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学者姓名：陈芸芝
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为建立适合省级尺度的海洋藻类养殖区高精度智能提取方法,推进海洋藻类养殖面积的准确测算和变化监测,本文基于国产高分辨率遥感影像,对海洋藻类养殖区遥感智能提取方法进行研究.对比U-Net模型、DeepLab V3+模型、MSUResUnet模型在典型海洋藻类养殖区提取的结果,MSUResUnet模型提取的准确率(accuracy)、召回率(recall)、平均交并比(mIoU)、F1分数(F1-score)较U-Net模型提高 0.14%、0.84%、0.34%、0.32%,较DeepLab V3+模型提高 0.18%、0.88%、0.40%、0.36%,因此,选择MSUResUnet模型进行福建全省海洋藻类养殖区自动化提取.经提取结果统计,2022年 7月至2023年5月,福建全省海洋藻类养殖面积约为345.6912 km2.
Keyword ：
三沙湾 三沙湾 海洋藻类养殖 海洋藻类养殖 深度学习 深度学习 高分辨率遥感影像 高分辨率遥感影像
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| GB/T 7714 | 陈红梅 , 吴婷 , 林万强 et al. 福建全省海洋藻类养殖区高精度智能提取方法研究 [J]. | 海洋环境科学 , 2025 , 44 (1) : 116-125 . |
| MLA | 陈红梅 et al. "福建全省海洋藻类养殖区高精度智能提取方法研究" . | 海洋环境科学 44 . 1 (2025) : 116-125 . |
| APA | 陈红梅 , 吴婷 , 林万强 , 陈芸芝 , 罗冬莲 . 福建全省海洋藻类养殖区高精度智能提取方法研究 . | 海洋环境科学 , 2025 , 44 (1) , 116-125 . |
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针对各类森林扰动响应阈值差异大导致单一特征检测效果不佳的问题,选取2000-2023年闽江流域Landsat时序数据,采用LandTrendr算法提取多个波段/光谱指数的扰动时间、扰动持续时间、扰动幅度、扰动发生光谱值、扰动发生光谱变化率和扰动信噪比6个时间序列扰动参数,并辅以地形变量构建最优特征集,结合随机森林模型监测森林扰动.结果表明,通过GFC数据和谷歌地球高分辨率影像标定的验证样本集验证,LandTrendr+RF模型的总体精度为96.91％,Kappa系数为0.938,监测效果优于单一指数的LandTrendr算法.2000-2023年,闽江流域森林扰动总面积为2 989.065 km2.扰动主要集中在流域北部、中部、东南部地区,且易发生于坡度25°以下和海拔600 m以下的区域.该研究可为闽江流域森林资源保护及管理政策制定提供依据.
Keyword ：
Landsat时间序列 Landsat时间序列 LandTrendr LandTrendr 森林扰动 森林扰动 闽江流域 闽江流域 随机森林 随机森林
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| GB/T 7714 | 王钰岢 , 陈芸芝 , 江洪 . 综合LandTrendr算法与随机森林的闽江流域森林扰动监测 [J]. | 测绘科学 , 2025 , 50 (3) : 112-122 . |
| MLA | 王钰岢 et al. "综合LandTrendr算法与随机森林的闽江流域森林扰动监测" . | 测绘科学 50 . 3 (2025) : 112-122 . |
| APA | 王钰岢 , 陈芸芝 , 江洪 . 综合LandTrendr算法与随机森林的闽江流域森林扰动监测 . | 测绘科学 , 2025 , 50 (3) , 112-122 . |
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Accurately delineating sediment export dynamics using high-quality vegetation factors remains challenging due to the spatio-temporal resolution imbalance of single remote sensing data and persistent cloud contamination. To address these challenges, this study proposed a new framework for estimating and analyzing monthly sediment inflow to rivers in the cloud-prone Minjiang River Basin. We leveraged multi-source remote sensing data and the Continuous Change Detection and Classification model to reconstruct monthly vegetation factors at 30 m resolution. Then, we integrated the Chinese Soil Loss Equation model and the Sediment Delivery Ratio module to estimate monthly sediment inflow to rivers. Lastly, the Optimal Parameters-based Geographical Detector model was harnessed to identify factors affecting sediment export. The results indicated that: (1) The simulated sediment transport modulus showed a strong Coefficient of Determination (R2 = 0.73) and a satisfactory Nash-Sutcliffe Efficiency coefficient (0.53) compared to observed values. (2) The annual sediment inflow to rivers exhibited a spatial distribution characterized by lower levels in the west and higher in the east. The monthly average sediment value from 2016 to 2021 was notably high from March to July, while relatively low from October to January. (3) Erosive rainfall was a decisive factor contributing to increased sediment entering the rivers. Vegetation factors, manifested via the quantity (Fractional Vegetation Cover) and quality (Leaf Area Index and Net Primary Productivity) of vegetation, exert a pivotal influence on diminishing sediment export.
