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学者姓名：王琳
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Abstract ：
基于土地利用数据和景观生态风险评价模型，分析2000—2020年长株潭都市圈景观生态风险时空演变特征，结合PLUS模型科学预测自然发展情景和生态保护情景下2030年长株潭都市圈的景观生态风险空间分布格局。结果表明：(1)2000—2020年长株潭都市圈景观生态风险呈现北高南低、西高东低的空间分布特征，较低和中等生态风险区域总面积占比大于60%,生态风险加剧区域面积不到生态风险降低区域面积的1%,整体表现出高等级生态风险区向低等级生态风险区转移的特征；(2)研究区景观生态风险表现出较强的空间集聚特征，高—高集聚区主要分布在宁乡市、望城区、渌口区、雨花区和长沙县，低—低集聚区主要分布在研究区边界；(3)相比自然发展情景，生态保护情景下生态用地减少速率变缓，有助于缓解研究区生态风险，有利于构建和谐有序的生态安全格局。
Keyword ：
PLUS模型 PLUS模型 多情景模拟 多情景模拟 景观生态风险 景观生态风险 长株潭都市圈 长株潭都市圈
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| GB/T 7714 | 邓晓辉 , 王琳 , 欧彩虹 et al. 基于PLUS模型的长株潭都市圈景观生态风险动态分析 [J]. | 地理与地理信息科学 , 2024 , 40 (01) : 47-54,98 . |
| MLA | 邓晓辉 et al. "基于PLUS模型的长株潭都市圈景观生态风险动态分析" . | 地理与地理信息科学 40 . 01 (2024) : 47-54,98 . |
| APA | 邓晓辉 , 王琳 , 欧彩虹 , 王文佳 . 基于PLUS模型的长株潭都市圈景观生态风险动态分析 . | 地理与地理信息科学 , 2024 , 40 (01) , 47-54,98 . |
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作为增加就业、提振消费及带动区域发展的城市消费“新蓝海”，夜间经济在“后疫情时代”逐渐成为研究热点。“夜间经济集聚中心”是夜间经济发展的核心和基础，国内外鲜有研究，它作为社会经济要素，具有非均匀对称和“灰色聚集”的特点，因此无法简单套用传统地理集聚中心的识别方法。研究从夜间经济的集聚机理出发，基于“点—轴系统”理论，提出了一种夜间经济集聚中心的识别提取方法，并利用广义对称图谱解构上海市中心城区夜间经济集聚中心的空间格局及其分异机理。首次为快速准确地识别夜间经济集聚中心，科学地挖掘其空间分布特点提供了系统的方法参考，为推动夜间经济的繁荣和可持续发展提供了决策支持。结果显示：在上海市中心城区范围内，共提取了12个一级夜间经济集聚中心，26个二级夜间经济集聚区，夜间经济平均活力值分别为0.49和0.24。研究表明：(1)该方法能快速识别和提取夜间经济集聚中心。(2)上海夜间经济集聚中心呈“中心—外围”空间分布格局，交通导向性强；(3)基础设施完善程度和距市中心距离，是上海夜间经济空间集聚分异的主要驱动因子。(4)集聚中心的“色对称”空间格局，表明上海夜经济处于一种合理、可持续的发展阶段；未来规划中，可沿地铁二号线东西扩展并内部填充，亦可将集聚对称中心连接线作为发展轴，以“集聚区”的形式提升夜经济集聚效应。
Keyword ：
地理探测器 地理探测器 夜间经济发展规划 夜间经济发展规划 夜间经济集聚中心 夜间经济集聚中心 广义对称图谱 广义对称图谱 “点-轴系统”理论 “点-轴系统”理论
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| GB/T 7714 | 王琳 , 欧彩虹 , 钟泓文 et al. “广义对称”视角下上海夜间经济集聚中心识别方法与空间分异机理 [J]. | 遥感技术与应用 , 2024 , 39 (01) : 209-221 . |
| MLA | 王琳 et al. "“广义对称”视角下上海夜间经济集聚中心识别方法与空间分异机理" . | 遥感技术与应用 39 . 01 (2024) : 209-221 . |
| APA | 王琳 , 欧彩虹 , 钟泓文 , 徐涵秋 . “广义对称”视角下上海夜间经济集聚中心识别方法与空间分异机理 . | 遥感技术与应用 , 2024 , 39 (01) , 209-221 . |
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The Russia-Ukraine conflict has persisted for over a year, posing challenges in assessing and verifying the extent of damage through on-site investigations. Nighttime light (NTL) remote sensing, an emerging approach for studying regional conflicts, can complement traditional methods. This article employs National Aeronautics and Space Administration's Black Marble products to reveal the response characteristics of NTL intensity at national and state scales during the first anniversary of the conflict (January 2022 to February 2023) in Ukraine. The article used the NTL ratio index to assess the relative