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学者姓名：王琳
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Abstract ：
As a geological disaster widely distributed in the southern regions of China, rainfall-induced shallow landslides pose a significant threat to affected areas. Timely detection of landslides is crucial in the effective response to such disasters. However, landslide detection faces adverse impacts from various factors, such as insufficient sample data, complex model structures, and limitations in detection accuracy during the actual detection process. In this study, high-quality image samples were collected from multiple landslide disaster areas in southern China, and a rainfall-induced shallow landslide sample database was constructed in the region. Based on this, a lightweight attention-guided YOLO model (LA-YOLO) was proposed to improve the detection performance of YOLO model for rainfall-induced shallow landslides. First, CG block is introduced to enhance the C2f module, enriching the feature representation capability through multiscale feature fusion and reducing the model's parameters and computational complexity. Second, the SimAM attention module is used to focus on the target regions, improving feature extraction effectiveness. Experimental results show that the model parameters of LA-YOLO were reduced by approximately 30%, with precision, recall, and mean average precision (mAP) on the landslide sample dataset increasing by 2.6%, 0.7%, and 2.2%, respectively. While ensuring model detection performance, the model structure was significantly optimized, achieving both lightweight and accuracy goals, confirming the model's superiority in monitoring rainfall-induced shallow landslide disasters.
Keyword ：
Accuracy Accuracy Attention mechanism Attention mechanism Biological system modeling Biological system modeling context guidance module context guidance module Data models Data models Disasters Disasters Feature extraction Feature extraction landslide detection landslide detection Neurons Neurons Rain Rain rainfall-induced shallow landslide rainfall-induced shallow landslide Terrain factors Terrain factors Training Training YOLO YOLO YOLO v8 YOLO v8
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| GB/T 7714 | Wang, Lin , Lei, Henggang , Jian, Wenbin et al. Enhancing Landslide Detection: A Novel LA-YOLO Model for Rainfall-Induced Shallow Landslides [J]. | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS , 2025 , 22 . |
| MLA | Wang, Lin et al. "Enhancing Landslide Detection: A Novel LA-YOLO Model for Rainfall-Induced Shallow Landslides" . | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 22 (2025) . |
| APA | Wang, Lin , Lei, Henggang , Jian, Wenbin , Wang, Wenjia , Wang, Hao , Wei, Nan . Enhancing Landslide Detection: A Novel LA-YOLO Model for Rainfall-Induced Shallow Landslides . | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS , 2025 , 22 . |
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The nighttime economy is instrumental in driving economic growth, particularly in the post-pandemic era. Nighttime Light (NTL) data is a key source in nighttime economy remote sensing study, with its angular effect directly affecting result accuracy. This study compares the accuracy of identifying nighttime economic agglomerations (NEAs) in Shanghai using Black Marble NTL and POI data at three observation angles: near-nadir, off-nadir, and all-angle. The results indicate that under all three angles, landmark NEAs can be identified fairly well. However, near-nadir demonstrates superior sample library identification accuracy and Theil index performance compared to all-angle and off-nadir. The study reveals that near-nadir observations offer higher accuracy and better suppression of "pseudo-accuracy units", making them more suitable for studying the nighttime economy. Furthermore, the study analyzes the spatial distribution characteristics of NEAs in Shanghai and finds a distinct "center-periphery" development pattern, suggesting imbalances in overall development. The presence of buildings with scattered high-low distribution and complex urban structures contributes to the variations in NEA identification under different satellite-observed angles. This study provides valuable insights into selecting the appropriate satellite-observed angle for studying NEAs using NTL data. It also explores the potential application of Black Marble NTL data products in socioeconomic remote sensing.
