PLANNING HARVESTING OPERATIONS IN FOREST ENVIRONMENT: REMOTE SENSING FOR DECISION SUPPORT

Author:

Piragnolo M.,Grigolato S.,Pirotti F.ORCID

Abstract

Abstract. The goal of this work is to assess a method for supporting decisions regarding identification of most suitable areas for two types of harvesting approaches in forestry: skyline vs. forwarder. The innovative aspect consists in simulating the choices done during the planning in forestry operations. To do so, remote sensing data from an aerial laser scanner were used to create a digital terrain model (DTM) of ground surface under vegetation cover. Features extracted from the DTM are used as input for several machine learning predictors. Features are slope, distance from nearest roadside, relative height from nearest roadside and roughness index. Training and validation is done using areas defined by experts in the study area. Results show a K value of almost 0.92 for the classifier with best results, random forest. Sensibility of each feature is assessed, showing that both distance and height difference from nearest road-side are more significant than overall DTM value.

Publisher

Copernicus GmbH

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ormancılıkta makine öğrenmesi kullanımı;Turkish Journal of Forestry | Türkiye Ormancılık Dergisi;2023-05-17

2. Europe’s Potential Wood Supply by Harvesting System;Forests;2023-02-16

3. Road network planning in native forest management using GIS;NATIVA;2023

4. Road Network Planning in Tropical Forests Using GIS;Croatian journal of forest engineering;2022-11-04

5. Smart Harvest Operations and Timber Processing for Improved Forest Management;Climate-Smart Forestry in Mountain Regions;2021-11-25

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