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CYGNSS GNSS-R Data for Inundation Monitoring in the Brazilian Pantanal Wetland 巴西潘塔纳尔湿地淹没监测的CYGNSS GNSS-R数据
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883409
Paulo T. Setti, S. Tabibi, T. Dam
{"title":"CYGNSS GNSS-R Data for Inundation Monitoring in the Brazilian Pantanal Wetland","authors":"Paulo T. Setti, S. Tabibi, T. Dam","doi":"10.1109/IGARSS46834.2022.9883409","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883409","url":null,"abstract":"Global Navigation Satellite System Reflectometry (GNSS-R) that uses signals of opportunity in L-band microwave frequency is an optimal system for Earth surface remote sensing. Spaceborne GNSS-R is a very promising bistatic radar system to detect, estimate and monitor inundation extents as it collects GNSS reflections in a good spatiotemporal resolution and is not affected by clouds and, to some extent, aboveground vegetation. In this contribution, we propose a new method to estimate the inundation extent of the Brazilian Pantanal wetland using three years (Aug. 2018 - Jul. 2021) of data from NASA Cyclone GNSS (CYGNSS) mission. The proposed method is independent in variations of the transmitted signal power and angle of incidence as the inundation extent is estimated track by track. We find very good agreement between the GNSS-R inundation extent retrievals and those derived from different remote sensing techniques with a correlation of 0.92.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123238306","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: 3
Subsurface Cavities Characterization from X-Band VHR Spaceborne SAR Images 基于x波段VHR星载SAR图像的地下空腔表征
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884672
L. Carrer, Davide Castelletti, R. Pozzobon, F. Sauro, L. Bruzzone
{"title":"Subsurface Cavities Characterization from X-Band VHR Spaceborne SAR Images","authors":"L. Carrer, Davide Castelletti, R. Pozzobon, F. Sauro, L. Bruzzone","doi":"10.1109/IGARSS46834.2022.9884672","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884672","url":null,"abstract":"Cave systems are one of the last frontiers of human exploration on both Earth and other celestial bodies. In this context, lava tubes are natural subsurface tunnels, which are not visible from the surface, that are ubiquitous on Earth as well as on the Moon and Mars. Skylights are one of the surface evidences of the presence of such conduits in the form of overhanging collapses of the cave ceiling, making these cavities partially observable and potentially accessible. In this paper, we propose a method for imaging and characterizing subsurface structures by spaceborne VHR SAR imaging. We performed several acquisitions over different Earth locations by exploiting Capella's X-band VHR SAR imaging radars in spotlight mode. The obtained results show that the proposed methodology is able to characterize the main geometric parameters of the first section of a lava tube (e.g. width, height) in the surroundings of a skylight and it provides an indication of the actual subsurface accessibility. The proposed methodology has several important implications for exploration and could be applied to different type of cavities other than lava tubes.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123397105","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
The Potential of Using Dynamic Surface Water Products for Drought Monitoring 利用动态地表水产品进行干旱监测的潜力
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884112
Xuqian Xiong, Jie Zhou, Xuan Liu, Yilin Cui
{"title":"The Potential of Using Dynamic Surface Water Products for Drought Monitoring","authors":"Xuqian Xiong, Jie Zhou, Xuan Liu, Yilin Cui","doi":"10.1109/IGARSS46834.2022.9884112","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884112","url":null,"abstract":"Surface water presence on the earth is highly variable, closely coupled to regional hydro-climatological conditions. Meanwhile, the rapid increase of earth observation-based global surface water datasets provides valuable opportunities for evaluating interannual or seasonal surface water dynamics. This study investigated the potential of using long-term EO-based surface water products for regional drought monitoring. In particular, the dynamic of surface water over the middle reach of the Yangtze River from 1999 to 2020 was analyzed based on the GLAD product. Furthermore, we explored the linkage between surface water anomalies (i.e., Dynamic Water Index, DWI) and Standardized Precipitation Index (measured by SPI). The preliminary results showed that: (1) DWI was significantly coupled to 12-month SPI, which confirmed that dynamic surface water extent can be used as an indicator for hydrological drought; (2) The correlation between DWI and SPI (1-month, 3-month, 6-month, 12-month) in extreme wet climate was lower than in extreme drought climate; (3) It is challengeable to distinguish the difference in coupling strength between dynamic surface water and hydrological drought caused by DWI defined with different water types (i.e., all types versus seasonal water). Much more attention should be paid to evaluating the uncertainty of the new index caused by missing values across regions.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123541681","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
