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学者姓名：梁娟珠
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Detecting the spatial organization patterns of urban networks with multiple traffic flows from the perspective of complex networks and traffic behavior will help to optimize the urban spatial structure and thereby promote the sustainable development of the city. However, there are notable differences in regional spatial patterns among the different modes of transportation. Based on the road, railway, and air frequency data, this article investigates the spatial distribution and accessibility patterns of multiple transportation flows in the Yangtze River Economic Belt. Next, we use the TCD (Transportation Cluster Detection) community discovery algorithm and integrate it with the Baidu Maps API to obtain real-time time cost data to construct a community detection model of a multiple traffic flow network. We integrate the geographical network and topological network to perform feature extraction and rule mining on the spatial organization model of the urban network in the Yangtze River Economic Belt. The results show that: (1) The multiple traffic flow network of the Yangtze River Economic Belt has significant spatial differentiation. The spatial differentiation of aviation and railway networks is mainly concentrated between regions and within provinces, while the imbalance of highway networks is manifested as an imbalance within regions and between provinces. (2) The accessibility pattern of the highway network in the Yangtze River Economic Belt presents a "core-edge" spatial pattern. The accessibility pattern of the railway network generally presents a spatial pattern of "strong in the east and weak in the west". Compared with sparse road and railway networks, the accessibility pattern of the aviation network shows a spatial pattern of "time and space compression in western cities". (3) A total of 24 communities were identified through the TCD algorithm, mainly encompassing six major "urban economic communities" located in Guizhou, Yunnan, Anhui, Sichuan-Chongqing, Hubei-Hunan-Jiangxi, and Jiangsu-Zhejiang-Shanghai. (4) The urban network space organization model of the Yangtze River Economic Belt can be roughly divided into three models: the "single-core" model, with Guizhou, Kunming, and Hefei as the core, the "dual-core" model, constructed by Chengdu-Chongqing, and the "multi-core" model, constructed by Changsha-Wuhan-Nanchang and Shanghai-Nanjing-Hangzhou. This model of urban network spatial organization holds indicative significance in revealing the spatial correlation pattern among prefecture-level city units.
Keyword ：
Baidu Maps Baidu Maps multiple traffic flow network multiple traffic flow network spatial organization model spatial organization model TCD algorithm TCD algorithm weighted average travel time weighted average travel time Yangtze River Economic Zone Yangtze River Economic Zone
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| GB/T 7714 | Liang, Juanzhu , Xie, Shunyi , Bao, Jinjian . Analysis of a Multiple Traffic Flow Network's Spatial Organization Pattern Recognition Based on a Network Map [J]. | SUSTAINABILITY , 2024 , 16 (3) . |
| MLA | Liang, Juanzhu 等. "Analysis of a Multiple Traffic Flow Network's Spatial Organization Pattern Recognition Based on a Network Map" . | SUSTAINABILITY 16 . 3 (2024) . |
| APA | Liang, Juanzhu , Xie, Shunyi , Bao, Jinjian . Analysis of a Multiple Traffic Flow Network's Spatial Organization Pattern Recognition Based on a Network Map . | SUSTAINABILITY , 2024 , 16 (3) . |
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The amount of actively cultivated land in China is increasingly threatened by rapid urbanization and rural population aging. Quantifying the extent and changes of active cropland and cropping intensity is crucial to global food security. However, national-scale datasets for smallholder agriculture are limited in spatiotemporal continuity, resolution, and precision. In this paper, we present updated annual Cropland Use Intensity maps in China (China-CUI10m) with descriptions of the extent of fallow/abandoned, actively cropped fields and cropping intensity at a 10-m resolution in recent six years (2018-2023). The dataset is produced by robust algorithms with no requirements for regional adjustments or intensive training samples, which take full advantage of the Sentinel-1 (S1) SAR and Sentinel-2 (S2) MSI time series. The China-CUI10m maps have achieved high accuracy when compared to ground truth data (Overall accuracy = 90.88%) and statistical data (R-2 > 0.94). This paper provides the recent trends in cropland abandonment and agricultural intensification in China, which contributes to facilitating geographic-targeted cropland use control policies towards sustainable intensification of smallholder agricultural systems in developing countries.
