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学者姓名：刘智才
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Abstract ：
Urbanization has disrupted the energy balance of natural surfaces, leading to the formation and intensification of urban heat island (UHI) phenomenon. Current research on the relationship between surface energy balance (SEB) and UHI mainly focuses on either a macro perspective of large-scale regions or a micro perspective based on numerical microclimate simulations. However, there are still relatively few studies conducted on the local scale of cities. Here, we investigated the relationships between seasonal SEB and land surface temperature (LST) based on local climate zones (LCZ) and explored the impact of three-dimensional (3D) urban morphology on SEB. Our results revealed that: (1) urban building spaces have relatively higher LST, sensible heat flux, and storage heat flux, but lower net radiation and latent heat flux, compared to urban blue and green spaces; (2) among LCZ built types, the compact and large low-rise buildings have high LST and heat-inducing energy fluxes, while the compact and open high-rise buildings exhibit the opposite situation; (3) the component proportions of SEB fluxes exhibit a more significant linear correlation with UHI intensity compared to the relative differences between SEB fluxes; and (4) 3D building morphology has a higher relative importance in influencing the variations of surface energy balance ratio (SEBR) components than 3D vegetation morphology. Specifically, building height has the greatest impact on the seasonal variations of SEBR components, while the 3D urban greening ratio has relatively high importance among vegetation morphology. These findings enable us to better consider local UHI effect from the perspective of SEB. © 2024 Elsevier Ltd
Keyword ：
Land surface temperature Land surface temperature Local climate zones Local climate zones Surface energy balance Surface energy balance Three-dimensional urban morphology Three-dimensional urban morphology Urban heat island Urban heat island XGBoost XGBoost
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| GB/T 7714 | Lin, Z. , Xu, H. , Hu, X. et al. Characterizing the seasonal relationships between urban heat island and surface energy balance fluxes considering the impact of three-dimensional urban morphology [J]. | Building and Environment , 2024 , 265 . |
| MLA | Lin, Z. et al. "Characterizing the seasonal relationships between urban heat island and surface energy balance fluxes considering the impact of three-dimensional urban morphology" . | Building and Environment 265 (2024) . |
| APA | Lin, Z. , Xu, H. , Hu, X. , Liu, Z. , Yao, X. , Zhu, Z. . Characterizing the seasonal relationships between urban heat island and surface energy balance fluxes considering the impact of three-dimensional urban morphology . | Building and Environment , 2024 , 265 . |
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琅岐岛是福建马尾新城建设的重点区域，其生态的可持续协调发展是实现琅岐岛“国际生态旅游岛”定位的关键。采用遥感生态指数（RSEI），评估了琅岐岛2004—2020年的生态质量变化。结果表明：（1）2004—2020年间，琅岐岛RSEI均值逐年降低，到2020年均值下降了9.28%，表明琅岐岛生态环境质量呈恶化趋势；（2）2004—2020年间，琅岐岛生态环境质量主要是由良等级向中等、较差、差等级转变，生态环境恶化的面积占37.04%，主要位于岛屿新开发区域；生态环境不变的面积占43.97%，主要为生态等级为优的山林地区；（3）至2020年，琅岐岛生态环境质量为良等级以上的区域占比为51%，结合回归分析模型发现绿度和干度是其生态质量影响的主要因素。
Keyword ：
城镇化 城镇化 琅岐岛 琅岐岛 生态环境质量 生态环境质量 遥感生态指数(RSEI) 遥感生态指数(RSEI)
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| GB/T 7714 | 王小飞 , 刘智才 . 城镇化引发的琅岐岛生态质量变化研究 [J]. | 能源与环境 , 2024 , PageCount-页数: 5 (04) : 149-153 . |
| MLA | 王小飞 et al. "城镇化引发的琅岐岛生态质量变化研究" . | 能源与环境 PageCount-页数: 5 . 04 (2024) : 149-153 . |
| APA | 王小飞 , 刘智才 . 城镇化引发的琅岐岛生态质量变化研究 . | 能源与环境 , 2024 , PageCount-页数: 5 (04) , 149-153 . |
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针对新时代背景下“双一流”高校人才培养的发展需求，在“三创五育”理念指导下，解析基于产学研合作理论引入的DIE模式的内涵，系统阐述了DIE理念贯彻下的教学系统设计并付诸实践，旨在打破教学系、研究所、企业之间的壁垒，为学生学习、实践提供更多样化的渠道。问卷调查结果表明DIE模式在本科生团队协作、学术创造、自信心树立等方面有切实作用，为培养全面发展的高素质本科人才提供了参考。
Keyword ：
DIE模式 DIE模式 “三创五育” “三创五育” “双一流”高校 “双一流”高校 本科人才培养 本科人才培养
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| GB/T 7714 | 许章华 , 张超飞 , 罗敏 et al. “三创五育”背景下“双一流”高校本科人才培养的DIE模式初探及评价 [J]. | 高等理科教育 , 2024 , 9 (02) : 53-61 . |
