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A novel spaceborne photon-counting laser altimeter denoising method based on parameter-adaptive density clustering 基于参数自适应密度聚类的新型空间光子计数激光高度计去噪方法
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-15 DOI: 10.1080/15481603.2024.2326702
Ren Liu, Xinming Tang, Junfeng Xie, Rujia Ma, Fan Mo, Xiaomeng Yang
{"title":"A novel spaceborne photon-counting laser altimeter denoising method based on parameter-adaptive density clustering","authors":"Ren Liu, Xinming Tang, Junfeng Xie, Rujia Ma, Fan Mo, Xiaomeng Yang","doi":"10.1080/15481603.2024.2326702","DOIUrl":"https://doi.org/10.1080/15481603.2024.2326702","url":null,"abstract":"To tackle the challenge of denoising spaceborne photon-counting laser altimeter point clouds with uneven noise density, this study proposes a denoising method based on adaptive parameter density cl...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"36 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135994","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
U-SeqNet: learning spatiotemporal mapping relationships for multimodal multitemporal cloud removal U-SeqNet：学习时空映射关系，实现多模态多时空云清除
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-14 DOI: 10.1080/15481603.2024.2330185
Qian Zhang, Xiangnan Liu, Tao Peng, Xiao Yang, Mengzhen Tang, Xinyu Zou, Meiling Liu, Ling Wu, Tingwei Zhang
{"title":"U-SeqNet: learning spatiotemporal mapping relationships for multimodal multitemporal cloud removal","authors":"Qian Zhang, Xiangnan Liu, Tao Peng, Xiao Yang, Mengzhen Tang, Xinyu Zou, Meiling Liu, Ling Wu, Tingwei Zhang","doi":"10.1080/15481603.2024.2330185","DOIUrl":"https://doi.org/10.1080/15481603.2024.2330185","url":null,"abstract":"Optical remotely sensed time series data have various key applications in Earth surface dynamics. However, cloud cover significantly hampers data analysis and interpretation. Despite synthetic aper...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"09 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140124182","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
Mapping invasive noxious weed species in the alpine grassland ecosystems using very high spatial resolution UAV hyperspectral imagery and a novel deep learning model 利用空间分辨率极高的无人机高光谱图像和新型深度学习模型绘制高寒草地生态系统中的入侵有害杂草物种地图
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-13 DOI: 10.1080/15481603.2024.2327146
Fei Xing, Ru An, Xulin Guo, Xiaoji Shen
{"title":"Mapping invasive noxious weed species in the alpine grassland ecosystems using very high spatial resolution UAV hyperspectral imagery and a novel deep learning model","authors":"Fei Xing, Ru An, Xulin Guo, Xiaoji Shen","doi":"10.1080/15481603.2024.2327146","DOIUrl":"https://doi.org/10.1080/15481603.2024.2327146","url":null,"abstract":"The term “invasive noxious weed species” (INWS), which refers to noxious weed plants that invade native alpine grasslands, has increasingly become an ecological and economic threat in the alpine gr...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"140 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140124210","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
Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation 衔接卫星任务：用于增强热带气旋强度估计的深度转移学习
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-11 DOI: 10.1080/15481603.2024.2325720
Minki Choo, Yejin Kim, Juhyun Lee, Jungho Im, Il-Ju Moon
{"title":"Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation","authors":"Minki Choo, Yejin Kim, Juhyun Lee, Jungho Im, Il-Ju Moon","doi":"10.1080/15481603.2024.2325720","DOIUrl":"https://doi.org/10.1080/15481603.2024.2325720","url":null,"abstract":"Geostationary satellites are valuable tools for monitoring the entire lifetime of tropical cyclones (TCs). Although the most widely used method for TC intensity estimation is manual, several automa...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"8 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140117942","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
Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation 基于过程的和地球静止气象卫星增强的死亡燃料水分含量估算
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-05 DOI: 10.1080/15481603.2024.2324556
Chunquan Fan, Binbin He, Jianpeng Yin, Rui Chen, Hongguo Zhang
{"title":"Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation","authors":"Chunquan Fan, Binbin He, Jianpeng Yin, Rui Chen, Hongguo Zhang","doi":"10.1080/15481603.2024.2324556","DOIUrl":"https://doi.org/10.1080/15481603.2024.2324556","url":null,"abstract":"Dead fuel moisture content (DFMC) is essential for assessing wildfire danger, fire behavior, and fuel consumption. Several process-based models have been proposed to estimate DFMC. Previous studies...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"71 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140037915","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
