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SSRN 2024年

作者： Li, Linxin Hu, Ting Yang, Guangyi He, Wei Zhang, Hongyan State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China School of Electronic Information Wuhan University Wuhan430079 China School of Computer Science China University of Geosciences Wuhan430074 China

Poverty is one of the most important social problems facing our present generation. Accurate identification of impoverished households is a primary concern as China enters the post-poverty alleviation era. However, few studies offer poverty estimates at a fine scale to help targeted poverty reduction. Therefore, this study constructed a comprehensive regional development index (CRDI) by integrating SDGSAT-1 glimmer imagery, land cover map, point of interest (POI), OpenStreetMap (OSM), and digital elevation model (DEM) data, aiming to evaluate the development level and relative poverty of Wuling Mountain area at a 10-meter resolution. The results demonstrated that over 90% of key assisted villages were identified as having a low CRDI value, thereby confirming the remarkable effectiveness of the proposed 10-meter-resolution CRDI map in identifying poverty at village level. The correlation analysis between multidimensional poverty index (MPI) and CRDI showed the superiority of CRDI products, with a statistically significant determination coefficient of 0.47. Besides, spatial autocorrelation analysis revealed that poverty in Wuling Mountain area exhibits significant clustering patterns, with underdeveloped areas concentrated in the central and southwestern regions. The findings of our study can offer insights into both macro-level and micro-scale poverty alleviation strategies, facilitating targeted prevention of poverty relapse. © 2024, The Authors. All rights reserved.

关键词： Surveying

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Masking Radar Signals with Two Masks Overlapping in Frequency Domain

Masking Radar Signals with Two Masks Overlapping in Frequenc...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Rui Ma Shenghua Zhou Hui Ma Jingshu Qing Jizhuan Li Aihua Li National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Science and Technology on Millimeter-Wave Laboratory Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Electronic attack (EA) equipment can interfere radar systems by emitting interference signals with the assistant of the electronic support measurement (ESM) equipment. In this case, masking signalss can be designed to deceive ESM equipment and prevent EA equipment from emitting interference. This paper proposes an active anti-interference signal design method for Multiple-input Multiple-output (MIMO) radar. Designed masking signals cover a radar signal in the time domain, but the frequency band of the masking signals in the frequency domain does not completely overlap with the radar signal, making it difficult for an enemy ESM equipment to determine whether the obtained signal is a radar signal or interference masking signals. To reduce the cross correlation sidelobes between radar signals and masking signals, the masking signals are designed with upper and lower frequency bands with an identical center frequency, and then the spectrum of the masking signals can be efficient shifted to achieve the spectrum overlap, therefore, low cross correlation sidelobes can be ensured. Simulation results indicate that the propsoed algorithm can reduce the cross-correlation sidelobe level to the level of −100 dB, and it is also shown that the proposed algorithm is robust to the radar transmission delay.

关键词： Time-frequency analysis Correlation Radar measurements Simulation MIMO radar Noise Radar detection Radar equipment Time-domain analysis Signal design

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WHU-RuR+: A benchmark dataset for global high-resolution rural road extraction

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International Journal of Applied Earth Observation and Geoinformation 2025年 139卷

作者： Wang, Ningjing Wang, Xinyu Pan, Yang Yao, Wanqiang Zhong, Yanfei College of Geomatics Xi'an University of Science and Technology Xi'an 710054 China School of Remote Sensing and Information Engineering Wuhan University 430079 China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS) Wuhan University 430079 China

Efficient and accurate extraction of road networks from high-resolution satellite images is essential for urban planning, construction, and traffic management. Recently, various road datasets and advances in deep learning models have greatly enhanced road extraction techniques. However, challenges remain when trying to apply existing research to rural areas. Specifically, most public road datasets focus on urban areas and only contain a small number of rural scenes with complex backgrounds. The application of current public datasets for rural road extraction is challenging due to significant stylistic differences between urban and rural roads. In this article, a large-scale high-resolution remote sensing road dataset, termed WHU-RuR+, is proposed for rural road extraction, which contains 36,098 pairs of 1024 × 1024 high-resolution satellite images with the corresponding road annotation, covering a 6866.35 km² of rural areas in eight countries around the world. In addition, the article comprehensively summarizes the characteristics of this dataset and comprehensively evaluates advanced deep learning methods for road extraction on the WHU-RuR + dataset. Experimental results show that this dataset not only meets the application needs of rural road mapping but also has great practical application potential. At the same time, this article analyzes the challenges faced by rural road extraction and explores future research directions. The proposed WHU-RuR + rural road dataset will be available at the following URL: http://***/WHU_RuR+_***. © 2025 The Author(s)

