Improving local forest growth prediction by terrain-derived attributes, airborne γ-ray, and leaf area index
نویسندگان
چکیده
منابع مشابه
Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry
a r t i c l e i n f o Keywords: Airborne lidar Leaf area index Urban ecosystem analysis Hemispherical photography Allometry Vegetation structure In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa B...
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The boreal zone land cover has a very significant influence on the northern hemisphere albedo and is an important component of the northern hemisphere carbon budget [1, 2] and is sensitive to changes in local and global climate [3]. Forest transition zones react to changes in mean temperature and moisture conditions in the long term [4] whereas changes in, for example, forest leaf area index (L...
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A new simple airborne method based on wide optics camera is developed for leaf area index (LAI) estimation in coniferous forests. The measurements are carried out in winter, when the forest floor is completely snow covered and thus acts as a light background for the hemispherical analysis of the images. The photos are taken automatically and stored on a laptop during the flights. The R value of...
متن کاملQuantifying the Effects of Normalisation of Airborne LiDAR Intensity on Coniferous Forest Leaf Area Index Estimations
The range between a sensor and the target, the incidence angle, and the target reflectance, are known factors that can influence the intensity values of LiDAR data and consequently, its use in many applications. However, very few studies have provided a quantitative analysis of the effects of normalisation of these three factors on forest leaf area index (LAI) estimations. In this paper, using ...
متن کاملEstimating Leaf Area Index in Mixed Forest Using an Airborne Laser Scanner
Leaf area index (LAI) is one of the most important parameter of forest structure. The study site was an isolated forest in Kyoto City in Japan and it vegetation type was mixed forest. We took fisheye photos at 102 points in the study area, and calculated the LAI and Canopy-open. We classified the laser data into 4 classes, that is, First pulse, Last pulse, Only pulse and Ground pulse. We counte...
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ژورنال
عنوان ژورنال: Dissertationes Forestales
سال: 2019
ISSN: 1795-7389
DOI: 10.14214/df.268