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6th International Conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Chen, Yuhan Yan, Qingyun Zhang, Sihan Chen, Ziyi Yang, Xinrui Wang, Jingjing Mu, Fangru Xu, Minghuan Zhang, Zixuan Jiang, Chen Zhao, Dinglong Zhao, Jiechen Qingdao China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9798331541750

Recent advancements in remote sensing have significantly enhanced ground object extraction capabilities from images. However, combining individual ground object extraction with accurate height estimation remains a challenging problem. With the rapid evolution of computer vision techniques, approaches leveraging convolutional neural networks (CNNs) and Transformers have demonstrated promising results in remote sensing image analysis. Despite these advancements, many existing methods superficially adapt models designed for other domains without fully addressing the complex relationships between multiple tasks inherent to remote sensing data. While transfer learning is commonly utilized to integrate multiple tasks, the variability of spectral channels, arising from the deployment of diverse sensors, introduces further complexity in the construction of robust datasets. To address these challenges, in this study, we propose a novel height estimation model that integrates multi-dimensional remote sensing images based on high-quality available datasets of city buildings. Our approach incorporates a shallow texture prompt, and combines a pre-trained model with an instance segmentation framework to better account for the distinct characteristics of remote sensing imagery. The proposed model achieves a correlation coefficient of 0.9439 on the height estimation task. Furthermore, it attains a box APso and mask APso of 73.6% and 71.4%, respectively, on the instance segmentation task, indicating its robustness and accuracy across multiple tasks. This method provides references for the potential applications in polar sea ice, iceberg, and marine ships estimations. © 2024 IEEE.

关键词： Sea ice

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An Anchor-free Method for Aircraft Detection in SAR Images Based on Density Map 2

An Anchor-free Method for Aircraft Detection in SAR Images B...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Chongsong Li, Yuzhao Shang, Yuanzhe Pu, Wei Han, Rui Liu, Weizong Zhang, Yin Wu, Junjie Huang, Yulin Yang, Jianyu University of Electronic Science and Technology of China Chengdu China Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (纸本)9798331515669

The accurate detection of aircraft targets in Synthetic Aperture Radar (SAR) imagery is pivotal for aviation safety monitoring and military strategic planning. This paper addresses the challenges in detecting densely arranged aircraft targets within SAR images by introducing a novel detection network based on aircraft density map prediction. Initially, we propose a method for predicting the aircraft density map, which incorporates an innovative coding and decoding approach for aircraft targets, effectively mitigating the issue of overlapping target labels caused by dense distributions. Subsequently, we devise an aircraft density loss function, tailored specifically for the aircraft density map. This method abandons the reliance on preset anchor boxes and significantly enhances the model's detection performance in scenarios with high-density targets. Comprehensive experimental validation on the SADD public dataset demonstrates that the proposed method exhibits high detection efficiency and accuracy when dealing with small-sized and densely distributed aircraft targets. © 2024 IEEE.

关键词： Aircraft detection

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3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV remote sensing

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Intelligent Automation & Soft Computing 2023年第8期37卷 1655-1672页

作者： Chao Chen Yankun Chen Haohai Jin Li Chen Zhisong Liu Haozhe Sun Junchi Hong Haonan Wang Shiyu Fang Xin Zhang School of Geography Science and Geomatics Engineering Suzhou University of Science and TechnologySuzhou215009China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of ScienceBeijing100101China School of Information Engineering Zhejiang Ocean UniversityZhoushan316022China Marine Science and Technology College Zhejiang Ocean UniversityZhoushan316022China China Aero Geophysical and Remote Sensing Center for Natural Resources Beijing100083China

The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture,spatial res-olution,and multiple parameter categories,which is challenging to achieve using satellite remote *** the convenient,facilitative,and flexible characteristics of UAV(unmanned air vehicle)remote sensing tech-nology,this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral *** professional software,including Context Capture,ENVI,and ArcGIS,a 3D(three-dimensional)campus model,a digital orthophoto map,and multi-spectral remote sensing map drawing are realized,and the geometric accuracy of typical feature selection is *** on a quantitative remote sensing model,the campus ecological environment assessment is performed from the perspectives of vegetation and water *** results presented in this study could be of great significance to the scientific management and sustainable development of regional natural resources.

关键词： Unmanned air vehicle multi-spectral camera oblique photography 3D model construction ecological environment investigation regional scale

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Urban Land Cover Classification from Sentinel-2 Images with Quantum-Classical Network

Urban Land Cover Classification from Sentinel-2 Images with ...

