2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)最新文献_第6页

Space-borne Interferometric SAR for digital elevation model in the tropical region: An initial result of Sentinel-1 RADAR data over the Indonesian archipelago 用于热带地区数字高程模型的星载干涉SAR:印度尼西亚群岛Sentinel-1 RADAR数据的初步结果

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688483

Z. Zylshal, Mega Saputra, A. A. Bayanuddin, S. E. Siwi, Musyarofah, Sartika, A. Setiyoko, R. Arief

{"title":"Space-borne Interferometric SAR for digital elevation model in the tropical region: An initial result of Sentinel-1 RADAR data over the Indonesian archipelago","authors":"Z. Zylshal, Mega Saputra, A. A. Bayanuddin, S. E. Siwi, Musyarofah, Sartika, A. Setiyoko, R. Arief","doi":"10.1109/APSAR52370.2021.9688483","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688483","url":null,"abstract":"Despite the fact that the Sentinel-1 satellites was designed for surface deformation monitoring, researchers have been able to produce digital elevation model (DEM) using repeat-pass Interferometry. It is, however, mostly conducted in the subtropical zone and the temperate zone. Only a couple of publications were found conducted in the tropical region. Highly dense vegetation in tropical region could cause temporal decorrelation when repeat-pass Interferometry is used. However, the vegetation cover, as well as landcover condition, is still varied within this region. Therefore, our main objective is to identify the suitable area for a successful DEM extraction using Sentinel-1 repeat-pass Interferometry in the tropical region. This paper presents our initial results on the repeat-pass Interferometry using Sentinel-1 data Indonesia. Thirty-two (32) interferometric pairs were chosen over two areas of interest (AOI). The pairs were chosen with different temporal and perpendicular baselines. Both AOI is located in South Sulawesi Province, Indonesia. The AOI has different climate conditions. The produced DEMs were visually inspected, and the best results were compared to ICESat-2 and DEMNAS datasets. The Root mean square error (RMSE) was calculated on 5368 sample points. Our initial results show that only AOI_2, with its relatively arid environment, can produce meaningful DEM. Finally, a pair with six days difference and 136-meter perpendicular baseline came out with the best results. Compared to ICESat-2 ATL08 and DEMNAS data, the RMSE produced was 33.92 and 35.13 meters, respectively. Our next task is to maximize the accuracy by tweaking several parameters, as well as identifying the same climatic and/or landcover conditions found on this paper throughout Indonesia and the whole tropical region.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130515788","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

Detection of surface deformation caused by the 2019 Ridgecrest earthquake sequence with ALOS-2 data 利用ALOS-2数据检测2019年山脊地震序列引起的地表变形

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688547

Kento Adachi, M. Omata, Jun Sugimoto, T. Shibayama

{"title":"Detection of surface deformation caused by the 2019 Ridgecrest earthquake sequence with ALOS-2 data","authors":"Kento Adachi, M. Omata, Jun Sugimoto, T. Shibayama","doi":"10.1109/APSAR52370.2021.9688547","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688547","url":null,"abstract":"We identified and interpreted surface deformation associated with the 2019 Ridgecrest earthquake sequence using L-band synthetic aperture radar (SAR) images acquired with the Advanced Land Observing Satellite-2 (ALOS-2). We produced “low coherence interferometric SAR” (LC-InSAR) images which contain differential InSAR (DInSAR) and coherence analysis information. Phase discontinuity lines that indicate surface rupture and displacements were interpreted from those LC-InSAR images. We also conducted pixel offset tracking to measure the offset between pixels of the same area in two different SAR images. By comparing these results, we found that LC-InSAR analysis is an effective method for detecting relatively small surface displacements, and pixel offset tracking is advantageous in that it can show clear boundary and slip direction of the main fault trace. We also compared our mapping of phase discontinuity lines with a previous study results that infer surface fractures with C-band SAR data from Sentinel-1 satellite. ALOS-2 images can detect surface displacements that occurred near the main fault in more detail, whereas Sentinel-1 images can detect smaller displacements that are distributed away from the main fault. Our study suggests that proper combination of LC-InSAR and pixel offset tracking depending on the scale and direction of the displacements is a key to a better understanding of the characteristics of surface deformation. Moreover, SAR data with different wavelength can help us to understand more detailed mapping of surface deformation.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133075789","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

Occurrence of Geothermal Features Based on Surface Roughness and Geobotanical Analyses derived by ALOS-2 PALSAR-2 and Sentinel-2 Images 基于ALOS-2 PALSAR-2和Sentinel-2图像地表粗糙度和地植物学分析的地热特征产状