Keyword ：
Angular effects Angular effects Black marble nighttime lights product suite Black marble nighttime lights product suite Nighttime economy agglomeration (NEA) Nighttime economy agglomeration (NEA) Shanghai city Shanghai city Socioeconomic remote sensing Socioeconomic remote sensing
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| GB/T 7714 | Ou, Caihong , Tang, Fei , Deng, Xiaohui et al. The Impact of Angular Effects on Nighttime Economy Observations: Determining the Optimal Observation Angle of Nighttime Light Remote Sensing [J]. | APPLIED SPATIAL ANALYSIS AND POLICY , 2025 , 18 (1) . |
| MLA | Ou, Caihong et al. "The Impact of Angular Effects on Nighttime Economy Observations: Determining the Optimal Observation Angle of Nighttime Light Remote Sensing" . | APPLIED SPATIAL ANALYSIS AND POLICY 18 . 1 (2025) . |
| APA | Ou, Caihong , Tang, Fei , Deng, Xiaohui , Wang, Lin . The Impact of Angular Effects on Nighttime Economy Observations: Determining the Optimal Observation Angle of Nighttime Light Remote Sensing . | APPLIED SPATIAL ANALYSIS AND POLICY , 2025 , 18 (1) . |
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Human activity is an important factor affecting regional thermal environment change, and it is of great significance to explore the response relationship between human activity intensity (HAI) and land surface temperature (LST) for regional sustainable development. Based on MOD11A1 ground temperature data and combined with multi-source data such as land use (LU),population density (PD),night light (NTL),grassland use intensity (GUI) and existing biomass (EB),this paper proposed a method suitable for measuring the HAI in Three-River Source Region,and analyzed the spatio-temporal variation characteristics of HAI and LST in Three-River Source Region from 2000 to 2020. Comprehensive use of spatial autocorrelation and spatial autoregressive model to explore the spatial relationship between them. The results show that: (1) According to the regional ecological characteristics of Three-River Source Region, the HAI index model constructed in this paper can effectively identify the spatial distribution of HAI in Three-River Source Region,and can better distinguish the spatial differences of HAI in Three-River Source Region;(2) The average value of HAI in Three-River Source Region in the past 20 years was 0.285,and the overall intensity was low.The spatial distribution characteristics of HAI and LST were both high in the east and low in the west,and the two were significantly positively correlated.(3) LU,PD,GUI and EB in HAI index significantly affect the change of LST in Three-River Source Region,while there is a phenomenon of ' warming lag' between NTL and LST,and its response to LST is not obvious.In general,in order to slow down the further rise of LST in this region and alleviate the challenges faced by the regional ecological security system,it is necessary to limit the spread of high human activity areas. © 2025 Editorial Board of Journal of Basic Science and Engineering. All rights reserved.
Keyword ：
Population statistics Population statistics
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| GB/T 7714 | Liu, Zhicai , Zheng, Weiwen , Long, Zihan et al. Modeling of Human Activity Intensity Index and Its Spatial Relationship with Land Surface Temperature in Three-River Source Region [J]. | Journal of Basic Science and Engineering , 2025 , 33 (2) : 349-361 . |
| MLA | Liu, Zhicai et al. "Modeling of Human Activity Intensity Index and Its Spatial Relationship with Land Surface Temperature in Three-River Source Region" . | Journal of Basic Science and Engineering 33 . 2 (2025) : 349-361 . |
| APA | Liu, Zhicai , Zheng, Weiwen , Long, Zihan , Wang, Lin , Xu, Zhanghua . Modeling of Human Activity Intensity Index and Its Spatial Relationship with Land Surface Temperature in Three-River Source Region . | Journal of Basic Science and Engineering , 2025 , 33 (2) , 349-361 . |
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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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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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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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为控制水产养殖塘无序发展带来的负面效应,促进水产养殖业进一步发展,首要解决的就是对其快速、准确识别和提取的问题.水产养殖塘是被复杂道路和堤坝分割的特殊网状水体,单纯的光谱特征或空间纹理特征都不足以对其准确提取,且混合特征规则集对计算机性能要求越发苛刻.鉴于此,以Landsat影像序列为数据源,基于谷歌地球引擎(Google Earth Engine,GEE)平台,提出了一种结合影像光谱信息、空间特征和形态学操作的沿海水产养殖塘自动提取方法.该方法联用了双特征水体光谱指数(改进型组合水体指数(modified combined index for water identification,MCIWI)与改进的归一化差异水体指数(modified normalized difference water index,MNDWI))以突出大面积水体与养殖塘的网格特征,再利用低频滤波空间卷积运算拉伸养殖与非养殖水体之间的差异特征,将水产养殖塘区作为一个整体准确识别和快速提取.研究结果表明:①该方法总精度达到93％,Kappa系数为0.86,典型区域叠加比对检验流程验证,提取结果和实际结果重叠比例均在90％以上,平均重叠比例达92.5％,反映了提取方法的高精度和可靠性;②2020年福建省近岸海域水产养殖塘区总面积为511.73 km2,主要分布在漳州市、福州市和宁德市;③核密度分析结果表明漳州市的水产养殖塘集聚度高,相应其养殖塘管理压力也较大.该方法可以实现近岸海域水产养殖塘的自动化提取,对促进渔业养殖的有序管理和科学发展具有重要的意义.
