Consistent forest leaf area index retrieval using ground and airborne data

Abstract : Leaf Area Index (LAI), defined as one half of the total leaf area per unit ground surface area, is a key parameter of vegetation structure for modeling Earth's ecological cycle and its acquisition accuracy always has the need and opportunity for improvement. Active laser scanning provides an opportunity for consistent LAI retrieval at multiple scales because terrestrial laser scanning (TLS) and airborne laser scanning (ALS) have the similar physical mechanism. However, the three-dimensional information of laser scanning is not fully explored in current methods and the traditional theories require adaptation. In this thesis, the path length distribution model is proposed to model the clumping effect, and it is applied to the TLS and ALS data. The method of obtaining the path length distribution of different platforms is studied, and the consistent retrieval model is established. This method is found to improve the individual tree measurement in urban areas and LAI mapping in natural forest, and its results at consistent at different scales. The model is expected to facilitate the consistent retrieval of the forest leaf area index using ground and airborne data.
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Ronghai Hu. Consistent forest leaf area index retrieval using ground and airborne data. Earth Sciences. Université de Strasbourg, 2018. English. ⟨NNT : 2018STRAD021⟩. ⟨tel-02159558⟩

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