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Spatiotemporal influence of driving factors on water conservation in underdeveloped plateau regions: a case in the Yellow River Basin of Sichuan, China

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Journal of Mountain science 2025年第4期22卷 1289-1305页

作者： WANG Xuan MA Lei LU Heng LIU Chao NIE Ruihua LI Naiwen TAN Xiao YANG Zhengli Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China State Key Laboratory of Hydraulics and Mountain River Engineering College of Hydraulic and Hydroelectric EngineeringSichuan UniversityChengdu 610065China

The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainable *** effectively enhancing WC necessitates a comprehensive understanding of its driving factors and corresponding intervention strategies,existing studies have largely neglected the spatiotemporal heterogeneity of both natural and socio-economic ***,this study explored the spatiotemporal heterogeneity of WC drivers in YRS using multi-scale geographically weighted regression(MGWR)and geographically and temporally weighted regression(GTWR)models from an eco-hydrological *** discovered that downstream regions,which are more developed,achieved significantly better WC than upstream *** results also demonstrated that the influence of temperature and wind speed is consistently dominant and temporally stable due to climate stability,while the influence of vegetation shifted from negative to positive around 2010,likely indicating greater benefits from understory *** growth positively impacted WC in upstream regions but had a negative effect in the more developed downstream *** findings highlight the importance of targeted water conservation strategies,including locally appropriate revegetation,optimization of agricultural and economic structures,and the establishment of eco-compensation mechanisms for ecological conservation and sustainable development.

关键词： Water conservation Multi-scale Geographically Weighted Regression Geographically and Temporally Weighted Regression The Yellow River Basin in Sichuan Province Spatiotemporal variation

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A novel adhesive bonding process in reflecting mirror 9

A novel adhesive bonding process in reflecting mirror

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9th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Zhang, Xue-Min Wang, Shi-Qi Cai, Jia-Wen Jin, Guang Institute of Aerospace Science and Technology School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China

ISBN: (纸本)9781510664432

The way the reflecting mirror is attached to the support structure can remarkably impact its surface shape accuracy. In order to improve the surface accuracy of the mirror, it is necessary to design a suitable adhesive bonding process. We finally designed an adhesive bonding process with uniform large gap gluing solution along the outer ring of the mandrel. By theoretically treating the cured adhesive as a linear elastic material, the thermal stress on the reflector under this scheme was analyzed, and the specific adhesive area was calculated. The surface shape accuracy of the reflector is analyzed by using the finite element analysis method. The analysis results obtained that the surface shape accuracy of the main reflector under the coupling effect of gravity load and temperature load satisfies RMS ≤ λ/50(λ=632.8nm). Also we tested the surface shape accuracy of the reflecting mirror, an interference self-accurate detection optical path is constructed and we got the surface shape accuracy which is 0.025λ, which verifies the feasibility of the new bonding process. © 2023 SPIE.

关键词： Adhesives

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Sparse Nonnegative Matrix Factorization based on Double Low-Rank and Sparse Matrix Factorization Model for Spectral Variability 7

Sparse Nonnegative Matrix Factorization based on Double Low-...

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2023 7th International Symposium on Computer science and Intelligent Control, ISCSIC 2023

作者： Yang, Tingting Song, Meiping Li, Sen Dalian Maritime University The Center of Hyperspectral Imaging in Remote Sensing Information Science and Technology College Dalian China

ISBN: (纸本)9798350342987

To reduce the interference of complex imaging environment on spectral unmixing, we introduce a double low-rank and sparse matrix factorization model (LRSMD) (DLRSMD) to better characterize the intrinsic and variant endmember components in the scene, and propose a sparse NMF based on DLRSMD (DLRSNMF) by accounting for the sparsity of intrinsic and variant abundances. The sparsity of abundances not only satisfies the practical significance of abundances, but also effectively promotes the representation ability of endmembers. The experimental results also demonstrate the better performance of DLRSNMF, which can provide reliable endmembers and abundances. © 2023 IEEE.

