IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium最新文献_第3页

Satellite-Scale Soil Surface Roughness Retrieval in the US Corn Belt 美国玉米带卫星尺度土壤表面粗糙度反演

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883654

Victoria A. Walker, M. Cosh, B. Hornbuckle

引用次数: 0

A Novel SAR Sidelobe Suppression Method based on Approximate Greatest Common Divisors 一种基于近似最大公因数的SAR旁瓣抑制方法

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884022

Yanfang Liu, Fei Zou, Wei Yang, Hongcheng Zeng, Chunsheng Li

引用次数: 0

Improving Streamflow Simulation in Mountainous Regions Using Multi-Sources Snow Remote Sensing Data 利用多源积雪遥感数据改进山区径流模拟

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884619

Yuhui Wu, Hui Lu

{"title":"Improving Streamflow Simulation in Mountainous Regions Using Multi-Sources Snow Remote Sensing Data","authors":"Yuhui Wu, Hui Lu","doi":"10.1109/IGARSS46834.2022.9884619","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884619","url":null,"abstract":"Snow is one of the most significant essential climate variables in global climate change study, and snowmelt accounts for a large part of the streamflow in mountainous regions on the Tibetan Plateau. However, previously researchers often calculate snow water equivalent using precipitation data, which is more unreliable in solid precipitation. This study is designed to combine a hydrological model and snow remote sensing data to improve the streamflow simulation in Lhasa river basin. Firstly, this study proposes a method to produce a set of snow cover maps with high temporal and spatial resolution from multiple satellite imagery (MODIS, Landsat, and Sentinel-1. Secondly, by comparing with this snow cover product, we evaluated the capability of a Geomorphology-Based Hydrological Model (GBHM) on snow cover simulation. Third, by margining the remotely sensed snow cover maps into the GBHM, the improvement of spring streamflow simulation was validated against in situ gauge observation. Finally, the GBHM simulated snow water equivalent (SWE), which was constrained by the water balance, was employed to assess the performance of SWE products in this basin. This study provide a method to estimate streamflow reliably in snow-covered mountainous regions, as well as to evaluate SWE at basin scale.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"36 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":"124944272","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

Back-Projection Tomography with Polarimetric HoloSAR data and Sub-aperture Processing 偏振HoloSAR数据的反投影层析成像和子孔径处理

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883942

E. M. Domínguez, D. Small, D. Henke

引用次数: 0

Analysis of Intensity Errors in OAM Beam via Interval Arithmetic 区间算法分析OAM波束强度误差

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884394

Chunlin Wu, Hu Tang, Y. Liao

引用次数: 0

Development of a Commercial-Off-the-Shelf Imaging Payload with Onboard Image Classification and Processing 具有机载图像分类和处理的商用现成成像有效载荷的开发

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884595

S. Oktaviani, I. H. Saugi, Aipujana T. Santaso, Edwar, F. A. Hidayat, Muhammad Alif P. Dafi, S. G. Muzhaffar, Maulana Muhammad Aziz, L. K. Fitriyanti, Mark Angelo C. Purio, Yasir M. O. Abbas, T. Leong

引用次数: 1

Dual Spatial Weighted Sparse Hyperspectral Unmixing 双空间加权稀疏高光谱分解

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883616

Yonggang Chen, Chengzhi Deng, Shaoquan Zhang, Fan Li, Ningyuan Zhang, Shengqian Wang

{"title":"Dual Spatial Weighted Sparse Hyperspectral Unmixing","authors":"Yonggang Chen, Chengzhi Deng, Shaoquan Zhang, Fan Li, Ningyuan Zhang, Shengqian Wang","doi":"10.1109/IGARSS46834.2022.9883616","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883616","url":null,"abstract":"Sparse unmixing is a semi-supervised method whose pur-pose is to find the best subset of library entries from the spec-tral library that best model the image. In sparse unmixing, the current main development direction is to incorporate the spatial information of the image into the model. Existing spa-tial sparse unmixing algorithms mainly use spatial weights or spatial regularization to characterize the spatial correlation between pixels to improve the unmixing results. For the complex and diverse hyperspectral data in reality, most al-gorithms are only good at processing a single scene, which brings greater challenges to their practicality. In order to ad-dress this issue, a new dual spatial weighted sparse unmixing model (DSWSU) is proposed, which simultaneously ex-ploits the spatially homogeneous information of images. For the proposed DSWSU, a pre-calculated superpixel weighting factor is designed to mitigate the effect of noise on unmixing. Meanwhile, the spatial neighborhood weighting factor aims to promote the local smoothness of the abundance maps. As a simple unmixing model, the proposed DSWSU can be quickly solved by the alternating direction multiplier method (ADMM). Experimental results on simulated hyperspectral data indicate that the proposed DSWSU method can achieve accurate abundance estimation in various scenarios (low or high noise interference), and obtain better unmixing results than other state-of-the-art unmixing algorithms.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"22 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":"126046091","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

Evaluating Sentinel-3 Viability for Vegetation Canopy Monitoring and Fuel Moisture Content Estimation 评价Sentinel-3在植被冠层监测和燃料含水量估算中的可行性

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884150

Valerio Pampanoni, G. Laneve, G. Santilli

引用次数: 2

Masking Method Based on Morphological Operations for InSAS 基于形态学操作的InSAS掩蔽方法

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9884245

Pan Huang, Xiaojie Teng, Xuebo Zhang, Heping Zhong

引用次数: 0

Drought Characterisation of Syrdarya River Basin in Central Asia Using Reconnaissance Drought Index 基于干旱指数的中亚锡尔达里亚河流域干旱特征

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2022-07-17 DOI: 10.1109/IGARSS46834.2022.9883653

A. Yegizbayeva, S. Ilyas, T. Berdimbetov

{"title":"Drought Characterisation of Syrdarya River Basin in Central Asia Using Reconnaissance Drought Index","authors":"A. Yegizbayeva, S. Ilyas, T. Berdimbetov","doi":"10.1109/IGARSS46834.2022.9883653","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883653","url":null,"abstract":"This study provides a comprehensive analysis of drought characteristics in Syrdarya River Basin (SRB) of Central Asia (CA) by using meteorological and environmental variables derived from reanalyzed information database. Drought Intensity and Frequency (DIF) curves were identified based on precipitation deficit and evapotranspiration rates by using Reconnaissance Drought Index (RDI). Climatic variables for the study period of 1985–2015 were derived from Climate Research Unit (CRU) database. The frequency and duration of events appearing from April to September of each year, and drought severity was calculated as the sum of an integral period from severe to the extreme range defined with RDI varied between −1.5 and −3, respectively. Several drought events, ranging between moderate, severe and extreme in past 30 years period, were revealed over the basin in this study. A significant decreasing trend at high elevations in contrast to obvious increasing trends at lower elevations of the river basin has been observed. The dynamic variations of drought events over the SRB indicates the variation patterns of climatic impacts on drought occurrences in the mountainous regions.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"88 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":"126195510","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