intensity of NTL and month-on-month change rate, nighttime light change rate index (NLCRI), and the rate (R value) of linear regression analysis to depict spatiotemporal dynamics. In addition, Theil-Sen median trend analysis and Mann-Kendall tests were employed to analyze intensity trends, with a "dual-threshold method" to reduce extensive noise interference. The results showed: At the national scale, the conflict resulted in an 84.0% decrease in NTL across Ukraine. At the state scale, the most severe NTL decline occurred near the southwestern border and eastern conflict zone under Ukrainian government control, witnessing over 80% decline rates. The correlation of decreases in NLCRI and R values with population displacement, infrastructure damage, or curfew measures demonstrated that the concentration of refugees and electricity facility restoration led to increased NLCRI and R values. Overall, NTL reflects critical moments at the national scale and provides insights into military intentions and humanitarian measures at the state scale. Therefore, NTL can effectively serve as a tool for observation and assessment in military conflicts.
Keyword ：
Black Marble nighttime lights (NTLs) product suite Black Marble nighttime lights (NTLs) product suite multiscale analysis multiscale analysis Russia-Ukraine conflict Russia-Ukraine conflict spatiotemporal dynamics spatiotemporal dynamics VNP46A3 product VNP46A3 product
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| GB/T 7714 | Wang, Lin , Lei, Henggang , Xu, Hanqiu . Analysis of Nighttime Light Changes and Trends in the 1-Year Anniversary of the Russia-Ukraine Conflict [J]. | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 : 4084-4099 . |
| MLA | Wang, Lin et al. "Analysis of Nighttime Light Changes and Trends in the 1-Year Anniversary of the Russia-Ukraine Conflict" . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17 (2024) : 4084-4099 . |
| APA | Wang, Lin , Lei, Henggang , Xu, Hanqiu . Analysis of Nighttime Light Changes and Trends in the 1-Year Anniversary of the Russia-Ukraine Conflict . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 , 4084-4099 . |
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选取我国大豆主产区黑龙江省为研究区，采用生命周期评价(LCA)法核算该地区2011—2020年大豆生产的碳足迹，分析其时空分布特征，利用灰色关联分析法分析全省各地级市(地区)大豆生产碳足迹的影响因素，确定其碳排放的主要来源，提出大豆生产的生态优化方案。结果表明：2011—2020年黑龙江省大豆生产碳足迹平均值为0.337 kg/kg(以CO_2当量计),整体呈现反复波动、“北多南少”的格局；在所选的9个黑龙江省大豆生产碳足迹影响因素中，农药、种子、柴油3个因素的贡献度最大。
Keyword ：
大豆生产 大豆生产 时空分布 时空分布 生命周期评价 生命周期评价 生态优化 生态优化 碳足迹 碳足迹 黑龙江省 黑龙江省
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| GB/T 7714 | 陈晗奕 , 陈一灵 , 洪志坤 et al. 黑龙江省大豆生产的碳足迹时空分布特征及生态优化研究 [J]. | 环境监测管理与技术 , 2024 , 36 (03) : 21-26 . |