关键词： Deep learning Road dataset Road extraction Rural road

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Multi-Modal Multi-Task Learning for Semantic Segmentation of Land Cover Under Cloudy Conditions

Multi-Modal Multi-Task Learning for Semantic Segmentation of...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Fang Xu Yilei Shi Wen Yang Xiaoxiang Zhu School of Electronic Information Wuhan University Data Science in Earth Observation Technical University of Munich Remote Sensing Technology Technical University of Munich

The majority of the Earth’s surface is covered by clouds, causing optical images to suffer serious degradation of ground information. Synthetic Aperture Radar (SAR) images with the cloud-penetration capability could provide supplementary information to optical images. Thus, the fusion of optical and SAR image can remarkably improve the interpretation accuracy under cloudy conditions. In this paper, we propose to exploit related cloud removal task for accurate multi-modal semantic segmentation of land cover. Towards this goal, we develop an end-to-end learnable architecture which solves the tasks of cloud removal and semantic segmentation of land cover jointly. The cloud removal task encourages to learn knowledgeable features to overcome negative effects of semantic ambiguity. Our experiments show that the proposed algorithm can effectively improve the semantic segmentation accuracy under cloudy conditions.

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Multi-Scale Correlation Reveals the Evolution of Socio-Natural Contributions to Tropospheric HCHO Over China from 2005 to 2022

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SSRN 2024年

作者： Xia, Hui Wang, Dakang Abad, Gonzalo González Yang, Xiankun Zhu, Lei Pu, Dongchuan Feng, Xu Zhang, Aoxing Song, Zhaolong Mo, Yongru Wang, Jinnian School of Geography and Remote Sensing Guangzhou University Guangzhou510006 China Institute of Aerospace Remote Sensing Innovations Guangzhou University Guangdong Guangzhou China Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States School of Environmental Science and Engineering Southern University of Science and Technology Guangdong Shenzhen China Southern University of Science and Technology China John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States

Monitoring the spatiotemporal distribution of formaldehyde is crucial for reducing volatile organic compounds (VOCs) emissions, and the long-term evolution of socio-natural sources contributions to tropospheric HCHO over China is still unclear. We propose an oversampling algorithm for quantitatively tracking the evolution of uncertainty, which lowers the uncertainty of the original Level 2 OMI HCHO data (50% -105%) to 0-50%, and then we examine the evolution of emissions sources contributions applying multi-scale correlation. We found that the high formaldehyde emissions caused by human activities in eastern China are crossing the Hu Huanyong Line, which was formerly used to demarcate the population distribution. National-scale analysis indicate that HCHO emissions are significantly correlated with per capita Gross Domestic Product (per capita GDP) (r = 0.948) and Normalized Difference Vegetation Index (r = 0.864), but no substantial correlation with Land surface temperature (r = 0.233). A valuable finding at city-scale is that the vast majority of cities exhibits clear latitude zoning characteristics in the correlation between HCHO emissions and per capita GDP. Diagnosis at pixel scale reveals that anthropogenic emissions continue to weaken the contributions of HCHO emissions caused by the increase in vegetation proportion. NDVI=0.8 is the critical characteristic point where the contribution of natural source emissions exceeds that of anthropogenic sources, while the point presents a decreasing trend in recent years due to the enhancement of human activity levels. Rise in LST over vegetation areas show a positive driving effect on formaldehyde emissions, but continuous urbanization is diminishing this contribution. NDVI=0.8 is a characteristic point to determine whether the contribution proportion of regional surface temperature to formaldehyde emissions from vegetation begun to rise. Our research identifies the evolutionary process and characteristics of the spati

关键词： Vegetation

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UCDFormer: Unsupervised Change Detection Using Real-time Transformers

UCDFormer: Unsupervised Change Detection Using Real-time Tra...