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| GB/T 7714 | Qiu, Bingwen , Liu, Baoli , Tang, Zhenghong et al. National-scale 10-m maps of cropland use intensity in China during 2018-2023 [J]. | SCIENTIFIC DATA , 2024 , 11 (1) . |
| MLA | Qiu, Bingwen et al. "National-scale 10-m maps of cropland use intensity in China during 2018-2023" . | SCIENTIFIC DATA 11 . 1 (2024) . |
| APA | Qiu, Bingwen , Liu, Baoli , Tang, Zhenghong , Dong, Jinwei , Xu, Weiming , Liang, Juanzhu et al. National-scale 10-m maps of cropland use intensity in China during 2018-2023 . | SCIENTIFIC DATA , 2024 , 11 (1) . |
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Monitoring vegetation photosynthesis in China's subtropical regions using remote sensing is challenging because of the complex ecosystems and climate variability. Previous studies often pay less attention on the influence of multiple climatic factors on the temporal effects (lag and accumulation) of vegetation photosynthesis, thereby underestimating their impact. This study utilizes a dataset comprising Solar-induced chlorophyll fluorescence (SIF) data (GOSIF product), MODIS Land Cover product (MCD12C1), and various climatic variables. Analytical methods including Theil-Sen Median trend analysis, the Mann-Kendall test, partial correlation analysis, and the optimal parameter-based geographical detector (OPGD) model were employed to explore the temporal dynamics of subtropical vegetation SIF responses to climatic factors and to identify their climate drivers in subtropical China. The study findings indicate that (1) vegetation photosynthesis, as indicated by SIF, exhibited an increasing trend in the majority of Chinese subtropical regions, which constitute over 80 % of the study area, with particularly pronounced enhancements in the southern and central western parts of the Chinese subtropics. (2) Soil moisture primarily exhibits lag effects on SIF, particularly in evergreen needleleaf forests, deciduous broadleaf forests, and mixed forests, whereas temperature does not exhibit significant temporal effects. Solar radiation and vapor pressure deficits impact SIF through both lag and accumulation effects. Under the lag and accumulation effects, the proportion of significant correlations between climatic factors and vegetation SIF increases by 36.71 % similar to 43.8 %, excluding temperature. (3) Temperature is the dominant factor affecting vegetation SIF, particularly in the evergreen needleleaf forest. Interactions between climatic factors have a significantly stronger influence on SIF than individual factors. Notably, the explanatory power of the vapor pressure deficit increases substantially when it interacts with other factors. Studying the lag and accumulation effects of climatic factors on photosynthesis aids in accurately predicting vegetation responses to climate change, thereby improving the accuracy of global carbon cycle models and guiding the development of carbon sequestration management strategies.
Keyword ：
Carbon cycle Carbon cycle Climate change Climate change Solar-induced chlorophyll fluorescence (SIF) Solar-induced chlorophyll fluorescence (SIF) Subtropical vegetation Subtropical vegetation Time-accumulation effect Time-accumulation effect Time-lag effect Time-lag effect Vegetation photosynthesis Vegetation photosynthesis
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| GB/T 7714 | Liang, Juanzhu , Han, Xueyang , Zhou, Yuke et al. Investigating the temporal lag and accumulation effect of climatic factors on vegetation photosynthetic activity over subtropical China [J]. | ECOLOGICAL INDICATORS , 2024 , 166 . |
| MLA | Liang, Juanzhu et al. "Investigating the temporal lag and accumulation effect of climatic factors on vegetation photosynthetic activity over subtropical China" . | ECOLOGICAL INDICATORS 166 (2024) . |
| APA | Liang, Juanzhu , Han, Xueyang , Zhou, Yuke , Yan, Luyu . Investigating the temporal lag and accumulation effect of climatic factors on vegetation photosynthetic activity over subtropical China . | ECOLOGICAL INDICATORS , 2024 , 166 . |
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Accurate and continuous maps of maize distribution are essential for food security and sustainable agricultural development. However, there are no continuous national-scale and fine-resolution maize maps and explicit updated information on the spatiotemporal dynamics of maize for most countries. Maize mapping at the national scale is challenging due to the spectral heterogeneity caused by crop growth conditions, cropping patterns, and inter-annual variations. To this end, this study developed a novel crop index-based algorithm for national-scale maize mapping. Compared to other crops, maize is characterized by large-leaf-dominated canopies and high photosynthetic efficiency. Maize shows significant changes in chlorophyll and anthocyanin content. Therefore, a robust maize index was established by exploring the temporal Variation of the Vegetation-Pigment index (VVP) during the growing period. A simple decision rule was coded on the Google Earth Engine (GEE) platform, which was used for maize mapping based on the Sentinel-2 time series in China and the contiguous United States (US) from 2018 to 2022. The national-scale 10 m annual maize maps for China and the contiguous