Identification of Urban Green Space Types and Estimation of Above-Ground Biomass Using Sentinel-1 and Sentinel-2 Data

High-quality urban green space supports the healthy functioning of urban ecosystems. This study aimed to rapidly assess the distribution, and accurately estimate the above-ground biomass, of urban green space using remote sensing methods, thus providing a better understanding of the urban ecological...

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Bibliographic Details
Published in:Forests 2022-07, Vol.13 (7), p.1077
Main Authors: Xiao, Jue, Chen, Longqian, Zhang, Ting, Li, Long, Yu, Ziqi, Wu, Ran, Bai, Luofei, Xiao, Jianying, Chen, Longgao
Format: Article
Language:English
Subjects:
Algorithms
Biomass
Carbon sequestration
Classification
Coniferous forests
Ecological effects
Environmental management
Estimation
Forest biomass
Grasses
Information processing
Open spaces
Regression analysis
Regression models
Remote sensing
Urban areas
Urban environments
Urban planning
Vegetation
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Summary:High-quality urban green space supports the healthy functioning of urban ecosystems. This study aimed to rapidly assess the distribution, and accurately estimate the above-ground biomass, of urban green space using remote sensing methods, thus providing a better understanding of the urban ecological environment in Xuzhou for more effective management. We performed urban green space classifications and compared the performance of Sentinel-2 MSI data and Sentinel-1 SAR data and combinations, for estimating above-ground biomass, using field data from Xuzhou, China. The results showed the following: (1) incorporating an object-oriented method and random forest algorithm to extract urban green space information was effective; (2) compared with stepwise regression models with single-source data, biomass estimation models based on multi-source data provide higher estimation accuracy (R2 = 0.77 for coniferous forest, R2 = 0.76 for shrub-grass vegetation, R2 = 0.75 for broadleaf forest); and (3) from 2016 to 2021, urban green space coverage in Xuzhou decreased, while the total above-ground biomass increased, with higher average above-ground biomass in broadleaf forests (133.71 tons/ha) compared to coniferous forests (92.13 tons/ha) and shrub-grass vegetation (21.65 tons/ha). Our study provides an example of automated classification and above-ground biomass mapping for urban green space using multi-source data and facilitates urban eco-management.
ISSN:1999-4907
1999-4907
DOI:10.3390/f13071077