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International Journal of Remote Sensing最新文献

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Pre- and post-fire forest canopy height mapping in Southeast Australia through the integration of multi-temporal GEDI data, satellite images, and Convolution Neural Network 通过整合多时 GEDI 数据、卫星图像和卷积神经网络，绘制澳大利亚东南部火灾前后的林冠高度图
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-07 DOI: 10.1080/01431161.2024.2343429
Tsung-Chi Chou, Xuan Zhu, Ruth Reef
{"title":"Pre- and post-fire forest canopy height mapping in Southeast Australia through the integration of multi-temporal GEDI data, satellite images, and Convolution Neural Network","authors":"Tsung-Chi Chou, Xuan Zhu, Ruth Reef","doi":"10.1080/01431161.2024.2343429","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343429","url":null,"abstract":"This study leveraged Convolutional Neural Network (CNN) models to estimate canopy height in Southeast Australian forests before and after the 2019–2020 bushfire event, using inputs from Sentinel-1,...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"30 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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-sensor transfer learning for fire smoke scene detection using variable-bands multi-spectral satellite imagery aided by spectral patterns 利用光谱模式辅助变波段多光谱卫星图像进行火灾烟雾场景探测的跨传感器迁移学习
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-07 DOI: 10.1080/01431161.2024.2343430
Liang Zhao, Jixue Liu, Stefan Peters, Jiuyong Li, Norman Mueller, Simon Oliver
{"title":"Cross-sensor transfer learning for fire smoke scene detection using variable-bands multi-spectral satellite imagery aided by spectral patterns","authors":"Liang Zhao, Jixue Liu, Stefan Peters, Jiuyong Li, Norman Mueller, Simon Oliver","doi":"10.1080/01431161.2024.2343430","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343430","url":null,"abstract":"This paper addresses the challenge of training deep learning models for fire smoke scene detection from multi-sensor, multi-spectral satellite imagery, where spectral bands vary and training data i...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"103 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
SRMA: a dual-branch parallel multi-scale attention network for remote sensing images sea-land segmentation SRMA：用于遥感图像海陆分割的双分支并行多尺度注意力网络
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-07 DOI: 10.1080/01431161.2024.2343432
Ye Zhu, Bo Wang, Qi Liu, Shihan Tan, Shengjie Wang, Wenyi Ge
{"title":"SRMA: a dual-branch parallel multi-scale attention network for remote sensing images sea-land segmentation","authors":"Ye Zhu, Bo Wang, Qi Liu, Shihan Tan, Shengjie Wang, Wenyi Ge","doi":"10.1080/01431161.2024.2343432","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343432","url":null,"abstract":"The use of deep learning-based high resolution remote sensing image sea and land segmentation method has become prevalent in various fields such as environmental monitoring, resource assessment, an...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"48 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140934059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
DEDU-Net: Dual-Encoder-Decoder-U-Net for road extraction from high-resolution remote sensing images DEDU-Net：用于从高分辨率遥感图像中提取道路的双编码器-解码器-U-网络
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-03 DOI: 10.1080/01431161.2024.2343138
Tong Ding, Xiaofei Wang
{"title":"DEDU-Net: Dual-Encoder-Decoder-U-Net for road extraction from high-resolution remote sensing images","authors":"Tong Ding, Xiaofei Wang","doi":"10.1080/01431161.2024.2343138","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343138","url":null,"abstract":"The development of the modern urban economy is closely tied to road construction, with roads being one of the most crucial components in urban development. The use of high-resolution remote sensing...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"38 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Transformer based ensemble deep learning approach for remote sensing natural scene classification 基于变压器的遥感自然场景分类集合深度学习方法
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-03 DOI: 10.1080/01431161.2024.2343141
Arrun Sivasubramanian, Prashanth VR, Sowmya V, Vinayakumar Ravi
{"title":"Transformer based ensemble deep learning approach for remote sensing natural scene classification","authors":"Arrun Sivasubramanian, Prashanth VR, Sowmya V, Vinayakumar Ravi","doi":"10.1080/01431161.2024.2343141","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343141","url":null,"abstract":"Very high resolution (VHR) remote sensing (RS) image classification is paramount for detailed Earth’s surface analysis. Feature extraction from VHR natural scenes is crucial, but it becomes a chall...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"3 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 spatiotemporal image fusion incorporating unmixing step by considering the point spread function effect 考虑点扩散函数效应，改进包含非混合步骤的时空图像融合技术
