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学者姓名：江洪
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Abstract ：
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 等. "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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以长汀县为研究区,采用当量因子法核算2010-2020年的生态系统服务价值,使用Pearson相关性分析方法和双变量自相关方法探讨生态系统间的权衡与协同关系,并借助自组织映射网络方法识别不同的生态系统服务簇.结果表明:2010-2020年长汀县生态系统服务价值在数量上呈现上升趋势,在空间上呈现"四周高、中心低"的环状分布特征;协同关系是长汀县生态系统服务的主导关系,主要分布在生态系统服务价值高的区域,权衡关系主要分布在生态系统服务价值低的区域;根据聚类结果和生态系统的主导服务功能将长汀县分为水源涵养簇、服务枯竭簇、生态调节簇和生产生态簇.研究结果可为长汀县生态系统服务可持续发展提供科学依据.
Keyword ：
权衡与协同 权衡与协同 生态系统服务价值 生态系统服务价值 生态系统服务簇 生态系统服务簇
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| GB/T 7714 | 林静 , 江洪 , 岳辉 et al. 长汀县生态系统服务权衡与协同关系 [J]. | 海南大学学报（自然科学版） , 2024 , 42 (3) : 301-311 . |
| MLA | 林静 et al. "长汀县生态系统服务权衡与协同关系" . | 海南大学学报（自然科学版） 42 . 3 (2024) : 301-311 . |
| APA | 林静 , 江洪 , 岳辉 , 林根根 , 金时来 , 唐丽芳 . 长汀县生态系统服务权衡与协同关系 . | 海南大学学报（自然科学版） , 2024 , 42 (3) , 301-311 . |
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竹林是南方山地丘陵区的重要森林资源,而该区域的地形阴影效应是影响竹林遥感提取精度的重要因素.为消除地形阴影影响,本研究使用新近提出的集成地形校正模型对福建省长汀县2010年和2022年的Landsat影像进行了地形校正,同时运用随机森林方法提取竹林数据,并采用变化幅度与变化率2个指标分析了 2010-2022年竹林的时空变化规律,揭示了竹林在高程和坡度上的地形分异效应.结果表明:集成地形校正有效恢复了本影和落影的光谱信息,使得校正后提取的竹林数据在总体分类精度、制图精度与用户精度上超过0.8.2010-2022年长汀县竹林面积变化幅度为34.79％,年均变化幅度为2.89％,呈现出明显的增长趋势,竹林分布具有明显的地形分异效应,主要分布于高程400～700 m,坡度8°～25°范围内.
Keyword ：
地形校正 地形校正 时空变化 时空变化 竹林 竹林 遥感提取 遥感提取
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| GB/T 7714 | 徐加其 , 江洪 , 林根根 et al. 基于集成地形校正的长汀县竹林提取与时空变化分析 [J]. | 海南大学学报（自然科学版） , 2024 , 42 (4) : 372-382 . |
| MLA | 徐加其 et al. "基于集成地形校正的长汀县竹林提取与时空变化分析" . | 海南大学学报（自然科学版） 42 . 4 (2024) : 372-382 . |
| APA | 徐加其 , 江洪 , 林根根 , 金时来 , 阮靖怡 , 于欣 . 基于集成地形校正的长汀县竹林提取与时空变化分析 . | 海南大学学报（自然科学版） , 2024 , 42 (4) , 372-382 . |
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Monitoring the extra-high-voltage transmission line corridor (EHVTLC) in mountains is critical for safe smart-grid operation. However, the transmission lines are so narrow that they are difficult to recognize using multispectral satellite images with a spatial resolution of 10 m. In this study, we developed a new method using the red band-shadow-eliminated vegetation index (SEVI)-blue band (RSB) composite image to enhance the EHVTLC in green mountains (named RSB-enhancement method). Using this method, the EHVTLC becomes evident in the false-color synthesis of the RSB composite of the Sentinel-2 image. Then, we recognized and extracted approximately 342.45 km of the EHVTLC in a mountainous region of Fuzhou City, China, including a 46.73 km three-parallel-lane segment of 1000 kV and a 295.72 km two-parallel-lane segment of 500 kV. Spatial analysis shows that the SEVI mean difference between the EHVTLC and the buffer zone reaches approximately 10%, and three landslides and 2.66 km(2) soil erosion reside in the buffer zone which area is approximately 73.67 km(2). Finally, the RSB-enhancement method can be used in other satellite images with spatial resolutions of greater than 10 m for enhancement and recognition the transmission line corridors in green mountains.
