研究目的
To provide a new method to acquire savanna clumping index at moderate resolution pixel scale considering herbaceous layer effects in growing seasons.
研究成果
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.
研究不足
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.
1:Experimental Design and Method Selection:
The study used a combination of hemispherical photographs and high-resolution remote sensing images (Geoeye-1 and WorldView-2) to estimate the clumping index (CI) for savanna canopies. The methodology involved deriving CI from gap size distributions using Hemiview software and integrating with image segmentation techniques to extract tree parameters.
2:Sample Selection and Data Sources:
Two study regions in Ejina Banner, Inner Mongolia, and Weichang County, Hebei, China, were selected. Data included 166 hemispherical photographs (107 from Ejina Banner and 59 from Weichang) taken during peak growing seasons, and high-resolution satellite images from Geoeye-1 and WorldView-
3:List of Experimental Equipment and Materials:
Canon EOS 50D camera with a fish-eye lens, Hemiview system (Delta-T Devices Ltd.), tripod, ENVI 4.8 software for image processing, Hemiview 2.1 software for photograph analysis, and CAN_EYE software for grassland gap fraction measurement.
4:8 software for image processing, Hemiview 1 software for photograph analysis, and CAN_EYE software for grassland gap fraction measurement.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Hemispherical photographs were taken with specific camera settings, processed to binary images for gap fraction calculation. High-resolution images were orthorectified, atmospherically corrected, and segmented to extract tree crowns. CI was calculated using derived parameters and equations based on average transmittance theory.
5:Data Analysis Methods:
Statistical analysis of CI values, comparison with existing MODIS-based CI products, and numerical simulation to assess sensitivity of parameters like LAI, canopy density, and background effects.
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