International Geoscience and Remote Sensing Symposium Proceedings 国际地球科学与遥感研讨会论文集
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/igarss46834.2022.9883887
{"title":"International Geoscience and Remote Sensing Symposium Proceedings","authors":"","doi":"10.1109/igarss46834.2022.9883887","DOIUrl":"https://doi.org/10.1109/igarss46834.2022.9883887","url":null,"abstract":"","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123553438","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: 4
Deriving Drought Vulnerability Index using Geographically Weighted Principal Component Analysis (GWPCA) and K-Means Clustering for Nile Basin 基于地理加权主成分分析和k -均值聚类的尼罗河流域干旱易损性指数
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883425
S. Perera, M. Allali, Erik J. Linstead, H. El-Askary
{"title":"Deriving Drought Vulnerability Index using Geographically Weighted Principal Component Analysis (GWPCA) and K-Means Clustering for Nile Basin","authors":"S. Perera, M. Allali, Erik J. Linstead, H. El-Askary","doi":"10.1109/IGARSS46834.2022.9883425","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883425","url":null,"abstract":"Climate impacts are particularly noticeable for the nations that share the Nile basin with an increase in hotter temperatures and fluctuating precipitation which expands natural catastrophes. Provincial work is required to precisely predict floods and dry seasons, thus preparing, and adapting to climatic events to build climate resilience among these Nile basin nations. In this context, an index indicating vulnerability to drought is derived for the Nile basin using Geographically Weighted Principal Component Analysis (GWPCA) and K-means clustering. Several climate indicators images related to atmosphere, land, and ocean are collected to build clusters categorized as high, mild, and low drought risk. Additionally, STL decomposition is conducted for the Palmer Drought Severity Index (PDSI) using time series data from 2010–2020 for the Nile basin to identify exceptional drought events for the past decade. Furthermore, correlations among PDSI and other climate indicators are analyzed using time series.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125314139","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
Automatic Methane Plume Quantification Using Sentinel-2 Time Series 利用Sentinel-2时间序列自动量化甲烷羽流
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884134
T. Ehret, A. D. Truchis, M. Mazzolini, J. Morel, G. Facciolo
{"title":"Automatic Methane Plume Quantification Using Sentinel-2 Time Series","authors":"T. Ehret, A. D. Truchis, M. Mazzolini, J. Morel, G. Facciolo","doi":"10.1109/IGARSS46834.2022.9884134","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884134","url":null,"abstract":"Methane emissions monitoring is essential to control methane pollution. In this paper, we propose an automatic practical methodology using time series to estimate the quantity of methane in a given plume using a multispectral satellite like Sentinel-2. Sentinel-2 proposes a low revisit time, a good spatial resolution and a low acquisition cost. Contrary to previous methods, the proposed approach does not require a manual selection of an optimal reference image. We compared its performance on an oil-and-gas site in Kazakhstan. This is the first step toward an automatic global monitoring system for methane plume detection and quantification with these satellites.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125673121","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
Permafrost Stability and Land Surface Temperature Distribution Study Using Multi-Source Remote Sensing Data in the Qinghai-Tibet Plateau 基于多源遥感数据的青藏高原冻土稳定性与地表温度分布研究
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884765
P. Zhang, Yuanchun Chen, Yunping Chen
{"title":"Permafrost Stability and Land Surface Temperature Distribution Study Using Multi-Source Remote Sensing Data in the Qinghai-Tibet Plateau","authors":"P. Zhang, Yuanchun Chen, Yunping Chen","doi":"10.1109/IGARSS46834.2022.9884765","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884765","url":null,"abstract":"This paper discusses the temperature factors leading to permafrost instability, and explains the causes of permafrost instability from the perspective of land surface temperature (LST). First, the land surface deformation of the typical permafrost area in some period is extracted by the using the dual-track differential interferometry (D-InSAR) technique with Sentinel-1A single look complex(SLC) data. Next, the annual average LST and LST range are calculated using the spatio-temporal interpolation algorithm for MYD11A2 products. Comparing the distribution of land surface deformation and LST, findings show that permafrost regions with lower average annual LST and larger annual temperature range are more unstable and more prone to surface deformation. This research can contribute to unveiling the process where LST affects the freezing and thawing of permafrost.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125674987","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
