复杂地形区植被覆盖度遥感精细估算方法——以青藏高原山地区为例  

A fine-scale remote sensing estimation method for fractional vegetation cover in complex terrain areas:a case study in the Qinghai-Tibet Plateau mountainous regions

作　　者：何邦科 朱文泉 史培军[3,4] 张慧 刘若杨 杨欣怡 赵涔良 HE Bangke;ZHU Wenquan;SHI Peijun;ZHANG Hui;LIU Ruoyang;YANG Xinyi;ZHAO Cenliang(State Key Laboratory of Remote Sensing Science,Beijing Normal University,Beijing 100875,China;Beijing Engineering Research Center for Global Land Remote Sensing Products,Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China;Academy of Disaster Reduction and Emergency Management,Ministry of Emergency Management&Ministry of Education,Beijing Normal University,Beijing 100875,China;Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China)

机构地区：[1]北京师范大学遥感科学国家重点实验室,北京100875 [2]北京师范大学地理科学学部北京市陆表遥感数据产品工程技术研究中心,北京100875 [3]北京师范大学应急管理部教育部减灾与应急管理研究院,北京100875 [4]北京师范大学地理科学学部,北京100875

出　　处：《生态学报》2024年第20期9039-9052,共14页Acta Ecologica Sinica

基　　金：第二次青藏高原综合科学考察研究项目(2019QZKK0606);国家自然科学基金重大项目(42192580,42192581)。

摘　　要：植被覆盖度(FVC)是刻画地表植被覆盖的重要参数,是生态监测的重要指标。遥感已成为区域尺度FVC估算的主要技术手段,但受限于地形所导致的太阳辐射变化及遥感像元内部较强的异质性和复杂性,复杂地形区的FVC遥感估算精度仍有很大提升空间。研究利用随机森林回归模型,发展了一种综合遥感地表反射率、地形特征和观测几何信息的复杂地形区FVC遥感精细估算方法(SRTVG)。选择青藏高原祁连山区、黄河源区和横断山区为测试区,利用Sentinel-2影像对新方法进行了应用,并利用基于无人机影像获取的FVC数据和现有FVC遥感产品对新方法进行了评估。加入地形特征与观测几何信息后,新方法估算FVC的R2为0.89,均方根误差(RMSE)为0.13;相较于未加入地形特征与观测几何信息,新方法估算FVC的RMSE降低了19.26%—28.02%;相较于已有的MultiVI FVC产品和GEOV3 FVC产品,新方法估算FVC的RMSE分别降低了40.91%和16.67%。新发展的SRTVG方法提高了复杂地形区的植被覆盖度遥感估算精度,丰富了植被覆盖度遥感估算的技术方法体系。Fractional Vegetation Cover(FVC)is an important parameter for the depiction of surface vegetation coverage and the monitoring of ecological conditions.Remote sensing has become the primary technique for regional FVC estimation.However,the accuracy of FVC estimation is greatly limited due to the variations in solar radiation caused by terrain and the strong heterogeneity and complexity within remote sensing pixels.This study utilized the random forest regression model to develop a fine-scale FVC estimation method for complex terrain areas by integrating surface reflectance,terrain features and view geometry(SRTVG).The Qilian Mountains region,Yellow River Source region,and Hengduan Mountains region on the Qinghai-Tibet Plateau were selected as the test areas.SRTVG was applied using Sentinel-2 imagery,and evaluated using FVC data obtained from UAV images and existing FVC remote sensing products.After incorporating terrain features and view geometry information,the new method achieved an R2 of 0.89 and a Root Mean Square Error(RMSE)of 0.13.Compared to methods not incorporating terrain features and view geometry information,the new method has reduced the RMSE of FVC estimation by 19.26%—28.02%.Compared to the existing MultiVI FVC and GEOV3 FVC products,the new method has reduced the RMSE by 40.91%and 16.67%,respectively.The newly developed SRTVG method can improve the accuracy of FVC remote sensing estimation in complex terrain areas,and enrich the technical methods for remote sensing estimation of FVC.

关 键 词：植被覆盖度 复杂地形区 地形效应 光学遥感 遥感估算 

分 类 号：Q948[生物学—植物学] TP751[自动化与计算机技术—检测技术与自动化装置]