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Urban remote sensing Joint Event

作者： Qingsong Xu Yilei Shi Xiao Xiang Zhu Data Science in Earth Observation Technical University of Munich Munich Germany Chair of Remote Sensing Technology Technical University of Munich Munich Germany

Change detection (CD) by comparing two bitemporal images is one of the most challenging tasks in remote sensing. With the advantages of requiring no cumbersome labeled change information, unsupervised CD has attracted extensive attention from researchers. However, rarely existing unsupervised CD approaches consider the seasonal differences in multi-temporal images. To this end, we propose a change detection with a domain shift setting for remote sensing images. Furthermore, we propose a novel unsupervised CD method using a real-time transformer, called UCDFormer. Specifically, a transformer-driven image translation is first proposed to mitigate domain shift between two images with real-time efficiency. Importantly, to effectively reduce the translation strength of changed pixels and to increase the translation of unchanged pixels, a domain-specific affinity weight is computed in an unsupervised fashion for a weighted translation loss. After image translation, we can generate the difference map between the translated before-event image and the original after-event image. Then, classification maps from the difference map are obtained by fuzzy c-means (FCM) clustering and adaptive threshold. However, these detection results are not very reliable. Thus, a novel reliable pixel extraction module is proposed to select significantly changed/unchanged pixel positions by fusing the results of FCM clustering and adaptive threshold. These selected pixel pairs are used to learn a binary classifier, and the other pixel pairs will be classified by this classifier to obtain the final CD results. Experimental results on different unsupervised CD tasks with seasonal changes demonstrate the effectiveness of the proposed UCDFormer compared with several other related methods.

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A Comprehensive Framework for Assessing the Spatiotemporal Impact of Land Use and Cover Change on Lake Eutrophication

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SSRN 2024年

作者： Lin, Yi Zhong, Daiqi Rong, Yu Yu, Jie Li, Lang Chen, Xin Zhou, Xuefei Wang, Hongtao College of Surveying and Geo-Informatics Tongji University Shanghai200092 China Research Center for Remote Sensing Technology and Application Tongji University Shanghai200092 China Xi'an Aerospace Remote Sensing Data Technology Co. Ltd Xi'An710054 China College of Environmental Science and Engineering Tongji University Shanghai200092 China

Excessive nitrogen and phosphorus (N/P) input is the important reason for lake eutrophication, a widespread environmental problem that harms freshwater ecosystems worldwide. Land use/cover changes (LUCC) strongly affect the migration and transformation of N/P on land. To deeply understand the spatiotemporal impact of LUCC on N/P distribution, this study proposes an optimized framework, InVEST-UM, by integrating an unmixing algorithm with the conventional InVEST model. A comprehensive and intuitive index (LPI) was developed for impact assessment and spatialization. This index was then used to analyze the corresponding spatiotemporal evolution pattern based on long-term, multi-sources RS data. The results indicate the proposed InVEST-UM framework can produce highly accurate N/P estimation with and effectively depict the spatiotemporal impact of LUCC on lake eutrophication. Notably, a strong correlation coefficient of 0.94 exists between LPI and the eutrophication degree of Dianshan Lake. Our findings reveal a strong positive correlation (0.91) between vegetation area and LUCC purification capacity for N/P. Conversely, the expansion of bare lands, water bodies, and artificial surfaces weakens the LUCC purification capacity, increasing the eutrophication risk. By employing this comprehensive framework, this study aims to provide valuable insights into the long-term dynamics of LUCC changes and their implications for lake ecosystems. This research contributes to the protection and sustainability of lake ecosystems and supports decision-making processes for improving water quality and ecological balance. © 2024, The Authors. All rights reserved.