Keyword ：
Enhancement method Enhancement method green mountains green mountains shadow-eliminated vegetation index (SEVI) shadow-eliminated vegetation index (SEVI) soil erosion soil erosion transmission line lane (TLL) transmission line lane (TLL)
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| GB/T 7714 | Jiang, Hong , Zhang, Yong , Lin, Jinglan et al. Developing a new red band-SEVI-blue band (RSB) enhancement method for recognition the extra-high-voltage transmission line corridor in green mountains [J]. | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2023 , 16 (1) : 806-824 . |
| MLA | Jiang, Hong et al. "Developing a new red band-SEVI-blue band (RSB) enhancement method for recognition the extra-high-voltage transmission line corridor in green mountains" . | INTERNATIONAL JOURNAL OF DIGITAL EARTH 16 . 1 (2023) : 806-824 . |
| APA | Jiang, Hong , Zhang, Yong , Lin, Jinglan , Zheng, Xiaogan , Yue, Hui , Chen, Yunzhi . Developing a new red band-SEVI-blue band (RSB) enhancement method for recognition the extra-high-voltage transmission line corridor in green mountains . | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2023 , 16 (1) , 806-824 . |
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The mountainous vegetation is important to regional sustainable development. However, the topographic effect is the main obstacle to the monitoring of mountainous vegetation using remote sensing. Aiming to retrieve the reflectance of frequently-used red-green-blue and near-infrared (NIR) wavebands of rugged mountains for vegetation mapping, we developed a new integrated topographic correction (ITC) using the SCS + C correction and the shadow-eliminated vegetation index. The ITC procedure consists of image processing, data training, and shadow correction and uses a random forest machine learning algorithm. Our study using the Landsat 8 Operational Land Imager (OLI) multi-spectral images in Fujian province, China, showed that the ITC achieved high performance in topographic correction of regional mountains and in transferability from the sunny area of a scene to the shadow area of three scenes. The ITC-corrected multi-spectral image with an NIR-red-green composite exhibited flat features with impressions of relief and topographic shadow removed. The linear regression of corrected waveband reflectance vs. the cosine of the solar incidence angle showed an inclination that nearly reached the horizontal, and the coefficient of determination decreased to 0.00 similar to 0.01. The absolute relative errors of the cast shadow and the self-shadow all dramatically decreased to the range of 0.30-6.37%. In addition, the achieved detection rate of regional vegetation coverage for the three cities of Fuzhou, Putian, and Xiamen using the ITC-corrected images was 0.92-6.14% higher than that using the surface reflectance images and showed a positive relationship with the regional topographic factors, e.g., the elevation and slope. The ITC-corrected multi-spectral images are beneficial for monitoring regional mountainous vegetation. Future improvements can focus on the use of the ITC in higher-resolution imaging.
