Fig5. Annual oxygen production (Kg/m2) based on the GWR model in Isfahan city
Estimating the total amount of carbon sequestration, CO2 absorption, and Oxygen production
The results obtained from the spatial distribution map showed that the biomass of all trees within the city sequestrated about 7704.22 tons of carbon. This amount of carbon absorbs a total of 28274.502 tons of carbon dioxide. Accordingly, 20570.16 tons of oxygen is produced by all trees across the city per year.
Discussion
Regarding the calculation of above-ground and below-ground biomass, previous studies used allometric equations using biophysical parameters like DBH, height, and wood density (Aboal et al., 2005, Basuki et al., 2009, Bond-Lamberty et al., 2002, Cai et al., 2013, Djomo et al., 2010, Henry et al., 2010, Joosten et al., 2004, Segura and Kanninen, 2005). Similarly, in this study, to calculate the biomass in an individual unit, we used the allometric equations that were developed by Ponce-Hernandez and colleagues in 2004.
In terms of calculating carbon sequestration, in this study, we used a photosynthesis equation to estimate carbon storage in the biomass. While previous studies used a constant to convert the biomass into carbon storage. In different species, it varies between 44.4 to 55.7 percent. Generally, in most of the studies, an average of 50 percent of the weight of the dried biomass is considered as a constant to convert biomass into carbon storage (Elias and Potvin, 2003, Singh et al., 2011, Zhang et al., 2009, Zhu et al., 2010).
Applying different processes to extract the trees’ canopy, we used different spectral variables, included band analysis, vegetation index, and texture analysis. The vegetation indices included the Excess Green Plant Index (ExG), the Excess Red Plant Index (ExR), and the difference between these indices (ΔExGR) (Meyer and Neto, 2008). Amongst all the variables the ΔExGR index showed a significant relationship with carbon sequestration. 
Regarding carbon sequestration and CO2 absorption by green areas in the urban ecosystem, the results of this study are in line with previous studies that emphasized the role of the green area to absorb CO2 in cities (Dwivedi et al., 2009, Groffman et al., 2006, Nowak et al., 2013, Qing-Biao et al., 2009, Raciti et al., 2014, Tor-ngern and Leksungnoen, 2020, Townsend‐Small and Czimczik, 2010, Velasco et al., 2016, Zirkle et al., 2012; Schlesinger and Lichter, 2001).
The green infrastructure of Isfahan city with a high diversity of tree species can provide climate regulation services. Addressing the monetary valuation can highlight the importance of the carbon sequestration service. Simply, previous studies have shown that the cost of separating carbon dioxide (CO2) from major point sources such as fossil fuel power plants and transporting to a storage site, and ultimately storing in an underground natural reservoir cost about 100 to $ 300 per ton of carbon (Bui et al., 2018, EASAC, 2019, Rubin and De Coninck, 2005). The results showed that the trees in Isfahan store 28274.502 tons of carbon in their biomass per year. If the average cost of carbon sequestration is assumed $ 200 per ton, then the annual value of carbon sequestration by trees will be $ 5654,900.
In addition, the results of the study confirm that the GWR method contributes to high accuracy in modeling a spatially heterogeneous pattern (i.e., carbon sequestration distribution pattern) within the city (in this research R2 was 0.915). Because the GWR method provides a separate regression equation for each observation rather than calibrating only a single regression equation for the whole statement (Fotheringham et al., 2001) . The result of this study is congruent with findings from other studies, arguing that the GWR method possesses a better potential to address the spatial distribution of parameters like primary production, land surface temperature, and fire density (Li et al., 2017, Oliveira et al., 2014, Wong and Lee, 2005).
Moreover, the results of this study indicated that determining the drip line radius (approximate radius of the canopy) plays an important role in matching the ground data of each tree and the spectral data of the satellite image. Because the surface of tree canopies in an urban area usually is not homogeneous and uniform in comparison with the canopies in a forest. Then, using plots in sampling to measure the variables is not recommended. Also, the drip line (approximate radius of the canopy) is calculated based on the trunk diameter for each single tree. So, the drip line can be more appropriate than the plot in establishing a regression relationship between the ground-collected information of every sample tree and image data related to the canopy of each sample tree.
Acknowledging the limitations in this study, in order to calculate the annual carbon sequestration, we used the annual diameter growth rate and the height growth rate which was obtained by previous research (i.e., these parameters are not the same in all trees, so it leads to error in carbon sequestration calculation). In addition, parameters like wood density can be different not only among species but also among trees of the same species (Domec and Gartner, 2002). In this study, we divided the trees into two categories: coniferous and broad leave. Therefore, this generalisation with using average densities brings about errors in allometric formulas. Weighing the biomass in the field may solve these kinds of issues and subsequently may contribute to high accuracy. But field measurement is considered a costly method and is just applicable in small areas. Besides, in this study, due to the high cost of worldview image, we just access red, green, and blue bands. We did not have a near-infrared band which may assess the green area better than other bands.
The results of this research can be implemented by urban land-use planners and decision -makers, because there is a growing need to integrate urban ecosystem service concept (i.e., carbon sequestration) into impact assessment, urban planning processes towards sustainability, livability, and resilience (Cortinovis and Geneletti, 2018, Gómez-Baggethun et al., 2013, Haase et al., 2014). In this way, for instance, the distribution map of CO2 absorption can help the planners to better understand which neighborhood needs to be planted to mitigate CO2 concentration.
Conclusion
Increasing concern with the climate change has led to the research which focusing on the green areas impacts in mitigating CO2concentration. However, the potential effect of urban forests on air quality and climate change mitigation remains an object of debate, mainly due to a lack of reliable data. In this research we proposed a modeling to contribute to estimating carbon sequestration and its spatial distribution within Isfahan city. Therefore, we developed a GWR model in which calculated carbon sequestration was the dependent variable, while the vegetation index of ΔExGR was regarded as the independent variable.
In general, it can be concluded that integrating high-resolution data with allometric calculations can make a contribution to analyze carbon sequestration and its spatial distribution efficiently and economically.
As a recommendation for future research, this research can be coupled with a study that analyze carbon emission and addresses its spatial variation within the city. The combination of these two approaches can give an insight, for instance, to recognize which sites need more planting strategy or whether there is a balance between CO2 emission and carbon sequestration in different places of the city.