| MLA | 陈晗奕 et al. "黑龙江省大豆生产的碳足迹时空分布特征及生态优化研究" . | 环境监测管理与技术 36 . 03 (2024) : 21-26 . |
| APA | 陈晗奕 , 陈一灵 , 洪志坤 , 游璐萍 , 郑先鑫 , 王琳 et al. 黑龙江省大豆生产的碳足迹时空分布特征及生态优化研究 . | 环境监测管理与技术 , 2024 , 36 (03) , 21-26 . |
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Bamboo groves predominantly thrive in tropical or subtropical regions. Assessing the efficacy of remote sensing data of various types in extracting bamboo forest information from bright and shadow areas is a critical issue for achieving precise identification of bamboo forests in complex terrain. In this study, 34 features were obtained from Sentinel-1 SAR and Sentinel-2 optical images using the Google Earth Engine platform. The normalized shaded vegetation index (NSVI) was then employed to segment the bright and shadow woodlands. Different features from diverse data sources were evaluated to extract bamboo forest information in the bright and shadow areas, then use the random forest (RF) classification algorithm to extract bamboo forest. The results showed that (1) the red-edge and short-wave infrared bands of Sentinel-2 optical images and their corresponding vegetation indices are significant in bamboo forest information extraction. (2) The dissimilarity and homogeneity of Sentinel-2 texture features in the bright area and dissimilarity in the shadow area, the Sentinel-1 backscatter features in the bright area and the VV and VH in the bright area and VV-VH in the shadow area have some variability between bamboo and nonbamboo forests, which can be used as effective features for bamboo forest extraction. (3) The combination of spectral, texture and backscatter features yields the highest overall classification accuracy and Kappa coefficient, at 87.96% and 0.7435, respectively. This study has the potential for remote sensing refinement of bamboo forest identification in complex terrain areas by utilizing subregion classification methods combined with optical and radar image features.
Keyword ：
Bamboo forest Bamboo forest Google Earth Engine Google Earth Engine Sentinel-1 Sentinel-1 Sentinel-2 Sentinel-2 subregion classification subregion classification
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| GB/T 7714 | Xiang, Songyang , Xu, Zhanghua , Shen, Wanling et al. Mapping of bamboo forest bright and shadow areas using optical and SAR satellite data in Google Earth Engine [J]. | GEOCARTO INTERNATIONAL , 2023 , 38 (1) . |
| MLA | Xiang, Songyang et al. "Mapping of bamboo forest bright and shadow areas using optical and SAR satellite data in Google Earth Engine" . | GEOCARTO INTERNATIONAL 38 . 1 (2023) . |
