2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS最新文献_第10页

CLC+ Backbone: Set the Scene in Copernicus for the Coming Decade CLC+ Backbone:为未来十年设定哥白尼的场景

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553252

M. Probeck, Inés Ruíz, G. Ramminger, C. Fourie, Pirmin Maier, Martin Ickerott, Cornelia Storch, A. Homolka, S. J. Muller, Himanshu Tiwari, A. Stumpf, Sooyeon Chun, C. Mattos, Amelie Lindmayer, Fahad Jahangir, Pilar Endara, F. Berndt, M. Dohr, W. Kapferer, C. Schleicher, S. Ralser, Florian Innerbichler, M. Riffler, Martin Siklar, Dorothea Aifantopoulou, Sideris Paralykidis, Camille Pinet, G. Jaffrain, A. D. Federico, M. Corsi, T. Langanke, H. Dufourmont

{"title":"CLC+ Backbone: Set the Scene in Copernicus for the Coming Decade","authors":"M. Probeck, Inés Ruíz, G. Ramminger, C. Fourie, Pirmin Maier, Martin Ickerott, Cornelia Storch, A. Homolka, S. J. Muller, Himanshu Tiwari, A. Stumpf, Sooyeon Chun, C. Mattos, Amelie Lindmayer, Fahad Jahangir, Pilar Endara, F. Berndt, M. Dohr, W. Kapferer, C. Schleicher, S. Ralser, Florian Innerbichler, M. Riffler, Martin Siklar, Dorothea Aifantopoulou, Sideris Paralykidis, Camille Pinet, G. Jaffrain, A. D. Federico, M. Corsi, T. Langanke, H. Dufourmont","doi":"10.1109/IGARSS47720.2021.9553252","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9553252","url":null,"abstract":"With the CLC+ product suite as part of the Copernicus Land Monitoring Service (CLMS), the European Environment Agency (EEA) has initiated a true paradigm change in European land cover/land use monitoring, building on the 30-years-long rich legacy of the European CORINE Land Cover (CLC) flagship product. The CLC+ Backbone, as first component of the upcoming CLC+ era, will feature an object-oriented wall-to-wall high-resolution inventory of European land cover and its characteristics in unprecedented quality and detail, for the reference year 2018. It will comprise a pan-European combined “hardbone” and “soft-bone” segmentation of vector-based stable landscape objects and a raster-based classification of 11 EAGLE compliant land cover classes at 10m spatial resolution. To this end, a combination of image segmentation and Deep Learning approaches are implemented within a cloud-based infrastructure for a fully integrated analysis of optical/radar time series of Sentinel-1/-2 satellite imagery and auxiliary data. Vector and raster datasets will be fused into a fully attributed, 18 land cover class, vector product with 0.5 ha minimum mapping unit (MMU), additionally incorporating a multitude of further information layers derived from satellite data and various other Copernicus products.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123824334","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

A Study on the Detection of Deformation of Tuotuohe Area on the Qinghai-Tibet Plateau 青藏高原沱沱河地区形变探测研究

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9555061

Xiaokang Kou, Xinda Liu, Yuzhi Zhang, Yichi Zhang, Tianliang Wang, Shuang Yan

{"title":"A Study on the Detection of Deformation of Tuotuohe Area on the Qinghai-Tibet Plateau","authors":"Xiaokang Kou, Xinda Liu, Yuzhi Zhang, Yichi Zhang, Tianliang Wang, Shuang Yan","doi":"10.1109/IGARSS47720.2021.9555061","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9555061","url":null,"abstract":"In permafrost regions, the ground surface deformation is closely related to the ice-water phase transition process in active layer and underground ice. It is of great significance to carry out ground surface deformation detection research for understanding the development of permafrost in the Qinghai- Tibet Plateau. The InSAR technology has been proved to be an effective method for monitoring frozen soil deformation. However, due to the limitation of spatial coverage and revisit cycle of SAR data, few scholars had paid attention on the unstable permafrost regions with less ice content in the previous studies. Thus, a less ice content permafrost region loceted in Tuotuohe was taken as the study area to carry out surface deformation detection research based on SBAS-InSAR technology, and the field measurement was carried out to do the verification. The result showed that there was a good agreement between them, and the errors are 0.9mm, 2.6mm and 2.8mm respectively. The deformation detected by SBAS-InSAR method well reflects the frost heaving and thaw subsidence trend along with seasonal changes. Considering the small content of underground ice, this trend mainly reflects the seasonal freezing-thawing variation of the active layer. This study further confirms the applicability of InSAR technology in unstable permafrost regions.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123842184","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

