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GIScience & Remote Sensing最新文献

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A new transferable deep learning approach for crop mapping 用于作物制图的新型可迁移深度学习方法
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-27 DOI: 10.1080/15481603.2024.2395700
Hongyan Che, Yaozhong Pan, Xingsheng Xia, Xiufang Zhu, Le Li, Yongsheng Huang, Xuechang Zheng, Lingang Wang
{"title":"A new transferable deep learning approach for crop mapping","authors":"Hongyan Che, Yaozhong Pan, Xingsheng Xia, Xiufang Zhu, Le Li, Yongsheng Huang, Xuechang Zheng, Lingang Wang","doi":"10.1080/15481603.2024.2395700","DOIUrl":"https://doi.org/10.1080/15481603.2024.2395700","url":null,"abstract":"Accurate crop mapping provides important information for government decision-making and agricultural management. Recent advancements in deep learning have significantly enhanced the capabilities of...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Deep learning-based mapping of total suspended solids in rivers across South Korea using high resolution satellite imagery 利用高分辨率卫星图像绘制基于深度学习的韩国河流总悬浮固体地图
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-26 DOI: 10.1080/15481603.2024.2393489
JunGi Moon, SungMin Suh, SangJin Jung, Sang-Soo Baek, JongCheol Pyo
{"title":"Deep learning-based mapping of total suspended solids in rivers across South Korea using high resolution satellite imagery","authors":"JunGi Moon, SungMin Suh, SangJin Jung, Sang-Soo Baek, JongCheol Pyo","doi":"10.1080/15481603.2024.2393489","DOIUrl":"https://doi.org/10.1080/15481603.2024.2393489","url":null,"abstract":"Managing total suspended solids (TSS) in inland water is crucial for maintaining water quality and aquatic ecosystems. To obtain spatial data, the conventional method of point sampling TSS is a tim...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142118178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving assessment of population exposure and health impacts to PM2.5 with high spatial and temporal data 利用高时空数据改进对 PM2.5 的人口暴露和健康影响的评估
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-09 DOI: 10.1080/15481603.2024.2388921
Xia Zhao, Yuyu Zhou, Xi Li, Tao Zhang, Yueying Wang, Zhengyuan Zhu, Kai Zhang, Deren Li
{"title":"Improving assessment of population exposure and health impacts to PM2.5 with high spatial and temporal data","authors":"Xia Zhao, Yuyu Zhou, Xi Li, Tao Zhang, Yueying Wang, Zhengyuan Zhu, Kai Zhang, Deren Li","doi":"10.1080/15481603.2024.2388921","DOIUrl":"https://doi.org/10.1080/15481603.2024.2388921","url":null,"abstract":"Exposure to ambient fine particulate matter (PM2.5) poses a significant global health challenge. However, a major obstacle for epidemiological studies and risk assessment lies in the absence of hig...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141909294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Spatiotemporal analysis of tropical vegetation ecosystems and their responses to multifaceted droughts in Mainland Southeast Asia using satellite-based time series 利用卫星时间序列对东南亚大陆热带植被生态系统及其对多方面干旱的响应进行时空分析
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-05 DOI: 10.1080/15481603.2024.2387385
Tuyen V. Ha, Soner Uereyen, Claudia Kuenzer
{"title":"Spatiotemporal analysis of tropical vegetation ecosystems and their responses to multifaceted droughts in Mainland Southeast Asia using satellite-based time series","authors":"Tuyen V. Ha, Soner Uereyen, Claudia Kuenzer","doi":"10.1080/15481603.2024.2387385","DOIUrl":"https://doi.org/10.1080/15481603.2024.2387385","url":null,"abstract":"Drought ranks among the costliest of all climate-related phenomena and manifests in various forms, posing significant challenges in understanding its influence on agriculture and natural ecosystems...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141900002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Solution for crop classification in regions with limited labeled samples: deep learning and transfer learning 标记样本有限地区的作物分类解决方案：深度学习和迁移学习
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-05 DOI: 10.1080/15481603.2024.2387393
Hengbin Wang, Yu Yao, Zijing Ye, Wanqiu Chang, Junyi Liu, Yuanyuan Zhao, Shaoming Li, Zhe Liu, Xiaodong Zhang
{"title":"Solution for crop classification in regions with limited labeled samples: deep learning and transfer learning","authors":"Hengbin Wang, Yu Yao, Zijing Ye, Wanqiu Chang, Junyi Liu, Yuanyuan Zhao, Shaoming Li, Zhe Liu, Xiaodong Zhang","doi":"10.1080/15481603.2024.2387393","DOIUrl":"https://doi.org/10.1080/15481603.2024.2387393","url":null,"abstract":"Reliable classification results are crucial for guiding agricultural production, forecasting crop yield, and ensuring food security. Generating reliable classification results is relatively simple ...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Home sharing or crime sharing? Evidences of the relationship between Airbnb, crime and structural factors in Malaga, Spain 共享房屋还是共享犯罪？西班牙马拉加 Airbnb、犯罪和结构性因素之间关系的证据
