Tree Crown Length Research Articles

Дифференциация климатипов лиственниц (Larix spp.) в географических культурах в лесостепи Средней Сибири

Дифференциация климатипов лиственниц (Larix spp.) в географических культурах в лесостепи Средней Сибири

Tree crown length prediction models for Larix olgensis and Fraxinus mandshurica in mixed plantations with different mixing methods

Tree crown length prediction models for Larix olgensis and Fraxinus mandshurica in mixed plantations with different mixing methods

Measuring Canopy Structure and Condition Using Multi-Spectral UAS Imagery in a Horticultural Environment

Tree condition, pruning and orchard management practices within intensive horticultural tree crop systems can be determined via measurements of tree structure. Multi-spectral imagery acquired from an unmanned aerial system (UAS) has been demonstrated as an accurate and efficient platform for measuring various tree structural attributes, but research in complex horticultural environments has been limited. This research established a methodology for accurately estimating tree crown height, extent, plant projective cover (PPC) and condition of avocado tree crops, from a UAS platform. Individual tree crowns were delineated using object-based image analysis. In comparison to field measured canopy heights, an image-derived canopy height model provided a coefficient of determination (R2) of 0.65 and relative root mean squared error of 6%. Tree crown length perpendicular to the hedgerow was accurately mapped. PPC was measured using spectral and textural image information and produced an R2 value of 0.62 against field data. A random forest classifier was applied to assign tree condition into four categories in accordance with industry standards, producing out-of-bag accuracies >96%. Our results demonstrate the potential of UAS-based mapping for the provision of information to support the horticulture industry and facilitate orchard-based assessment and management.

An enhanced forest classification scheme for modeling vegetation–climate interactions based on national forest inventory data

Abstract. Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface–atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

Biosocial diversity of tree crown length and crown ratio of oak in a 56-years-old stand

Biosocial diversity of tree crown length and crown ratio of oak in a 56-years-old stand

A method to estimate the structural parameters of windbreaks using remote sensing

Windbreaks are a major component of agroforestry practices and play an important role in agroforestry ecosystems. They can reduce wind velocity and protect shelter crops from wind damage and soil from wind erosion. Porosity is one of the most important structural parameters that affect wind speed and is widely used in the study of wind protection provided by windbreaks. In this paper, a method to estimate porosity using high-resolution satellite imagery is represented. Porosity was difficult to estimate through the direct use of remote sensing data due to the poor relationship with vegetation indices. Thus, two intermediate variables, that is, CL 2 × LAI and CL × LAI × W, which were highly related to porosity, were selected. Leaf area index (LAI) and average tree crown length (CL) were estimated using vegetation indices, and W, which refers to the width of a windbreak, was identified using object-based image analysis. Porosity was estimated using a statistical relationship between porosity and intermediate variables. The average prediction accuracy of the estimated porosity value was 76.104 %. Based on the estimated porosity value, the windbreaks were grouped into three types, and their efficiency of wind protection was evaluated. The evaluation result indicated that the windbreaks have a very good protective structure in the study area and they can effectively shelter crops from wind damage and erosion. This study can provide a useful guide for studying the wind protection provided by windbreaks on spatial and temporal scales using remote sensing.

Spatial partitioning of biomass and diversity in a lowland Bolivian forest: Linking field and remote sensing measurements

Large-scale inventories of forest biomass and structure are necessary for both understanding carbon dynamics and conserving biodiversity. High-resolution satellite imagery is starting to enable structural analysis of tropical forests over large areas, but we lack an understanding of how tropical forest biomass links to remote sensing. We quantified the spatial distribution of biomass and tree species diversity over 4 ha in a Bolivian lowland moist tropical forest, and then linked our field measurements to high-resolution Quickbird satellite imagery. Our field measurements showed that emergent and canopy dominant trees, being those directly visible from nadir remote sensors, comprised the highest diversity of tree species, represented 86% of all tree species found in our study plots, and contained the majority of forest biomass. Emergent trees obscured 1–15 trees with trunk diameters (at 1.3 m, diameter at breast height (DBH)) ≥20 cm, thus hiding 30–50% of forest biomass from nadir viewing. Allometric equations were developed to link remotely visible crown features to stand parameters, showing that the maximum tree crown length explains 50–70% of the individual tree biomass. We then developed correction equations to derive aboveground forest biomass, basal area, and tree density from tree crowns visible to nadir satellites. We applied an automated tree crown delineation procedure to a high-resolution panchromatic Quickbird image of our study area, which showed promise for identification of forest biomass at community scales, but which also highlighted the difficulties of remotely sensing forest structure at the individual tree level.

Two-dimensional needle-area density distribution within the crowns of Pinus radiata

The vertical and horizontal distribution of needle-area density ( nad) within the crowns of Pinus radiata trees is described with a two-dimensional beta function. The maximum nad for the entire needle population within the tree crowns was located approximately one-third of tree-crown length from the crown base in the vertical and half-way along the crown radious at that height in the horizontal. The relative heights of maximum nad of needles in different age classes decrease with needle age in the vertical, whilst the relative radial distances of maximum nad of needles in different age classes are close to the centre of the tree crown in the horizontal. It was found that the maximum nad within the tree crown can be up to four times larger than the average nad. The spatial nad distribution was poorly related to trunk diameter at breast height, tree height, and the total area of needles within the crown. The spatial nad distributions of leaves in different age classes were altered by irrigation and fertilization: the relative proportion of current needles increased, and the location of maximum nad of current needles shifted towards the crown base in the vertical and the crown centre in the horizontal. The spatial nad distribution of the entire needle population was unaffected by irrigation and fertilization.