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Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China

The Crop Journal 2024年第2期12卷 614-629页

作者： Bingwen Qiu Linhai Yu Peng Yang Wenbin Wu Jianfeng Chen Xiaolin Zhu Mingjie Duan Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Academy of Digital China(Fujian)Fuzhou UniversityFuzhou 350116FujianChina Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural AffairsBeijing 100081China Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic UniversityKowloon 999077Hong KongChina

Upland crop-rice cropping systems(UCR)facilitate sustainable agricultural *** UCR cultivation mapping is needed to ensure food security,sustainable water management,and rural ***,datasets describing cropping systems are limited in spatial coverage and crop *** UCR is more challenging than crop identification and most existing approaches rely heavily on accurate phenology calendars and representative training samples,which limits its applications over large *** describe a novel algorithm(RRSS)for automatic mapping of upland crop-rice cropping systems using Sentinel-1 Synthetic Aperture Radar(SAR)and Sentinel-2 Multispectral Instrument(MSI)*** indicator,the VV backscatter range,was proposed to discriminate UCR and another two indicators were designed by coupling greenness and pigment indices to further discriminate tobacco or oilseed *** RRSS algorithm was applied to South China characterized by complex smallholder rice cropping systems and diverse topographic *** study developed 10-m UCR maps of a major rice bowl in South China,the Xiang-Gan-Min(XGM)*** performance of the RRSS algorithm was validated based on 5197 ground-truth reference sites,with an overall accuracy of 91.92%.There were7348 km^(2) areas of UCR,roughly one-half of them located in *** UCR was represented mainly by oilseed-UCR and tobacco-UCR,which contributed respectively 69%and 15%of UCR *** patterns accounted for only one-tenth of rice production,which can be tripled by intensification from single rice *** to complex and fragmented subtropical regions suggested the spatiotemporal robustness of the RRSS algorithm,which could be further applied to generate 10-m UCR datasets for application at national or global scales.

关键词： Cropping-pattern mapping Paddy rice Sentinel-1/2 China Sustainable intensification

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Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements

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Geodesy and Geodynamics 2025年第1期16卷 42-54页

作者： Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu School of Electrical and Electronic Information Engineering Hubei Polytechnic UniversityHuangshi 435003China Hubei Luojia Laboratory GNSS Research CenterWuhan UniversityWuhan 430079China Changjiang Spatial Information Technology Engineering Co. Ltd.Wuhan 430010China Key Laboratory of Spatial Data Mining&Information Sharing of the Ministry of Education Fuzhou UniversityFuzhou 350108China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China The First Surveying and Mapping Institute of Hunan Province Changsha 410114China

The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical *** this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic *** include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time *** decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF *** SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten ***,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal *** could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.

关键词： GNSS coordinate time series Singularspectrumanalysis Time-varying seasonal signals Loading effects GRACE

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Tracking Topics and Hot Issues in Marine Remote Sensing Research Between 2018 and 2022 24

Tracking Topics and Hot Issues in Marine Remote Sensing Rese...

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2024 International Conference on Intelligent Education and Computer Technology, IECT 2024

作者： Yang, Yang Zhang, Hongyue College of Geography and Oceanography Minjiang University Fujian Fuzhou China Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Fuzhou University Fujian Fuzhou China

ISBN: (纸本)9798400709920

Large number of publications have been published in marine remote sensing study, and it is of great importance to explore and discover the key research topics and hotspots for domain researchers. In this study, a combination of topic modeling and keywords co-occurrence analysis was applied to 7,509 articles published between 2018 and 2022 obtained from the Web of Science database. The findings of this research indicate that marine remote sensing can be categorized into five major themes: Land Surface Temperature (LST), Sea Surface Temperature (SST), SAR/InSAR for target identification and detection, SAR, and altimetry technology for monitoring oceanographic and atmospheric phenomena, and water quality and organic substance monitoring. Changes in topic strengths reflect a growing emphasis on SAR-based target identification and detection research. keyword co-occurrence evolution results highlight the increasing importance of SAR and Sentinel theme clusters. In terms of research trends, applications in marine remote sensing are likely to prioritize feature extraction, sea measurement, and marine vehicles. In addition to traditional data sources such as MODIS and Landsat, Sentinel, Cryosat-2, AMSR-E and TerraSAR-X data offer significant potential for marine remote sensing applications. © 2024 ACM.

