International Journal of Applied Earth Observation and Geoinformation最新文献

{"title":"Investigating heat-related health risks related to local climate zones using SDGSAT-1 high-resolution thermal infrared imagery in an arid megacity","authors":"Muhammad Fahad Baqa, Linlin Lu, Huadong Guo, Xiaoning Song, Seyed Kazem Alavipanah, Syed Nawaz-ul-Huda, Qingting Li, Fang Chen","doi":"10.1016/j.jag.2024.104334","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104334","url":null,"abstract":"Due to the compounding impacts of urbanization and climate change-induced warming, urban inhabitants face increasing risks of thermal health issues. The use of high-resolution maps that categorize intra-urban thermal environment and Local Climate Zones (LCZ) could enhance the understanding of the correlation between heat-related health risks and microclimates. In this study, a fine-scale heat risk assessment framework was applied in an arid megacity, Karachi, Pakistan. Following Crichton’s Risk Triangle framework, heat health risks were mapped by considering hazard-exposure-vulnerability components at the census ward level. The heat hazard was mapped using SDGSAT-1 thermal infrared data at a 30 m spatial resolution during summer season. Factors contributing most to heat vulnerability were identified as the availability of electricity facilities, bathroom facilities, and housing density, with contribution rates of 47.51 %, 21.86 %, and 8.07 %, respectively. Heat risks were considerably higher for built types (0.16) compared to natural LCZ types (0.07), with 65 % of LCZ 2, 3, 6, and 7 (compact mid-rise, compact low-rise, open low-rise, and lightweight low-rise areas) identified as high-risk areas. To mitigate heat risks, green space should be planned in LCZ2 and LCZ3 characterized by dense population and compact buildings arrangement, and public cooling facilities and infrastructure should be improved in LCZ7 featured with squatter and slum settlements. Urban planners may consider restricting the growth of these areas in newly-developed regions, including encroachments and unplanned settlements, to prevent further exacerbation of heat stress. This study offers a valuable guide for assessing and alleviating heat risks at the community level, thereby promoting the development of heat resilient urban areas.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"14 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A spatiotemporal framework to assess the bio-geomorphic interplay of saltmarsh vegetation and tidal emergence (Western Scheldt estuary)","authors":"Jing Feng, Tim J. Grandjean, Johan van de Koppel, Daphne van der Wal","doi":"10.1016/j.jag.2024.104337","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104337","url":null,"abstract":"Sea level changes will significantly drive hydrodynamic, morphological, and ecological development of estuaries. However, the interplay of geomorphology and vegetation at estuary scales remains unclear. To better understand this process, we take the Western Scheldt estuary in the Netherlands as an example to reveal the link between changes in emersion duration and vegetation dynamics in the period 1993–2016. We found that tidal flats in the Western Scheldt become steeper—higher intertidal areas increased in elevation and emersion duration, whereas the low-lying edges of tidal flats experienced a decrease in elevation and emersion duration. We found that longer emersion duration was associated with increased plant diversity and cover. Furthermore, we detected the unique spatiotemporal response patterns of four abundant plant species to geomorphological variations. Our study suggests that on a large estuary scale, geomorphological changes are coupled to the richness and cover of plant communities, and that potential changes in relative sea level can induce structural modifications of the plant communities. It also emphasizes the importance of assessing the potential effects of localized relative sea level changes while considering all aspects of natural processes and direct and indirect human influences. Our study provides a framework to assess the bio-geomorphic processes in a spatially explicit way.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"283 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing phenological differences of invasive shrubs in a forest matrix using high resolution VENµS time series","authors":"Liang Liang, Jian Yang, William C. Wittenbraker, Ellen V. Crocker, Monika A. Tomaszewska, Geoffrey M. Henebry","doi":"10.1016/j.jag.2024.104333","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104333","url":null,"abstract":"Many invasive shrubs in the eastern deciduous forests of the United States use the temporal niche before and after the native tree canopy leaf-on period (leafing out prior to most native species and retaining leaves after most natives senesce) to establish in the light-limited environment of the understory. To support an increased understanding of invasive shrub species’ ecology and distribution patterns and inform better management plans, this key phenological difference needs to be characterized in detail. Here we leveraged the high-resolution observations from the French-Israel VENµS mission to examine the phenological characteristics of a widespread invasive shrub species—Amur honeysuckle (AH; <ce:italic>Lonicera maackii</ce:italic> (Rupr.) Herder)—compared to native deciduous trees in Robinson Forest, Kentucky. VENµS offered daily superspectral (12 narrow bands) observations at 4 m resolution in a limited number of global sites, providing us with crucial data for the analysis. We identified three forest communities with respect to AH presence through field surveys (<ce:italic>i.e.,</ce:italic> uninvaded forest stands, forest stands with AH understory, and AH shrub thickets) and compared their VENµS-derived spectral