Abstract
Urban vegetation biomass is a key indicator of the carbon storage and sequestration capacity and ecological effect of an urban ecosystem. Rapid and effective monitoring and measurement of urban vegetation biomass provide not only an understanding of urban carbon circulation and energy flow but also a basis for assessing the ecological function of urban forest and ecology. In this study, field observations and Sentinel-2A image data were used to construct models for estimating urban vegetation biomass in the case study of the east Chinese city of Xuzhou. Results show that (1) Sentinel-2A data can be used for urban vegetation biomass estimation; (2) compared with the Boruta based multiple linear regression models, the stepwise regression models—also multiple linear regression models—achieve better estimations (RMSE = 7.99 t/hm2 for low vegetation, 45.66 t/hm2 for broadleaved forest, and 6.89 t/hm2 for coniferous forest); (3) the models for specific vegetation types are superior to the models for all-type vegetation; and (4) vegetation biomass is generally lowest in September and highest in January and December. Our study demonstrates the potential of the free Sentinel-2A images for urban ecosystem studies and provides useful insights on urban vegetation biomass estimation with such satellite remote sensing data.
Highlights
According to the World Urbanized Prospects, urban residents are expected to compose 68% of the global population by 2050 [1], and this would bring increasingly intensive urban heat island (UHI) effects, environmental degradation, and ecological damage
By the support vector machine (SVM) classifier, the urban vegetation of the study area was classified into three types, namely low vegetation, broadleaved forest, and coniferous forest (Figure 3) in the 24-July-2107 image; namely low vegetation, broadleaved forest, and coniferous forest (Figure 3) in the 24-July-2107 image; the overall accuracy of this classification was 89.86% with a Kappa coefficient of 0.83
This study demonstrates how Sentinel-2A image data can be used for vegetation biomass in an urban context
Summary
According to the World Urbanized Prospects, urban residents are expected to compose 68% of the global population by 2050 [1], and this would bring increasingly intensive urban heat island (UHI) effects, environmental degradation, and ecological damage. As an important carrier of urban ecosystems, urban vegetation—which refers to all naturally growing and human-planted vegetation within an urban area [2,3]—brings considerable ecological, economic, and social benefits [4]. These include improving urban microclimates, mitigating UHI effects, increasing surface runoffs, maintaining the urban carbon–oxygen balance, and importantly, enhancing the quality of urban life by providing spaces for relaxation and recreation [5,6,7,8]. Urban vegetation biomass is an effective indicator of the capacity of carbon storage and sequestration, and ecological effect of an urban ecosystem [10,11]; it is, important to estimate urban vegetation biomass in urban eco-environmental management.
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