Piotr Janiec , Luiza Tymińska-Czabańska , Paweł Hawryło , Michał Woda , Jarosław Socha
{"title":"使用基于ALS数据的半自动方法确定波兰森林的垂直结构","authors":"Piotr Janiec , Luiza Tymińska-Czabańska , Paweł Hawryło , Michał Woda , Jarosław Socha","doi":"10.1016/j.ecolind.2025.113825","DOIUrl":null,"url":null,"abstract":"<div><div>The vertical structure of the forest is one of the key characteristics of forest management, influencing biodiversity, resource competition, and various ecological processes. Despite its importance, determining the vertical structure of stands over large areas is still a challenge. This study presents the first country-wide assessment of the vertical forest structure in Poland using airborne laser scanning (ALS) data. The research introduces a semi-automatic method for classifying forest stands into vertical structure classes without the need for extensive fieldwork. The main strength and innovation of our approach is demonstrating that a model can be built and validated almost without field-acquired data. By processing point-cloud metrics derived from ALS data and employing machine learning techniques, particularly the random forest algorithm, the method generated a high-resolution vertical structure map across the country. The five-class model developed had a overall accuracy of 0.78. The results show that Polish forests are predominantly characterized by a single-story vertical structure, influenced by the dominance of Scots pine, with more complex structures in mountainous and biodiversity-rich areas. The methodology significantly reduces costs and time associated with traditional forest surveys, offering a scalable tool for forest monitoring, biodiversity assessment, and sustainable management, particularly under changing environmental conditions and habitat loss.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"178 ","pages":"Article 113825"},"PeriodicalIF":7.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determining vertical structure of forests in Poland using a semi-automated approach based on ALS data\",\"authors\":\"Piotr Janiec , Luiza Tymińska-Czabańska , Paweł Hawryło , Michał Woda , Jarosław Socha\",\"doi\":\"10.1016/j.ecolind.2025.113825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The vertical structure of the forest is one of the key characteristics of forest management, influencing biodiversity, resource competition, and various ecological processes. Despite its importance, determining the vertical structure of stands over large areas is still a challenge. This study presents the first country-wide assessment of the vertical forest structure in Poland using airborne laser scanning (ALS) data. The research introduces a semi-automatic method for classifying forest stands into vertical structure classes without the need for extensive fieldwork. The main strength and innovation of our approach is demonstrating that a model can be built and validated almost without field-acquired data. By processing point-cloud metrics derived from ALS data and employing machine learning techniques, particularly the random forest algorithm, the method generated a high-resolution vertical structure map across the country. The five-class model developed had a overall accuracy of 0.78. The results show that Polish forests are predominantly characterized by a single-story vertical structure, influenced by the dominance of Scots pine, with more complex structures in mountainous and biodiversity-rich areas. The methodology significantly reduces costs and time associated with traditional forest surveys, offering a scalable tool for forest monitoring, biodiversity assessment, and sustainable management, particularly under changing environmental conditions and habitat loss.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"178 \",\"pages\":\"Article 113825\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X25007551\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25007551","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Determining vertical structure of forests in Poland using a semi-automated approach based on ALS data
The vertical structure of the forest is one of the key characteristics of forest management, influencing biodiversity, resource competition, and various ecological processes. Despite its importance, determining the vertical structure of stands over large areas is still a challenge. This study presents the first country-wide assessment of the vertical forest structure in Poland using airborne laser scanning (ALS) data. The research introduces a semi-automatic method for classifying forest stands into vertical structure classes without the need for extensive fieldwork. The main strength and innovation of our approach is demonstrating that a model can be built and validated almost without field-acquired data. By processing point-cloud metrics derived from ALS data and employing machine learning techniques, particularly the random forest algorithm, the method generated a high-resolution vertical structure map across the country. The five-class model developed had a overall accuracy of 0.78. The results show that Polish forests are predominantly characterized by a single-story vertical structure, influenced by the dominance of Scots pine, with more complex structures in mountainous and biodiversity-rich areas. The methodology significantly reduces costs and time associated with traditional forest surveys, offering a scalable tool for forest monitoring, biodiversity assessment, and sustainable management, particularly under changing environmental conditions and habitat loss.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.