Keyword ：
Chinese soil loss equation Chinese soil loss equation cloud-prone regions cloud-prone regions monthly remote sensing vegetation index monthly remote sensing vegetation index optimal parameters-based geographical detector optimal parameters-based geographical detector sediment delivery ratio sediment delivery ratio sediment inflow to rivers sediment inflow to rivers
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| GB/T 7714 | Wang, Xiaoqin , Yu, Zhichao , Li, Lin et al. Unveiling the Intra-Annual and Inter-Annual Spatio-Temporal Dynamics of Sediment Inflow to Rivers and Driving Factors in Cloud-Prone Regions: A Case Study in Minjiang River Basin, China [J]. | WATER , 2024 , 16 (22) . |
| MLA | Wang, Xiaoqin et al. "Unveiling the Intra-Annual and Inter-Annual Spatio-Temporal Dynamics of Sediment Inflow to Rivers and Driving Factors in Cloud-Prone Regions: A Case Study in Minjiang River Basin, China" . | WATER 16 . 22 (2024) . |
| APA | Wang, Xiaoqin , Yu, Zhichao , Li, Lin , Li, Mengmeng , Lin, Jinglan , Tang, Lifang et al. Unveiling the Intra-Annual and Inter-Annual Spatio-Temporal Dynamics of Sediment Inflow to Rivers and Driving Factors in Cloud-Prone Regions: A Case Study in Minjiang River Basin, China . | WATER , 2024 , 16 (22) . |
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High consequence areas within oilfields are critical zones for the safety management of petroleum transport pipelines. Accurately and efficiently capturing the spatial distribution of key features in high-consequence areas of oilfields is essential for the smooth operation of petroleum safety production and the scientific management of oilfield regions. However, there are still challenges in extraction tasks of the high-consequence areas of oilfields, such as diverse ground object shapes, small spectral differences, and complex types, and the extraction results often include misclassification, omissions, and road discontinuities. To address these challenges, we propose an SML_ResUnet model for land cover extraction in high-consequence areas of oil fields based on ResUnet architecture. This model integrates Strip Pooling (SP) units in the pooling stages and incorporates Mixed Pooling Modules (MPM) and Label Attention Modules (LAM) between the encoding and decoding processes. The SP units are designed to capture elongated and isolated features, excluding information from other irrelevant areas, while the MPM combines the advantages of standard pooling and strip pooling, effectively preserving feature information across different spatial positions. The label attention module introduces label information to optimize the attention probability maps generated within the attention module, further enhancing the extraction results. We applied the proposed model on a high-resolution dataset of a high-consequence area of an oilfield. The results of the ablation experiments indicated that the proposed SML_ResUnet network achieved the optimal extraction results. The metrics of Overall Accuracy (OA), Mean Intersection over Union (MIoU), and F1-score reached 97.24%, 84.23%, and 91.26%, respectively. Compared to the classical ResUnet model, improvements are observed in all evaluation metrics of the proposed model, with OA, MIoU, and F1-score increasing by 0.48%, 2.49%, and 1.55%, respectively. For a land cover extraction task within a high consequence area of an oilfield in Shandong Province, the OA of the extraction results averaged at 97.66%. We then extended the model in other high- consequence areas of oilfields in Shandong Province and achieved an Overall Accuracy (OA) of 95.63%. Our results meet the accuracy requirements for rapid acquisition of surface information in large- scale high- consequence areas of oilfields and demonstrate that the SML_ResUnet model is particularly suitable for large-scale land cover extraction tasks within oilfields characterized by diverse and complex terrain types. © 2024 Science Press. All rights reserved.