关键词： Surface temperature

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SLK-SLAM: Integrating semantics and optical flow for SLAM in dynamic environments

SLK-SLAM: Integrating semantics and optical flow for SLAM in...

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Computer, Control and Robotics (ICCCR), International Conference on

作者： Gang Wang Yu Sun Xin Yu Zhanchao Huang Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Fuzhou China

ISBN: (数字)9798350373141

ISBN: (纸本)9798350373158

Many contemporary visual SLAM algorithms en-counter significant biases when localizing and mapping in dynamic environments, largely stemming from their extensive reliance on static environment assumptions. In this paper, we propose a semantic SLAM system, called SLK-SLAM, that skill-fully recognizes dynamic objects and generates clean point cloud maps. We determine dynamic objects based on reprojection error, and to improve the number of feature matches in low texture target regions, optical flow is used to track the current frame and tracking sensitivity is applied to measure the tracking error, and ultimately the dynamism of the object is determined with the help of chi-square test. The proposed system is evaluated on the TUM dynamic benchmark dataset. Experimental results show that SLK-SLAM reduces the average absolute tracking error by about 85% compared to ORB-SLAM3. In addition, SLK-SLAM has higher localization accuracy and system robustness compared to other state-of-the-art dynamic SLAM systems.

关键词： Point cloud compression Location awareness Simultaneous localization and mapping Target tracking Accuracy Heuristic algorithms Dynamics

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Unsupervised part extraction of substation equipment based on joint multi-level voxels’ features of point clouds 5

Unsupervised part extraction of substation equipment based o...

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5th International Conference on Signal Processing and Computer Science, SPCS 2024

作者： Zhang, Meng Lin, Ding Ding, Jing Fang, Tao Key Lab of Spatial Data Mining and Information Sharing Ministry of Education Fuzhou University Fujian Fuzhou350108 China State Grid Hangzhou Power Supply Company State Grid ZHEJIANG Electric Power co. LTD Zhejiang Hangzhou310000 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

Aiming at the segmentation and extraction of the main part of substation equipment, we use Fast Point Feature Histograms (FPFH) and Locally Convex Connected Patches (LCCP) to obtain voxels’ integrated geometric features, then aggregate these features and their K nearest neighbors’ on voxels to build multi-level voxels’ features by bottom-up hierarchy, and achieve pre-segmentation of shapes with the flow-constrained super-voxel clustering algorithm;After the pre-segmentation, we conduct shape analysis to extract semantically meaningful instances of equipment components, achieving part-level point cloud data instance extraction of artificial equipment geometric features. Without training data or manual annotations, the work presented is simple and easy to implement. It can merge patches across surface-singularities. It needs a few parameters, can achieve automatic 3D instance extraction from point clouds for different scenes with the same or similar parameters. © 2025 SPIE.

关键词： Superpixels

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Retrieving chlorophyll content and equivalent water thickness of Moso bamboo(Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

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Forest Ecosystems 2023年第2期10卷 252-267页

作者： Zhanghua Xu Anqi He Yiwei Zhang Zhenbang Hao Yifan Li Songyang Xiang Bin Li Lingyan Chen Hui Yu Wanling Shen Xuying Huang Xiaoyu Guo Zenglu Li College of Environment and Safety Engineering Academy of Geography and Ecological EnvironmentFuzhou UniversityFuzhou350108China Fujian Provincial Key Laboratory of Resources and Environment Monitoring&Sustainable Management and Utilization Sanming365004China Key Laboratory of Spatial Data Mining&Information Sharing Ministry of EducationThe Academy of Digital ChinaFuzhou UniversityFuzhou350108China College of Forestry Fujian Agriculture and Forestry UniversityFuzhou350002China International Institute for Earth System Science Nanjing UniversityNanjing210023China

Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the *** coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content ***,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be ***,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation *** inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were *** scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were *** results showed that LAI,CCC,and CEWT were inversely related with PPC-induced *** applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),*** to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for *** feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.

