2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)最新文献_第2页

Seasonal Analysis of the Hotspot Spatial Grid in Indonesia and the Relationship of the Hotspot Grid with the Nino SST Indices 印度尼西亚热点空间网格的季节分析及热点网格与Nino海温指数的关系

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452775

I. Dewa Gede Arya Putra, E. Heriyanto, A. Sopaheluwakan, R. P. Pradana, D. Nuryanto

{"title":"Seasonal Analysis of the Hotspot Spatial Grid in Indonesia and the Relationship of the Hotspot Grid with the Nino SST Indices","authors":"I. Dewa Gede Arya Putra, E. Heriyanto, A. Sopaheluwakan, R. P. Pradana, D. Nuryanto","doi":"10.1109/AGERS51788.2020.9452775","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452775","url":null,"abstract":"Forest fires have caused significant economic losses and environmental damage. The phenomenon of Nino variability in the Pacific region has affected the occurrence of forest fires in Indonesia. The hotspot data gridding in this study aims to change the host data format to make it more universal with other geodata, most of which are already in the grid matrix format in the NetCDF data format to facilitate the need for spatial and temporal analysis and interpretation. The method in this analysis is to add up the daily hotspots with a hotspot confidence level above 80% in a grid area with a spatial resolution of 25 km2 per month, then create a time series from 2001 to 2019 with the research domain of all parts of Indonesia. Based on gridding data, the spatial distribution of the number of dominant hotspots over 100 hotspots occurs during the JJA and SON seasons in Jambi, South Sumatra, West Kalimantan, Central Kalimantan, South Kalimantan, and East Kalimantan. Based on the spatial correlation of hotspots with Nino 1.2, Nino 3, Nino 3.4, and Nino 4, there is a positive correlation with coefficient values ranging from 0.1 to 0.4 for almost all parts of Indonesia except northern Sumatra which is negatively correlated around -0.1.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115190814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Effect of Resnet Model as Feature Extractor Network to Performance of DeepLabV3 Model for Semantic Satellite Image Segmentation Resnet模型作为特征提取网络对DeepLabV3模型语义卫星图像分割性能的影响

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452768

Y. Heryadi, E. Irwansyah, Eka Miranda, Haryono Soeparno, Herlawati, Kiyota Hashimoto

{"title":"The Effect of Resnet Model as Feature Extractor Network to Performance of DeepLabV3 Model for Semantic Satellite Image Segmentation","authors":"Y. Heryadi, E. Irwansyah, Eka Miranda, Haryono Soeparno, Herlawati, Kiyota Hashimoto","doi":"10.1109/AGERS51788.2020.9452768","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452768","url":null,"abstract":"Semantic image segmentation is an interesting problem in Computer Vision with many potential applications. The DeepLab model is combined with two other networks: Resnet and Conditional Random Field networks, making the DeepLab model a fairly deep network structure to increase semantic segmentation performance. Many previous studies argued that there are some limits on the deep learning model's depth as the deep structure may lead to vanishing/exploding gradient, which the model's performance. This paper presents an experimental study to compare the effect of several ImageNet pre-trained Resnet variant models with different network layers used as feature extractor in DeepLab model to solve semantic image segmentation task. In this study, three Resnet34, Resnet50, and Resnet101 models as network extractor of DeepLabV3were explored. The experiment found that semantic image segmentation model performance measured by the best accuracy and average accuracies of DeepLabV3- Resnet34, DeepLabV3-Resnet50, and DeepLabV3-Resnet101 are (0.87, 0.86) (0.86, 0.84), and (0.92, 0.88) respectively. Based on the experiment, DeepLabV3-Resnet101 achieved the best semantic segmentation performance than the other models","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123790626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Determination of Tidal Components and Tidal Types Using Harmonic Analysis in the West Sumatera Waters 用调和分析测定西苏门答腊水域潮汐成分和潮汐类型

