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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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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

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 annual winter wheat *** experiments demonstrate that

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

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Relationship between spatial heterogeneity and wavelength in multisensor airborne images

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Geo-Spatial Information Science 2015年第1期18卷 56-64页

作者： bingwen qiu Wen QI Chongcheng CHEN Weijiao LI Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian ProvinceFuzhou UniversityFuzhou 350002China

Variogram has been utilized to exploring the spatial heterogeneity of remote sensing images,especially its association with spatial ***,very few attentions have been drawn on evaluating the spatial heterogeneity of multisensor airborne imagery and its relationship with spectral ***,an investigation was carried out on multisensor airborne images to determine the relation between spatial heterogeneity and spectral wavelength for woodland,grass,and urban landscapes by applying variogram *** airborne thematic mapper(ATM),compact airborne spectrographic imager(CASI),and Specim AISA Eagle airborne images at Harwood Forest,Monks wood,Cambridge,and River Frome areas,UK,were *** revealed that(1)the red band contained greater spatial variability than near-infrared wavelengths and other visible wavebands;(2)there was a steep gradient at the red edge in reference to its spatial variability of multisensor airborne images;(3)only for natural landscape such as woodland and grass,near-infrared waveband contains greater within-scene variations than the blue and green bands;(4)compared with the discrepancy of spatial resolution introduced by multisensor images(ATM,CASI,and Eagle),the specific landscape and spectral bands were more important in determining heterogeneity by means of original visible,near-infrared bands,and normalized difference vegetation index(NDVI).These findings remained us to be caution when combining and interpreting spatial variability and spatial structures derived from airborne images with different spatial resolution and spectral ***,the outcomes of this study also have considerable implications in terms of designing and choosing suitable images for different applications.

关键词： variogram modeling spatial heterogeneity airborne thematic mapper(ATM)imagery compact airborne spectrographic imager(CASI)imagery Eagle airborne imagery landscape wavelength

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Comparative spatio-spectral heterogeneity analysis using multispectral and hyperspectral airborne images

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Geo-Spatial Information Science 2013年第2期16卷 83-90页

作者： qiu bingwen ZENG Canying CHEN Chongcheng Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian ProvinceFuzhou University 523 Gongye RoadFuzhou 350002China

Knowledge of spatio-spectral heterogeneity within multisensor remote sensing images across visible,near-infrared and short wave infrared spectra is *** now,little comparative research on spatio-spectral heterogeneity has been conducted on real multisensor images,especially on both multispectral and hyperspectral airborne *** this study,four airborne images,Airborne Thematic Mapper,Compact Airborne Spectrographic Imager,Specim AISA Eagle and AISI Hawk hyperspectral airborne images of woodland and heath landscapes at Harwood,UK,were applied to quantify and evaluate the differences in spatial heterogeneity through semivariogram *** revealed that spatial heterogeneity of multisensor airborne images has a close relationship with spatial and spectral resolution and *** the visible,near-infrared spectra and short wave infrared spectra,greater spatial heterogeneity is generally observed from the relatively longer wavelength in short wave infrared *** are dramatic changes across the red and red edge spectra,and the peak value is generally examined in the red middle or red edge wavelength across the visible and near-infrared spectra for vegetation or non-vegetation landscape *** all,for real multisensor airborne images,the change in spatial heterogeneity with spatial resolution will accord with the change of support theory depending on whether dramatic change exists across the corresponding ***,if with close spatial resolution,the spatial heterogeneity of multispectral images might be far from the overall integration of these bands from the hyperspectral images involved.A comparative assessment of spatio-spectral heterogeneity using real hyperspectral and multispectral airborne images provides practical guidance for designing the placement and width of a spectral band for different applications and also makes a contribution to the understanding of how to reconcile spatial patterns generated by m

关键词： variogram modelling spatio-spectral heterogeneity ATM CASI Eagle Hawkairborne imagery multi-sensors

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Effect of Topography and Accessibility on Vegetation Dynamic Pattern in Mountain-hill Region

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Journal of Mountain Science 2012年第6期9卷 879-890页

作者： qiu bingwen ZHONG Ming ZENG Canying TANG Zhenghong CHEN Chongcheng Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian ProvinceFuzhou UniversityFuzhou 350002FujianChina Community and Regional Planning Program University of Nebraska-LincolnLincolnNebraskaUSA