signatures and time series of vegetation indices. In 2023, AH shrub thickets greened up one month earlier than uninvaded forest stands (mid-March vs. mid-April). AH leaf growth advanced into full green before the canopy tree greenup started in early April, marking an optimal window for isolating areas with AH understory from the uninvaded forest using remote sensing. Based on the phenological differences identified, we predicted the distribution of AH in the study area using a two-date differencing model and a spectral mixture analysis. Our detailed findings using VENµS data offer insights into the temporal dynamics of invasive shrubs and native trees in a typical eastern deciduous forest. While our prediction of the AH distribution was confounded by the presence of native early greening and/or evergreen understory plants at a few locations, it was still moderately accurate (overall accuracy ∼ 70 %) and its abundance estimates agreed with observations in forest stands with minimal native understory growth. Moving forward, high-resolution remote sensing observations combined with a phenology-based approach will likely support more precise monitoring and management of invasive understory plants in native forest ecosystems.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"85 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ComHazAsTC-RRE: Compound Hazard Assessment of Tropical Cyclones within Repeatable, Reproducible, and Expandable Framework","authors":"Ziying Zhou, Saini Yang, Siqin Wang, Xiaoyan Liu, Fuyu Hu, Yaqiao Wu, Yu Chen","doi":"10.1016/j.jag.2024.104314","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104314","url":null,"abstract":"Compound hazards caused by tropical cyclones involve interactions among multiple hazards, such as wind, rainfall, and storm surge, significantly increasing the uncertainty and destructiveness of disasters. Existing studies primarily focus on probabilistic analyses of single or dual hazards associated with tropical cyclones, revealing limitations in handling high-dimensional data and complex dependencies. This study developed the ComHazAsTC-RRE (<ce:underline>Com</ce:underline>pound <ce:underline>Haz</ce:underline>ard <ce:underline>As</ce:underline>sessment of <ce:underline>T</ce:underline>ropical <ce:underline>C</ce:underline>yclones within <ce:underline>R</ce:underline>epeatable, <ce:underline>R</ce:underline>eproducible, and <ce:underline>E</ce:underline>xpandable Framework) model to analyze the compound hazards of wind, rainfall, and storm surge induced by tropical cyclones and successfully applied it to China’s coast. We collected globally accessible daily records of maximum wind speed, cumulative rainfall, and maximum storm surge for China’s coastal areas from 1979 to 2018. Using a C-Vine Copula with wind speed as the core, incorporating rainfall and storm surge as branches, we accurately captured complex dependencies of tropical cyclones. Our various return period analyses underscore the importance of considering multiple hazards and their interactions. Additionally, the application of Compound Hazard Index in China reveals that southeastern coastal areas are subjected to significantly higher compound hazards, driven by high wind speeds and strong spatial–temporal consistency of hazards. An in-depth analysis of failure probabilities indicates that neglecting the interactions among hazards can result in substantial additional cost for engineering projects, especially during severe tropical cyclones. This study offers new perspectives and scientific tools for understanding and addressing compound hazards, formulating effective disaster prevention and mitigation strategies, and supporting the sustainable development of coastal regions worldwide.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"22 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scale effects in mangrove mapping from ultra-high-resolution remote sensing imagery","authors":"Hanwen Zhang, Shan Wei, Xindan Liang, Yiping Chen, Hongsheng Zhang","doi":"10.1016/j.jag.2024.104310","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104310","url":null,"abstract":"Mangroves, critical for ecological sustainability, are challenging to map accurately due to their fragmented nature and difficult accessibility. Existing datasets, often constrained to 10 m or above resolutions, could misrepresent fragmented mangrove regions and suffer from sampling biases, limiting their regional applicability. Furthermore, scale conversion’s spatial and statistical implications on mangrove mapping accuracy and area estimation remain largely unexplored. This study proposes a novel framework that leverages UHR (0.2 m) aerial photos and the DeepLabV3+ model for fine-scale mapping and systematically simulates and quantifies scale-induced effects. The resultant 20 cm-resolution mangrove map of Hong Kong achieved an overall accuracy (OA) of 92.1 %, with up to 53 % improvement compared to various existing datasets. It delineates complex boundaries in diverse coastal settings while preserving the structural integrity of fragmented patches. The total mangrove area in Hong Kong is estimated at ∼720 ha, with Deep Bay comprising 77.5 %. The scale effects analysis revealed pronounced sensitivity in fragmented habitats, where each 1 m increase in resolution could result in an average area underestimation of 5000 m<ce:sup loc=\"post\">2</ce:sup> and up to 25 % OA degradation when transitioning from 0.2 m to 30 m. Moreover, integrating patch geometry and scale responses indicated that 6 m is the optimal scale for monitoring. Beyond this, OA could sharply decline to below 82 % at the commonly used 10 m resolution and drop as low as 66 % at 30 m. These findings highlight the critical importance of fine-scale mapping using UHR images for effective mangrove conservation and management.