Keyword ：
Deep learning Deep learning Extraction Extraction Gasoline Gasoline Oil fields Oil fields Petroleum transportation Petroleum transportation Pipelines Pipelines
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| GB/T 7714 | Gao, Chen , Chen, Yunzhi , Dong, Yan et al. Integration of Mixed Pooling and Label Information Optimization for Oilfield Land Cover Extraction Model [J]. | Journal of Geo-Information Science , 2024 , 26 (3) : 753-763 . |
| MLA | Gao, Chen et al. "Integration of Mixed Pooling and Label Information Optimization for Oilfield Land Cover Extraction Model" . | Journal of Geo-Information Science 26 . 3 (2024) : 753-763 . |
| APA | Gao, Chen , Chen, Yunzhi , Dong, Yan , Liu, Lei , Guo, Jun . Integration of Mixed Pooling and Label Information Optimization for Oilfield Land Cover Extraction Model . | Journal of Geo-Information Science , 2024 , 26 (3) , 753-763 . |
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The construction of China's ecological civilization, known as 'Beautiful China', necessitates implementing precision watershed management through scientifically informed decision-making. This entails optimizing the spatial distribution of watershed best management practices (the so- called BMP scenario) and proposing multistage implementation plans, or roadmaps that align with practical requirements based on the overarching vision of comprehensive water shed management.The'water shed system simulation-scenariooptimization' method frame work (the simulation-and-optimization-based frame work for short) has demonstrated considerable potential in recent years. To address challenges arising from practical applications of this framework, this study systematically conducted the methodological research: (1) proposing a novel watershed process modeling framework that strikes a balance between modeling flexibility and high-performance computing to model and simulate watershed systems efficiently; (2) introducing slope position units as BMP configuration units and enabling dynamic boundary adjustments during scenario optimization, effectively incorporating practical knowledge of watershed management to ensure reasonable outcomes; (3) presenting an optimization method for determining the implementation orders of BMPs that considers stepwise investment constraints, thereby recommending feasible roadmaps that meet practical needs; and (4) designing a user-friendly participatory watershed planning system to facilitate collaborative decision-making among stakeholders. The effectiveness and practical value of these new methods, tools, and prototype systems are validated through application cases in a representative small watershed. This research contributes to advancing precision watershed management and provides valuable insights for sustainable ecological conservation. The methods proposed within the simulation-and-optimization-based framework in this study are universal methods, which means their application does not depend on the specific implementation, such as the watershed process model, the BMP types considered, the designed BMP configuration strategy, and so on. Further studies should be conducted not only to deepen related theory and method research but also to strengthen promotion and application, especially cooperating with local watershed management agents to provide valuable insights for their sustainable ecological conservation. © 2024 Science Press. All rights reserved.
