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Mapping Spatially Seamless Fractional Vegetation Cover over China at a 30-m Resolution and Semimonthly Intervals in 2010-2020 Based on Google Earth Engine

Journal of Remote Sensing

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Journal of Remote Sensing 2023年第1期3卷 444-462页

作者： Tian Zhao Xihan Mu Wanjuan Song Yaokai Liu Yun Xie Bo Zhong Donghui Xie Lingmei Jiang Guangjian Yan State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Beijing Engineering Research Center for Global Land Remote Sensing Products Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China Key Laboratory of Quantitative Remote Sensing Information Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China College of Arts and Sciences Beijing Normal UniversityZhuhai 519087China

Fractional vegetation cover(FVC)is a critical biophysical parameter that characterizes the status of terrestrial *** spatial resolutions of most existing FVC products are still at the kilometer ***,there is growing demand for FVC products with high spatial and temporal resolutions in remote sensing *** study developed an operational method to generate 30-m/15-day FVC products over *** datasets were employed to generate a continuous normalized difference vegetation index(NDVI)time series based on the Google Earth Engine platform from 2010 to *** NDVI was transformed to FVC using an improved vegetation index(VI)-based mixture model,which quantitatively calculated the pixelwise coefficients to transform the NDVI to FVC.A comparison between the generated FVC,the Global LAnd Surface Satellite(GLASS)FVC,and a global FVC product(GEOV3 FVC)indicated consistent spatial patterns and temporal profiles,with a root mean square deviation(RMSD)value near 0.1 and an R^(2) value of approximately *** validation was conducted using ground measurements from croplands at the Huailai site and forests at the Saihanba ***,validation was performed with the FVC time series data observed at 151 plots in 22 small *** generated FVC showed a reasonable accuracy(RMSD values of less than 0.10 for the Huailai and Saihanba sites)and temporal trajectories that were similar to the field-measured FVC(RMSD values below 0.1 and R^(2) values of approximately 0.9 for most small watersheds).The proposed method outperformed the traditional VIbased mixture model and had the practicability and flexibility to generate the FVC at different resolutions and at a large scale.

关键词： Mapping Engine Spatial

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Unsupervised 3D Animal Canonical Pose Estimation with Geometric Self-Supervision 17

Unsupervised 3D Animal Canonical Pose Estimation with Geomet...

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17th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2023

作者： Dai, Xiaowei Li, Shuiwang Zhao, Qijun Yang, Hongyu National Key Laboratory of Fundamental Science on Synthetic Vision Sichuan University Chengdu China College of Information Science and Engineering Guilin University of Technology Guilin China College of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9798350345445

Although analyzing animal shape and pose has potential applications in many fields, there is little work on 3D animal pose estimation. This can be attributed to two aspects: the lack of large-scale well-annotated datasets, and perspective ambiguities which make it difficult to map 2D space to 3D space. To address data scarcity, we propose an unsupervised method to estimate 3D animal pose, given only 2D poses. To deal with perspective ambiguities, we introduce a canonical consistency loss and a camera consistency loss to impose geometric priors in the training process, and combine the reprojection loss and the 2D pose discriminator to enable self-supervised learning. Specifically, given a 2D pose, the pose generator network generates a corresponding 3D pose and the camera network estimates a camera rotation. During training, the generated 3D pose is randomly reprojected onto camera viewpoints to synthesize a new 2D pose. The synthesized 2D pose is decomposed into a 3D pose and a camera rotation, based on which consistency losses are imposed in both 3D canonical poses and camera rotations for self-supervised training. We evaluate the proposed method on real and synthetic datasets, i.e., SMAL and AcinoSet. The experimental results demonstrate the effectiveness of the proposed method and we achieve state-of-the-art performance among unsupervised algorithms for 3D animal canonical pose estimation. © 2023 IEEE.

关键词： Animals

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Super-resolution GANs for upscaling unplanned urban settlements from remote sensing satellite imagery - the case of Chinese urban village detection

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International Journal of Digital Earth 2023年第1期16卷 2623-2643页

作者： Alessandro Crivellari Hong Wei Chunzhu Wei Yuhui Shi Department of Computer Science and Engineering SouthernUniversity of Science and TechnologyShenzhenPeople’s Republic of China Ministry of Education Ecological Field Station for East Asian Migratory Birds Department of Earth System ScienceInstitute for Global Change StudiesTsinghua UniversityBeijingPeople’s Republic of China School of Geography and Planning Sun Yat-sen UniversityGuangzhouPeople’s Republic of China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiPeople’s Republic of China

The semantic segmentation of informal urban settlements represents an essential contribution towards renovation strategies and reconstruction *** this context,however,a big challenge remains unsolved when dealing with incomplete data acquisitions from multiple sensing devices,especially when study areas are depicted by images of different *** practice,traditional methodologies are directed to downgrade the higher-resolution data to the lowest-resolution measure,to define an overall homogeneous dataset,which is however ineffective in downstream segmentation activities of such crowded unplanned urban *** this purpose,we hereby tackle the problem in the opposite direction,namely upscaling the lower-resolution data to the highest-resolution measure,contributing to assess the use of cutting-edge super-resolution generative adversarial network(SR-GAN)*** experimental novelty targets the particular case involving the automatic detection of‘urban villages’,sign of the quick transformation of Chinese urban *** aligning image resolutions from two different data sources(Gaofen-2 and Sentinel-2 data),we evaluated the degree of improvement with regard to pixel-based landcover segmentation,achieving,on a 1 m resolution target,classification accuracies up to 83%,67%and 56%for 4x,8x,and 10x resolution upgrades respectively,disclosing the advantages of artificially-upscaled images for segmenting detailed characteristics of informal settlements.