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"24 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A gravity-inspired model integrating geospatial and socioeconomic distances for truck origin–destination flows prediction","authors":"Yibo Zhao, Shifen Cheng, Song Gao, Feng Lu","doi":"10.1016/j.jag.2024.104328","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104328","url":null,"abstract":"Accurately predicting truck origin–destination (OD) flows is essential for optimizing logistics systems and promoting coordinated regional development. Existing methods typically assume a monotonic decrease in truck OD flows with increasing geospatial distance, which oversimplifies the complex non-monotonic distribution patterns observed in practice. Moreover, these methods overlook interregional socioeconomic distances and their interaction with geospatial distances, thereby limiting the prediction accuracy and reliability. This study introduces a gravity-inspired model that integrates both geospatial and socioeconomic distances (GSD-DG) to explicitly represent their combined influence on truck OD flows. Specifically, we 1) develop a geospatial distance relation graph using the Weibull function to model the complex spatial distribution patterns of truck OD flows with varying geospatial distances; 2) propose a gravity-inspired representation learning method based on graph attention mechanism to quantify the influence of socioeconomic distance on truck OD flows; and 3) construct a deep gravity model that integrates these distances and their interactions to capture their non-linear relationship with truck OD flows. Extensive experiments on four datasets with varying spatial scale and economic development levels demonstrate that the GSD-DG model improves the robustness and prediction accuracy across diverse spatial distribution patterns, reducing RMSE by 14.2%–85.8% and MSE by 23.5%–92.5% compared to the six baseline models. Incorporating socioeconomic distance and its interaction with geospatial distance further reduces RMSE by 8.5%–36.0%. Additionally, explainable artificial intelligence techniques highlight how these distances affect truck OD flows, providing valuable policy insights for logistics planning and coordinated regional development.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"149 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying indoor navigation map information considering the dynamic map elements for scale adaptation","authors":"Jingyi Zhou, Jie Shen, Cheng Fu, Robert Weibel, Zhiyong Zhou","doi":"10.1016/j.jag.2024.104323","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104323","url":null,"abstract":"The indoor map is an indispensable component to visualize human users’ real-time locations and guided routes to find their destinations in large and complex buildings efficiently. The map design in existing mobile indoor navigation systems mostly considers either the user locations or the route segments but seldom considers the adaptation of the base map scale. Due to uneven densities of spatial elements, the complexity of routes, and the diversity of spatial distribution of navigation decision points, the base map information of indoor navigation maps varies greatly. Hence, it is inevitable to cause an inappropriate amount of map information at different locations and routes. Additionally, existing multi-scale representations of indoor maps are limited to certain scales but not adapted to building locations. Users have to adjust the map scales frequently through multiple interactions with the navigation system. In this study, we propose a method that considers the dynamic elements of indoor maps to quantify the map information for scale adaptation. The indoor navigation map information calculation includes both geometry information and spatial distribution information of static base map elements (area elements, POIs) and dynamic route elements (segments, decision points). The total map information is quantified by setting the weights of the two types of elements. An empirical study on indoor navigation map selection was conducted. Results show that the quantified map information using the proposed method can reflect a user-desired map better than the traditionally used scales.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"85 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PCET: Patch Confidence-Enhanced Transformer with efficient spectral–spatial features for hyperspectral image classification","authors":"Li Fang, Xuanli Lan, Tianyu Li, Huifang Shen","doi":"10.1016/j.jag.2024.104308","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104308","url":null,"abstract":"Hyperspectral image (HSI) classification based on deep learning has demonstrated promising performance. In general, using patch-wise samples helps to extract the spatial relationship between pixels and local contextual information. However, the presence of background or other category information in an image patch that is inconsistent with the central target category has a negative effect on classification. To solve this issue, a patch confidence-enhanced transformer (PCET) approach for HSI classification is proposed. To be specific, we design a patch quality assessment (PQA) branch model to evaluate the input patches during training process, which effectively filters out the intrusive non-central pixels. The output confidence of the branch model serves as a quantitative indicator of the contribution degree of the input patch to the overall training efficacy, which is subsequently weighted in the loss function, thereby endowing the model with the capability to dynamically adjust its learning focus based on the qualitative of the inputs. Second, a spectral–spatial multi-feature fusion (SSMF) module is devised to procure scores of representative information simultaneously and fully exploit the potential of multi-scale feature HSI data. Finally, to enhance feature discrimination, global context is efficiently modeled using the efficient additive attention transformer (<mml:math altimg=\"si4.svg\" display=\"inline\"><mml:mrow><mml:msup><mml:mrow><mml:mi mathvariant=\"normal\">EA</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mi mathvariant=\"normal\">T</mml:mi></mml:mrow></mml:math>) module, which streamlines the attention process and allows the model to learn efficient and robust global representations for accurate classification of the central pixel. A series of experimental results executed on real HSI datasets have substantiated that the proposed PCET can achieve outstanding performance, even when only 10 samples per category are used for training.