Cloud restoration of optical satellite imagery using time-series spectral similarity group 利用时间序列光谱相似性组对光学卫星图像进行云恢复
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-03-05 DOI: 10.1080/15481603.2024.2324553
Yerin Yun, Jinha Jung, Youkyung Han
{"title":"Cloud restoration of optical satellite imagery using time-series spectral similarity group","authors":"Yerin Yun, Jinha Jung, Youkyung Han","doi":"10.1080/15481603.2024.2324553","DOIUrl":"https://doi.org/10.1080/15481603.2024.2324553","url":null,"abstract":"According to climate statistics, clouds cover more than a third of the Earth’s land surface on average. This cloud coverage obstructs optical satellite imagery, resulting in a loss of essential inf...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"13 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140048047","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
Inferring the heterogeneous effect of urban land use on building height with causal machine learning 利用因果机器学习推断城市土地利用对建筑高度的异质性影响
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-02-25 DOI: 10.1080/15481603.2024.2321695
Yimin Chen, Jing Chen, Shuai Zhao, Xiaocong Xu, Xiaoping Liu, Xinchang Zhang, Honghui Zhang
{"title":"Inferring the heterogeneous effect of urban land use on building height with causal machine learning","authors":"Yimin Chen, Jing Chen, Shuai Zhao, Xiaocong Xu, Xiaoping Liu, Xinchang Zhang, Honghui Zhang","doi":"10.1080/15481603.2024.2321695","DOIUrl":"https://doi.org/10.1080/15481603.2024.2321695","url":null,"abstract":"Machine learning has become an important approach for land use change modeling. However, conventional machine learning algorithms are limited in their ability to capture causal relationships in lan...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"201 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139987548","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
Fine classification of crops based on an inductive transfer learning method with compact polarimetric SAR images 利用紧凑型偏振合成孔径雷达图像，基于归纳转移学习法对农作物进行精细分类
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-02-23 DOI: 10.1080/15481603.2024.2319939
Xianyu Guo, Junjun Yin, Jian Yang
{"title":"Fine classification of crops based on an inductive transfer learning method with compact polarimetric SAR images","authors":"Xianyu Guo, Junjun Yin, Jian Yang","doi":"10.1080/15481603.2024.2319939","DOIUrl":"https://doi.org/10.1080/15481603.2024.2319939","url":null,"abstract":"Compact polarimetric synthetic aperture radar (CP SAR) reduces fully polarimetric SAR system complexity and expands the imaging swath. Generally, fine classification of crop types relies on many la...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"38 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139957160","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
Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods 陆地总初级生产力遥感：理论基础、关键参数和方法进展综述
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-02-20 DOI: 10.1080/15481603.2024.2318846
Wenquan Zhu, Zhiying Xie, Cenliang Zhao, Zhoutao Zheng, Kun Qiao, Dailiang Peng, Yongshuo H. Fu
{"title":"Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods","authors":"Wenquan Zhu, Zhiying Xie, Cenliang Zhao, Zhoutao Zheng, Kun Qiao, Dailiang Peng, Yongshuo H. Fu","doi":"10.1080/15481603.2024.2318846","DOIUrl":"https://doi.org/10.1080/15481603.2024.2318846","url":null,"abstract":"Accurately estimating gross primary productivity (GPP), the largest carbon flux in terrestrial ecosystems, is crucial for advancing our understanding of global carbon cycle and predicting climate f...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"162 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139909046","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
Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time 基于 MODIS 本地越过时间，定量评估各种天空条件下从瞬时 GPP 到每日 GPP 的尺度转换
IF 6.7 2区 地球科学
GIScience & Remote Sensing Pub Date : 2024-02-20 DOI: 10.1080/15481603.2024.2319372
Junghee Lee, Jungho Im
{"title":"Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time","authors":"Junghee Lee, Jungho Im","doi":"10.1080/15481603.2024.2319372","DOIUrl":"https://doi.org/10.1080/15481603.2024.2319372","url":null,"abstract":"With the increasing frequency of extreme events, daily gross primary productivity (GPP) is necessary to be accurately assessed to determine when and how much it is affected. Fluctuating environment...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"273 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139909195","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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