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452788

S. Koesuma, Riza Vina Chrismiantari

{"title":"Determination of Tidal Components and Tidal Types Using Harmonic Analysis in the West Sumatera Waters","authors":"S. Koesuma, Riza Vina Chrismiantari","doi":"10.1109/AGERS51788.2020.9452788","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452788","url":null,"abstract":"The tidal of the sea is a phenomenon of rising and falling sea levels periodically caused by the influence of gravity from celestial objects, especially the moon and sun. The purpose of this research is to determine the tidal type in West Sumatra Water, especially in Sabang, Sibolga, and Padang cities. Tidal type can be used as a reference for the port to determine when the ship can go in or out of the port. We used satellite altimetry and tide gauge data. Tidal types in the West Sumatra Waters are influenced by the characteristics of tides in the Andaman Sea and the Indian Ocean. Determining the tidal type required the Formzahl number obtained from the comparison of tidal constants using harmonic analysis. We obtained that the West Sumatra Waters has semidiurnal tidal types with a Formzahl number 0.2013 at Sabang station and has a mixed tidal type (semidiurnal dominant) at Padang and Sibolga stations with Formzahl number values of 0.4306 and 0.4893, respectively. We found 9 tidal components with different amplitudes and phase angles in each component and each station. The tidal components obtained are Z0, M2, S2, K2, K1, 01, P1, M4, and MS4.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117128923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cloud Spectral Characteristics Prior To Convective Initiation Event Based on Himawari-8 Satellite Around Surabaya 基于Himawari-8卫星在泗水附近对流起始事件前的云谱特征

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452758

Ilham Fajar Putra Perdana, D. Septiadi

{"title":"Cloud Spectral Characteristics Prior To Convective Initiation Event Based on Himawari-8 Satellite Around Surabaya","authors":"Ilham Fajar Putra Perdana, D. Septiadi","doi":"10.1109/AGERS51788.2020.9452758","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452758","url":null,"abstract":"Geostationary satellite-based heavy rain prediction algorithm called convective initiation (CI) nowcasting recently becomes a solution in providing an earlier heavy rain forecast. However, this algorithm depends on the threshold value of the interest fields to predict whether a cloud object could potentially produce heavy rain, so it is important to understand the cloud physical characteristics in a particular area if the CI nowcasting algorithm is going to be developed. This research aims to assess the cloud spectral characteristics based on twelve interest fields of Satellite Convection Analysis and Tracking (SATCAST), one of the promising CI nowcasting algorithms, in Surabaya during the June-July-August period in 2018. Six bands of Himawari-8 and Surabaya weather radar data are used to quantify the cloud object spectral characteristics and determine the CI event, respectively. Four main processes conducted in this research include CI detection, cloud masking, backward cloud object tracking, and cloud spectral evaluation. The results show that 4 of 12 interest fields depict a significant change since 30–60 minutes before the CI event with $mathbf{T}_{mathbf{b11.2}}$ as the most significant interest field. Meanwhile, five interest fields tend to be constant until a significant change has reached 10 minutes before the CI event.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131652038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Use of Cloud Computing with Crowd Participation to Have an Alternative National Mangrove Map 使用云计算与人群参与，有一个替代性的国家红树林地图

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452756

H. Sanjaya, Zilda Dona Okta Permata, R. Amaliyah, Ela Nurdianti

引用次数: 1

Radiometric Enhancement of Landsat 8 OLI Imagery Using Coastal/Aerosol Band 海岸带/气溶胶波段对Landsat 8 OLI影像的辐射增强

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452778

Syam’ani

{"title":"Radiometric Enhancement of Landsat 8 OLI Imagery Using Coastal/Aerosol Band","authors":"Syam’ani","doi":"10.1109/AGERS51788.2020.9452778","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452778","url":null,"abstract":"The presence of atmospheric particles in multispectral imageries such as Landsat 8 OLI can reduce the visual acuity of the imageries. The most ideal method to reduce the existence of atmospheric particles in the imagery, as well as to enhance the visual appearance of the imagery, is to employ atmospheric corrections. However, atmospheric corrections are a very complex process. Besides, sometimes the results don't have an impact visually. There are many other methods to enhance imagery radiometrically, either by stretching the pixel value, shifting the histogram, or reducing the presence of clouds. This research aims to develop practical formulations to enhance the spectral value of the Landsat 8 OLI imagery bands, by reducing the presence of aerosol particles using the C/A band. Several regression models were involved in the construction process of these formulations. The accuracy assessment was performed using the Pearson correlation coefficient and RMSE, using the USGS Landsat 8 OLI TOC imagery as a comparison. The results showed that the radiometric imagery enhancement using the C/A band gave satisfactory results. Apart from providing a significant visual sharpness increase, for the exponential model with parameters, the average Pearson correlation coefficient is 0.96, with an RMSE value of 0.04, relative to the USGS Landsat 8 OLI TOC product. For a more practical model, we can omit the parameters in the exponential model. The results that will be obtained are still quite accurate. Furthermore, we can implement this enhancement model directly on digital numbers.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115294533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of near real-time and archival Tsunami data visualization dashboard for Indonesia 印度尼西亚近实时和存档海啸数据可视化仪表板的开发