Keyword ：
cast shadow cast shadow integrated topographic correction integrated topographic correction mountainous vegetation mountainous vegetation random forest random forest regional vegetation coverage regional vegetation coverage transferability transferability
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| GB/T 7714 | Jiang, Hong , Chen, Ailin , Wu, Yongfeng et al. Vegetation Monitoring for Mountainous Regions Using a New Integrated Topographic Correction (ITC) of the SCS plus C Correction and the Shadow-Eliminated Vegetation Index [J]. | REMOTE SENSING , 2022 , 14 (13) . |
| MLA | Jiang, Hong et al. "Vegetation Monitoring for Mountainous Regions Using a New Integrated Topographic Correction (ITC) of the SCS plus C Correction and the Shadow-Eliminated Vegetation Index" . | REMOTE SENSING 14 . 13 (2022) . |
| APA | Jiang, Hong , Chen, Ailin , Wu, Yongfeng , Zhang, Chunying , Chi, Zhaohui , Li, Mengmeng et al. Vegetation Monitoring for Mountainous Regions Using a New Integrated Topographic Correction (ITC) of the SCS plus C Correction and the Shadow-Eliminated Vegetation Index . | REMOTE SENSING , 2022 , 14 (13) . |
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为了从Sentinel-2A影像中快速、准确提取竹林分布信息,以福建省永安市上坪乡竹林为研究区开展竹林提取研究.在影像分割的基础上,提取原始波段光谱、红边光谱指数、纹理3类共18个特征变量,利用随机森林Gini系数法进行特征变量重要性排序,设计5种不同特征变量组合方案,采用随机森林分类进行竹林分布信息提取.结果表明:原始波段光谱特征在Sentinel-2A影像竹林信息提取中具有重要作用,红边光谱指数特征次之,纹理特征未发挥显著作用.在红边光谱指数特征中,基于红边综合效应指数(MVIred1)构建的红边竹林指数3(BImvired1)具有良好的分类性能;利用随机森林Gini指标结合OOB泛化误差法有效减少了噪声数据的影响,筛选出最有利于竹林提取的特征变量子集,基于该特征子集的竹林分类总体精度(0A)达到94.58％、Kappa系数0.91、生产者精度(PA)为95.09％、用户精度(UA)85.54％.
Keyword ：
光谱指数 光谱指数 竹林 竹林 红边综合效应指数 红边综合效应指数 随机森林Gini指标 随机森林Gini指标
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| GB/T 7714 | 姚茂林 , 江洪 , 张丽玉 . 基于Sentinel-2影像红边光谱指数与特征优选的竹林提取研究 [J]. | 海南大学学报（自然科学版） , 2022 , 40 (4) : 373-381 . |
| MLA | 姚茂林 et al. "基于Sentinel-2影像红边光谱指数与特征优选的竹林提取研究" . | 海南大学学报（自然科学版） 40 . 4 (2022) : 373-381 . |
| APA | 姚茂林 , 江洪 , 张丽玉 . 基于Sentinel-2影像红边光谱指数与特征优选的竹林提取研究 . | 海南大学学报（自然科学版） , 2022 , 40 (4) , 373-381 . |
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In order to reveal the characteristics of spatial distribution and dynamic change of the forest in the Wuyishan Nature Reserve from 2000 to 2019, the recently proposed shadow-eliminated vegetation index (SEW) and the method of Sen+Mann-Kendall were used together in this study. The results show a trend of "decreasing first and then increasing" of vegetation cover change of the Reserve during the sub-periods of 2000-2011 and 2012-2019, but, as a whole, the vegetation cover of the Reserve was improved during 2000-2019, with 43.76% slight improvement and 55.18% significant improvement, approximately.
