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Monitoring Changes to Small-Sized Lakes Using Medium spatial and Temporal Satellite Imagery in the Badain Jaran Desert from 2015 to 2020

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International Journal of Crowd Science 2025年第2期9卷 96-109页

作者： Qinyu Zhao Luyan Ji Yonggang Su Kai Yu Yongchao Zhao College of Electronic and Information Engineering Hebei University Baoding China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial information Processing and Application System Beijing China Key Laboratory of Target Cognition and Application Technology (TCAT) Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

The Badain Jaran Desert is the second-largest desert in China, and its lakes, which are generally small-sized and highly dynamic, play a significant role for plants and animals in this arid region. Therefore, long-term monitoring of the distribution of lakes in the Badain Jaran Desert with high spatial and temporal resolution is of great importance. However, due to the tradeoff between pixel size and swath width, currently no single satellite sensor can provide such a time series. Thereby, in this study, we focus on applying the deep learning based spatiotemporal fusion method (super-resolution based spatial fusion with Generative Adversarial Network (GAN)) to a low spatial yet high temporal resolution data (i.e., MODIS 250 m daily reflectance time series) and a high spatial yet low temporal resolution data (i.e., Landsat 30 m 16-day reflectance time series) to generate a daily 30 m time series for 37 selected lakes in the Badain Jaran Desert. Then, an automatic water extraction algorithm is proposed, and a daily 30 m water mapping production is generated for our study area from 2015 to 2020. The overall accuracy can reach 0.92, while the average error of lake areas is less than 9.21%, which is much higher than that derived from the MODIS time series. Moreover, based on our daily high spatial resolution results, it is possible to analyze the water phenology for all sizes of lakes in the Badain Jaran Desert. We have performed a detailed analysis of interannual variability and seasonal changes for the selected 37 lakes in the Badain Jaran Desert. The results show that from 2015 to 2020, the shrinkage of the small lakes (<0.5 km 2 ) is more severe than lakes with a larger size. As for seasonal changes, the lake area can be divided into four stages: quick increase due to ice melting from winter to spring, slow decrease due to evaporation from spring to summer, moderate recovery due to the arrival of the rainy season from summer to autumn, and quick decrease due to lake

关键词： Reflectivity Heuristic algorithms Time series analysis Landsat Lakes Deserts Spatiotemporal phenomena spatial resolution MODIS Monitoring

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Against Mobile Collusive Eavesdroppers: Cooperative Secure Transmission and Computation in UAV-Assisted MEC Networks

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IEEE Transactions on Mobile Computing 2025年第6期24卷 5280-5297页

作者： Zhao, Mingxiong Wang, Zirui Guo, Kun Zhang, Rongqian Quek, Tony Q. S. Ministry of Education Engineering Research Center of Integration and Application of Digital Learning Technology Beijing100039 China Ministry of Education Engineering Research Center of Cyberspace Kunming650504 China Yunnan University of Finance and Economics Yunnan Key Laboratory of Service Computing Kunming650221 China Yunnan University Yunnan Key Laboratory of Software Engineering Kunming650091 China East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing School of Communications and Electronics Engineering Shanghai200241 China Yunnan University School of Information Science and Engineering Kunming650500 China Singapore University of Technology and Design Information Systems Technology and Design 487372 Singapore National Pilot School of Software Yunnan University Kunming China

In Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) networks, the security of transmission faces significant challenges due to the vulnerabilities of line-of-sight links and potential eavesdropping on two-hop links. This paper addresses these challenges with an innovative Cooperative Secure Transmission and Computation strategy (CSTC), specifically engineered for time-slotted UAV-assisted MEC networks plagued by mobile collusive eavesdroppers. These eavesdroppers significantly bolster their interception capabilities through coordinated and optimized movements, escalating the security threats. To neutralize these risks, the proposed CSTC employs the UAV and remote devices as helper nodes to emit jamming signals, thereby thwarting eavesdropping activities, while simultaneously facilitating the efficient relay of users' tasks to the base station for advanced processing. The CSTC aims to maximize the sum Secrecy Transmission Rate (STR) satisfying task latency constraints. It involves a joint optimization of UAV trajectory, jamming beamformers, transmit power, and data offloading strategy to expedite task transmission. Additionally, a real-time computation scheduling approach is developed based on a newly defined metric, the Urgency Degree of Users (UDoU), to enhance task processing efficiency. Our extensive simulations validate that the CSTC not only elevates the sum STR but also consistently meets latency constraints, demonstrating its robustness against advanced mobile eavesdropping techniques. © 2002-2012 IEEE.