| APA | Xiang, Songyang , Xu, Zhanghua , Shen, Wanling , Chen, Lingyan , Hao, Zhenbang , Wang, Lin et al. Mapping of bamboo forest bright and shadow areas using optical and SAR satellite data in Google Earth Engine . | GEOCARTO INTERNATIONAL , 2023 , 38 (1) . |
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深入探究都市圈尺度碳排放空间网络结构演化特征及其影响因素，有助于更好理解区域协同发展与生态环境之间的影响关系。该文利用夜间灯光数据和统计资料估算2000—2020年福州都市圈碳排放量，采用社会网络分析法深入剖析碳排放的空间关联特征，并结合地理探测器探究碳排放空间分异的影响因素。结果表明：(1)研究期内福州都市圈碳排放总量从346.4万t增至2 912.5万t,增加约7.4倍；(2)福州都市圈整体碳排放网络关联度升高，碳排放网络结构愈加复杂，但个体中心性差异显著，福州中心城区的个体中心性最高，对整体碳排放网络具有重要控制作用；(3)土地利用程度对碳排放空间分异的作用增强，城镇化率、人口规模、经济发展水平、社会资本和社会服务的影响作用减弱，以社会资本为主导的因子交互作用对碳排放空间分异影响突出。未来福州都市圈应持续推进区域协同发展，促进地区间的低碳交流，深化区域碳排放污染的联防联控联治。
Keyword ：
影响因子 影响因子 社会网络分析 社会网络分析 福州都市圈 福州都市圈 空间网络结构 空间网络结构 能源消费碳排放 能源消费碳排放
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| GB/T 7714 | 朱嘉豪 , 许章华 , 李诗涵 et al. 福州都市圈能源消费碳排放空间网络结构演化及其影响因素研究 [J]. | 地理与地理信息科学 , 2023 , 39 (06) : 75-83 . |
| MLA | 朱嘉豪 et al. "福州都市圈能源消费碳排放空间网络结构演化及其影响因素研究" . | 地理与地理信息科学 39 . 06 (2023) : 75-83 . |
| APA | 朱嘉豪 , 许章华 , 李诗涵 , 陈秋霞 , 林中原 , 凌金瑶 et al. 福州都市圈能源消费碳排放空间网络结构演化及其影响因素研究 . | 地理与地理信息科学 , 2023 , 39 (06) , 75-83 . |
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[目的]分析福州都市圈社会经济水平与生态环境韧性的协调状态及其发展趋势，为该都市圈区高质量、可持续发展提供调控建议与理论参考。[方法]以福州都市圈27个县域城市为例，构建基于韧性“抵抗—恢复—适应”特征的三维生态环境韧性评价模型，建立普适性的社会经济水平评价指标体系，结合熵权法、耦合协调度模型、核密度估计、剪刀差计算以及重心迁移模型，综合分析福州都市圈社会经济水平与生态环境韧性的耦合协调水平及其时空演化趋势，并通过Pearson相关分析方法探讨影响协调发展的主要因素。[结果](1)福州都市圈的社会经济水平均值由0.181 2上升至0.320 8,高值区在空间上呈现以福州市辖区为核心的“一核三中心”分布特征。(2)都市圈的生态环境韧性均值由0.429 4下降至0.349 4;韧性及其子系统在空间上存在较强的正自相关性，其中韧性高值区主要集聚于“延平—古田”等内陆山区，而低值区分布于“马尾—湄洲岛”沿海一带，并在福州市辖区及其周围形成了韧性“洼地”。(3)福州都市圈的耦合协调度均值从0.51稳步提升至0.56,县域社会经济水平与生态环境韧性的发展速度趋于平衡，剪刀差角度普遍减小；协调发展重心向都市圈中部地区移动，进入同步发展类型的县域数量大幅提升；影响都市圈耦合协调发展的主要因素为抗风险指数、人均GDP以及每千人拥有医院床位数。[结论]福州都市圈的社会经济水平与生态环境韧性在时空上呈现“错位”发展趋势，两系统的耦合协调水平尚有较大的提升空间。
Keyword ：
“抵抗—恢复—适应”模型 “抵抗—恢复—适应”模型 时空演化 时空演化 生态环境韧性 生态环境韧性 社会经济水平 社会经济水平 福州都市圈 福州都市圈 耦合协调发展 耦合协调发展
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| GB/T 7714 | 李诗涵 , 陈秋霞 , 许章华 et al. 福州都市圈社会经济水平与生态环境韧性的时空演化及耦合协调性 [J]. | 水土保持通报 , 2023 , 43 (06) : 311-323 . |
| MLA | 李诗涵 et al. "福州都市圈社会经济水平与生态环境韧性的时空演化及耦合协调性" . | 水土保持通报 43 . 06 (2023) : 311-323 . |
| APA | 李诗涵 , 陈秋霞 , 许章华 , 俞辉 , 朱嘉豪 , 刘智才 et al. 福州都市圈社会经济水平与生态环境韧性的时空演化及耦合协调性 . | 水土保持通报 , 2023 , 43 (06) , 311-323 . |
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针对机场出租车"待客-返程"决策模式,基于机会成本视角构建一种决策支持模型.综合考虑影响出租车司机决策的相关因素,构建旅客搭乘出租车的意愿函数和出租车司机机会成本的线性对数回归模型;定义"选择决策因子",建立"待客-返程"决策支持模型,分析研究不同季节、时段的最优解;用南京禄口国际机场的数据进行模型训练,得到该机场出租车司机决策方案;采用敏感性分析法定量分析模型对决策因子的依赖性,以验证模型性能.实验结果表明,该模型决策方案可靠,对决策因子变化敏感,能有效提高机场的客流集散效率.
