope of >25%. This information is important related to sustainability and conservation efforts for this gymnosperm plant in Tapak Hill. 

scholarly journals Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Timothy Shields ◽  
Jessie Pinchoff ◽  
Jailos Lubinda ◽  
Harry Hamapumbu ◽  
Kelly Searle ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Population Distribution ◽  
Satellite Image ◽  
Public Health Research ◽  
Cluster Detection ◽  
Practical Significance ◽  
Programme Implementation ◽  
Detection Analysis ◽  
High Resolution Satellite Imagery

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Post-Disaster Urban Recovery Monitoring in Pisco After the 2007 Peru Earthquake Using Satellite Image

2014 ◽  
Vol 9 (6) ◽  
pp. 1059-1068 ◽  
Author(s):  
Tomoyo Hoshi ◽  
◽  
Osamu Murao ◽  
Kunihiko Yoshino ◽  
Fumio Yamazaki ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Urban Areas ◽  
Satellite Image ◽  
Recovery Process ◽  
Visual Interpretation ◽  
Field Surveys ◽  
Recovery Processes ◽  
The City ◽  
Post Disaster

Pisco was the area most damaged by the 2007 Peru earthquake. The purpose of this research is to develop possibilities of using satellite imagery to monitor postdisaster urban recovery processes, focusing on the urban change in Pisco between 2007 and 2011. To this end, the authors carried out field surveys in the city in 2012 and 2013 and also examined previous surveys to determine that building reconstruction peaked between 2008 and 2009. After analyzing the five-year recovery process, the authors compared its reconstruction conditions by visual interpretation with those by image analysis using satellite image. An accuracy of 71.2% was achieved for the visual interpretation results in congested urban areas, and that for developed districts was about 60%. The result shows that satellite imagery can be a useful tool for monitoring and understanding post-disaster urban recovery processes in the areas in which conducting long-term field survey is difficult.

A Novel Region-Based Approach for Automatic Road Extraction from High Resolution Satellite Images

2013 ◽  
Vol 284-287 ◽  
pp. 2998-3003
Author(s):  
Young Gi Byun
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Image ◽  
Road Surface ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Road Extraction ◽  
High Resolution Satellite Images ◽  
High Resolution Satellite Imagery ◽  
One Class Classification

With the constantly increasing public availability of high resolution satellite imagery, interest in automatic road extraction from this imagery has recently increased. Road extraction from high resolution satellite imagery refers to reliable road surface extraction instead of road line extraction because roads in the imagery mostly correspond to an elongated region with a locally constant spectral signature rather than traditional thin lines. This paper proposes a novel automatic road extraction approach that is based on a combination of image segmentation and one-class classification and consists of two main steps. First, the image is segmented using a modified previous segmentation algorithm to achieve more reliable segmentation for road extraction. The key road objects are then automatically extracted from the segmented image to obtain road training samples. Then one-class classification, based on a support vector data description classifier, is carried out to extract the road surface area from the image. The experimental results from a pan-sharpened KOMPSAT-2 satellite image demonstrate the correctness and efficiency of the proposed method for its application to road extraction from high resolution satellite image.

scholarly journals Change in tropical forest cover of Southeast Asia from 1990 to 2010

2013 ◽  
Vol 10 (8) ◽  
pp. 12625-12653 ◽  
Author(s):  
H.-J. Stibig ◽  
F. Achard ◽  
S. Carboni ◽  
R. Raši ◽  
J. Miettinen
Keyword(s):  
Southeast Asia ◽  
Satellite Imagery ◽  
Forest Cover ◽  
Satellite Image ◽  
Image Interpretation ◽  
Selective Logging ◽  
Automated Classification ◽  
Forest Cover Change ◽  
Forest Change ◽  
The One

Abstract. The study assesses the extent and trends of forest cover in Southeast Asia for the period 1990–2000–2010 and provides an overview on the main drivers of forest cover change. A systematic sample of 418 sites (10 km × 10 km size) located at the one-degree geographical confluence points and covered with satellite imagery of 30 m resolution is used for the assessment. Techniques of image segmentation and automated classification are combined with visual satellite image interpretation and quality control, involving forestry experts from Southeast Asian countries. The accuracy of our results is assessed through an independent consistency assessment, performed from a subsample of 1572 mapping units and resulting in an overall agreement of > 85% for the general differentiation of forest cover vs. non-forest cover. The total forest cover of Southeast Asia is estimated at 268 Mha in 1990, dropping to 236 Mha in 2010, with annual change rates of 1.75 Mha (~0.67% and 1.45 Mha (~0.59%) for the periods 1990–2000 and 2000–2010, respectively. The vast majority of forest cover loss (~2/3 for 2000–2010) occurred in insular Southeast Asia. Combining the change patterns visible from satellite imagery with the output of an expert consultation on the main drivers of forest change highlights the high pressure on the region's remaining forests. The conversion of forest cover to cash crop plantations (e.g. oil palm) is ranked as the dominant driver of forest change in Southeast Asia, followed by selective logging and the establishment of tree plantations.