Knowledge of both vegetation distribution pattern and phenology changes is very *** complicated relationship with elevation and accessibility were explored through a geographically weighted regression(GWR) framework in Fujian province,*** 16-day time series of 250 m Moderate Resolution Imaging Spectroradiometer(MODIS) Enhanced Vegetation Index(EVI) dataset from 2000 to 2010 was *** transform method was adopted to decompose the original time series and construct the annual maximum EVI and amplitude of the annual phenological cycle(EVI).Candidate explaining factors included topographic conditions,accessibility variables and proportions of primary vegetation *** revealed very strong positive influence from parameters of elevation and accessibility to big rivers and negative effect from accessibility to resident on both maximum EVI and phenological magnitude through ordinary linear least square(OLS) regression *** analysis revealed that spatially,the parameters of topography and accessibility had a very complex relationship with both maximum EVI and phenology magnitude,as a result of the various combinations of environmental factors,vegetation composition and also intensive anthropogenic *** from the continuously increasing trend of phenology magnitude with increasing altitude,the influence of topography and accessibility on maximum EVI and phenological magnitude generally decreased,even from strongly positive to negative,with increasing altitude or ***,the most rapid change of correlation coefficient between them was observed within a low elevation or close distance;less variation was discovered within a certain range of medium altitude or distance and their relationship might change above this ***-stationary approaches are needed to better characterize the complex vegetation dynamic pattern in Mountain-hill Region.

关键词： Vegetation phenology Elevation gradient Accessibility Geographic weighted regression Enhanced Vegetation Index Spatial non-stationality

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Spatiotemporal variability of vegetation phenology with reference to altitude and climate in the subtropical mountain and hill region, China

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Chinese Science Bulletin 2013年第23期58卷 2883-2892页

作者： qiu bingwen ZHONG Ming TANG ZhengHong CHEN ChongCheng Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian Province Community and Regional Planning Program University of Nebraska-Lincoln

Understanding the seasonal behaviour of a subtropical forest and its inter-annual variation is crucial to understanding and monitoring its ecosystem function in the context of global warming. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index dataset, a wavelet transform method was used to investigate the inter-annual variations of vegetation phenology in a subtropical mountain and hill region in Fujian, China, during 2001-2010. The results show a distinct inter-annual variation of vegetation phenology related to climate variability even if most areas presented non-significant trends. The start dates significantly advanced and end dates delayed in 2003 and 2008, due to anomalously warm conditions. There was generally a gradient of increasing start dates, and earlier end dates of vegetation growing season, due to colder temperatures at higher altitudes. However, the altitudinal phenology relationship also depends on its corresponding rainfall conditions. Earlier start dates were observed at higher altitudes during rainfall deficit years such as 2008, which coincides with relatively abundant rainfall at higher altitudes. This paper reveals that vegetation phenology was coupled with altitudinal gradient, with distinct responses at different combinations of alternate temperature and precipitation conditions variability.

关键词：全球气候变暖植被物候亚热带山地丘陵地区时空变异海拔高度中国中分辨率成像光谱仪

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Spatiotemporal analysis of vegetation variability and its relationship with climate change in China

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Geo-Spatial Information Science 2014年第3期17卷 170-180页

作者： bingwen qiu Weijiao LI Ming ZHONG Zhenghong TANG Chongcheng CHEN National Engineering Research Centre of Geospatial Information Technology Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of EducationFuzhou UniversityFuzhou 350002FujianChina Community and Regional Planning Program University of Nebraska-LincolnLincolnNEUSA

This paper investigated spatiotemporal dynamic pattern of vegetation,climate factor,and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS ***,most vegetation canopies demonstrated obvious seasonality,increasing with latitudinal ***,obvious dynamic trends were observed in both vegetation and climate change,especially the positive *** 70%areas were observed with obvious vegetation greening up,with vegetation degradation principally in the Pearl River Delta,Yangtze River Delta,and *** warming trend was observed across the whole country(>98%area),stronger in Northern *** over half of area(58.2%)obtained increasing rainfall trend,around a quarter of area(24.5%),especially the Central China and most northern portion of China,exhibited significantly negative rainfall ***,significantly positive normalized difference vegetation index(NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions,corresponding to their synchronous stronger seasonal ***,at inter-annual level,the NDVI–climate relationship differed with climatic regions and their long-term trends:in humid regions,positive coefficients were observed except in regions with vegetation degradation;in arid,semiarid,and semihumid regions,positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing *** study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process.