| MLA | 许章华 et al. "“三创五育”背景下“双一流”高校本科人才培养的DIE模式初探及评价" . | 高等理科教育 9 . 02 (2024) : 53-61 . |
| APA | 许章华 , 张超飞 , 罗敏 , 杨远垚 , 刘智才 . “三创五育”背景下“双一流”高校本科人才培养的DIE模式初探及评价 . | 高等理科教育 , 2024 , 9 (02) , 53-61 . |
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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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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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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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To control the negative effects resulting from the disorderly development of aquaculture ponds and promote the development of the aquaculture industry, rapid and accurate identification and extraction techniques are essential. An aquaculture pond is a special net-like water body divided by complex roads and dikes. Simple spectral features or spatial texture features are not sufficient to accurately extract it, and the mixed feature rule set is more demanding on computer performance. Supported by the GEE platform, and using the Landsat satellite data set and corresponding DEM combined with field survey data, we constructed a decision-making model for the extraction of aquaculture ponds in the coastal waters, and applied this method to the coastal waters of Southeast China. This method combined the image spectral information, spatial features, and morphological operations. The results showed that the total accuracy of this method was 93%, and the Kappa coefficient was 0.86. The overlapping proportions of results between the automated extraction and visual interpretation for test areas were all more than 90%, and the average was 92.5%, which reflected the high precision and reliability of this extraction method. Furthermore, in 2020, the total area of coastal aquaculture ponds in the study area was 6348.51 km(2), which was distributed primarily in the cities of Guangdong and Jiangsu. Kernel density analysis suggested that aquaculture ponds in Guangdong and Jiangsu had the highest degree of concentration, which means that they face higher regulatory pressure in the management of aquaculture ponds than other provinces. Therefore, this method can be used to extract aquaculture ponds in coastal waters of the world, and holds great significance to promote the orderly management and scientific development of fishery aquaculture.
Keyword ：
aquaculture pond area aquaculture pond area GEE platform GEE platform spatial convolution spatial convolution threshold segmentation threshold segmentation
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| GB/T 7714 | Wang, Lin , Li, Yefan , Zhang, Dongzhu et al. Extraction of Aquaculture Pond Region in Coastal Waters of Southeast China Based on Spectral Features and Spatial Convolution [J]. | WATER , 2022 , 14 (13) . |
| MLA | Wang, Lin et al. "Extraction of Aquaculture Pond Region in Coastal Waters of Southeast China Based on Spectral Features and Spatial Convolution" . | WATER 14 . 13 (2022) . |
| APA | Wang, Lin , Li, Yefan , Zhang, Dongzhu , Liu, Zhicai . Extraction of Aquaculture Pond Region in Coastal Waters of Southeast China Based on Spectral Features and Spatial Convolution . | WATER , 2022 , 14 (13) . |
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叶绿素是反映绿色植被健康状态的重要生理参数，虫害胁迫下叶绿素与叶光谱的变化机制较为复杂，深入剖析二者关系对于虫害检测有重要意义。以福建省南平市顺昌县为试验区，测定不同受害情景下毛竹叶叶绿素含量(SPAD)与叶光谱，采用Pearson相关法筛选叶光谱特征指标，建立叶SPAD的多元线性回归、岭回归、随机森林与XGBoost估测模型。通过比较光谱特征指标筛选结果及模型估测效果，分析刚竹毒蛾胁迫下毛竹叶绿素与叶光谱特征的关系及其变化。结果表明：(1)随着虫害程度上升，毛竹叶SPAD呈下降趋势；(2)较之于未受害状态，刚竹毒蛾胁迫下毛竹叶光谱特征发生明显变化，“绿峰”和“红谷”趋于消失，“红边”斜率减小...
Keyword ：
叶光谱特征 叶光谱特征 叶绿素含量 叶绿素含量 机器学习 机器学习 相关分析 相关分析 虫害胁迫 虫害胁迫
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| GB/T 7714 | 胡新宇 , 许章华 , 黄旭影 et al. 刚竹毒蛾胁迫下毛竹叶绿素与叶光谱特征的关系及其变化 [J]. | 光谱学与光谱分析 , 2022 , 42 (09) : 2726-2739 . |
| MLA | 胡新宇 et al. "刚竹毒蛾胁迫下毛竹叶绿素与叶光谱特征的关系及其变化" . | 光谱学与光谱分析 42 . 09 (2022) : 2726-2739 . |
| APA | 胡新宇 , 许章华 , 黄旭影 , 张艺伟 , 陈秋霞 , 王琳 et al. 刚竹毒蛾胁迫下毛竹叶绿素与叶光谱特征的关系及其变化 . | 光谱学与光谱分析 , 2022 , 42 (09) , 2726-2739 . |
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