US were developed and in good agreement with the corresponding agricultural statistics data for many years (R-2 > 0.94) and 9,412 reference points (overall accuracy of 90.09 %). Compared with simply applying the vegetation index, the VVP index took account of spectral heterogeneity caused by variations in crop growth conditions, cropping patterns, and inter-annual, and the omission error of maize was reduced by over 20 %. Moreover, the VVP index can significantly improve the spatial transferability of the Random Forest (RF) classifier. The first 10 m annual maize maps for China revealed that the planted area trend decreased and then increased from 2018 to 2022. The year 2020 was the turning point. The maize planted area consisted of 68 % single maize and 32 % double cropping with maize in 2020, with the northern boundary for double cropping with maize in the Yanshan Mountains. The maize planted area in China consistently decreased by 39,352 km(2) (about 9 %) from 2018 to 2020. This is mainly due to the adjustment of the maize-planted structure in the "Sickle Bend" region of China (the "Sickle Bend" policy). However, the maize planted area gradually recovered from 2020 to 2022, primarily concentrated in regions with ever-planted. This study will provide essential information for cropping structure adjustment and related agricultural policy formulation and contribute to sustainable agricultural development by mapping maize from a national to a global scale.
Keyword ：
Crop mapping Crop mapping Cross -region Cross -region Maize index Maize index National -scale National -scale Spatiotemporal variations Spatiotemporal variations
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| GB/T 7714 | Huang, Yingze , Qiu, Bingwen , Yang, Peng et al. National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series [J]. | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2024 , 221 . |
| MLA | Huang, Yingze et al. "National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series" . | COMPUTERS AND ELECTRONICS IN AGRICULTURE 221 (2024) . |
| APA | Huang, Yingze , Qiu, Bingwen , Yang, Peng , Wu, Wenbin , Chen, Xuehong , Zhu, Xiaolin et al. National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series . | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2024 , 221 . |
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Tea trees (Camellia sinensis), a quintessential homestead agroforestry crop cultivated in over 60 countries, hold significant economic and social importance as a vital specialty cash crop. Accurate nationwide crop data is imperative for effective agricultural management and resource regulation. However, many regions grapple with a lack of agroforestry cash crop data, impeding sustainable development and poverty eradication, especially in economically underdeveloped countries. The large-scale mapping of tea plantations faces substantial limitations and challenges due to their sparse distribution compared to field crops, unfamiliar characteristics, and spectral confusion among various land cover types (e.g., forests, orchards, and farmlands). To address these challenges, we developed the Manual management And Phenolics substance-based Tea mapping (MAP-Tea) framework by harnessing Sentinel-1/2 time series images for automated tea plantation mapping. Tea trees, exhibiting higher phenolic content, evergreen characteristics, and multiple shoot sprouting, result in extensive canopy coverage, stable soil exposure, and radar backscatter signal interference from frequent picking activities. We developed three phenology-based indicators focusing on phenolic content, vegetation coverage, and canopy texture leveraging the temporal features of vegetation, pigments, soil, and radar backscattering. Characteristics of biochemical substance content and manual management measures were applied to tea mapping for the first time. The MAP-Tea framework successfully generated China's first updated 10 m resolution tea plantation map in 2022. It achieved an overall accuracy of 94.87% based on 16,712 reference samples, with a kappa coefficient of 0.83 and an F1 score of 85.63%. The tea trees are typically cultivated in mountainous and hilly areas with a relatively low planting density (averaging about 10%). Alpine tea trees exhibited a notably dense concentration and dominance, mainly found in regions with elevations ranging from 700 m to 2000 m and slopes between 2 degrees to 18 degrees. The areas with low altitudes and slopes hold the largest tea plantation area and output. As the slope increased, there was a gradual decline in the dominance of tea areas. The results suggest a good potential for the knowledge-based approaches, combining biochemical substance content and human activities, for national-scale tea plantation mapping in complex environment conditions and challenging landscapes, providing important reference significance for mapping other agroforestry crops. This study contributes significantly to advancing the achievement of the Sustainable Development Goals (SDGs) considering the crucial role that agroforestry crops play in fostering economic growth and alleviating poverty. The first 10m national Tea tree data products in China with good accuracy (ChinaTea10m) are publicly accessed at https://doi.org/10.6084/m9.figshare .25047308.