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2023 Joint Urban remote sensing Event, JURSE 2023

作者： Fan, Fan Shi, Yilei Zhu, Xiao Xiang Data Science in Earth Observation Munich Germany Remote Sensing Technology Munich Germany

ISBN: (纸本)9781665493734

Exploiting deep learning techniques to automatically analyze multi-spectral remote sensing imagery plays an essential role in urban land cover and land use classification. However, the computation power required to analyze large earth observation data with complex machine learning models for this task becomes an intractable bottleneck. Leveraging quantum computing might tackle this challenge. In this paper, we present two hybrid quantum-classical deep learning frameworks. They both exploit quantum computing to extract features from multi-spectral images efficiently and classical computing for final classification. The effectiveness of our models is verified with the LCZ42 dataset through the TensorFlow Quantum platform. © 2023 IEEE.

关键词： Quantum computers

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Data-Driven Real-Time Scheduling for Reconfigurable Workshop Using End-To-End Deep Reinforcement Learning

Data-Driven Real-Time Scheduling for Reconfigurable Workshop...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Li, Yuxin Li, Xinyu Gao, Liang Lu, Zhibing Qin, Yan School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Beijing Institute of Remote Sensing Equipment Beijing100000 China

ISBN: (纸本)9798350378658

The multi-variety and small-batch production mode has made reconfigurable manufacturing systems a promising manufacturing paradigm. Meanwhile, frequent dynamic events in the workshop require scheduling methods with fast response capability. Therefore, this paper proposed a deep reinforcement learning (DRL) method for dynamic reconfigurable shop scheduling problem to minimize the total weighted tardiness. Specifically, a real-Time scheduling framework is proposed firstly. Then, a DRL-based agent training algorithm is developed, where the state spaces with generality, rule weighting based action spaces, and a reward function based on the estimated weighted tardiness are designed for two agents. Moreover, a mechanism is proposed for handling new job arrivals and job reworks. The experimental results on 120 instances show that the proposed method can obtain better solutions than nine high-quality composite rules, and can effectively deal with dynamic events through training and learning. © 2024 IEEE.

关键词： Deep reinforcement learning

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Automated and refined wetland mapping of Dongting Lake using migrated training samples based on temporally dense Sentinel 1/2 imagery

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International Journal of Digital Earth 2023年第1期16卷 3199-3221页

作者： Yawen Deng Weiguo Jiang Ziyan Ling Xiaoya Wang Kaifeng Peng Zhuo Li Faculty of Geographical Science State Key Laboratory of Remote Sensing ScienceBeijing Normal UniversityBeijingPeople’s Republic of China Faculty of Geographical Science Beijing Key Laboratory for Remote Sensing of Environment and Digital CitiesBeijing Normal UniversityBeijingPeople’s Republic of China School of Geography and Planning Nanning Normal UniversityNanningPeople’s Republic of China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and TechnologyNanjingPeople’s Republic of China College of Geographic and Environmental Sciences Tianjin Normal UniversityTianjinPeople’s Republic of China

Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and *** this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial *** applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during ***,the continuous change detection(CCD)algorithm was utilized to migrate stable training ***,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated ***,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland *** methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.

关键词： Wetland classification continuous change detection algorithm sample migration time series Dongting Lake wetland Google Earth Engine

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Application and practice of remote sensing technology in analysis of water environment change and ecological effect

Journal of Biotech Research

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Journal of Biotech Research 2024年 16卷 156-166页

作者： Liu, Jiao Yi, Zhenyan Fang, Yahui Wu, Caiyan School of Environment and Resource Southwest University of Science and Technology Sichuan Mianyang China Mianyang S&T City Division of National Remote Sensing Center of China Sichuan Mianyang China

With the intensification of global environmental changes, the changes of water environment and ecosystem have brought profound impacts on human society and natural ecology. In order to monitor and evaluate these changes more accurately and in real time, this study explored the application of remote sensing technology in the analysis of water environment changes and ecological effects and compared it with traditional ground observation technology. The results showed that remote sensing technology had obvious advantages in spatial and temporal resolution, large-scale continuous monitoring, and so on, and could provide more comprehensive and timely information for decision makers and researchers. Especially in the monitoring of water area, water quality, ecosystem structure and ecological service function, remote sensing data and ground observation data were highly consistent. On the whole, remote sensing technology would play an increasingly important role in the study of water environment and ecological effects in the future and was expected to provide strong support for global environmental protection and ecological restoration. © (2024), (Bio Tech System). All Rights Reserved.