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| GB/T 7714 | Jiang, Hong , Wu, Yongfeng . Change trend analysis of the time-series shadow-eliminated vegetation index (SEVI) for the Wuyishan Nature Reserve with the Sen plus Mann-Kendall method [C] . 2021 . |
| MLA | Jiang, Hong et al. "Change trend analysis of the time-series shadow-eliminated vegetation index (SEVI) for the Wuyishan Nature Reserve with the Sen plus Mann-Kendall method" . (2021) . |
| APA | Jiang, Hong , Wu, Yongfeng . Change trend analysis of the time-series shadow-eliminated vegetation index (SEVI) for the Wuyishan Nature Reserve with the Sen plus Mann-Kendall method . (2021) . |
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本发明提出一种基于三类阴影的地形校正效果评估方法，该方法包括以下步骤：数据准备、影像分类、样本划分、本影提取、落影提取、灰影提取、结果输出。评估结果采用箱形图、玫瑰图、地表反射率与太阳入射角余弦值(cosi)散点图、三类阴影相对光照区误差柱状图等可视化方法。本发明的验证方法完善了地形校正效果定量评估中对山区地形阴影的分类和量化分析，定量评估结果可靠、直观，对科学认知山区地形影响和定量评估实际地形校正效果具有重要的科学意义与实用价值。
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| GB/T 7714 | 江洪 , 李健 , 陈爱琳 . 基于三类阴影的地形校正效果评估方法 : CN202111125474.5[P]. | 2021-09-24 . |
| MLA | 江洪 et al. "基于三类阴影的地形校正效果评估方法" : CN202111125474.5. | 2021-09-24 . |
| APA | 江洪 , 李健 , 陈爱琳 . 基于三类阴影的地形校正效果评估方法 : CN202111125474.5. | 2021-09-24 . |
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In order to study the vegetation growth changing in the Wuyishan Nature Reserve, the recently proposed shadow-eliminated vegetation index (SEVI) and patch density (PD) were used to evaluate the inter-annual variability of the vegetation growth in the Reserve during 2000-2019. The resultant normalized SEVI sequence eliminated the terrain shadow effect shows an increasing trend overall during 2000-2019. Meanwhile, the series of PD show a decreasing trend with two significant different mean levels of 40.67/km2 during 2000-2011 and 18.69/km2 during 2012-2019. The SEVI and PD had an overall negative correlation with coefficient of determination r2 = 0.53. The result suggests that the promotion of ecology civilization may contribute to the protection and growth of the nature reserve vegetation. © 2020 Institute of Physics Publishing. All rights reserved.
Keyword ：
Geology Geology Time series analysis Time series analysis Vegetation Vegetation
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| GB/T 7714 | Jiang, Hong , Zhou, Nian . Time series analysis of the shadow-eliminated vegetation index (SEVI) and patch density index for the Wuyishan Nature Reserve [C] . 2020 . |
| MLA | Jiang, Hong et al. "Time series analysis of the shadow-eliminated vegetation index (SEVI) and patch density index for the Wuyishan Nature Reserve" . (2020) . |
| APA | Jiang, Hong , Zhou, Nian . Time series analysis of the shadow-eliminated vegetation index (SEVI) and patch density index for the Wuyishan Nature Reserve . (2020) . |
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植物吸收性光合有效辐射分量(FPAR)的遥感反演是生态环境领域的核心研究内容之一,但在复杂地形山区,其估算精度严重受到地形效应的影响(包括本影与落影).本文利用能够消除地形阴影影响的阴影消除植被指数(SEVI)对山区遥感影像进行FPAR反演,并分别与基于不同影像预处理程度计算的归一化植被指数(NDVI)、比值型植被指数(RVI)反演的FPAR做对比分析,以评估复杂山区反演FPAR存在的地形效应.结果 表明:在不做地形校正的情况下,基于NDVI与RVI反演FPAR会使得本影及落影区域的值远小于非阴影区域的值,它们的相对误差均大于70％;基于C校正后的NDVI与RVI反演FPAR可以较好地校正本影区域,相对误差降至约6.974％,但落影处的校正效果不明显,相对误差约为48.133％;而基于SEVI反演FPAR无需DEM数据的支持,可以达到经FLAASH+C组合校正后NDVI与RVI反演FPAR相似的结果,且能改善落影区域的地形校正效果,相对误差降至约2.730％.
Keyword ：
FPAR FPAR SEVI SEVI 地形校正 地形校正 复杂地形山区 复杂地形山区 本影 本影 植被指数 植被指数 落影 落影
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| GB/T 7714 | 蒋世豪 , 江洪 , 陈慧 . 基于SEVI的复杂地形山区植被FPAR遥感反演与地形效应评估 [J]. | 地球信息科学学报 , 2020 , 22 (8) : 1725-1734 . |
| MLA | 蒋世豪 et al. "基于SEVI的复杂地形山区植被FPAR遥感反演与地形效应评估" . | 地球信息科学学报 22 . 8 (2020) : 1725-1734 . |
| APA | 蒋世豪 , 江洪 , 陈慧 . 基于SEVI的复杂地形山区植被FPAR遥感反演与地形效应评估 . | 地球信息科学学报 , 2020 , 22 (8) , 1725-1734 . |
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