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Estimating Savanna Clumping Index Using Hemispherical Photographs Integrated with High Resolution Remote Sensing Images

DOI:10.3390/rs9010052 期刊:Remote Sensing 出版年份:2017 更新时间:2025-09-23 15:22:29
摘要: In contrast to herbaceous canopies and forests, savannas are grassland ecosystems with sparsely distributed individual trees, so the canopy is spatially heterogeneous and open, whereas the woody cover in savannas, e.g., tree cover, adversely affects ecosystem structures and functions. Studies have shown that the dynamics of canopy structure are related to available water, climate, and human activities in the form of porosity, leaf area index (LAI), and clumping index (CI). Therefore, it is important to identify the biophysical parameters of savanna ecosystems, and undertake practical actions for savanna conservation and management. The canopy openness presents a challenge for evaluating canopy LAI and other biophysical parameters, as most remotely sensed methods were developed for homogeneous and closed canopies. Clumping index is a key variable that can represent the clumping effect from spatial distribution patterns of components within a canopy. However, it is a difficult task to measure the clumping index of the moderate resolution savanna pixels directly using optical instruments, such as the Tracing Radiation and Architecture of Canopies, LAI-2000 Canopy Analyzer, or digital hemispherical photography. This paper proposed a new method using hemispherical photographs combined with high resolution remote sensing images to estimate the clumping index of savanna canopies. The effects of single tree LAI, crown density, and herbaceous layer on the clumping index of savanna pixels were also evaluated. The proposed method effectively calculated the clumping index of moderate resolution pixels. The clumping indices of two study regions located in Ejina Banner and Weichang were compared with the clumping index product over China's landmass.
作者: Jucai Li,Wenjie Fan,Yuan Liu,Gaolong Zhu,Jingjing Peng,Xiru Xu
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To provide a new method to acquire savanna clumping index at moderate resolution pixel scale considering herbaceous layer effects in growing seasons.

The proposed method effectively estimates the clumping index for savanna pixels by combining hemispherical photographs and high-resolution remote sensing images. It accounts for background effects (bare soil vs. grassland) and shows consistency with existing products when appropriate backgrounds are considered. Future work should address manual processing limitations and incorporate additional factors for improved accuracy.

The method requires manual isolation of single trees from hemispherical photos, which may affect accuracy due to photo clarity and isolation issues. It does not fully account for factors like tree height and canopy shape, and is limited to specific seasons (growing seasons) for grassland backgrounds.

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