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-05 DOI: 10.1080/15481603.2024.2384330
Diego J. Maldonado-Guzmán, Francisco José Chamizo-Nieto, Sergio Reyes-Corredera
{"title":"Home sharing or crime sharing? Evidences of the relationship between Airbnb, crime and structural factors in Malaga, Spain","authors":"Diego J. Maldonado-Guzmán, Francisco José Chamizo-Nieto, Sergio Reyes-Corredera","doi":"10.1080/15481603.2024.2384330","DOIUrl":"https://doi.org/10.1080/15481603.2024.2384330","url":null,"abstract":"Negative externalities stemming from overtourism have been widely reported in the literature. However, a consequence less explored in scientific research is the increase in crime rates derived from...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141909303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine learning-based retrieval of total column water vapor over land using GMI-sensed passive microwave measurements 利用全球海洋观测系统传感的被动微波测量数据，基于机器学习的陆地总水汽柱检索
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-08-05 DOI: 10.1080/15481603.2024.2385180
Jiafei Xu, Zhizhao Liu
{"title":"Machine learning-based retrieval of total column water vapor over land using GMI-sensed passive microwave measurements","authors":"Jiafei Xu, Zhizhao Liu","doi":"10.1080/15481603.2024.2385180","DOIUrl":"https://doi.org/10.1080/15481603.2024.2385180","url":null,"abstract":"The Global Precipitation Measurement (GPM) Microwave Imager (GMI) is a microwave (MW) radiometer that has near-global coverage and frequent revisit time. To date, operational total column water vap...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141900003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cross attention is all you need: relational remote sensing change detection with transformer 交叉关注即可：利用变压器进行关系遥感变化检测
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-07-21 DOI: 10.1080/15481603.2024.2380126
Kaixuan Lu, Xiao Huang, Ruiheng Xia, Pan Zhang, Junping Shen
{"title":"Cross attention is all you need: relational remote sensing change detection with transformer","authors":"Kaixuan Lu, Xiao Huang, Ruiheng Xia, Pan Zhang, Junping Shen","doi":"10.1080/15481603.2024.2380126","DOIUrl":"https://doi.org/10.1080/15481603.2024.2380126","url":null,"abstract":"Deep-learning-based change detection methods have received wide attention, thanks to their strong capability in obtaining rich features from images. However, existing AI-based change detection (CD)...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Vegetation canopy height shapes bats’ occupancy: a remote sensing approach 植被冠层高度影响蝙蝠的栖息：一种遥感方法
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-07-17 DOI: 10.1080/15481603.2024.2374150
F. C. Martins, S. Godinho, N. Guiomar, D. Medinas, H. Rebelo, P. Segurado, J. T. Marques
{"title":"Vegetation canopy height shapes bats’ occupancy: a remote sensing approach","authors":"F. C. Martins, S. Godinho, N. Guiomar, D. Medinas, H. Rebelo, P. Segurado, J. T. Marques","doi":"10.1080/15481603.2024.2374150","DOIUrl":"https://doi.org/10.1080/15481603.2024.2374150","url":null,"abstract":"Anthropogenic activities have significantly altered land cover on a global scale. These changes often have a negative effect on biodiversity limiting the distribution of species. The extent of the ...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141732694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Ensemble learning-based crop yield estimation: a scalable approach for supporting agricultural statistics 基于集合学习的作物产量估算：支持农业统计的可扩展方法
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-06-28 DOI: 10.1080/15481603.2024.2367808
Patric Brandt, Florian Beyer, Peter Borrmann, Markus Möller, Heike Gerighausen
{"title":"Ensemble learning-based crop yield estimation: a scalable approach for supporting agricultural statistics","authors":"Patric Brandt, Florian Beyer, Peter Borrmann, Markus Möller, Heike Gerighausen","doi":"10.1080/15481603.2024.2367808","DOIUrl":"https://doi.org/10.1080/15481603.2024.2367808","url":null,"abstract":"Detailed and accurate statistics on crop productivity are key to inform decision-making related to sustainable food production and supply ensuring global food security. However, annual and high-res...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","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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