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-03 DOI: 10.1080/01431161.2024.2343140
Peng Wang, Mingxuan Huang, Kang Ni, Wenjian Liu, Bo Huang, Mingzuan Xu
{"title":"Improving spatiotemporal image fusion incorporating unmixing step by considering the point spread function effect","authors":"Peng Wang, Mingxuan Huang, Kang Ni, Wenjian Liu, Bo Huang, Mingzuan Xu","doi":"10.1080/01431161.2024.2343140","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343140","url":null,"abstract":"In this paper, an improving spatiotemporal image fusion (STIF) incorporating unmixing step by considering the point spread function (PSF) effect model (CPSF) is proposed to address the problem that...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"162 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
MFMENet: multi-scale features mutual enhancement network for change detection in remote sensing images MFMENet：用于遥感图像变化检测的多尺度特征相互增强网络
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-05-03 DOI: 10.1080/01431161.2024.2343139
Shuaitao Li, Yonghong Song, Xiaomeng Wu, You Su, Yuanlin Zhang
{"title":"MFMENet: multi-scale features mutual enhancement network for change detection in remote sensing images","authors":"Shuaitao Li, Yonghong Song, Xiaomeng Wu, You Su, Yuanlin Zhang","doi":"10.1080/01431161.2024.2343139","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343139","url":null,"abstract":"Change detection, an important task in remote sensing image analysis, has been extensively studied in recent years. However, change detection still faces problems such as difficulty in detecting sm...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"22 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Annual mapping of Spartina alterniflora with deep learning and spectral-phenological features from 2017 to 2021 in the mainland of China 利用深度学习和光谱-表观特征绘制中国大陆 2017 年至 2021 年的交替红叶石楠年度分布图
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-04-29 DOI: 10.1080/01431161.2024.2343136
Xiarong Li, Jinyan Tian, Xiaojuan Li, Yongxin Yu, Yang Ou, Lin Zhu, Xiumin Zhu, Bingfeng Zhou, Huili Gong
{"title":"Annual mapping of Spartina alterniflora with deep learning and spectral-phenological features from 2017 to 2021 in the mainland of China","authors":"Xiarong Li, Jinyan Tian, Xiaojuan Li, Yongxin Yu, Yang Ou, Lin Zhu, Xiumin Zhu, Bingfeng Zhou, Huili Gong","doi":"10.1080/01431161.2024.2343136","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343136","url":null,"abstract":"Spartina alterniflora (S. alterniflora) expanded continuously in the coastal zone of the mainland in China, which caused serious ecological problems. Currently, there are several studies on large-s...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"294 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140811574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
A fast hypergraph neural network with detail preservation for hyperspectral image classification 用于高光谱图像分类的具有细节保护功能的快速超图神经网络
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-04-26 DOI: 10.1080/01431161.2024.2343133
Feilong Cao, Jieqin Bao, Bing Yang, Hailiang Ye
{"title":"A fast hypergraph neural network with detail preservation for hyperspectral image classification","authors":"Feilong Cao, Jieqin Bao, Bing Yang, Hailiang Ye","doi":"10.1080/01431161.2024.2343133","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343133","url":null,"abstract":"Hypergraph neural networks (HGNNs), extending the techniques of graph neural networks, have been applied to various fields due to their ability to capture more complex high-order node relationships...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"44 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
A novel graph-based multiple kernel learning framework for hyperspectral image classification 用于高光谱图像分类的基于图的新型多核学习框架
IF 3.4 3区 地球科学
International Journal of Remote Sensing Pub Date : 2024-04-26 DOI: 10.1080/01431161.2024.2343132
Shirin Hassanzadeh, Habibollah Danyali, Azam Karami, Mohammad Sadegh Helfroush
{"title":"A novel graph-based multiple kernel learning framework for hyperspectral image classification","authors":"Shirin Hassanzadeh, Habibollah Danyali, Azam Karami, Mohammad Sadegh Helfroush","doi":"10.1080/01431161.2024.2343132","DOIUrl":"https://doi.org/10.1080/01431161.2024.2343132","url":null,"abstract":"Multiple kernel learning (MKL) is an efficient way to improve hyperspectral image classification with few training samples by integrating spectral and spatial features. Nonetheless, presenting a MK...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"90 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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