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452771

J. Matondang, L. Sumargana, Yudi Adityawarman, R. M. Taufik Yuniantoro

引用次数: 2

Analysis of Fishing with Led Lights in and around MPA and No Take Zones at Natuna Indonesia through VMS and VIIRS Data 利用VMS和VIIRS数据分析印尼纳土纳群岛海洋保护区和禁渔区及其周围的Led灯捕鱼

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452785

R. van Beek, J. Lumban-Gaol, Syamsul Bahri Agus

{"title":"Analysis of Fishing with Led Lights in and around MPA and No Take Zones at Natuna Indonesia through VMS and VIIRS Data","authors":"R. van Beek, J. Lumban-Gaol, Syamsul Bahri Agus","doi":"10.1109/AGERS51788.2020.9452785","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452785","url":null,"abstract":"Protected Areas (MPA) and No Take Zones are an effective tool for marine ecosystem preservation. Indonesia requires fishing vessels larger than 30 gross tons to use a Vessel Monitoring System (VMS). Another way to detect fisheries is through Visible Infrared Radiometer Suite (VIIRS) data. To compare VMS and VIIRS data, an R package, “LLFI” (Led Light Fisheries Identifier) was created. This package provides several R-functions that can calculate the location of VMS using vessels at the overpass time of the VIIRS satellite. An MPA near the Natuna archipelago was chosen as the research area. VMS and VIIRS data for the entire year of 2018 were obtained for this Region of Interest. The R function “vms2viirs” calculated activity for small purse seine fisheries all through the ROI and for bouke ami fisheries in the southwestern part of the ROI. The R Function “vms2viirsanalysis” created three buffers around detected fishing vessels by the VIIRS satellite and linked the closest found vessels from the VMS dataset. The amount of identified vessels for Class C was significantly higher than those for class A and B. Approximately 10% of all detected led lights could be identified with a shipping number from the VMS data set. Only around 8% of identified vessels could be found inside MPA and around 3% could be found in a No Take Zone. Paths of identified vessels that some vessels did cross MPA's and No Take Zones. It can be concluded that the LLFI package is working successfully.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123139577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing landslide susceptibility using ANN and ANFIS to forecast landslides in Sumatera Indonesia 利用人工神经网络和ANFIS对印尼苏门答腊滑坡易感性进行评估

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452781

G. P. Dinanta, D. Cassidy, J. Octariady, D. Fernando, M. Yusuf

引用次数: 2

Data Interoperability and Repository for Oceanography Research 海洋学研究的数据互操作性与存储库

2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2020-12-07 DOI: 10.1109/AGERS51788.2020.9452755

R. M. Taufik Yuniantoro, Yudi Adityawarman, M. Frederik, A. Eugenie, Agits Agnia Fidzly Almatin, Irham Farhan Herdiardi, Fauzan Muhajir, Imas Muliatie, Sumirah Said

{"title":"Data Interoperability and Repository for Oceanography Research","authors":"R. M. Taufik Yuniantoro, Yudi Adityawarman, M. Frederik, A. Eugenie, Agits Agnia Fidzly Almatin, Irham Farhan Herdiardi, Fauzan Muhajir, Imas Muliatie, Sumirah Said","doi":"10.1109/AGERS51788.2020.9452755","DOIUrl":"https://doi.org/10.1109/AGERS51788.2020.9452755","url":null,"abstract":"Large amount of oceanic data have been acquired over Indonesian waters by various institutions over the years. These collections are normally stored in the multiple institutions' archives, resulting in scattered storages. Indonesian National Oceanographic Data Center (InaNODC) aims to integrate these data collections using a portal that enables integrated access that allows data exchange between different formats for interoperability. InaNODC integrates data collections from Konsorsium Riset Samudera (KRS) - a collection of government institutions that conduct ocean research and operate research vessels. In this paper, we present the flow process of accessing data collection using CTD data from the Arafura Sea as an example of one of the data types stored in InaNODC. This shows the capability of InaNODC to do a query, extract, and display the intended data. In the future, InaNODC is designed to be a part of IODE-UNESCO as one of the oceanographic and marine data centers in compliance with international standards.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116873257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1