A novel approach for measuring treeline spatial complexity

1st Workshop on Metrology for Agriculture and Forestry

农业科学;数学

Spinsante, S.^1 ; Montalto, L.^2 ; Garbarino, M.^3 ; Malandra, F.^4 ; Weisberg, P.J.^5 ; Paone, N.^6 ; Scalise, L.^6

Dept. of Information Engineering, Universita Politecnica Delle Marche, Italy^1

Dept. of Materials, Environmental Sciences and Urban Planning, Universita Politecnica Delle Marche, Italy^2

Dept. of Agricultural, Forestry and Food Sciences, Universita Degli Studi di Torino, Italy^3

Dept. of Agricultural, Food and Environmental Sciences, Universita Politecnica Delle Marche, Italy^4

Dept. of Natural Resources and Environmental Science, University of Nevada, Reno, United States^5

Dept. of Industrial Engineering and Mathematical Sciences, Universita Politecnica Delle Marche, Italy^6

关键词: Anthropic activity;    Different mechanisms;    High-precision;    Land-use change;    Spatial complexity;    Spatial patterns;    Spatial structure;    Textural analysis;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/275/1/012017/pdf
DOI  :  10.1088/1755-1315/275/1/012017

学科分类：农业科学（综合）

来源: IOP

【 摘 要 】

Treelines, defined as ecotonal zones between closed forest and the uppermost trees, are particularly sensitive to global changes related to climate and anthropic activities. Different mechanisms of treeline formation can be detected as subtle differences in ecotonal structure, which in turn have important implications for how treelines function and potentially respond to global changes. So, it is of interest to be able to measure in a precise and quantitative way treelines' properties reflecting climate and land use changes. Classical tools adopted to measure treeline spatial patterns are not able to fully understand the limiting factors affecting them. This work presents a novel textural analysis of treeline spatial structure based on the measurement of surface roughness, and applies the corresponding metrics to twenty study areas at both Upper and Lower treelines, where all tree crowns have been mapped at high precision. Preliminary results are promising and motivate future and more extensive evaluations on bigger datasets.