scholarly journals Analysis of Rice Field Area Conversion in Sleman Regency from 2000 to 2015, Using High-Resolution Satellite Imagery (Case Study: Ngaglik, Mlati and Depok Sub-District)

2019 ◽  
Vol 3 (1) ◽  
pp. 195-203
Author(s):  
Prelin Leunupun ◽  
Frederik Samuel Papilaya
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Rice Field ◽  
Research Area ◽  
Visual Interpretation ◽  
High Resolution Satellite Imagery ◽  
Interpretation Method ◽  
Field Area ◽  
Yogyakarta City

The purpose of this research is to find out how much area of rice fields which is reduced due to being converted into built-up land in Sleman Regency, especially in sub-districts which adjacent to Yogyakarta City, such as Depok Sub-district, Mlati Sub-district and Ngaglik Sub-district, from 2000 to 2015. Classification method used in this research is visual interpretation method which utilized on-screen digitization. The output of this research is a Map of Rice Field Conversion into Built-up Land at Depok, Mlati and Ngaglik Sub-district in Sleman Regency from 2000 to 2015. The results of this research prove that GIS can be used to determine the extent of changes in a rice field at Ngaglik, Depok and Mlati sub-districts. The area of rice field that was converted into built-up land in the research area is 864.45 ha.

scholarly journals INTEGRASI DATA INDERAJA DAN DATA GEOLOGI UNTUK MENDUKUNG EKSPLORASI TAMBANG EMAS, Studi Kasus di Kabupaten Paniai Provinsi Papua

2017 ◽  
Vol 19 (1) ◽  
pp. 75 ◽  
Author(s):  
Iksal Yanuarsyah ◽  
Yatin Suwarno
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Spatial Data ◽  
Satellite Image ◽  
Image Interpretation ◽  
Geological Mapping ◽  
Alteration Zone ◽  
Mineralized Zone ◽  
Landsat Satellite ◽  
Mining Exploration

<p align="center"><strong><span style="text-decoration: underline;">ABSTRAK</span></strong></p><p>Pemetaan potensi sumberdaya geologi pertambangan khususnya potensi mineral perlu dilakukan sebagai awal dalam pengelolaan sumberdaya pertambangan terlebih dalam tahapan eksplorasi pendahuluan. Penginderaan jauh (Inderaja) merupakan alat bantu yang merekam rona lingkungan bumi yang mampu menginterpretasi potensi eksplorasi mineral logam seperti emas. Dengan menggunakan data citra satelit, biaya eksplorasi akan lebih rendah, termasuk efisiensi dalam melakukan pemboran. Tujuan dari studi ini yaitu mampu mendeliniasi Jalur Alterasi dengan interpretasi citra satelit agar untuk mendukung kegiatan eksplorasi tambang lebih efektif dan efisien. Lokasi kajian berada di Distrik Bogobaida, Kabupaten Paniai, Propinsi Papua seluas 40.116 Ha yang merupakan lokasi Izin Usaha Pertambangan (IUP) Eksplorasi PT. Kotabara Mitratama (izin berdasarkan Keputusan Bupati Paniai No. 017 Tahun 2010). Metode yang digunakan dalam kajian ini yaitu metode konseptual dengan memanfaatkan faktor geologi yang berpengaruh pada terbentuknya endapan minera). Tahapan analisa dimulai dari pengumpulan data spasial (peta) dan non spasial (tabular), analisa interpretasi citra Landsat dan identifikasi kelurusan zona lemah (lineament) untuk menentukan zona mineralisasi. Berdasarkan hasil interpretasi citra Landsat dengan didukung analisa geologi untuk daerah IUP PT. Kotabara Mitratama berprospek Tembaga (Cu) dan Emas (Au) yang terbagi dalam 9 Zona Mineralisasi dengan luas mencapai 2.922,48 Ha (yang terdiri dari 8 zona mineralisasi primer seluas 2.208,83 Ha dan 1 zona mineralisasi aluvial seluas 713,65 Ha).</p><p> Kata kunci: data inderaja, data geologi, eksplorasi emas</p><p align="center"> </p><p align="center"> <strong><em>ABSTRACT</em></strong></p><p> <em>Geological mapping of the mineral potential has to be done as the preliminary stages of mining exploration. Remote sensing is a common tool that used to records the earth's environment through image interpretation such for gold mine potential exploration. </em><em>By using satellite imagery data, will be lower exploration costs, including efficiency in drilling</em><em> </em><em>The aim of this study is to delineate alteration zone with satellite image interpretation to support mining exploration activities more effectively and efficiently. The study Located in Bogobaida District, Paniai Regency, Papua Province, covering an area of 40 116 hectares, in site case of Legal Mining Exploration Permit (IUP) PT. Kotabara Mitratama (Paniai Regent Decree No. 017 of 2010). The method used is utilizing conceptual geological factors that alleged the formation of mineral deposits. Stages of analysis starting from spatial data (maps) and non-spatial (tabular) collection, then Landsat satellite imagery interpretation and identification of weak zones straightness (lineament) due to define the mineralized zones. Based on the results of image interpretation with geological analysis in IUP PT. Kotabara Mitratama was prospected Copper (Cu) and gold (Au) which is divided into 9 Mineralization Zone with an area of 2,922.48 ha (consisting of 8 primary mineralized zone covering an area of 2,208.83 ha and 1 alluvial mineralized zone measuring 713.65 ha).</em></p><p> </p><p><em>K</em><em>eywords: Remote sensing, geological data, gold exploration</em></p>