Keyword ：
Computation theory Computation theory Decision making Decision making Decision support systems Decision support systems Ecology Ecology Investments Investments Soil conservation Soil conservation Water conservation Water conservation Water management Water management Watersheds Watersheds
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| GB/T 7714 | Qin, Chengzhi , Zhu, Liangjun , Shen, Shen et al. Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization [J]. | Acta Geographica Sinica , 2024 , 79 (1) : 58-75 . |
| MLA | Qin, Chengzhi et al. "Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization" . | Acta Geographica Sinica 79 . 1 (2024) : 58-75 . |
| APA | Qin, Chengzhi , Zhu, Liangjun , Shen, Shen , Wu, Tong , Xiao, Guirong , Wu, Sheng et al. Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization . | Acta Geographica Sinica , 2024 , 79 (1) , 58-75 . |
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Evaluation ecosystem service value (ESV) is critical, as "lucid waters and lush mountains are invaluable assets". To assess the incremental effects of ecological assets on soil and water conservation in subtropical mountains, we developed a remote-sensing-driven mountainous equivalent factor (RS-MEF) method to estimate the ESV of Changting County, China. This method is a hybrid of a conventional equivalent factor framework and remote sensing techniques for mountains, achieving several advancements, including spatial adjustment using vegetation activity merged with productivity, improved spatial resolution, and the removal of topographic effects. Using the RS-MEF method, we estimated that the ESV of Changting County was approximately CNY 15.80 billion in 2010 and CNY 34.83 billion in 2022. Specifically, the ESV per unit area of the major soil erosion area (MSEA) in the county was less than that of the non-major soil erosion area (n-MSEA); however, the ESV growth rate of the MSEA from 2010 to 2022 was faster than that of the n-MSEA. Therefore, the ESV gap between the two areas was reduced from 28.99% in 2010 to 15.83% in 2022. Topographic gradient analysis illustrates that areas with elevations of 385 to 658 m and steep slopes achieved a high ESV, while high-elevation areas with gentle slopes will be a focus of control in the next phase. Our study demonstrates that significant achievements have been made in ecological restoration from an ESV perspective, with a notable reduction in low-ESV areas in the MSEA; the insights gained into ESV growth and its underlying factors are valuable and instructive for future soil and water conservation efforts.
Keyword ：
ecosystem service value ecosystem service value soil erosion soil erosion spatial adjustment coefficient spatial adjustment coefficient spatial-temporal pattern spatial-temporal pattern subtropical mountain subtropical mountain
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| GB/T 7714 | Jiang, Hong , Lin, Jing , Liu, Bibao et al. Discovering the Ecosystem Service Value Growth Characteristics of a Subtropical Soil Erosion Area Using a Remote-Sensing-Driven Mountainous Equivalent Factor Method [J]. | REMOTE SENSING , 2024 , 16 (19) . |
| MLA | Jiang, Hong et al. "Discovering the Ecosystem Service Value Growth Characteristics of a Subtropical Soil Erosion Area Using a Remote-Sensing-Driven Mountainous Equivalent Factor Method" . | REMOTE SENSING 16 . 19 (2024) . |
| APA | Jiang, Hong , Lin, Jing , Liu, Bibao , Yue, Hui , Lin, Jinglan , Shui, Wei et al. Discovering the Ecosystem Service Value Growth Characteristics of a Subtropical Soil Erosion Area Using a Remote-Sensing-Driven Mountainous Equivalent Factor Method . | REMOTE SENSING , 2024 , 16 (19) . |
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针对现有方法对于养殖池塘和干扰地物的区分效果不足,在多源高分辨率遥感影像上的普适性有待验证等问题,提出一种融合全局上下文信息的PG-Unet养殖池塘提取模型.该模型在U-Net的基础上,通过增加金字塔特征提取单元来捕捉丰富的全局上下文信息,增加全局引导流来改善不同级别特征图的质量,提升模型在多干扰地物环境定位目标的能力.在GF-2 PMS和BJ-2 PMS数据集上的实验结果表明,PG-Unet模型精度最优,其 IoU 和 F1 分数分别达到 92.30％、96.00％和 92.07％、95.87％,优于 U-Net、DensenetUnet 和 U2Net等方法,具有更强的抗干扰能力和普适性,能更好地区分养殖池塘和干扰地物;同时,PG-Unet模型在诏安湾养殖区域应用也取得了较高的提取精度,能够实现大范围养殖池塘空间分布信息自动精准提取.