Fast Majorize-Minimization based Super-Resolution Algorithm for Radar Forward-Looking Imaging 基于快速最大最小化的雷达前视成像超分辨率算法
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883171
Xichen Yin, Lin Liu, Yulin Huang, Mengxi Feng, Yin Zhang, Jianyu Yang
{"title":"Fast Majorize-Minimization based Super-Resolution Algorithm for Radar Forward-Looking Imaging","authors":"Xichen Yin, Lin Liu, Yulin Huang, Mengxi Feng, Yin Zhang, Jianyu Yang","doi":"10.1109/IGARSS46834.2022.9883171","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883171","url":null,"abstract":"Recently, super-resolution techniques have been widely used in real aperture radar superresolution imaging. In this paper, we propose a fast sparse superresolution algorithm which is based on majorize-minimization(MM) method to realize fast superresolution imaging of sparse targets in radar forward-looking area. First, we establish a model of rader forward-looking imaging and analyze the echo signal. Second, we use the majorize-minimization (MM) method to obtain the real target distribution. Due to the expensive computational cost of MM algorithm, we proposed an fast matrix inversion approach which is based on divide and conquer strategy. The superior performance of the proposed method is verified by simulations.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126615233","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
Constant-Time-Delay Interferences in Near-Field SAR: Analysis and Suppression in Image Domain 近场SAR中的等时延干扰:图像域分析与抑制
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884332
Xu Zhan, Xiaoling Zhang, Jun Shi, Shunjun Wei
{"title":"Constant-Time-Delay Interferences in Near-Field SAR: Analysis and Suppression in Image Domain","authors":"Xu Zhan, Xiaoling Zhang, Jun Shi, Shunjun Wei","doi":"10.1109/IGARSS46834.2022.9884332","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884332","url":null,"abstract":"Inevitable interferences exist for the SAR system, adversely affecting the imaging quality. However, current analysis and suppression methods mainly focus on the far-field situation. Due to different sources and characteristics of interferences, they are not applicable in the near field. To bridge this gap, in the first time, analysis and the suppression method of interferences in near-field SAR are presented in this work. We find that echoes from both the nadir points and the antenna coupling are the main causes, which have the constant-time-delay feature. To characterize this, we further establish an analytical model. It reveals that their patterns in 1D, 2D and 3D imaging results are all comb-like, while those of targets are point-like. Utilizing these features, a suppression method in image domain is proposed based on low-rank reconstruction. Measured data are used to validate the correctness of our analysis and the effectiveness of the suppression method.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126704885","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: 4
Multiple-Platform/Sensor Real-Time Sounding and Cloud Retrieval Through Community Satellite Processing Package (CSPP) 基于社区卫星处理包(CSPP)的多平台/传感器实时探测和云检索
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883825
A. Huang, M. Goldberg
{"title":"Multiple-Platform/Sensor Real-Time Sounding and Cloud Retrieval Through Community Satellite Processing Package (CSPP)","authors":"A. Huang, M. Goldberg","doi":"10.1109/IGARSS46834.2022.9883825","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883825","url":null,"abstract":"The Community Satellite Processing Package (CSPP) was developed in 2011 with its first release in 2012 (http://cimss.ssec.wisc.edu/cspp/history.shtml). Since then, as of January 2022, over 70 new and updated releases of software packages to process the satellite direct broadcast raw data into sensor data records (SDRs) and produce various Environmental Data Records (EDRs). CSPP supports the Direct Broadcast (DB) meteorological and environmental satellite community through the packaging and distribution of open-source science software when possible. CSPP supports DB users of both polar-orbiting and geostationary satellite data processing and regional real-time applications through the distribution of free open source software and training in local product applications. So far comprehensive multiple sensors (A VHRR, MODIS, AIRS, AMSU, VIIRS, CrIS, ATMS, IASI, MHS, ABI, and AHI) onboard multiple international satellite platforms (NOAA-17, NOAA-20, S-NPP, Terra, Aqua, METOP-A/B, GOES 16/17, and Himawari-8) are making global visible, infrared, and microwave imaging and sounding spectral measurements and producing environment products (composite color images, cloud property, aerosol, dust, fire, flood, drought, temperature/water vapor profile, total precipitable water, precipitation, trace gases, ocean/land surface property, and many others).","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"BC-31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126720376","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
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