One of the significant issues in urban ecosystems is investigating the urban heat island pattern to assess the ecological comfort. Given the ecological function and cooling effect of green spaces, it is necessary to eva‎luate the performance of these spaces over time. The present study aimed to analyze the spatial pattern and quantify the ecosystem services of green spaces to moderate the temperature at the surface of Tehran city for the years 2015 and 2023. Initially, using Landsat 8 satellite imagery and the Google Earth Engine platform, the land surface temperature (LST) map and the Normalized Difference Vegetation Index (NDVI) were calculated. Then, to investigate cold temperature spots, the study area was gridded using Fishnet analysis, and the calculated LST value for each part of the area was entered into HighLowClustering analysis. Afterward, using the Getis-Ord-Gi index, cold temperature spots at a significance level of 95% and above were extracted using Zscore. Other significance levels in this study were also analyzed using landscape metrics at the class and landscape levels. Considering that the aim of this study was to investigate the performance of green spaces, green spaces were identified using the NDVI index and with the help of training samples and threshold values (TSS) in the ROC package. Then, these green spots were overlaid with areas that were significantly cold in terms of temperature to obtain significant green cold spaces. To model the connection paths between these cold cores, the electrical circuit theory in the Circuitscape software was used. However, since the number of green cold spots was high, to obtain the main spots, the multi-scale fragmentation analysis (FAD) was used. Finally, the spots in the dominant class were considered as connection cores. In this process, the inverse of the NDVI map was also used as a cost map. The results showed that the distribution of LST in Tehran city was not uniform in the two years of this study. In a way that the northern and northeastern parts of the city had the most significant cold spots and the southern and southwestern parts of the city had the most significant hot spots. Also, based on the results, cold spaces (with a probability of 99%) decreased by 1400 hectares during this period, most of which were concentrated in the north of the city. The kappa agreement coefficient between cold spaces in 2015 and 2023 was also calculated as 0.84. Meanwhile, the area of hot spots (with a probability of 99%) increased by 1618 hectares during this time, and this increase was concentrated in the southern and southwestern parts of Tehran. TSS thresholding using NDVI also identified green cold spots with better power compared to LST. However, the analysis of landscape metrics showed that green spaces were fragmented, and therefore their cooling effect was also reduced. Based on the FAD analysis, 15 cores were also identifiable for both years, and the flow intensity between these cold cores increased from 0.2 amperes in 2015 to 1.5 amperes in 2023, indicating an increase in the connection between dense urban green spaces. Also, corresponding to the decrease in significant green cold spaces, the cooling flow bottlenecks between them also decreased in 2015 compared to 2023, and their location was also more concentrated in the northern parts of the city. The results of this study show that urban green spaces in the southern, western, and central parts of Tehran do not have the expected cooling effect, and green space development programs should focus on these areas.

10/19/2024 12:00:00 AM

639

ESE49

زهرا اميدي قلعه محمدي