关键词： Purification

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An Independent Degree-eight Mars Gravity Field Model and the Expected Results from the Tianwen-1 Mission

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Research in Astronomy and Astrophysics 2023年第10期23卷 267-276页

作者： Shanhong Liu Jianfeng Cao Jianguo Yan Hao Huang Xie Li Jean-Pierre Barriot National Key Laboratory of Science and Technology on Aerospace Flight Dynamics Beijing 100094China Beijing Aerospace Control Center Beijing 100094China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China Department of Astronomy Beijing Normal UniversityBeijing 100875China Observatoire Géodésique de Tahiti University of French PolynesiaF-98702 Faa’aBP 6570 TahitiFrench PolynesiaFrance

Tianwen-1 is China's first independent interplanetary exploration mission,targeting Mars,and includes orbiting,landing,and rover *** to previous Mars missions,the Tianwen-1 orbiter was designed for polar orbits during the scientific mission period but has an exceptional eccentricity of approximately *** provide the first independent eight-degree Martian gravity field model in this paper,which was developed exclusively by a team working in China with our independent software as well,based on about two months of radiometric Doppler and range data from only the Tianwen-1 *** model is independent from the models created by the groups at NASA Jet Propulsion Laboratory and Goddard Space Flight Center in the United States,as well as the Centre National d'Etudes Spatiales in ***,in order to optimize the engineering and scientific benefits,we proposed a number of potential orbits for the extended Tianwen-1 *** order to solve a higher-degree independent Mars gravity field model,the viability of modifying the perigee height was investigated,with the priority considerations of fuel savings and implementation hazards being controlled.

关键词： gravitation planets and satellites:fundamental parameters methods:observational

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A Multi-Site Photometric Analysis of Biomass Burning Activity in South-East Asia During October 2023

A Multi-Site Photometric Analysis of Biomass Burning Activit...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Santo V. Salinas Tan Li Fernando Santos Liew Soo Chin Moritz Müeller Cheah Wee Centre For Remote Imaging Sensing and Processing (CRISP) National University of Singapore Singapore Faculty of Engineering Computing and Science Swinburne University of Science and Technology Kuching Malaysia Institute of Ocean and Earth Sciences Universiti Malaya Kuala Lumpur Malaysia

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Satellite and ground level observations during the period of August to October 2023 captured an elevated number of fire hot spots and biomass burning (smoke) activity over the South-East Asia landmasses of Sumatra and Borneo. Over this region, fire activity can be a yearly occurrence due to prevalent regional dryness and low rainfall, such activity can also be enhanced by other tropical phenomena like El Nino Southern Oscillation. In this paper, we present a multi—site photometric analysis of smoke emissions during this period with emphasis on aerosol physical and optical characteristics that would allow us to differentiate the source levels of emissions, aerosol composition and possibly transport pathways to downwind receptor sites.

关键词： Satellites Rain Stimulated emission Asia Geoscience and remote sensing Aerosols Optical variables control

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Treatment of industrial wastewater using coconut shell based activated carbon

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Materials Today: Proceedings 2021年 81卷 1167-1171页

作者： Packialakshmi, S. Anuradha, B. Nagamani, K. Sarala Devi, J. Sujatha, S. Department of Civil Engineering Sathyabama Institute of Science and Technology India Department of Civil Engineering Chennai Institute of Technology India Centre for Remote Sensing and Geoinformatics Sathyabama Institute of Science and Technology India Queen Mary's College Chennai India Department of Civil Engineering K.Ramakrishnan College of Technology Trichy India

Coconut Shell is a waste product derived from agriculture which is utilized as bio adsorbent for treating the wastewater discharged from electroplating industries. The physio chemical characterization of raw waste water and batch adsorption study using coconut shell charcoal (CSC) with a reference to effluent characterization is conducted to identify the potential contaminant and efficiency of adsorbent. The parameters such as effective particle size of adsorbent, contact time and dosage influencing the treatment efficiency of zinc and potassium which are identified as the potential contaminant in the waste water. Increase in dosage and specific surface area with reduced particle size increases the treatment efficiency up to the approved level, beyond which the portion adsorbed which remains constant. It is apparent that a dosage of 15 g/l and duration of 90 min is satisfactory to remove 90% of phosphate and 97% of zinc for 150 µm particle size. The adsorption equilibrium data were tailored well with the Freundlich isotherm for the removal of zinc and potassium. The baseline study is manifested the potential of CSC in the reduction of zinc and potassium from the industrial waste water. © 2021

关键词： Activated carbon

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