Keyword ：
GEE平台 GEE平台 水产养殖塘区 水产养殖塘区 空间卷积 空间卷积 阈值分割 阈值分割
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| GB/T 7714 | 李叶繁 , 王琳 , 张冬珠 . 光谱特征和空间卷积相协同的近岸海域养殖塘遥感信息提取 [J]. | 自然资源遥感 , 2022 , 34 (4) : 42-52 . |
| MLA | 李叶繁 et al. "光谱特征和空间卷积相协同的近岸海域养殖塘遥感信息提取" . | 自然资源遥感 34 . 4 (2022) : 42-52 . |
| APA | 李叶繁 , 王琳 , 张冬珠 . 光谱特征和空间卷积相协同的近岸海域养殖塘遥感信息提取 . | 自然资源遥感 , 2022 , 34 (4) , 42-52 . |
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以往研究生态脆弱性多集中于宏观区域角度,而针对工程建设项目等微观尺度的生态脆弱性影响研究则较为少见.为了探究道路建设对路域生态环境的影响,以Landsat 8 OLI/TIRS遥感影像和DEM为数据源,以莆炎高速YA12段公路两侧1000 m路域为研究区,将定量化和空间化的理念引入南方红壤丘陵区公路建设项目尺度下的生态脆弱性研究,利用"缓冲区阶梯"探寻了公路建设活动对路域生态脆弱性影响的空间分异规律.结果表明:路域生态脆弱性程度与缓冲距离成反比,随着与公路距离的接近而逐渐增大,路域30 m缓冲范围内是受公路建设影响最强的区域,根据该缓冲范围内平均生态脆弱性指数相较于背景值的上升程度(仅升高0.293),可推断该标段的公路建设行为所引起的地表扰动对路域生态脆弱性的影响较为有限;公路两侧300 m缓冲区范围认定为路域生态环境重点保护区域,而针对路基、桥梁为主的建设形式则需要外延至360 m缓冲范围;隧道出入口建设对生态脆弱性的影响远大于隧道内部,因此隧道出入口也是公路建设期间及竣工之后的生态监控、生态重建的重点区域.研究可为高速公路等各类公路工程建设对生态环境影响的监测与评价提供帮助和参考.