关键词： Jamming

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A SAR Deceptive Jamming Suppression Method Based on PRI Variation Design and Multi-Channel Principle

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IEEE Transactions on geoscience and Remote Sensing 2025年

作者： Shi, Haixu Xu, Zhongqiu Li, Guangzuo Lin, Kuan Liu, Tianqu Hong, Wen Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Key Laboratory of Spatial Information Processing and Application System Technology Beijing100094 China Key Laboratory of Target Cognition and Application Technology Beijing100094 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing101499 China

The synthetic aperture radar (SAR) can be affected by various types of jamming during operation. Among them, the deceptive jamming generated by digital radio frequency memory (DRFM) jammers poses a serious threat to SAR imaging by creating highly realistic false targets. Moreover, with advancements in deceptive jamming technology, the generation speed of deceptive jamming has increased, rendering existing methods less effective. To address this issue, an anti-deceptive jamming method based on pulse repetition interval (PRI) variation design and multi-channel principle is proposed to mitigate the effects of deceptive jamming. First, a PRI variation strategy that will not cause the loss of echo signals in the imaging area is designed. By utilizing this strategy for imaging, deceptive jamming signals are dispersed across different ranges, resulting in preliminary suppression of the jamming. Subsequently, after azimuth non-uniform sampling reconstruction and range processing, most of the jamming signals are suppressed due to the azimuth timing differences between SAR and jamming signals. However, when the jammer uses specific retransmission intervals, such as the average PRI of the PRI sequence, the jamming signals may be concentrated at certain ranges, retaining some coherence and posing a threat to SAR imaging. To overcome this challenge, a residual jamming detection and suppression algorithm based on multi-channel principle is proposed, which can detect and filter out the channels affected by jamming. Finally, an azimuth sparse reconstruction is introduced for azimuth processing. Since the anti-jamming principle of this method relies on the differences in azimuth timing between SAR and jamming, it can suppress deceptive jamming even when the generation speed of deceptive jamming is rapid, which some other anti-deceptive jamming methods cannot achieve. Simulations of SAR imaging under deceptive jamming conditions are conducted for point target scene and complex target

关键词： Synthetic aperture radar

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Provincial anthropogenic emission inventory of carbonyl sulfide (COS) in China from 2015 to 2021

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Journal of geographical Sciences 2025年第5期35卷 923-940页

作者： Jiang, Yunhao Chen, Bin Wang, Shaoqiang Li, Tingyu Chen, Shiliang Wang, Lunche Wang, Lizhe School of Future Technology China University of Geosciences Wuhan China Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information Engineering China University of Geosciences Wuhan China Engineering Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks Ministry of Natural Resources Wuhan China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research CAS Beijing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China

Carbonyl sulfide (COS) is an effective tracer for estimating Gross Primary Productivity (GPP) in the carbon cycle. As the largest contribution to the atmosphere, anthropogenic COS emissions must be accurately quantified. In this study, an anthropogenic COS emission inventory from 2015 to 2021 was constructed by applying the bottom-up approach based on activity data from emission sources. China’s anthropogenic COS emissions increased from approximately 171 to 198 Gg S yr−1 from 2015–2021, differing from the trends of other pollutants. Despite an initial decline in COS emissions across sectors during the early stage of the COVID-19 pandemic, a rapid rebound in emissions occurred following the resumption of economic activities. In 2021, industrial sources, coal combustion, agriculture and vehicle exhaust accounted for 76.8%, 12.3%, 10.5% and 0.4% of total COS emissions, respectively. The aluminum industry was the primary COS emitter among industrial sources, contributing 40.7% of total emissions. Shandong, Shanxi, and Zhejiang were the top three provinces in terms of anthropogenic COS emissions, reaching 39, 21 and 17 Gg S yr−1, respectively. Provincial-level regions (hereafter province) with high COS emissions are observed mainly in the eastern and coastal regions of China, which, together with the wind direction, helps explain the pattern of high COS concentrations in the Western Pacific Ocean in winter. The Green Contribution Coefficient of COS (GCCCOS) was used to assess the relationship between GDP and COS emissions, highlighting the disparity between GDP and COS contributions to green development. As part of this analysis, relevant recommendations are proposed to address this disparity. The COS emission inventory in our study can be used as input for the Sulfur Transport and Deposition Model (STEM), reducing uncertainties in the atmospheric COS source–sink budget and promoting understanding of the atmosphere sulfur cycle.

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Bell State Preparation Based on Switching Between Quantum System Models

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Journal of systems Science & Complexity 2017年第2期30卷 347-356页

作者： ZHOU Juan KUANG Sen CONG Shuang Department of Automation University of Science and Technology of ChinaHefei 230027China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science

For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between two control channels under one model. Proper control Hamiltonians are selected for the two system models, a switching strategy between the two models is designed, and the stability of the whole switching system is proved in theory. For a given target Bell state, the effectiveness of the proposed switching control strategy between different models is illustrated through simulation experiments.

关键词： Bell state model switching quantum systems switching strategy.