关键词： Moso bamboo Chlorophyll content Equivalent water thickness PROSAIL model Multiple LUTs Pantana phyllostachysae Chao Sentinel-2A/B images

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Prediction of river water quality considering spatiotemporal correlation and meteorological factors 9

Prediction of river water quality considering spatiotemporal...

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9th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2021

作者： Lu, Yi-Min Zhang, Hong Shao, Wei Fuzhou University Fuzhou Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Fujian350108 China

ISBN: (纸本)9781728165615

With the rapid development of economy, the problem of river pollution is becoming more and more serious. It is very important and challenging to build a high-precision water quality prediction model for the comprehensive management of water environment and prevention of water pollution. At present, some achievements have been made in data-driven river water quality prediction, mainly including grey model, time series model, support vector machine model and neural network model. However, these existing prediction methods are limited to single station prediction. The influence of the upstream water quality on the downstream water quality is ignored and the upstream stations at different locations will have different effects on the downstream water quality. In order to solve the problem that the traditional model of water quality prediction does not consider the upstream influence and difficulties in long-term prediction, a new water quality prediction model based on spatiotemporal attention mechanism and long-short-term memory neural network (TS-Attention-LSTM) was proposed, which considers the spatiotemporal correlation and meteorological factors. Firstly, the spatial attention module was embedded in the encoder to extract the significant spatial correlation between upstream and downstream. The interaction among the water quality indicators was also extracted. Then, the temporal attention module was embedded in the decoder to extract the important time series features. Moreover, the meteorological factors and spatial characteristics were fused in the decoder. Finally, the multi-step prediction of water quality was carried out by using LSTM model. In this paper, the research area located in Jinjiang River Watershed in Fujian Province, China. The nonpoint source pollution in this river basin mainly interrelated with livestock discharge, agricultural field runoff and rural domestic sewage. The results show that the TS-Attention-LSTM model can effectively capture the spa

关键词： Water quality

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Scale problem:Influence of grid spacing of digital elevation model on computed slope and shielded extra-terrestrial solar radiation

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Frontiers of Earth Science 2020年第1期14卷 171-187页

作者： Nan CHEN Key Laboratory of Spatial Data Mining&Information Sharing(Ministry of Education) Fuzhou UniversityFuzhou 350108 China Spatial Information Research Center of Fujian Province Fuzhou UniversityFuzhou 350108 China

Solar radiation is the primary energy source that drives many of Earth’s physical and biological processes and determines the patterns of climate and productivity on the surface of the Earth.A fundamental proportion of solar radiation is composed of shielded extraterrestrial solar radiation(SESR),which can be computed using the slope and aspect derived from a digital elevation model(DEM).The objective of this paper is to determine the influence of the grid spacing of the DEM(the influence of the scale of the DEM)on the errors of slope,aspect and *** paper puts forward the concepts of slope representation error,aspect representation error,and SESR representation error and then studies the relations among these errors and the grid spacing of *** find that when the grid spacing of a DEM becomes coarser,the average SESR increases;the increase in SESR is dominated by the grid cells of the DEM with a negative slope representation error,whereas SESR generally decreases in the grid cells with a positive slope representation *** the grid spacing varies,the distribution of the percentages of positive SESR representation errors on the slope,which is classified into 11 slope intervals,is independent of the grid spacing;this distribution is concentrated across some slope ***,the average absolute value and mean square error of the SESR representation error are closely related to those of the slope representation error and the aspect representation *** findings in this study may be useful for predicting and reducing the errors in SESR measurements and may help to avoid mistakes in foture research and in practical applications in which SESR is the data of interest or plays a vital role in an analysis.