关键词： vegetation variability wavelet transform climate change non-stationary normalized difference vegetation index(NDVI)

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Characterizing Landscape Spatial Heterogeneity in Multisensor Images with Variogram Models

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Chinese Geographical Science 2014年第3期24卷 317-327页

作者： qiu bingwen ZENG Canying CHENG Chongcheng TANG Zhenghong GAO Jianyang SUI Yinpo Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Community and Regional Planning Program University of Nebraska-Lincoln Geological Remote Sensing Centre of Fujian Province

Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.

关键词： variogram modeling spatial heterogeneity characteristic scale multisensor image

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福建省耕地多尺度空间分布特征分析

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农业工程学报 2008年第11期24卷 63-68,F0003页

作者：邱炳文福州大学空间数据挖掘与信息共享教育部重点实验室福州大学空间信息工程研究中心福州350002

区域土地利用格局分析应优先考虑影响因子识别及其尺度效应研究。该文分别通过整体与分区研究,采用统计方法与GIS技术,从自然环境、社会经济以及基础设施条件各方面选取25个候选影响因子,开展福建省耕地多尺度空间分布特征研究。采用的... 详细信息

区域土地利用格局分析应优先考虑影响因子识别及其尺度效应研究。该文分别通过整体与分区研究,采用统计方法与GIS技术,从自然环境、社会经济以及基础设施条件各方面选取25个候选影响因子,开展福建省耕地多尺度空间分布特征研究。采用的基本研究单元为1km×1km,在此基础上生成2km×2km,3km×3km～10km×10km共10个空间尺度序列数据图层。不同空间尺度上分别构建福建省6个农业综合分区耕地空间分布模型,探讨了福建省耕地空间分布影响因子的尺度规模效应。研究表明模型不仅会随着研究尺度发生变化,在不同的农业综合分区内也有较大的差异。分区研究比整体研究的模型解释能力要高,模型的解释能力总体上随研究尺度的增大而升高。除坡度因子外,其他影响因子本身及其影响系数在不同的农业综合分区间发生变化,但总体规律是福建省耕地受坡度、海拔高程等不易随时间改变的自然条件的严格制约,并且这种制约作用随尺度增大呈逐渐增强趋势。

关键词：耕地尺度效应影响因子农业综合分区福建省

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Vegetation distribution pattern along altitudinal gradient in subtropical mountainous and hilly river basin, China

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Journal of Geographical Sciences 2013年第2期23卷 247-257页

作者： qiu bingwen ZENG Canying CHEN Chongcheng ZHANG Chungui ZHONG Ming KeyLaboratoryofSpatialDataMining&InformationSharingofMinistryofEducation.SpatialInformationResearchCentreofFujianProvince FuzhouUniversityFuzhou350002China FujianMeteorologicalResearchInstitute Fuzhou350002China

Knowledge of vegetation distribution patterns is very important. Their relationships with topography and climate were explored through a geographically weighted regression （GWR） framework in a subtropical mountainous and hilly region, Minjiang River Basin of Fujian in China. The HJ-1 satellite image acquired on December 9, 2010 was utilized and NDVI index was calculated representing the range of vegetation greenness. Proper analysis units were achieved through segregation based on small sub-basins and altitudinal bands. Results indicated that the GWR model was more powerful than ordinary linear least square （OLS） regression in interpreting vegetation-environmental relationship, indicated by higher adjusted R2 and lower Akaike information criterion values. On one side, the OLS analysis revealed dominant positive influence from parameters of elevation and slope on vegetation distribution. On the other side, GWR analysis indicated that spatially, the parameters of topography had a very complex relationship with the vegetation distribution, as results of the various combinations of environmental factors, vegetation composition and also anthropogenic impact. The influences of elevation and slope generally decreased, from strongly positive to nearly zero, with increasing altitude and slope. Specially, most rapid changes of coefficients between NDVI and elevation or slope were observed in relatively flat and low-lying areas. This paper confirmed that the non-stationary analysis through the framework of GWR could lead to a better understanding of vegetation distribution in subtropical mountainous and hilly region. It was hoped that the proposed scale selection method combined with GWR framework would provide some guidelines on dealing with both spatial （horizontal） and altitudinal （vertical） non-stationarity in the dataset, and it could easily be applied in characterizing vegetation distribution patterns in other mountainous and hilly river basins and related research.

关键词： vegetation altitudinal gradient GWR non-stationary Minjiang River Basin

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