关键词： SR-GAN resolution upscaling informal settlements urban villages cross-sensor analytics

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Evaluation and Quantitative Attribution Analysis of Water Yield Services in the Peak-cluster Depression Basins in Southwest of Guangxi,China

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Chinese Geographical science 2023年第1期33卷 116-130页

作者： WANG Donghua TIAN Yichao ZHANG Yali HUANG Liangliang TAO Jin YANG Yongwei LIN Junliang ZHANG Qiang School of Resources and Environment Beibu Gulf UniversityQinzhou 535011China College of Environmental Science and Engineering Guilin University of TechnologyGuilin 541004China Key Laboratory of Marine Geographic Information Resources Development and Utilization in the Beibu Gulf Beibu Gulf UniversityQinzhou 535011China

Karst environmental issues have become one of the hot spots in contemporary international geological research. The same problem of water shortage is one of the hot spots of global concern. The peak-cluster depression basins in southwest of Guangxi is an important water connotation and ecological barrier areas in the Pearl River Basin of China. Thus, studying the spatial and temporal variations and the influencing factors of its water yield services is critical to achieve the sustainable development of water resources and ecological environmental protection in this region. As such, this paper uses the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST) model to assess the spatial and temporal variabilities of water yield services and its trends in the peak-cluster depression basins in southwest of Guangxi from 2000 to 2020. This work also integrates precipitation(Pre), reference evapotranspiration(ET), temperature(Tem), digital elevation model(DEM), slope, normalized difference vegetation index(NDVI), land use/land cover(LULC) and soil type to reveal the main factors that influence water yield services with the help of Geodetector. Results show that: 1) in time scale,the total annual water yield in the study area show a fluctuating and increasing trend from 2000 to 2020, with a growth rate of 7.3753 × 10^(8)m^(3)/yr, and its multi-year average water yield was 538.07 mm;2) in spatial pattern, with high yield areas mainly distributed in the south of the study area(mainly including Shangsi County, Pingxiang City, Ningming County, Longzhou County and Jingxi County), and low yield areas mainly distributed in Baise City and Nanning City;3) the dominant factor of water yield within karst and non-karst landforms is not necessarily controlled by precipitation, and the explanation degree of DEM factors in karst areas is significantly higher than that in non-karst areas;4) amongst the climatic factors, Pre, ET and Tem are dominant in the spatial pattern of region w

关键词： water yield Integrated Valuation of Ecosystem Services and Trade-offs(InVEST) Geodetector peak-cluster depression basins in southwest of Guangxi China

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Trusted Polarimetric Feature Fusion for Polsar Image Classification

Trusted Polarimetric Feature Fusion for Polsar Image Classif...

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SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA)

作者： Fangzhou Han Lamei Zhang Hongwei Dong Department of Information Engineering Harbin Institute of Technology Harbin China Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China

Benefiting from the rapid advancements in Deep Learning (DL), data-driven features exhibit remarkable separability in PolSAR image classification. However, data-driven features are challenging to interpret and susceptible to resolution and noise. On the contrary, polarimetric features based on the target decomposition not only have high robustness, but also has physical interpretability. Consequently, researchers have begun to explore ways to integrate both types of features to achieve enhanced performance, which typically concat the data-driven features and polarimetric features directly. However, polarimetric features are not stable in separability, which is because the inherent defects of the target decomposition algorithm. To mitigate the adverse effects of low-quality features, this paper proposes a trusted polarimetric feature fusion (TPFF). The new paradigm calculates the confidence of features and employs a novel feature fusion method. The proposed method has been tested on the EMISAR Foulum dataset, with experimental results demonstrating improved classification performance and robustness.

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Vulnerability Detection Based on Adapter Tuning and Enhanced Feature Learning 36

Vulnerability Detection Based on Adapter Tuning and Enhanced...