关键词： Matrix algebra

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Research on AGV task path planning based on improved A^(*) algorithm

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Virtual Reality & Intelligent Hardware 2023年第3期5卷 249-265页

作者： Xianwei WANG Jiajia LU Fuyang KE Xun WANG Wei WANG School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China School of Remote Sensing and Geomatics Nanjing University of Information Science&TechnologyNanjing 210044China School of Internet of Things Engineering Wuxi UniversityWuxi 214000China

Background Automatic guided vehicles(AGVs)have developed rapidly in recent years and have been used in several fields,including intelligent transportation,cargo assembly,military testing,and others.A key issue in these applications is path *** path planning results based on known environmental information are used as the ideal path for AGVs combined with local path planning to achieve safe and rapid arrival at the *** the global planning method,the ideal path should meet the requirements of as few turns as possible,a short planning time,and continuous path *** We propose a global path-planning method based on an improved A^(*)*** robustness of the algorithm was verified by simulation experiments in typical multiobstacle and indoor *** improve the efficiency of the path-finding time,we increase the heuristic information weight of the target location and avoid invalid cost calculations of the obstacle areas in the dynamic programming ***,the optimality of the number of turns in the path is ensured based on the turning node backtracking optimization *** the final global path needs to satisfy the AGV kinematic constraints and curvature continuity condition,we adopt a curve smoothing scheme and select the optimal result that meets the *** Simulation results show that the improved algorithm proposed in this study outperforms the traditional method and can help AGVs improve the efficiency of task execution by planning a path with low complexity and ***,this scheme provides a new solution for global path planning of unmanned vehicles.

关键词： Autonomous guided vehicle(AGV) Map modeling Global path planning Improved A^(*)algorithm Path optimization Bezier curves

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AIDEDNet:anti-interference and detail enhancement dehazing network for real-world scenes

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Frontiers of Computer science 2023年第2期17卷 225-235页

作者： Jian ZHANG Fazhi HE Yansong DUAN Shizhen YANG School of Computer Science Wuhan UniversityWuhan 430072China College of Sport Engineering and Information Technology Wuhan Sports UniversityWuhan 430079China School of Remote Sensing and Information Engineering Wuhan UniversityWuhan 430072China

The haze phenomenon seriously interferes the image acquisition and reduces image *** to many uncertain factors,dehazing is typically a challenge in image *** most existing deep learning-based dehazing approaches apply the atmospheric scattering model(ASM)or a similar physical model,which originally comes from traditional dehazing ***,the data set trained in deep learning does not match well this model for three ***,the atmospheric illumination in ASM is obtained from prior experience,which is not accurate for dehazing ***,it is difficult to get the depth of outdoor scenes for ***,the haze is a complex natural phenomenon,and it is difficult to find an accurate physical model and related parameters to describe this *** this paper,we propose a black box method,in which the haze is considered an image quality problem without using any physical model such as ***,we propose a novel dehazing equation to combine two mechanisms:interference item and detail enhancement *** interference item estimates the haze information for dehazing the image,and then the detail enhancement item can repair and enhance the details of the dehazed *** on the new equation,we design an antiinterference and detail enhancement dehazing network(AIDEDNet),which is dramatically different from existing dehazing networks in that our network is fed into the haze-free images for ***,we propose a new way to construct a haze patch on the flight of network *** patch is randomly selected from the input images and the thickness of haze is also randomly *** experiment results show that AIDEDNet outperforms the state-of-the-art methods on both synthetic haze scenes and real-world haze scenes.

关键词： dehaze anti-interference detail enhancement network

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Large-scale synoptic and weather drivers for the co-occurrence of fine particulate matter and ozone extremes over China

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science China Earth sciences 2025年第5期68卷 1448-1457页

作者： Wei WANG Yiting ZHOU Mengmeng LI Yuting LU Xinyi JIANG Tijian WANG Bingliang ZHUANG Shu LI Chenchao ZHAN Xiaoyun SUN Xin HUANG School of Atmospheric Sciences Nanjing UniversityNanjing 210023China Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences Nanjing UniversityNanjing 210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing 210023China School of Atmospheric Physics Nanjing University of Information Science and TechnologyNanjing 210044China Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing Anhui Institute of Meteorological SciencesHefei 230031China