Keyword ：
Agroforestry crop mapping Agroforestry crop mapping Phenology-based algorithm Phenology-based algorithm Sentinel-1/2 Sentinel-1/2 Special cash crop Special cash crop Tea plantation Tea plantation
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| GB/T 7714 | Peng, Yufeng , Qiu, Bingwen , Tang, Zhenghong et al. Where is tea grown in the world: A robust mapping framework for agroforestry crop with knowledge graph and sentinels images [J]. | REMOTE SENSING OF ENVIRONMENT , 2024 , 303 . |
| MLA | Peng, Yufeng et al. "Where is tea grown in the world: A robust mapping framework for agroforestry crop with knowledge graph and sentinels images" . | REMOTE SENSING OF ENVIRONMENT 303 (2024) . |
| APA | Peng, Yufeng , Qiu, Bingwen , Tang, Zhenghong , Xu, Weiming , Yang, Peng , Wu, Wenbin et al. Where is tea grown in the world: A robust mapping framework for agroforestry crop with knowledge graph and sentinels images . | REMOTE SENSING OF ENVIRONMENT , 2024 , 303 . |
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Global climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, assessing the response of vegetation dynamics to drought can offer valuable insights into the physiological mechanisms of terrestrial ecosystems. Here, we applied long-term datasets (2001-2020) of solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) to unveil vegetation dynamics and their relationship to meteorological drought (SPEI) across different vegetation types in the Yangtze River Basin (YRB). Linear correlation analysis was conducted to determine the maximum association of SPEI with SIF and NDVI; we then compared their responses to meteorological drought. The improved partial wavelet coherence (PWC) method was utilized to quantitatively assess the influences of large-scale climate patterns and solar activity on the relationship between vegetation and meteorological drought. The results show that: (1) Droughts were frequent in the YRB from 2001 to 2020, and the summer's dry and wet conditions exerted a notable influence on the annual climate. (2) SPEI exhibits a more significant correlation with SIF than with NDVI. (3) NDVI has a longer response time (3-6 months) to meteorological drought than SIF (1-4 months). Both SIF and NDVI respond faster in cropland and grassland but slower in evergreen broadleaf and mixed forests. (4) There exists a significant positive correlation between vegetation and meteorological drought during the 4-16 months period. The teleconnection factors of Pacific Decadal Oscillation (PDO), El Nino Southern Oscillation (ENSO), and sunspots are crucial drivers that affect the interaction between meteorological drought and vegetation, with sunspots having the most significant impact. Generally, our study indicates that drought is an essential environmental stressor that disrupts vegetation growth over the YRB. Additionally, SIF demonstrates great potential in monitoring vegetation response to drought. These findings will be meaningful for drought prevention and ecosystem conservation planning in the YRB.