关键词： scale problem digital elevation model grid spacing slope shielded extra-terrestrial solar radiation

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A virtual geographic environment for dynamic simulation and analysis of tailings dam failure

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International Journal of Digital Earth 2021年第9期14卷 1194-1212页

作者： Dayu Yu Liyu Tang Fan Ye Chongcheng Chen Key Laboratory of Spatial Data Mining&Information Sharing Ministry of Education of ChinaFuzhou UniversityFuzhouPeople’s Republic of China National Engineering Research Center of Geospatial Information Technology Fuzhou UniversityFuzhouPeople’s Republic of China School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China

It is of great significance for disaster prevention and mitigation to carry out disaster simulations for dam failure accidents in advance,but at present,there are few professional systems for disaster simulations of tailings *** this paper,we focused on the construction of a virtual geographic environment(VGE)system that provides an effective tool for visualizing the dam-break process of a tailings *** dam-break numerical model of the tailings dam based on computational fluid dynamics(CFD)was integrated into the VGE *** infrastructure of the VGE was supported by a 3-D geographic information system(GIS)with a user-friendly interface for the initiation,visualization,and analysis of the dynamic process of tailings dam *** technologies,including the integration of numerical models,rendering of large-scale scenes,and optimizations of disaster simulation and visualization,were discussed in *** the prototype system,information on the run-out path,travel distance,*** be obtained to visually describe the flow motion released by two dam failure *** simulation results showed that the VGE can be used for the multidimensional,dynamic and interactive visualization of dam-break disasters,and can also be useful for assessing the risk associated with tailings dams.

关键词： Vitrual geographic environment tailings dam break computational fluid dynamics spatiotemporal process simulation visualization analysis

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Long-term(2013-2022)mapping of winter wheat in the North China Plain using Landsat data:classification with optimal zoning strategy

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Big Earth data 2024年第3期8卷 494-521页

作者： Yifei Liu Xuehong Chen Jin Chen Yunze Zang Jingyi Wang Miao Lu Liang Sun Qi Dong Bingwen Qiu Xiufang Zhu State Key Laboratory of Remote Sensing Science Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina Beijing Engineering Research Center for Global Land Remote Sensing Products Institute of Remote Sensing Science and EngineeringFaculty of Geographical ScienceBeijing Normal UniversityBeijingChina State Key Laboratory of Crop Gene Resources and Breeding Institute of Crop SciencesChinese Academy of Agricultural Sciences(CAAS)BeijingChina State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Academy of Digital China(Fujian)Fuzhou UniversityFuzhouChina

Long-term mapping of winter wheat is vital for assessing food security and formulating agricultural *** data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this *** various methods,such as index-based methods,curve similarity-based methods and machine learning-based methods,have been developed for winter wheat mapping based on remote sensing,the former two often require satellite data with high temporal resolution,which are unsuitable for Landsat data with sparse *** learning is an effective method for crop classification using Landsat ***,applying machine learn-ing for winter wheat mapping in the North China Plain encounters two main issues:1)the lack of adequate and accurate samples for classifier training;and 2)the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this *** address these two issues,we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data,with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop ***,we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion,which divided the study area into six subzones with uni-form classification *** each subzone,a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI *** sample validation confirmed the high accuracy of the produced maps,with an average overall accuracy of 91.1%and an average kappa coefficient of 0.810 across different *** derived winter wheat area also has a good correlation(R2=0.949)with census area at the provincial *** results underscore the reliability of the produced ann

关键词： Winter wheat mapping Landsat machine learning North China Plain optimal zoning

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