The co-occurrence of extreme weather events and air pollution events,such as elevated fine particulate matter(PM2.5)and ozone(O3),poses a significant threat to human health,a concern that is anticipated to be exacerbated under climate *** a 9-year dataset of surface air pollutant observations and reanalysis data,this study investigated the large-scale synoptic and weather drivers behind the co-occurrence of PM2.5and O3extremes in *** co-occurrences are mostly observed during the warm season(March to October)and are particularly prevalent(25.8 days y^(r-1))in cleaner regions situated in South *** co-occurrences are usually associated with elevated air temperatures(~27.7°C),lower wind speeds(~1.4 ms^(-1))and atmospheric humidity(~51.9%).Notably,a substantial proportion of these co-occurrences(up to 76.4%)coincide with extreme weather linked to stagnant weather and extreme heat *** employing an objective clustering approach,we identified the typical synoptic systems conducive to the widespread co-occurrence of PM2.5and O3extremes,including the Western Pacific Subtropical High,Northeast Blocking High,Mongolian High,and *** findings underscore a robust correlation between the co-occurrence of PM2.5and O3extremes and the annual variations in extreme weather and prevailing weather patterns,suggesting an increased likelihood of concurrent air pollution and extreme weather episodes under a warming climate across China.

关键词： Co-occurrence pollution Ozone PM2.5 Extreme weather T-PCA

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On the occurrence of Sorbus tianschanica Rupr. (Rosaceae), a climate relict from Ladakh, Indian Trans Himalaya

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International Journal of Environmental Studies 2024年第6期81卷 2777-2789页

作者： Bushra, Aimon Stanzin, Jikmat Kumar, Amit Talukdar, Gautam Padalia, Hitendra Rawat, Gopal Singh Habitat Ecology Department Wildlife Institute of India Dehradun India Forestry and Ecology Department Indian Institute of Remote Sensing Indian Space Research Organisation Dehradun India Uttarakhand State Council for Science and Technology Dehradun India

A new distribution record of Sorbus tianschanica Rupr., a tree or shrub native to the temperate northern hemisphere, is reported for Ladakh. Thirty-one individuals of S. tianschanica were seen growing on exposed cliffs and also on shadowed cliff bases in a remote valley in the western Ladakh region of Kargil. A detailed taxonomic description, diagnostic features and notes on the habitat of the species along with its distribution and climatic range in the adjacent phytogeographic regions (Gilgit-Baltistan, Tajikistan, Kyrgyzstan, Kazakhstan and some provinces of China) are provided. Further, information on the species palaeoecology and biogeography has been reviewed, and its conservation significance is discussed. Our findings emphasise the importance of keeping records of local biodiversity up to date. This is critical for implementing global biodiversity policies and meeting conservation goals. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Biotic

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Intercomparison of gross primary productivity in spatio-temporal distribution over a typical tropical region based on different datasets

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Environmental science and Pollution Research 2024年第50期31卷 60650-60667页

作者： Zhang, Sha Bai, Yun Zhang, Jiahua Zheng, Xin Ali, Shawkat Ullah, Hidayat The Key Laboratory of Earth Observation of Hainan Province Hainan Aerospace Information Research Institute Sanya572000 China School of Geographic Sciences Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change Hebei Normal University Shijiazhuang050024 China Remote Sensing and Digital Earth Center College of Computer Science and Technology Qingdao University Qingdao266071 China Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China