Keyword ：
二分类逻辑回归模型 二分类逻辑回归模型 敏感性分析 敏感性分析 机会成本 机会成本 机场出租车 机场出租车 线性对数回归 线性对数回归
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| GB/T 7714 | 林瑶 , 王琳 , 徐宗煌 et al. 机场出租车"待客-返程"决策支持模型——以南京禄口国际机场为例 [J]. | 计算机应用与软件 , 2023 , 40 (8) : 24-31,79 . |
| MLA | 林瑶 et al. "机场出租车"待客-返程"决策支持模型——以南京禄口国际机场为例" . | 计算机应用与软件 40 . 8 (2023) : 24-31,79 . |
| APA | 林瑶 , 王琳 , 徐宗煌 , 王武林 . 机场出租车"待客-返程"决策支持模型——以南京禄口国际机场为例 . | 计算机应用与软件 , 2023 , 40 (8) , 24-31,79 . |
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Leaf water content (LWC) is very important in the growth of vegetation. LWC and leaf spectra change when the leaves are under pest stress; exploring the change mechanism between LWC, leaf spectra, and pest stress can lay the foundation for pest detection. In this study, we measured the LWC and leaf spectra of moso bamboo leaves under different damage levels, used the Pearson-Lasso method to screen the features, and established a multiple linear regression (MLR) and random forest regression (RFR) model to estimate the LWC. We analyzed the relationship between LWC and spectral features of moso bamboo leaves under Pantana phyllostachysae Chao (PPC) stress and their changes. The results showed that: (1) the LWC showed a decreasing trend as the pest level increased. (2) The spectra changed substantially when the leaves were under pest stress. (3) The number and significance of response features associated with the LWC were diverse under different damage levels. (4) The estimation of LWC under different damage levels differed significantly. LWC, leaf spectra, response features, and the model estimation effect were diverse under different damage levels. The correlation between LWC and features was higher for healthy leaves than for damaged and off-year leaves. The two models were more effective in estimating the LWC of healthy leaves but less effective for damaged and off-year leaves. This study provides theoretical support for the prediction of PPC stress and lays the foundation for remote sensing monitoring.
Keyword ：
changing relationships changing relationships moso bamboo moso bamboo Pantana phyllostachysae Chao Pantana phyllostachysae Chao Pearson-Lasso Pearson-Lasso spectral features spectral features water content water content
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| GB/T 7714 | Xu, Zhanghua , Li, Bin , Yu, Hui et al. Changing Relationships between Water Content and Spectral Features in Moso Bamboo Leaves under Pantana phyllostachysae Chao Stress [J]. | FORESTS , 2023 , 14 (4) . |
| MLA | Xu, Zhanghua et al. "Changing Relationships between Water Content and Spectral Features in Moso Bamboo Leaves under Pantana phyllostachysae Chao Stress" . | FORESTS 14 . 4 (2023) . |
| APA | Xu, Zhanghua , Li, Bin , Yu, Hui , Zhang, Huafeng , Guo, Xiaoyu , Li, Zenglu et al. Changing Relationships between Water Content and Spectral Features in Moso Bamboo Leaves under Pantana phyllostachysae Chao Stress . | FORESTS , 2023 , 14 (4) . |