Analyzing Long-Term Artificial Light at Night Using Viirs Monthly Product with Land Use Data: Preliminary Result of Hong Kong 利用Viirs每月产品及土地用途数据分析长期夜间人工照明:香港的初步结果

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553915

Shengjie Liu, C. So, C. Pun

{"title":"Analyzing Long-Term Artificial Light at Night Using Viirs Monthly Product with Land Use Data: Preliminary Result of Hong Kong","authors":"Shengjie Liu, C. So, C. Pun","doi":"10.1109/IGARSS47720.2021.9553915","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9553915","url":null,"abstract":"Long-term monitoring of artificial light at night (ALAN) is essential for our understanding of the source of light pollution and developing mechanisms to control it. In this study, based on the VIIRS monthly product and land use data, we analyzed the long-term ALAN in Hong Kong between 2012 and 2019. We could not detect any long-term trend in the level of ALAN of Hong Kong from this dataset over the eight years of observations at the level of detection accuracy of the VIIRS monthly data. We performed a detailed analysis of the ALAN from Hong Kong and its relationship with land use classes. We found that in Hong Kong, the public residential areas are brighter than the private ones, likely the consequence of a combination of population density and lighting designs. Using the clustering method, we were able to identify some persistently bright (or dark) facilities, such as the Hong Kong-Zhuhai-Macau Bridge Port, airport and port facilities. Transient phenomena such as wildfires were identified as well. Finally, we observed a brighter background ALAN associated with an elevated humidity level $(mathrm{R}=0.54)$, which can possibly be attributed to the dispersing effect of water vapor on radiation. Since large public transportation facilities emitted the most ALAN in Hong Kong, we suggest adopting sustainable design in future transportation projects to reduce the emitted ALAN to the space, thereby reducing light pollution.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123932236","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

Analysis of the Influence of Sky View Factor on Urban Surface Temperature Based on Multi-Source Data 基于多源数据的天景因子对城市地表温度的影响分析

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553054

Qianhao Cheng, Qiang Chen, Yuanyuan Li, Beilei Cao

引用次数: 0

Online Education of Remote Sensing in China During the Covid-19 Pandemic: A Case of Study in Jiangsu Normal University 新冠肺炎疫情期间中国遥感在线教育——以江苏师范大学为例

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554238

Qi Zhang, Qingmiao Ma, Yingjie Li, Shuguo Wang, Tianchen Qu, Zhuohao Liu, Ying Zhang, Chengzhi Gao

引用次数: 0

Assessment of Four Model-Based Surface Soil Temperature Products Unsing Global Dense in Situ Observations 基于四种模式的地表土壤温度产品在全球密集原位观测下的评估

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554151

Hongliang Ma, J. Zeng, J. Wigneron, Xiang Zhang, Nengcheng Chen, Xiaojun Li, A. Al-Yaari, Xiangzhuo Liu, Mengjia Wang, L. Fan, F. Frappart

{"title":"Assessment of Four Model-Based Surface Soil Temperature Products Unsing Global Dense in Situ Observations","authors":"Hongliang Ma, J. Zeng, J. Wigneron, Xiang Zhang, Nengcheng Chen, Xiaojun Li, A. Al-Yaari, Xiangzhuo Liu, Mengjia Wang, L. Fan, F. Frappart","doi":"10.1109/IGARSS47720.2021.9554151","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9554151","url":null,"abstract":"Assessment of the model-based surface soil temperature (ST) products is very important for hydrometeorological and ecological applications, as well as model refinements. Distinguished from previous regional validations using only in situ observations from sparse networks, this study focused on the evaluation of model-based ST products by considering ground observations from 15 dense networks worldwide from April 2015 to December 2017 covering a wide range of ground conditions. Four model-based ST products were selected for the assessment, including the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Goddard Earth Observing System Model version 5 Forward Processing (GEOS-5 FP), the ERA-Interim and its successor, the newly developed ERA5. The results indicate the GEOS-5 ST product slightly outperforms other ST products by showing an averaged ubRMSD of 1.84 K. All model-based ST products underestimate in situ ST with a negative bias. All four model-based ST products are demonstrated to well capture the temporal trends of ground observations with very promising $R$ values larger than 0.97. The ERA5 shows visible improvements compared to its predecessor ERA-Interim by exhibiting smaller ubRMSD, absolute bias and larger $R$ values. These findings are expected to provide useful suggestions for the enhancement and specific usage of the model-based ST products.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124244379","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