Keyword ：
climate change climate change meteorological drought meteorological drought NDVI NDVI SIF SIF vegetation dynamics vegetation dynamics Yangtze River Basin Yangtze River Basin
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| GB/T 7714 | Dong, Xiujuan , Zhou, Yuke , Liang, Juanzhu et al. Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data [J]. | REMOTE SENSING , 2023 , 15 (14) . |
| MLA | Dong, Xiujuan et al. "Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data" . | REMOTE SENSING 15 . 14 (2023) . |
| APA | Dong, Xiujuan , Zhou, Yuke , Liang, Juanzhu , Zou, Dan , Wu, Jiapei , Wang, Jiaojiao . Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data . | REMOTE SENSING , 2023 , 15 (14) . |
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植被净初级生产力(net primary productivity, NPP)是评价生态系统固碳能力的重要指标。长江流域作为中国重要的农业生产区和生态安全屏障，深入开展长江流域植被NPP时空变化特征的研究，对了解流域植被生长情况和生物固碳能力具有重要意义。基于CASA模型，反演长江流域植被NPP,分析长江流域2001—2018年不同时空尺度下的植被NPP的演变特征以及与地形因子的关系。结果显示：CASA模型对于长江流域植被NPP的反演效果较好，可以反映研究区的植被NPP的实际状态，长江流域多年植被NPP为572.72 gC/(m~2·a)。时间上，长江流域植被NPP年际变化可分为2个阶段，2001—2007年NPP年均值变化明显，呈波动式上升；2008—2018年相对变化趋于平稳，植被NPP年内变化层次感比较明显，夏半年(4—9月)NPP月均值较高，对全年NPP总量的贡献率为77.61%。长江流域植被NPP空间格局上具有明显的差异性，总体呈现自西北向东南递增，长江流域在18年间植被NPP增加的面积大于减少的面积，NPP增加趋势主要分布在岷沱江水系南部、嘉陵江水系西部、乌江水系西部和洞庭湖水系东部地区。NPP与各地形因子分级的关系都不同，高程在3 000 m以下时，长江流域植被NPP随着高程的增加而增加，高程>3 000 m的地区植被NPP显著减少，最适合植被生长的高程带是2 000～3 000 m。<6°坡度对NPP的解释较差，6°～15°和>15°～25°坡度对植被NPP的解释较好；除半阴坡外，其他坡向对NPP影响不大。
Keyword ：
CASA模型 CASA模型 地形因子 地形因子 时空变化 时空变化 植被净初级生产力 植被净初级生产力 长江流域 长江流域
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| GB/T 7714 | 李俊豪 , 梁娟珠 . 基于CASA模型长江流域植被NPP时空演变及与地形因子的关系 [J]. | 贵州大学学报(自然科学版) , 2023 , 40 (03) : 30-40 . |
| MLA | 李俊豪 et al. "基于CASA模型长江流域植被NPP时空演变及与地形因子的关系" . | 贵州大学学报(自然科学版) 40 . 03 (2023) : 30-40 . |
| APA | 李俊豪 , 梁娟珠 . 基于CASA模型长江流域植被NPP时空演变及与地形因子的关系 . | 贵州大学学报(自然科学版) , 2023 , 40 (03) , 30-40 . |
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从复杂网络和个体出行行为角度挖掘多中心城市网络空间组织模式，有助于优化城市空间结构。该文基于长江经济带多元交通流数据，采用TCD(Transportation Cluster Detection)社区发现算法融合百度地图API获取的城市内外部实时时间成本数据，构建多元交通流网络社区结构探测模型，对长江经济带城市网络的空间组织模式进行特征提取和规则挖掘。结果表明：(1)公路网络在省域尺度表现出显著的“核心—边缘”结构；铁路网络表现出“东高西低”的分布态势；航空网络分布态势与铁路网络相反，西部城市航空网络的枢纽效应强于中部、东部城市；综合交通网络总体呈现“以铁路为主、公路为辅、航空为补”的共振状态。(2)利用TCD算法合并节点过程中，社区数量与城市节点的邻近指数符合幂律分布，共识别出24个社区，其中包括贵州、云南、安徽、川渝、鄂湘赣和江浙沪六大“城市经济社区”。(3)长江经济带城市网络空间组织模式包括以贵州、昆明、合肥为核心的“单核心”模式、成都—重庆构建的“双核心”模式以及长沙—武汉—南昌和上海—南京—杭州构建的“多核心”模式，该城市网络空间组织模式对于揭示地级市网络空间关联格局具有指示意义。