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36th International Conference on Software engineering and Knowledge engineering, SEKE 2024

作者： Luo, Hui Lu, Lu Liang, Zhihong Suo, Siliang School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China PengCheng Laboratory Shenzhen China Electric Power Research Institute CSG Guangdong Guangzhou China Guangdong Provincial Key Laboratory of Power System Network Security Guangdong Guangzhou China

ISBN: (纸本)1891706594

Pre-trained code models have achieved promising results in the vulnerability detection field. The prevailing approach is to adapt these models with vulnerability datasets using inefficient full-model fine-tuning. These pre-trained models primarily capture the semantic features of code, while neglecting its structural characteristics. To address these issues, this paper proposes a vulnerability detection method with adapter tuning and enhanced feature learning. First, adapter modules are introduced to UniXcoder and tune only the parameters in the adapters to extract semantic features. This significantly reduces the number of training parameters and better adapts the model to downstream tasks. Then, structural features, including control and data flow information, are extracted from the Program Dependence Graph (PDG) to compensate for the limitations of pre-trained models that rely solely on semantic features. Finally, the semantic and structural features are integrated to train the detection model. The experimental results demonstrate that our proposed method outperforms state-of-the-art approaches and is highly efficient in terms of both training parameters and training data. © 2024 Knowledge systems Institute Graduate School. All rights reserved.

关键词： Data flow graphs

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A Digitally assisted nonlinearity suppression architecture using over-the-air beam cancelation

A Digitally assisted nonlinearity suppression architecture u...

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作者： Mu, Qin Li, Nanxi Chen, Cong Wei, Xiaozheng Wen, Rong Wu, Muqing Li, Xiang Liu, Ying School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China National Key Lab of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu China School of Network and Communication Engineering Chengdu Technological University Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

Using a large number of power amplifiers brings serious nonlinear distortion to 5G communication systems, which becomes a challenging problem for conventional digital predistortion (DPD) to linearize signals. To address this challenge, we propose a digitally assisted nonlinearity suppression architecture for applications in multiple antenna arrays. In this architecture, we use an auxiliary array to generate a nonlinear cancelation signal to cancel with the main beam at the receiving end. We explore a two-step method to model the nonlinear signal and combine neural network to complete the modeling. In addition, we introduce a novel method for estimating and tracking the channel to update the model coefficients. To verify the proposed methods, we design a scene and compare the performance of our architecture with that of conventional DPD. Our experiments demonstrate that our proposed methods can significantly enhance the adjacent channel power leakage ratio performance by 12 dB while also optimizing in-band distortion. Moreover, our architecture outperforms conventional DPD approaches even with enhanced distortion. © 2023 John Wiley & Sons Ltd.

关键词： Power amplifiers

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A New Predefined Time Stability Theorem and its Application in Multi-Modal Memristive Neural Network Synchronization

A New Predefined Time Stability Theorem and its Application ...

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2023 IEEE International Conference on Memristive Computing and Applications, ICMCA 2023

作者： Zhao, Hui Zhou, Lei Wang, Qingjie Liu, Aidi Peng, Jingliang School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China College of Information Science and Engineering Northeastern University Shenyang China Collaborative Innovation Center of Memristive Computing Application Qilu Institute of Technology Jinan China

ISBN: (纸本)9798350316230

This article proposes a new predefined-time (PDT) stability theorem, which offers more evident advantages compared to previous predefined-time stability. Firstly, based on the limitations of existing PDT stability, this theorem relaxed the limitations of sufficient conditions, which fill the gap in the research on PDT stability. Secondly, the PDT synchronization of multi-modal memristive neural networks (MM-MNN) is analyzed by the usability of the new judgment theorem. A matching PDT controller is designed and sufficient synchronization control conditions is obtained by utilizing generalized Lyapunov functional method, set-valued mapping, inequality analysis technique and differential inclusion theory. Meanwhile, the topological characteristics of multi-modal neuron and its impact on network synchronization behavior are presented. Finally, we provide some confirmatory numerical simulations. © 2023 IEEE.

关键词： Topology

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Dual-Frequency High-Power Rectifying Metasurface for Microwave Power Transfer 6

Dual-Frequency High-Power Rectifying Metasurface for Microwa...

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6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Yang, Jinlong Deng, Li Feng, Botao Xiao, Long Chen, Lijie Yao, Gengjiang School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China Science and Technology on Electromagnetic Compatibility Laboratory China Ship Development and Design Center Wuhan China

ISBN: (纸本)9798350399059

This paper presents a design for a dual-frequency high-power rectifying metasurface. It comprises a dual-frequency receiving metasurface and a rectifier. The metasurface utilizes an ELC structure and achieves nearly 90% power absorption at both 2.4GHz and 3.5GHz, while consuming minimal energy in the medium and on the surface. The rectifying circuit incorporates GaN HEMT transistors and is designed based on a power amplifier. At an input power of approximately 40dBm, the rectifier demonstrates a high rectification efficiency, reaching 70% at 2.4GHz and 60% at 3.5GHz. © 2023 IEEE.

关键词： Power amplifiers

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Single-molecule MIR absorption detection and nanoscale imaging

Single-molecule MIR absorption detection and nanoscale imagi...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Meng, Zhao-Dong You, En-Ming Yi, Jun Tian, Zhong-Qun State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering School of Electronic Science and Engineering Fujian Key Laboratory of Ultrafast Laser Technology and Applications Xiamen University Xiamen361005 China Xiamen361005 China School of Ocean Information Engineering Jimei University Xiamen361021 China

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