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"32 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plant Phenology Index leveraging over conventional vegetation indices to establish a new remote sensing benchmark of GPP for northern ecosystems","authors":"Hanna Marsh, Hongxiao Jin, Zheng Duan, Jutta Holst, Lars Eklundh, Wenxin Zhang","doi":"10.1016/j.jag.2024.104289","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104289","url":null,"abstract":"Northern ecosystems, encompassing boreal forests, tundra, and permafrost areas, are increasingly affected by the amplified impacts of climate change. These ecosystems play a crucial role in determining the global carbon budget. To improve our understanding of carbon uptake in these regions, we evaluate the effectiveness of employing the physically-based Plant Phenology Index (PPI) to estimate gross primary productivity across ten different ecosystems. Based on eddy-covariance measurements from 65 sites, the vegetation index (VI)-driven GPP models (six different algorithms) are calibrated and validated. Our findings highlight that the Michaelis–Menten algorithm has the best performance and PPI is superior to the other five VIs, including NDVI, NIRv, EVI-2, NDPI, and NDGI, at predicting gross primary productivity (GPP) rates on a weekly scale (with an average R<mml:math altimg=\"si21.svg\" display=\"inline\"><mml:msup><mml:mrow></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math> of 0.64 and RMSE of 1.70 g C m<mml:math altimg=\"si2.svg\" display=\"inline\"><mml:msup><mml:mrow></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math> d<mml:math altimg=\"si3.svg\" display=\"inline\"><mml:msup><mml:mrow></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>), regardless of short-term environmental constraints on photosynthesis. Through our scaled-up analysis, we estimate the annual GPP of the vast 37 million km<mml:math altimg=\"si21.svg\" display=\"inline\"><mml:msup><mml:mrow></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math> study region to be around 22 Pg C yr<mml:math altimg=\"si3.svg\" display=\"inline\"><mml:msup><mml:mrow></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>, aligning with other recently developed products such as GOSIF-GPP, FluxSat-GPP, and FLUXCOM-X GPP. Derived from a climate-independent approach, the PPI-GPP product offers distinct advantages in exploring relationships between climate variables and terrestrial ecosystem productivity and phenology. Furthermore, this product holds significant value for assessing forestry and agricultural production in northern regions and for benchmarking terrestrial biosphere models and Earth system models.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"125 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau","authors":"Renzhe Wu, Guoxiang Liu, Xin Bao, Jichao Lv, Age Shama, Bo Zhang, Wenfei Mao, Jie Chen, Zhihan Yang, Rui Zhang","doi":"10.1016/j.jag.2024.104329","DOIUrl":"https://doi.org/10.1016/j.jag.2024.104329","url":null,"abstract":"Glacial lakes (GLs), which serve as natural reservoirs, are also prospective sources of risk, and their risk levels are continuously increasing as a result of global climate warming. Nevertheless, GLs are situated in mountainous and valley regions, which are distinguished by their complex terrain and unpredictable weather conditions. This leads to restricted availability of optical imagery as a consequence of the frequent cloud cover. Synthetic Aperture Radar (SAR), however, encounters issues with geometric distortion. This paper introduces an unsupervised method based on geometric distortion detection (without orbit state information) and historical positioning using dual-orbit SAR imagery to research GL extraction effectively. This method detects low-quality pixels from dual-orbit SAR imagery through geometric distortion. It extracts GLs using a majority voting integration of unsupervised classification algorithms constrained by historical GL center points. The Southeastern Tibetan Plateau (SETP) was chosen as a representative region for the study, and experiments were conducted from July to August 2018 using dual-orbit Sentinel-1 imagery. A total of 600 refined samples were used for comparative verification. The results demonstrate that this method is capable of reliably identifying the active and passive geometric distortions in SAR imagery. The fusion of dual-orbit SAR based on geometric distortion can effectively enhance the classification performance of remote sensing imagery and achieve the acquisition of GL water storage area during the flood season. The geometric distortion rate was reduced from 29.9% to 7.9% after fusion correction, and the accuracy, recall rate, precision, Intersection over Union (IoU), and F1-Score were 0.989, 0.900, 0.908, 0.825, and 0.904, respectively. This serves as a reference for research that investigates the mechanisms of glacier-GL-climate change.","PeriodicalId":50341,"journal":{"name":"International Journal of Applied Earth Observation and Geoinformation","volume":"11 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}