Keyword ：
U-Net模型 U-Net模型 全局引导流 全局引导流 养殖池塘 养殖池塘 金字塔特征提取单元 金字塔特征提取单元
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| GB/T 7714 | 彭俊 , 陈红梅 , 罗冬莲 et al. 融合全局上下文的近岸养殖池塘提取算法 [J]. | 福州大学学报（自然科学版） , 2024 , 52 (5) : 520-527 . |
| MLA | 彭俊 et al. "融合全局上下文的近岸养殖池塘提取算法" . | 福州大学学报（自然科学版） 52 . 5 (2024) : 520-527 . |
| APA | 彭俊 , 陈红梅 , 罗冬莲 , 陈芸芝 . 融合全局上下文的近岸养殖池塘提取算法 . | 福州大学学报（自然科学版） , 2024 , 52 (5) , 520-527 . |
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Chlorophyll-a (Chla) and total suspended solid (TSS) concentrations are important parameters for water quality assessment, and in recent years, machine learning has been shown to have great potential in this field. However, current water quality parameter inversion models lack interpretability and rarely consider the morphological characteristics of the spectrum. To address this limitation, we used Sentinel-3 OLCI data to construct an interpretable CatBoost model guided by spectral morphological characteristics for remote sensing monitoring of Chla and TSS along the coast of Fujian. The results show that the coastal waters of Fujian Province can be divided into five clusters, and the areas of different clusters will change with the alternation of seasons. Clusters 2 and 4 are the main types of coastal waters. The CatBoost model combined with spectral feature engineering has a high accuracy in predicting Chla and TSS, among which Chla is slightly better than TSS (R2 = 0.88, MSE = 8.21, MAPE = 1.10 for Chla predictions; R2 = 0.77, MSE = 380.49, MAPE = 2.48 for TSS predictions). We further conducted an interpretability analysis on the model output and found that the combination of BRI and TBI indexes composed of bands such as b8, b9, and b10 and the fluctuation of spectral curves will have a significant impact on the prediction of model output. The interpretable CatBoost model based on spectral morphological features proposed in this study can provide an effective technical means of estimating the chlorophyll-a and total suspended particulate matter concentrations in the coastal areas of Fujian.
Keyword ：
CatBoost CatBoost chlorophyll-a concentration chlorophyll-a concentration OLCI OLCI spectral clustering spectral clustering total suspended matter total suspended matter
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| GB/T 7714 | Chen, Baofeng , Chen, Yunzhi , Chen, Hongmei . An Interpretable CatBoost Model Guided by Spectral Morphological Features for the Inversion of Coastal Water Quality Parameters [J]. | WATER , 2024 , 16 (24) . |
| MLA | Chen, Baofeng et al. "An Interpretable CatBoost Model Guided by Spectral Morphological Features for the Inversion of Coastal Water Quality Parameters" . | WATER 16 . 24 (2024) . |
| APA | Chen, Baofeng , Chen, Yunzhi , Chen, Hongmei . An Interpretable CatBoost Model Guided by Spectral Morphological Features for the Inversion of Coastal Water Quality Parameters . | WATER , 2024 , 16 (24) . |
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为制定适合河道型水库的网箱养殖信息提取方法,实现水库网箱养殖自动化精准提取,该文基于"U"型编解码结构,顾及多尺度特征信息,通过引入残差单元(RU)、高效多尺度注意力(EMA)、改进级联多尺度卷积(MCP)以及嵌入多尺度特征(IAC)等模块改进深度学习网络构建EAMRNet模型,以闽江流域水口库区为研究区,开展水库网箱养殖信息提取研究.结果表明,EAMRNet模型提取的交并比(IoU)、召回率(Recall)、精准率(Precision)、F1分数(F1-score)分别为 80.26％、90.94％、87.23％、89.05％,相比于 UNet、ResUNet、DeepLab V3+、TransUNet、HRNet 等 5 种经典模型精度评价结果,精度均为最高.同时,将EAMRNet模型应用于提取闽江流域水口库区2019年-2023年网箱养殖信息,经提取结果统计,闽江流域水口库区网箱养殖面积从2019年的333.965 2 hm2减少至2023年的156.771 3 hm2,总体呈现先增后减的趋势.综上,改进后的模型在水库网箱养殖提取任务上具备较高的提取精度,该研究可以为当地养殖管理部门进行养殖动态监测及合理规划养殖提供理论依据和数据支撑.