A Disentangled Variational Autoencoder for Prediction of Above Ground Biomass from Hyperspectral Data 利用高光谱数据预测地面生物量的解纠缠变分自编码器

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554415

Parth Naik, M. Dalponte, L. Bruzzone

{"title":"A Disentangled Variational Autoencoder for Prediction of Above Ground Biomass from Hyperspectral Data","authors":"Parth Naik, M. Dalponte, L. Bruzzone","doi":"10.1109/IGARSS47720.2021.9554415","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9554415","url":null,"abstract":"The prediction of forest biophysical parameters is an important task in remote sensing for understanding global carbon cycle. Spectral remote sensing data are available globally at a relatively economical cost making them a viable resource for forest remote sensing. However, the main drawbacks associated with such data is the uncertainty of predictions and cluttered process of selecting band combinations from hyperspectral/multispectral data to produce spectral features for modelling. In this paper, we present an approach that exploits the latest developments in generative variational autoencoders (VAE) that produce disentangled representation from input data to assess the capability of hyperspectral data to model forest aboveground biomass (AGB). The proposed VAE generates a special kind of deep spectral features that are proportional to AGB. A modelling accuracy of R2 = 0.57 (cross-validated) was obtained by the proposed approach, thus pointing out the potential of hyperspectral data to model AGB using disentangled deep spectral features. The proposed approach also enables in bypassing the unreliable process of selecting band combinations to produce spectral features and shows good prospects for mapping global level biomass.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123380640","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

Deep multi-modal satellite and in-situ observation fusion for Soil Moisture retrieval 深度多模态卫星与原位观测融合反演土壤水分

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553848

Grigorios Tsagkatakis, M. Moghaddam, P. Tsakalides

引用次数: 1

Adapting Kernels for Hyperspectral Image Classification 基于核函数的高光谱图像分类

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553134

J. M. Haut, Mercedes Eugenia Paoletti, R. Pastor-Vargas, L. Tobarra, A. Robles-Gómez, R. Hernandez, E.M.T. Hendrix, J. Li

引用次数: 1

The Indian Contribution to the CEOS-VC 印度对ceo - vc的贡献

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553467

Raj Kumar, P. Chakraborty, D. Mankad, S. A. Bhowmick, Abhisek Chakraborty

{"title":"The Indian Contribution to the CEOS-VC","authors":"Raj Kumar, P. Chakraborty, D. Mankad, S. A. Bhowmick, Abhisek Chakraborty","doi":"10.1109/IGARSS47720.2021.9553467","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9553467","url":null,"abstract":"Indian Space Research Organization (ISRO) has started contributing towards international tandem space-borne scatterometer missions by successfully launching a Ku-band pencil-beam scatterometer onboard Oceansat-2 in September 2009. The Oceansat-2 scatterometer (OSCAT) continued to provide good quality observations of ocean surface vector winds till February 2014, when a major power failure ceased the mission. In September 2016, ISRO launched another Ku-band scatterometer as a sole payload onboard Scatsat-1. The Scatsat-1 followed the design heritage of OSCAT with some improved configuration. After the initial CAL/VAL phase, the Scatsat-1was to found to provide excellent quality of wind products. The present status of Scatsat-1 is operational. The operational data products from Scatsat-1 as well as archived products from OSCAT are available from both National Remote Sensing Centre (NRSC, www.nrsc.gov.in) and Meteorological and Oceanographic Satellite Data Archival Centre (MOSDAC, www.mosdac.gov.in). Apart from the operational products from these scatterometers, there are several other value added products are routinely generated and disseminated from MOSDAC. Table-1 shows the brief descriptions of the operational and value added products available from Scatsat-1.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123525852","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