Keyword ：
TCD算法 TCD算法 多元交通流网络 多元交通流网络 旅行成本 旅行成本 百度地图 百度地图 空间组织模式 空间组织模式 长江经济带 长江经济带
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| GB/T 7714 | 鲍进剑 , 梁娟珠 , 周玉科 et al. 多元交通流视角下长江经济带城市网络空间组织模式分析 [J]. | 地理与地理信息科学 , 2023 , 39 (02) : 46-54,143 . |
| MLA | 鲍进剑 et al. "多元交通流视角下长江经济带城市网络空间组织模式分析" . | 地理与地理信息科学 39 . 02 (2023) : 46-54,143 . |
| APA | 鲍进剑 , 梁娟珠 , 周玉科 , 贾红霞 . 多元交通流视角下长江经济带城市网络空间组织模式分析 . | 地理与地理信息科学 , 2023 , 39 (02) , 46-54,143 . |
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为深入研究河北省石家庄、邯郸、唐山以及邢台4座“退后十”重点城市干湿季PM_(2.5)的重污染传输潜在源区，结合GDAS数据，基于HYSPLIT后向轨迹，通过聚类分析、潜在污染源以及浓度权重的计算，对4座重点城市进行大气污染来源的分析。结果表明：1)PM_(2.5)质量浓度呈现为干季浓度较高、湿季浓度较低，同时地域差异较大；2)干季气团4个城市主要受山西省、陕西省、河南省和山东省重工业城市春冬季大量的燃煤、机动车尾气及二次反应携带高浓度气团的影响，该类气团轨迹传输路径较短，传输速度快，影响显著；3)湿季气团大多来源于沿海地区和北部内陆地区，由蒙古国传输至内蒙古地区，以自然源排放为主，受北部冷空气持续影响，使得大气污染物浓度稀释；4)PM_(2.5)较强潜在源区都集中在内蒙古西南部、陕西省东北部、山西省中南部、河南省北部，其中强潜在源区相似，主要集中在延安市、吕梁市、临汾市。
Keyword ：
PM_(2.5) PM_(2.5) 后向轨迹 后向轨迹 干湿季 干湿季 河北省 河北省 潜在源区 潜在源区 输送路径 输送路径
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| GB/T 7714 | 鲍进剑 , 梁娟珠 . 河北省重点城市干湿季PM_(2.5)输送路径和来源分析 [J]. | 测绘与空间地理信息 , 2023 , 46 (10) : 50-53,57 . |
| MLA | 鲍进剑 et al. "河北省重点城市干湿季PM_(2.5)输送路径和来源分析" . | 测绘与空间地理信息 46 . 10 (2023) : 50-53,57 . |
| APA | 鲍进剑 , 梁娟珠 . 河北省重点城市干湿季PM_(2.5)输送路径和来源分析 . | 测绘与空间地理信息 , 2023 , 46 (10) , 50-53,57 . |
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土地覆盖变化影响局域的能源和水平衡，并在全球范围内促进碳的净排放。基于欧空局气候变化倡议项目最新发布的1992年—2015年300 m分辨率的全球土地覆盖数据集，本文分析了1992年—2015年“一带一路”沿线主要土地覆盖类型变化的时空特征及其驱动力。研究结果表明：1992年—2015年沿线耕地、草地和建设用地面积分别增加190.00×10~3km~2、57.97×10~3km~2和260.39×10~3km~2，森林、灌木、湿地和水体面积分别减少61.14×10~3km~2、34.22×10~3km~2、74.28×10~3km~2和44.41×10~3km~2。2000年—2015年与19...
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“一带一路”沿线 “一带一路”沿线 土地覆盖变化 土地覆盖变化 时空特征 时空特征 遥感 遥感 驱动力 驱动力
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| GB/T 7714 | 海凯 , 王思远 , 涂平 et al. “一带一路”沿线国家1992年—2015年土地覆盖变化的时空格局及其驱动力分析 [J]. | 遥感学报 , 2022 , 26 (06) : 1220-1235 . |
| MLA | 海凯 et al. "“一带一路”沿线国家1992年—2015年土地覆盖变化的时空格局及其驱动力分析" . | 遥感学报 26 . 06 (2022) : 1220-1235 . |
| APA | 海凯 , 王思远 , 涂平 , 杨瑞霞 , 马元旭 , 梁娟珠 et al. “一带一路”沿线国家1992年—2015年土地覆盖变化的时空格局及其驱动力分析 . | 遥感学报 , 2022 , 26 (06) , 1220-1235 . |
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