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Chlorophyll is an important physiological parameter reflecting the health status of green vegetation. The change mechanism of chlorophyll and leaf spectrum under pest stress is complex. It is of great significance to analyze the relationship between chlorophyll and leaf spectrum in depth for pest detection. Taking Shunchang County, Nanping City, Fujian Province as the experimental area, the leaf SPAD and leaf spectrum of Phyllostachys pubescens under different damage scenarios were measured. Pearson correlation method was used to screen the leaf spectrum characteristic indexes, and multiple linear regression, ridge regression, random forest and XGBoost estimation models of leaf SPAD were established. By comparing the screening results of spectral characteristics and the estimation effect of the model, the relationship between chlorophyll and leaf spectral characteristics of Phyllostachys pubescens under the stress of Pantana phyllostachysae was analyzed. The results showed that: (1) SPAD of Phyllostachys pubescens leaves showed a downward trend with the increase of insect pests; (2) Compared with the undamaged state, the spectral characteristics of Phyllostachys pubescens leaves changed obviously under the stress of Pantana phyllostachysae, and the "green peak" and "red valley" tended to disappear, the slope of "red edge" decreased, and the reflectance of near infrared wavelength decreased. (3) The best spectral characteristics of leaf SPAD based on full sample fitting are VOG(2), R-515/R-570, CIred, PRI and NDVI705, and the best estimation model is multiple linear regression model (R-2=0.7537, RMSE=3.0150). (4) SPAD of Phyllostachys pubescens leaves was fitted based on samples with different damage degrees. The optimal spectral characteristic indexes were health: CIred, VOG(2), ARVI, R-515/R-570, DVI; mild hazard: RENDVI, RERVI and REDVI; moderate hazard: RENDVI, RERVI and REDVI; severe hazard: VOG(2), CIred, NDVI705; off year: PRI, NDVI705, VOG(1), CIred. The best estimation model is the multiple linear regression model, and the model accuracy is healthy (R-2 = 0.8823; RMSE=1.6388); mild hazard(R-2=0.1802; RMSE=3.3354); moderate hazard(R-2 = 0.3604; RMSE=3.8867); severe hazard (R-2=0.4677; RMSE=2.6018); off year (R-2=0.7324; RMSE=2.3754). It was found that with the increase of the damage grade, the spectral characteristic index of Phyllostachys pubescens leaves changed, and the estimation accuracy of the relational model showed a trend of sharp decline at first and then slowly rising. The model had better estimation effect on SPAD of healthy and young leaves, but poor estimation effect on SPAD of light-medium-severe damaged leaves. When the relationship between SPAD and spectral characteristics of Phyllostachys pubescens leaves tends to be disordered, it indicates that the harm of Pantana phyllostachysae may occur.
Keyword ：
Correlation analysis Correlation analysis Machine learning Machine learning Pest stress Pest stress SPAD SPAD Spectral characteristics of leaves Spectral characteristics of leaves
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| GB/T 7714 | Hu Xin-yu , Xu Zhang-hua , Huang Xu-ying et al. Relationship Between Chlorophyll and Leaf Spectral Characteristics and Their Changes Under the Stress of Phyllostachys Praecox [J]. | SPECTROSCOPY AND SPECTRAL ANALYSIS , 2022 , 42 (9) : 2726-2739 . |
| MLA | Hu Xin-yu et al. "Relationship Between Chlorophyll and Leaf Spectral Characteristics and Their Changes Under the Stress of Phyllostachys Praecox" . | SPECTROSCOPY AND SPECTRAL ANALYSIS 42 . 9 (2022) : 2726-2739 . |
| APA | Hu Xin-yu , Xu Zhang-hua , Huang Xu-ying , Zhang Yi-wei , Chen Qiu-xia , Wang Lin et al. Relationship Between Chlorophyll and Leaf Spectral Characteristics and Their Changes Under the Stress of Phyllostachys Praecox . | SPECTROSCOPY AND SPECTRAL ANALYSIS , 2022 , 42 (9) , 2726-2739 . |
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