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688361

A. Saepuloh, Wahyuni Candra Dewi, A. B. Harto, Agustan

{"title":"Occurrence of Geothermal Features Based on Surface Roughness and Geobotanical Analyses derived by ALOS-2 PALSAR-2 and Sentinel-2 Images","authors":"A. Saepuloh, Wahyuni Candra Dewi, A. B. Harto, Agustan","doi":"10.1109/APSAR52370.2021.9688361","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688361","url":null,"abstract":"Geothermal energy as renewable, reliable, and environmentally friendly is one of the most important energy resources. Based on government regulation about the National Energy Policy, the use of geothermal energy must reach 23% by 2025. This regulation is in line with the goal of the 7th of Sustainable Development Goals (SDGs). In order to achieve the government’s targets, a preliminary assessment on a wide scale by minimizing time consumption is necessary. Remote sensing technology utilizing radar and optic sensors promises as an alternative solution for preliminary surveys. The occurrence of geothermal system could be characterized by surface features associated with thermal system near the surface. Geothermal features originated from sub surface hydrothermal fluids to surface through fractures or pores in the rock formations. The chemical composition of the fluid composed by hot and acidic constituent affects the surrounding environment such as host rocks and vegetation. In this study, surface roughness and geobotanical analyses were used as indicator of geothermal features occurrence. The ALOS-2 PALSAR-2 and Sentinel-2 images were selected to calculate surface roughness and geobotanical anomalies including NDVI, GNDVI, SAVI, and RDVI, respectively. Combining ALOS-2 PALSAR-2 and Sentinel-2 images, we could characterize the occurrence of geothermal features by surface roughness more than 17.2 cm and the vegetation index less than 0.2. Accuracy of obtained occurrence map has been calculated about 71.43% with a predicting error rate of 28.57%. The likely prediction zones agreed to the up flow and discharge zones of geothermal system in selected study area.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124112669","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

Performance Analysis of Weight Window STAP for Spaceborne Early Warning Radar 星载预警雷达权重窗口STAP性能分析

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688515

Zihao Zou, Penghui Huang, Xingzhao Liu, Xin Lin, Guozhong Chen, Yanyang Liu

{"title":"Performance Analysis of Weight Window STAP for Spaceborne Early Warning Radar","authors":"Zihao Zou, Penghui Huang, Xingzhao Liu, Xin Lin, Guozhong Chen, Yanyang Liu","doi":"10.1109/APSAR52370.2021.9688515","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688515","url":null,"abstract":"The moving target signal is usually masked in the strong and broadened clutter in a space borne early warning radar system, indicating the necessity of effective clutter suppression processing. To solve the problem of high computational complexity of the space-time adaptive processing (STAP) algorithm, the reduced-dimension STAP algorithm is proposed, which conventionally utilizes the discrete Fourier transform (DFT) to perform the Doppler localization processing. However, the non-synchronous sampling of clutter is unavoidable, leading to the clutter spectral leakage, degrading the clutter suppression performance. In this paper, an extended factored approach with weight window is analyzed, which applies the weight window to suppress the spectral leakage effect. The clutter suppression performances after using different weight windows are analyzed according to the simulated space borne radar data. As a conclusion, the extended factored approach with weight window shows a better clutter suppression performance, and the application of Hann window exhibits the best performance. Finally, the theoretical analyses are verified by the processing results of real-measured airborne radar data.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121259221","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

Regression Neural Network for Soil Moisture Estimation 回归神经网络在土壤水分估算中的应用

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688481

Blaž Pongrac, D. Gleich

引用次数: 2

Bridging Consecutive DInSAR Method for Long Term Land Deformation Observation 长期陆地变形观测的桥接连续DInSAR方法

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688444

J. Sumantyo, D. Perissin, J. Widodo, H. Andreas, K. Wikantika, M. R. Darminto, A. Kurniawan, M. N. Cahyadi, T. Hariyanto

引用次数: 0

Monitoring Vertical Deformations of the Coastal City of Palu After Earthquake 2018 Using Parallel-SBAS 利用平行sbas监测2018年地震后沿海城市帕卢的垂直变形

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688380

A. G. Suhadha, A. Julzarika, M. Ardha, F. Chusnayah

{"title":"Monitoring Vertical Deformations of the Coastal City of Palu After Earthquake 2018 Using Parallel-SBAS","authors":"A. G. Suhadha, A. Julzarika, M. Ardha, F. Chusnayah","doi":"10.1109/APSAR52370.2021.9688380","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688380","url":null,"abstract":"Surface deformation is a phenomenon that can occur both naturally and by human intervention. Remote sensing known can be used to obtain information regarding surface deformation. Various methods have been developed, such as DInSAR, TS-NSAR, SBAS, and PSBAS. The PSBAS method is on the geohazard exploration platform issued by Terradue. This research aims to determine whether the PSBAS method can see the condition of surface deformation after the hammer earthquake in Central Sulawesi in 2018 using a data range from 2019-2021. Research results show that several points after the hammer earthquake experienced subsidence and uplift. The highest subsidence is -3.893 cm, and the highest uplift is 3.935 cm. The accuracy check results show that areas experiencing subsidence correlate with urban areas related to groundwater extraction. In contrast, uplift areas correlate with the uplift location being at the collision zone of the Palu-koro fault facing the Makassar fault. The result proves that PSBAS in Geohazard Exploration Platform cloud computing-based could get information about surface deformation.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130264598","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

