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Stand delineation based on laser scanning data and simulated annealing
European Journal of Forest Research ( IF 2.8 ) Pub Date : 2021-05-08 , DOI: 10.1007/s10342-021-01384-x
Yusen Sun , Weifang Wang , Timo Pukkala , Xingji Jin

The use of airborne laser scanning (LS) is increasing in forestry. Scanning can be conducted from manned aircrafts or unmanned aerial vehicles (UAV). The scanning data are often used to calculate various attributes for small raster cells. These attributes can be used to segment the forest into homogeneous areas, called segments, micro-stands, or, like in this study, stands. Delineation of stands from raster data is equal to finding the most suitable stand number for each raster cell, which is a combinatorial optimization problem. This study tested the performance of the simulated annealing (SA) metaheuristic in the delineation of stands from grids of UAV-LS attributes. The objective function included three criteria: within-stand variation of the LS attributes, stand area, and stand shape. The purpose was to create delineations that consisted of homogeneous stands with a low number of small stands and a regular and roundish stand shape. The results showed that SA is capable of producing stand delineations that meet these criteria. However, the method tended to produce delineations where the stands often consisted of disconnected parts and the stand borders were jagged. These problems were mitigated by using a mode filter on the grid of stand numbers and giving unique numbers for all disconnected parts of a stand. Three LS attributes were used in the delineation. These attributes described the canopy height, the height of the bottom of the canopy and the variation of echo intensity within 1-m2 raster cells. Besides, a texture variable that described the spatial variation of canopy height in the proximity of a 1-m2 raster cell was found to be a useful variable. Stand delineations where the average stand area was about one hectare explained more than 80% of the variation in canopy height.



中文翻译:

基于激光扫描数据和模拟退火的机架描述

在林业中,机载激光扫描(LS)的使用正在增加。可以从有人驾驶飞机或无人机(UAV)进行扫描。扫描数据通常用于计算小型栅格像元的各种属性。这些属性可用于将森林划分为同质区域,称为片段,微型林分,或像本研究中一样,林分。从栅格数据中划定林分等于等于为每个栅格像元找到最合适的林分编号,这是一个组合优化问题。这项研究测试了模拟退火(SA)元启发式算法在从UAV-LS属性网格描绘林分的过程中的性能。目标函数包括三个标准:LS属性的机架内变化,机架面积和机架形状。目的是创建由均匀的机架组成的轮廓,这些机架具有少量的小机架和规则且呈圆形的机架形状。结果表明,SA能够产生符合这些标准的林分。但是,该方法往往会产生轮廓,其中机架通常由不连贯的零件组成,并且机架边界呈锯齿状。通过在展位号网格上使用模式过滤器并为展位的所有未连接部分提供唯一的编号,可以缓解这些问题。轮廓中使用了三个LS属性。这些属性描述了冠层高度,冠层底部的高度以及1-m以内的回波强度的变化 结果表明,SA能够产生符合这些标准的林分。但是,该方法往往会产生轮廓,其中机架通常由不连贯的零件组成,并且机架边界呈锯齿状。通过在展位号网格上使用模式过滤器并为展位的所有未连接部分提供唯一的编号,可以缓解这些问题。轮廓中使用了三个LS属性。这些属性描述了冠层高度,冠层底部的高度以及1-m以内的回波强度的变化 结果表明,SA能够产生符合这些标准的林分。但是,该方法往往会产生轮廓,其中机架通常由不连贯的零件组成,并且机架边界呈锯齿状。通过在展位号网格上使用模式过滤器并为展位的所有未连接部分提供唯一的编号,可以缓解这些问题。轮廓中使用了三个LS属性。这些属性描述了冠层高度,冠层底部的高度以及1-m以内的回波强度的变化 通过在展位号网格上使用模式过滤器并为展位的所有未连接部分提供唯一的编号,可以缓解这些问题。轮廓中使用了三个LS属性。这些属性描述了冠层高度,冠层底部的高度以及1-m以内的回波强度的变化 通过在展位号网格上使用模式过滤器并为展位的所有未连接部分提供唯一的编号,可以缓解这些问题。轮廓中使用了三个LS属性。这些属性描述了冠层高度,冠层底部的高度以及1-m以内的回波强度的变化2个栅格像元。此外,发现描述1 m 2栅格像元附近冠层高度的空间变化的纹理变量是有用的变量。平均林分面积约为一公顷的林分轮廓解释了冠层高度变化的80%以上。

更新日期:2021-05-08
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