Determination of the optimum number of sample points to classify land cover types and estimate the contribution of trees on ecosystem services using the I‐Tree Canopy tool

Abstract

The process of producing information about dynamic land use and land cover and ecosystem health quickly with high accuracy and low cost is important. This information is one of the basic data used for sustainable land management. For this purpose, remote sensing technologies are generally used, and sampling points are mostly assigned. Determination of the optimum number of sampling points using the I-Tree Canopy tool was the main focus of this study. The I-Tree Canopy tool classifies land cover, revealing the effects of tree cover on ecosystem services, such as carbon (C) sequestration and storage, temperature regulation, air pollutant filtering, and air quality improvement, with numerical data. It is used because it is practical, open source, and user-friendly. This software works based on sampling point assignment, but it is unclear how many sampling points should be assigned. Therefore, determining the optimum number of sample points by statistical methods will increase the effectiveness of this tool and guide users. For this purpose, reference data were created for comparison. Then, 31 I-Tree Canopy reports were created with 100-point increments up to 3100. The data obtained from the reports were compared with the reference data, and statistical analysis based on Gaussian and a second-order polynomial fit was performed. At the end of the analysis, the following results were obtained; the results of this study demonstrated that the optimum number of sample points for a 1-ha area is 760 ± 32 from the comparison of the real area and I-Tree Canopy results. Similar results from the Gaussian fit of annually sequestered and stored C and carbon dioxide (CO 2 ) amounts in trees and the reduction in air pollution in grams were obtained as 714 ± 16. Therefore, we may conclude that taking more than 800 sample points will not be statistically significant.

Measuring Air Quality Impacts of Green Areas and Ecosystem Services (Ess) Using Web-Based I-Tree Canopy Tool: A Case Study in Istanbul

“…Users can reveal the removal of pollutants causing air pollution from the atmosphere by trees according to the types of land cover they have determined, as well as the effects on ecosystem services for the capture and storage of atmospheric carbon with numerical data. Besides, the module is designed to provide easy and accurate estimation of monetary values (Hirabayashi, 2014;Selim et al, 2023). i-Tree recommends 500-1000 search points for studies, but reports that the more points identified, the better the prediction results will be (USDA, 2022).…”