Gross Primary Productivity (GPP) plays a vital role in the carbon cycle of terrestrial ecosystems. For the purpose of assessing the performance of various GPP products in a typical tropical area, this study conducted an intercomparison of seven different GPP products over Hainan Island, China, and analyzed spatiotemporal characteristics of GPP in different elevation regions and vegetation types over study area. The results showed that although the GPP spatial distribution pattern over Hainan Island, as presented by different GPP products, is similar— showing that GPP values in the southwest are higher than those in the northeast— there are significant differences in the spatial distributions and magnitudes of each GPP product. The multi-annual mean GPP values from the seven GPP products exhibited similar temporal variation trends, with GOSIF being obviously higher than other GPP products. The GPP products indicated significant differences in different elevation and vegetation type groups. The GPP gap between GLASS AVHRR and BESS V2 decreases slightly with the increase in elevation. Most GPP products show a consistent change trend over time. There were also significant differences in the results of significance tests for the change trends of GPP products. Though GOSIF is significantly higher than other GPP products, it demonstrated a relatively high correlation with all GPP products, while AGPP exhibited relatively low correlations with all GPP products. The quantitatively comparative analysis of seven different GPP products in this study is valuable for improving GPP retrieval models and can also serve as a scientific reference for the application of GPP products in tropical region vegetation studies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Miocene

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Robust template feature matching method using motion-constrained DCF designed for visual navigation in asteroid landing

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Astrodynamics 2023年第1期7卷 83-99页

作者： Yaqiong Wang Xiongfeng Yan Zhen Ye Huan Xie Shijie Liu Xiong Xu Xiaohua Tong College of Surveying and Geo-Informatics and Shanghai Key Laboratory of Space Mapping and Remote Sensing for Planetary EaplorationTongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Shanghai 200092China

A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing *** on the visual navigation framework and motion characteristics of asteroids,a robust and efficient template feature matching method is proposed to adapt to feature distortion and scale change cases for visual navigation of *** proposed method is primarily based on a motion-constrained discriminative correlation filter(DCF).The prior information provided by the motion constraints between sequence images is used to provide a predicted search region for template feature ***,some specific template feature samples are generated using the motion constraints for correlation filter learning,which is beneficial for training a scale and feature distortion adaptive correlation filter for accurate feature ***,average peak-to-correlation energy(APCE)and jointly consistent measurements(JCMs)were used to eliminate false *** captured by the Touch And Go Camera System(TAGCAMS)of the Bennu asteroid were used to evaluate the performance of the proposed *** particular,both the robustness and accuracy of region matching and template center matching are *** qualitative and quantitative results illustrate the advancement of the proposed method in adapting to feature distortions and large-scale changes during spacecraft landing.

关键词： discriminative correlation filter(DCF) motion constraints feature distortion adaptive scale changes adaptive template feature matching

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Comparison of corrected surface reflectance, principal component analysis, and kernel principal component analysis for seagrass percent cover mapping using Sentinel-2 based on various regression models

Comparison of corrected surface reflectance, principal compo...

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Active and Passive remote sensing of Oceans, Seas, and Lakes 2024

作者： Wicaksono, Pramaditya Harahap, Setiawan Djody Kamal, Muhammad Kartika, Candra Sari Djati Department of Geographic Information Science Faculty of Geography Universitas Gadjah Mada 55281 Indonesia Remote Sensing Master Program Faculty of Geography Universitas Gadjah Mada 55281 Indonesia

ISBN: (数字)9781510682719

ISBN: (纸本)9781510682702

Variations in seagrass percent cover is one of the key indicators of the health of a seagrass ecosystem. Given that seagrass is regarded as one of the most effective and efficient nature-based solutions for the mitigation and adaptation to climate change, there is a clear need for spatially explicit and extensive information on seagrass percent cover in order to inform management, restoration and conservation efforts. This paper presents a comparison of the accuracy of seagrass percent cover mapping derived from the sunglint and water column corrected surface reflectance (SR), principal component analysis (PCA), and kernel principal component analysis (KPCA) bands of Sentinel-2 L2A. The comparison is based on the application of various regression models, including stepwise regression (SWR), automated partial least squares regression (AutoPLSR), random forest regression (RFR), and support vector machine regression (SVR). The metrics for evaluating the accuracy of different input-model combinations are R², RMSE, and plot 1:1 between reference and estimated percent cover. The findings indicate that incorporating PCA or KPCA into deglint bands and DII within the SWR, SVR, RFR, and AutoPLSR models has varying effects on accuracy. Notably, accuracy consistently improved when deglint bands or DII were combined with both PCA and KPCA, suggesting that this combination is preferable for enhancing model performance and mapping accuracy. © 2025 SPIE.

关键词： Support vector regression

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