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An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar

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Journal of Zhejiang University-Science C(Computers and Electronics) 2014年第11期15卷 1071-1085页

作者： Xin GUAN Li-hua ZHONG Dong-hui HU Chi-biao DING Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences

In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function(CAF) and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is:(1) divide the signal into snapshots;(2) perform matched filtering on each snapshot;(3) perform fast Fourier transform(FFT) across the snapshots. The matched filtering method is computationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform(MDCFT) is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.

关键词： keystone transform Matched filtering MDCFT Mismatching Passive radar Velocity estimation

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Dynamic data packing towards the optimization of QoC and QoS in networked control systems

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Science China(Technological Sciences) 2016年第1期59卷 72-80页

作者： KANG Yu ZHAO YunBo Department of Automation and State Key Laboratory of Fire Science University of Science and Technology of China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Department of Automation Zhejiang University of Technology

A class of networked control systems is investigated whose communication network is shared with other applications. The design objective for such a system setting is not only the optimization of the control performance but also the efficient utilization of the communication resources. We observe that at a large time scale the data packet delay in the communication network is roughly varying piecewise constant, which is typically true for data networks like the Internet. Based on this observation, a dynamic data packing scheme is proposed within the recently developed packet-based control framework for networked control systems. As expected this proposed approach achieves a fine balance between the control performance and the communication utilization: the similar control performance can be obtained at dramatically reduced cost of the communication resources. Simulations illustrate the effectiveness of the proposed approach.

关键词： networked control systems packet delay variation dynamic data packing quality of control quality of service

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A general law of human mobility

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Science China(information Sciences) 2015年第10期58卷 24-37页

作者： LIANG Xiao ZHAO JiChang XU Ke Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences School of Economics and Management Beihang University State Key Laboratory of Software Development Environment Beihang University

The intrinsic factors that drive human mobility have remained unclear for decades. Our observations from both intra-urban and inter-urban trips demonstrate a general law of human mobility. Specifically, the probability that a trip will occur is inversely proportional to the size of population located inside a circle with radius equal to the travel distance centered at the trip origin. A simple parameterless rank-based model is presented; this model can predict human flows with a convincing fidelity. Moreover, existing models can be implemented as special cases of our model, suggesting that our model is stable at more spatial scales. Our model also creates a fundamental bridge between individual mobility and social relationships.

关键词： human mobility social mobility general law rank-based model flux prediction

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RFID Cardinality Estimation Method for Intelligent Warehouse 35

RFID Cardinality Estimation Method for Intelligent Warehouse

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第35届中国控制会议

作者： SHEN Jingjing TAN Xiaobin WU Fan YAN Pei CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781509009107

With the rapid development of RFID technologies,RFID has been introduced into applications such as supply chain management,inventory control,sampling inspection,3-D positioning and object ***,the reader accesses all the tags in its interrogation region while some applications may only need to identify the tags in a specified area which is smaller than the reader's interrogation *** paper concerns the essential problem of estimating cardinality of tags in the specified *** key novelty of our solution builds on an estimation synopsis that can capture key counting information by moving the reader as well as a simple *** the help of this data structure,a BS can be obtained which only contains the target *** computing the number of 1 in the BS,we can easily get cardinality |E| of the tags in the specified *** conduct extensive experiments to examine this design and the results shows that our solution achieves high *** it not requires any modification of tags and can be implemented with only one reader and some passive RFID tags,the proposed method is easy to deploy in a practical system.

关键词： Cardinality estimation RFID tags algorithm design

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Intertidal area classification with generalized extreme value distribution and Markov random field in quad-polarimetric synthetic aperture radar imagery

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Frontiers of information technology & Electronic Engineering 2019年第2期20卷 253-264页

作者： Ting-ting JIN Xiao-qiang SHE Xiao-lan QIU Bin LEI Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of ElectronicsChinese Academy of Sciences University of Chinese Academy of Sciences Huawei Software Technologies Co. Ltd.

Classification of intertidal area in synthetic aperture radar(SAR) images is an important yet challenging issue when considering the complicatedly and dramatically changing features of tidal fluctuation. The difficulty of intertidal area classification is compounded because a high proportion of this area is frequently flooded by water, making statistical modeling methods with spatial contextual information often ineffective. Because polarimetric entropy and anisotropy play significant roles in characterizing intertidal areas, in this paper we propose a novel unsupervised contextual classification algorithm. The key point of the method is to combine the generalized extreme value(GEV) statistical model of the polarization features and the Markov random field(MRF) for contextual smoothing. A goodness-of-fit test is added to determine the significance of the components of the statistical model. The final classification results are obtained by effectively combining the results of polarimetric entropy and anisotropy. Experimental results of the polarimetric data obtained by the Chinese Gaofen-3 SAR satellite demonstrate the feasibility and superiority of the proposed classification algorithm.

关键词： Intertidal classification Polarimetric synthetic aperture radar Finite mixture model Markov random field Generalized extreme value model

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