scholarly journals Spatiotemporal Optimization for Short-Term Solar Forecasting Based on Satellite Imagery

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2216
Author(s):  
Myeongchan Oh ◽  
Chang Ki Kim ◽  
Boyoung Kim ◽  
Changyeol Yun ◽  
Yong-Heack Kang ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Spatial Data ◽  
Motion Vector ◽  
Satellite Image ◽  
Skill Score ◽  
Solar Forecasting ◽  
Short Term ◽  
Forecast Horizon ◽  
Forecasting Models ◽  
Optimized Model

Solar forecasting is essential for optimizing the integration of solar photovoltaic energy into a power grid. This study presents solar forecasting models based on satellite imagery. The cloud motion vector (CMV) model is the most popular satellite-image-based solar forecasting model. However, it assumes constant cloud states, and its accuracy is, thus, influenced by changes in local weather characteristics. To overcome this limitation, satellite images are used to provide spatial data for a new spatiotemporal optimized model for solar forecasting. Four satellite-image-based solar forecasting models (a persistence model, CMV, and two proposed models that use clear-sky index change) are evaluated. The error distributions of the models and their spatial characteristics over the test area are analyzed. All models exhibited different performances according to the forecast horizon and location. Spatiotemporal optimization of the best model is then conducted using best-model maps, and our results show that the skill score of the optimized model is 21% better than the previous CMV model. It is, thus, considered to be appropriate for use in short-term forecasting over large areas. The results of this study are expected to promote the use of spatial data in solar forecasting models, which could improve their accuracy and provide various insights for the planning and operation of photovoltaic plants.

Derivation and assessment of vegetation maps for reindeer pasture analysis in Arctic European Russia

Polar Record ◽  
2007 ◽  
Vol 43 (4) ◽  
pp. 290-304 ◽  
Author(s):  
W.G. Rees ◽  
F.S. Danks
Keyword(s):  
Satellite Imagery ◽  
Satellite Image ◽  
Northern Eurasia ◽  
Sufficient Detail ◽  
Routine Basis ◽  
Vegetation Maps ◽  
High Resolution Satellite Imagery ◽  
Circumpolar Arctic ◽  
Satellite Image Analysis ◽  
Land Cover Maps

ABSTRACTThroughout northern Eurasia, the presence of reindeer is a complicating factor in the consideration of interactions between vegetation and climate. The ability to interpret future changes in these interactions will depend on access to maps of sufficient detail to represent aspects of vegetation distribution relevant to reindeer grazing, amongst which we particularly identify lichens and shrubs. Such maps, if they are to have circumpolar coverage, can only feasibly be produced on a routine basis using satellite imagery having wide swaths but comparatively coarse resolution. This paper presents qualitative and quantitative comparisons between three such maps, and two more detailed vegetation maps compiled from fieldwork and from recent field-trained satellite image analysis, all for a study area in the Nenets Autonomous Okrug, Russia. It is shown that, despite its high degree of generalisation, the Circumpolar Arctic Vegetation Map provides the best representation of the vegetation in the study area amongst the three circumpolar land-cover maps that were examined, but that none of the three is entirely satisfactory. While the adequate representation of shrubs and lichens currently continues to depend on the analysis of field data or high-resolution satellite imagery which is unsuitable for circumpolar mapping, it is suggested that the prospects for satellite-based circumpolar vegetation mapping capable of including these components is promising.

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