关键词： Water quality

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Unveiling urbanization effects on trees outside forests along the urban-rural gradient in megacity Bengaluru

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Forest Ecosystems 2025年第1期12卷 56-65页

作者： Tao Jiang Maximilian Freudenberg Christoph Kleinn V.P.Tewari B.N.Diwakara Nils Nolke Forest Inventory and Remote Sensing Department Faculty of Forest Sciences and Forest EcologyUniversity of GottingenGottingenGermany Himalayan Forest Research Institute ICFREShimlaIndia Institute of Wood Science and Technology IWSTMalleswaramBengaluruIndia

Rapid urbanization has caused significant changes along the urban-rural gradient,leading to a variety of landscapes that are mainly shaped by human *** dynamic interplay also influences the distribution and characteristics of trees outside forests(TOF).Understanding the pattern of these trees will support informed decision-making in urban planning,in conservation strategies,and altogether in sustainable land management practices in the urban *** this study,we employed a deep learning-based object detection model and high resolution satellite imagery to identify 1.3 million trees with bounding boxes within a 250 km^(2)research transect spanning the urban-rural gradient of Bengaluru,a megacity in Southern ***,we developed an allometric equation to estimate diameter at breast height(DBH)from the tree crown diameter(CD)derived from the detected bounding *** study focused on analyzing variations in tree density and tree size along this *** findings revealed distinct patterns:the urban domain displayed larger tree crown diameters(mean:8.87 m)and DBH(mean:43.78 cm)but having relatively low tree density(32 trees per hectare).Furthermore,with increasing distance from the city center,tree density increased,while the mean tree crown diameter and mean tree basal area decreased,showing clear differences of tree density and size between the urban and rural domains in *** study offers an efficient methodology that helps generating instructive insights into the dynamics of TOF along the urban-rural *** may inform urban planning and management strategies for enhancing green infrastructure and biodiversity conservation in rapidly urbanizing cities like Bengaluru.

关键词： Individual tree detection Urbanization Tree density Tree crown diameter

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Comparison of interaction supervised classification methods with indices to identify areas contaminated with hydrocarbons

Comparison of interaction supervised classification methods ...

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2024 International Conference on Technologies and Materials for Renewable Energy, Environment and Sustainability, Tmrees24Gr 2024

作者： Khaleel, Zahraa A. Shaban, Auday H. Al Maliki, Ali A. Department of Remote Sensing & GIS College of Science University of Baghdad Baghdad Iraq Ministry of Science and Technology Environment Water and Renewable Energy Directorate Baghdad Iraq

Field companies and laboratories impose certain controls to preserve the environment, and it has recently been proven that oil facilities are among the main causes of pollution in the environment due to non-compliance with environmental safety instructions and the quantities of crude oil extracted on a daily basis. In this study, some of the remote sensing techniques were used, which is interaction supervised classification by relying on data Real field samples. The study area was classified based on dividing the study area into five regions. To determine the effective ranges for detecting hydrocarbon pollution, it will apply four indices to find out which of them gives better results, based on the range of the wavelength that response to the hydrocarbon components. The image from Landsat were downloaded at the same date of collecting the samples. Adaptive methods were generated along with the four indices and evaluated through an assessment's methods. The adaptive method gives a magnificent result to be used in detecting hydrocarbon contamination. © Published under licence by IOP Publishing Ltd.

关键词： Crude oil

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Characterization of the Upper Atmosphere from Neutral and Electron Density Observations 27th

Characterization of the Upper Atmosphere from Neutral and El...

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27th General Assembly of the International Union of Geodesy and Geophysics, IUGG 2019

作者： Calabia, Andres Jin, Shuanggen School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9783031098567

Upper-atmospheric processes under different space weather conditions are still not well understood, and the existing models are far away from the desired operational requirements due to the lack of in-situ measurements input. The ionospheric perturbation of electromagnetic signals affects the accuracy and reliability of Global Navigation Satellite Systems (GNSS), satellite communication infrastructures, and Earth observation techniques. Furthermore, the variable aerodynamic drag, due to variable thermospheric mass density, disturbs orbital tracking, collision analysis, and re-entry calculations of Low Earth Orbit (LEO) objects, including manned and unmanned artificial satellites. In this paper, we use the Principal Component Analysis (PCA) technique to study and compare the main driver-response relationships and spatial patterns of total electron content (TEC) estimates from 2003 to 2018, and total mass density (TMD) estimates at 475 km altitude from 2003 to 2015. Comparison of the first TEC and TMD PCA mode shows a very similar response to solar flux, but annual cycle shown by TEC is approximately one order of magnitude larger. A clear hemispheric asymmetry is shown in the global distribution of TMD, with higher values in the southern hemisphere than in the northern hemisphere. The hemispheric asymmetry is not visible in TEC. The persistent processes including a favorable solar wind input and particle precipitation over the southern magnetic dip may produce a higher thermospheric heating, which results in the hemispheric asymmetry in TMD. © 2020, The Author(s).

关键词： Principal component analysis

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