Keyword ：
环境工程 环境工程 生态脆弱性指数 生态脆弱性指数 空间分异 空间分异 缓冲区阶梯 缓冲区阶梯 遥感 遥感
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| GB/T 7714 | 李春强 , 王琳 , 刘智才 et al. 南方红壤丘陵区公路路域生态脆弱性空间分异规律 [J]. | 公路交通科技 , 2022 , 39 (12) : 224-230 . |
| MLA | 李春强 et al. "南方红壤丘陵区公路路域生态脆弱性空间分异规律" . | 公路交通科技 39 . 12 (2022) : 224-230 . |
| APA | 李春强 , 王琳 , 刘智才 , 刘辉 , 张冬珠 . 南方红壤丘陵区公路路域生态脆弱性空间分异规律 . | 公路交通科技 , 2022 , 39 (12) , 224-230 . |
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"夜间经济"蕴含巨大的消费潜能和市场空间,夜间经济集聚区作为其载体,其准确识别、合理分类和科学布局是发展夜间经济的切入点和主要抓手,更是夜间经济可持续发展的保障.本文在"点轴发育、定量识别"的认知框架下,在定量表达夜间经济活力测度的基础上,利用焦点统计和ISO聚类分析方法提取和识别夜间经济集聚中心和集聚区,并根据区位熵及其变异系数对识别结果进行类型划分,克服了目前夜间经济实践中存在的集聚区范围划定主观随意、类型标准不一的问题,为夜间经济定量化研究开辟了新的思路.研究表明:①相较于DMPS/OLS及NPP-VIIRS等夜光遥感数据,Luojial-01数据的空间分辨率高,溢出效应低,更适合于"夜间经济区"这种小尺度的精细化研究.②夜间灯光和兴趣点数据是夜间社会活力和功能活力的良好表征,其综合影响可通过夜间经济活力测度来定量表达;③上海推出的12个地标性夜生活集聚区中,有11个被识别,识别率达91.7％;④根据集聚区的功能结构差异,可将其划分为非平衡发展-起步型、平衡发展-起步型、非平衡发展-成熟型、平衡发展-成熟型4种类型,该分类方式具有普适性;⑤在起步阶段,上海中心城区夜间经济集聚区主导功能为购物、餐饮;在成熟阶段,其特色发展方向为住宿、科教文化和体育休闲功能.四大集聚区类型在空间分布上形成明显的圈层结构.
Keyword ：
ISO)聚类分析 ISO)聚类分析 Luojia-01夜间灯光数据 Luojia-01夜间灯光数据 POI) POI) 兴趣点(Point of Interest 兴趣点(Point of Interest 夜间经济集聚区 夜间经济集聚区 "点-轴系统"理论 "点-轴系统"理论 迭代自组织(Iterative self-organization 迭代自组织(Iterative self-organization
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| GB/T 7714 | 王琳 , 钟泓文 , 许章华 et al. Luojia-01夜光数据和"点轴发育"理论支持下的夜间经济集聚区定量识别与分类方法 [J]. | 地球信息科学学报 , 2022 , 24 (11) : 2141-2152 . |
| MLA | 王琳 et al. "Luojia-01夜光数据和"点轴发育"理论支持下的夜间经济集聚区定量识别与分类方法" . | 地球信息科学学报 24 . 11 (2022) : 2141-2152 . |
| APA | 王琳 , 钟泓文 , 许章华 , 王武林 . Luojia-01夜光数据和"点轴发育"理论支持下的夜间经济集聚区定量识别与分类方法 . | 地球信息科学学报 , 2022 , 24 (11) , 2141-2152 . |
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为实现碳中和目标,国家亟需培养大量碳中和相关的实践型人才.地理学专业的自然地理学、植物地理学、土壤地理学、环境科学概论和基础生态学等课程均包含碳循环相关实践环节,但分散在各课程中,且内容高度重叠.因此,依托滨海湿地控制实验系统,将分散在上述课程中的碳循环相关实践环节进行整合优化,形成以碳中和为核心,碳吸收、碳排放、碳储存、碳分解为模块的"一心多点"实践教学模式.改革后,实践课由60学时优化至24学时,实践课程目标明确、内容相互联系,教学效率明显提高.该实践教学改革可有效提高学生碳中和相关的知识水平和实践动手能力,并可积极引导学生参与实验设计,申报创新实践项目,撰写学术论文和申请专利,对提高学生碳中和思想认识具有促进作用.
Keyword ：
地理学 地理学 实践教学 实践教学 控制实验系统 控制实验系统 滨海湿地 滨海湿地 碳中和 碳中和
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| GB/T 7714 | 罗敏 , 黄佳芳 , 许章华 et al. 碳中和背景下基于滨海湿地控制实验系统的地理学实践教学改革 [J]. | 实验室研究与探索 , 2022 , 41 (10) : 173-178 . |
| MLA | 罗敏 et al. "碳中和背景下基于滨海湿地控制实验系统的地理学实践教学改革" . | 实验室研究与探索 41 . 10 (2022) : 173-178 . |
| APA | 罗敏 , 黄佳芳 , 许章华 , 王琳 , 仝川 . 碳中和背景下基于滨海湿地控制实验系统的地理学实践教学改革 . | 实验室研究与探索 , 2022 , 41 (10) , 173-178 . |
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