Keyword ：
国产高分辨率遥感影像 国产高分辨率遥感影像 多尺度特征 多尺度特征 水库网箱养殖 水库网箱养殖 河道型水库 河道型水库 深度学习 深度学习
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| GB/T 7714 | 林万强 , 陈芸芝 . 融合多尺度特征的河道型水库网箱养殖信息提取研究 [J]. | 测绘科学 , 2024 , 49 (10) : 133-145 . |
| MLA | 林万强 et al. "融合多尺度特征的河道型水库网箱养殖信息提取研究" . | 测绘科学 49 . 10 (2024) : 133-145 . |
| APA | 林万强 , 陈芸芝 . 融合多尺度特征的河道型水库网箱养殖信息提取研究 . | 测绘科学 , 2024 , 49 (10) , 133-145 . |
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Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With the technological development of satellite-based LiDAR, it is possible to determine forest canopy height over a large area. However, the forest canopy height that is acquired by this technology is influenced by topography and climate, and the canopy height that is acquired in complex subtropical mountainous regions has large errors. In this paper, we propose a method for estimating forest canopy height by combining long-time series Landsat images with GEDI satellite-based LiDAR data, with Fujian, China, as the study area. This approach optimizes the quality of GEDI canopy height data in topographically complex areas by combining stand age and tree height, while retaining the advantage of fast and effective forest canopy height measurements with satellite-based LiDAR. In this study, the growth curves of the main forest types in Fujian were first obtained by using a large amount of forest survey data, and the LandTrendr algorithm was used to obtain the forest age distribution in 2020. The obtained forest age was then combined with the growth curves of each forest type in order to determine the tree height distribution. Finally, the obtained average tree heights were merged with the GEDI_V27 canopy height product in order to create a modified forest canopy height model (MGEDI_V27) with a 30 m spatial resolution. The results showed that the estimated forest canopy height had a mean of 15.04 m, with a standard deviation of 4.98 m. In addition, we evaluated the accuracy of the GEDI_V27 and the MGEDI_V27 using the sample dataset. The MGEDI_V27 had a higher accuracy (R-2 = 0.67, RMSE = 2.24 m, MAE = 1.85 m) than the GEDI_V27 (R-2 = 0.39, RMSE = 3.35 m, MAE = 2.41 m). R-2, RMSE, and MAE were improved by 71.79%, 33.13%, and 22.53%, respectively. We also produced a forest age distribution map of Fujian for the year 2020 and a forest disturbance map of Fujian for the past 32 years. The research results can provide decision support for forest ecological protection and management and for carbon sink analysis in Fujian.
Keyword ：
canopy height canopy height forest age forest age Fujian Fujian GEDI GEDI LiDAR LiDAR time-series remote sensing time-series remote sensing
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| GB/T 7714 | Zhou, Xiaocheng , Hao, Youzhuang , Di, Liping et al. Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China [J]. | REMOTE SENSING , 2023 , 15 (2) . |
| MLA | Zhou, Xiaocheng et al. "Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China" . | REMOTE SENSING 15 . 2 (2023) . |
| APA | Zhou, Xiaocheng , Hao, Youzhuang , Di, Liping , Wang, Xiaoqin , Chen, Chongcheng , Chen, Yunzhi et al. Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China . | REMOTE SENSING , 2023 , 15 (2) . |
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