Assessment of Sentinel-1 and Sentinel-2 Data for Landslides Identification using Google Earth Engine 利用谷歌Earth Engine对Sentinel-1和Sentinel-2滑坡识别数据的评价

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688356

Ferman Setia Nugroho, P. Danoedoro, S. Arjasakusuma, D. S. Candra, A. A. Bayanuddin, G. Samodra

{"title":"Assessment of Sentinel-1 and Sentinel-2 Data for Landslides Identification using Google Earth Engine","authors":"Ferman Setia Nugroho, P. Danoedoro, S. Arjasakusuma, D. S. Candra, A. A. Bayanuddin, G. Samodra","doi":"10.1109/APSAR52370.2021.9688356","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688356","url":null,"abstract":"Quick and accurate landslide mapping is crucial for emergency response, disaster mitigation, and increasing the understanding of landslide events. Satellite remote sensing data, such as Synthetic Aperture Radar (SAR) and optical imagery, have been used for identifying landslides. SAR data possess several benefits, such as the ability to penetrate the clouds, operate day and night, and regular revisit time. However, processing SAR data require large amounts of data downloaded to the local system to be processed on a local computer. This study explored the SAR-based amplitude change detection approach using multi-temporal and multi-orbit (ascending and descending) Sentinel-1 data to identify landslides utilizing the cloud computing platform of Google Earth Engine (GEE), which aimed to assist in rapid response in mapping and inventorying landslide location data. This study took two case studies in the Lebak Regency, Banten Province, and Masamba Regency, South Sulawesi Province. Additional topographic data was used to filter out the flat areas which were unlikely to suffer from landslides. For comparison, this study also identified landslides using Sentinel-2 supported optical images on the GEE platform. In this study, the overall value of landslide mapping accuracy is 97.66% on Sentinel-2 and 68.75% on Sentinel-1 for the case study in the Lebak Regency, Banten Province. In comparison, the case study in the Masamba Regency, South Sulawesi Province, shows the overall value of landslide mapping accuracy of 96.69% in Sentinel-2 and 87.6% on Sentinel-1. Thus, the benefits of Sentinel-2 over Sentinel-1 are associated with the resulting accuracy. Still, optical-based images have a weakness in quick response efforts because optical images require sunlight and cloud/shadow-free conditions to spot landslides accurately.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134242342","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

Inshore Ship Detection in SAR Images Via an Improved SSD Model with Wavelet Decomposition 基于小波分解改进SSD模型的SAR图像近岸船舶检测

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688344

Tian Miao, Hongcheng Zeng, He Wang, Wei Yang

引用次数: 0

Influence of Earth Rotation on Observation Region Loss for A Multi-static Spaceborne HRWS-SAR Constellations in A Chasing Mode 地球自转对多静态星载HRWS-SAR星座追踪模式下观测区域损失的影响

2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) Pub Date : 2021-11-01 DOI: 10.1109/APSAR52370.2021.9688427

He Huang, Penghui Huang, Xingzhao Liu, Shaoqiang Li, Fengwei Shao, W. Gong

{"title":"Influence of Earth Rotation on Observation Region Loss for A Multi-static Spaceborne HRWS-SAR Constellations in A Chasing Mode","authors":"He Huang, Penghui Huang, Xingzhao Liu, Shaoqiang Li, Fengwei Shao, W. Gong","doi":"10.1109/APSAR52370.2021.9688427","DOIUrl":"https://doi.org/10.1109/APSAR52370.2021.9688427","url":null,"abstract":"In the traditional SAR system, it is difficult to realize both high resolution and wide swath due to the limitation of the minimum antenna area. To deal with this issue, the high-resolution and wide-swath SAR system (HRWS-SAR) is developed, which can be mainly classified into two categories: 1) multichannel HRWS-SAR system (MC-HRWS-SAR) in one satellite and 2) distributed spaceborne HRWS-SAR system (DSHRWS-SAR). Compared with the MCHRWS-SAR system, a DSHRWS-SAR system has higher flexibility and reliability. Unfortunately, in a DSHRWS-SAR system with a large along-track baseline, the differences of Doppler center and equivalent speed may deteriorate the reconstruction performance when the radar echoes recorded by the different satellites are simultaneously used to realize the HRWS-SAR imaging. To solve this problem, the multi-static spaceborne HRWS-SAR constellations in a chasing mode (CMSHRWS-SAR) is applied in this paper, which utilizes the echoes at a different time to achieve the multichannel reconstruction. However, in a CMSHRWS-SAR system, the effective observation scene will be lost due to the earth's rotation. Based on this, in this paper, we discuss the impact of earth rotation in the different satellite orbits, which will provide the system suggestions for the next generation SAR imaging system.","PeriodicalId":104561,"journal":{"name":"2021 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122484561","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