Forest and Grassland Resources Research >
Analysis of Tree Canopy Cover in Built-up Srea of Huize County, Yunnan Province Based on eCognition Image Interpretation
Received date: 2022-05-05
Revised date: 2022-07-09
Online published: 2022-10-13
Urban ecological construction is an effective way to solve the environmental deterioration caused by the urbanization process,forest canopy coverage is a landmark index to measure urban ecology and reflect the effectiveness of forest city construction,the analysis results of forest canopy coverage can provide reference for the forest city construction of small and medium-sized cities in southwest China.Based on the 0.5m resolution aerial remote sensing images in the built-up area of Huize County from July to August 2019,and the ArcGIS10.4 platform,the canopy coverage and patch distribution of trees in the built-up area of Huize County were calculated and analyzed by using eCognition 9.0 software interpretation and multi-scale segmentation algorithm processing.The results showed that the actual canopy coverage of trees in the built-up area of Huize County was 275.55hm2,which gradually spread from the urban center to the surrounding areas,showing an increasing trend,and the canopy coverage rate of trees was 17.78%.There were 5 270 patches in total,and the overall urban forest was small in area but big in number,with serious fragmentation.The potential forest canopy coverage was 8.98%,with a total of 2 067 patches,and the theoretical value of the maximum forest canopy coverage that could be achieved was only 26.76%.The patch distribution of new and old residential areas was significantly different,and the construction of urban forest played a positive role in promoting the improvement of urban ecology.
Key words: urban forest; tree canopy cover; eCognition; Huize county built-up area
Xiaofei HE , Xin CHEN , Mengyao WANG , Xue MIAO , Changmeng FAN , Jiansong PENG . Analysis of Tree Canopy Cover in Built-up Srea of Huize County, Yunnan Province Based on eCognition Image Interpretation[J]. Forest and Grassland Resources Research, 2022 , 0(4) : 100 -108 . DOI: 10.13466/j.cnki.lyzygl.2022.04.013
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