Spatial Pattern of Urban Heat Island to Enhance Urban Cooling Ecosystem Services in the Post-Pandemic Era

Urbanization, followed by reduced green space, often leads to increased land surface temperatures (LST), which is also known as the urban heat island (UHI) effect. Urban cooling ecosystem services provided by forests and parks play a crucial role in reducing the UHI effect (which is reflected in LST) and improving the liveability and sustainability of cities. The pandemic has changed many people’s views about the importance of ecosystem services to their well-being. The post-pandemic era is a turning point for infrastructure and environmental improvements to increase ecosystem services’ benefits. This study aims to look at the potential for increasing ecosystem services’ benefits through the provision of urban forests and parks based on UHI conditions in Surakarta city. In this study, UHI was identified from LST based on Landsat 8 and Landsat 9 remote sensing images. The spatial pattern of the UHI was analyzed based on block units using road boundaries using cluster and outlier statistical spatial analysis. In formulating alternatives to provide urban forests and parks, we also interviewed stakeholders from a village revitalization program in Kampung Mojo, Surakarta city. The results show that after the pandemic, in a revitalized neighborhood, the surface temperature was still high. The revitalization program did not include the provision of parks because the basic issue of this program is land ownership legality. Nevertheless, the UHI spatial pattern provides evidence that the provision of urban forests and parks is needed on the central and southern sides of Surakarta city to enhance urban cooling ecosystem services.


Introduction
Urbanization, the process of population growth and expansion of cities, often leads to increased land surface temperatures (LST).Urbanization has greatly affected regional and urban spaces, both from social, economic, and environmental aspects.Urbanization has also reduced the area of green open space to meet the needs of residents' housing and infrastructure.The impact of urbanization is not only spatial change but also climate change and the thermal environment.Rapid urbanization causes a drastic reduction in green open space, rising surface temperatures, and a worsening thermal environment [1].Along with urbanization, land use and land cover change (LUCC) has been shown to affect regional climate, including increasing surface temperatures [2].The main cause of the increase in LST is urban green open space being converted into other types of land use.In an effort to slow down the spread of COVID-19, strict measures were put in place by many governments around the world, such as lockdown, aiming to reduce people interactions [3].During the strict COVID-19 lockdown, the surface urban heat island in Chinese urban area and Pakistan significantly dropped [4,5].The UHI that caused land surface heat stress in Iran cities also reduced significantly during the lockdown period [6,7].The implementation of social restrictions also reported affects changes in UHI and decreases LST in some Java Island big cities [8].Many studies have investigated that UHIs have a great deal of decline during pandemic times, especially when lockdown is in place.This study looked at UHI at a post-pandemic time to examine which clusters of areas in Surakarta City that still have high LSTs after the pandemic.
The pandemic has changed many ways of thinking, lifestyles, and infrastructure in various regions of the world.In Indonesia and many other countries, many infrastructure improvements have been made during the pandemic.The COVID-19 pandemic did, in fact, provide governments and authorities in Indonesia, a rare opportunity to implement numerous infrastructural arrangements and upgrades.Infrastructure projects could be completed with less interruption to daily life if there were fewer people on the move and less traffic congestion.In addition, the travel budget can be diverted to improvement in the health sector (in relation to the Covid-19 pandemic) and infrastructure.This research takes postpandemic time to analyze the condition of post-pandemic urban heat island (UHI) and after infrastructure improvements made.
Green open spaces can reduce the higher temperatures caused by the urban heat island effect [9].The surface temperature is expected to be reduced through land use arrangements and the fulfilment of green open space as urban cooling ecosystem services.In order to be able to find out the areas that spatially need action related to the provision of green open spaces, researcher feel the need to understand the urban heat island spatial patterns that occur, especially in the city of Surakarta.

Data & Methods
Surakarta City was chosen as the study area because it is included in the urban area category [10,11] with 11,187.52 people per km2 of population density [12].This study uses data from satellite imagery on 2022 and interview data on 2023.The acquisition of LST data comes from Landsat 8 and 9 satellite data, which will hereinafter be referred to as Landsat.The tool used for data acquisition is the Google Earth Engine (GEE), so the data can be directly used.Each Landsat used is Collection 2 Level 2 Tier 1. Collection 2 and Level 2 here are corrected Landsat data at the Surface Reflectance (SR) level so that they can be used for land analysis.In obtaining image data for year 2022, a median temporal composite is used or combining several images in a year into one image.The goal is to reduce anomalies, reduce cloud cover, and correct errors on Landsat image.LST (Land Surface Temperature) data is obtained from band 10 for Landsat 8 and Landsat 9. Surakarta City road data is used in this study to create polygon blocks.While the boundaries of analysis and data cutting used the administrative boundaries of Surakarta City as seen on Figure 2. LST data that has been aggregated into attribute values on polygons is analyzed using Cluster and Outlier Analysis (Anselin Local Moran's I) in ArcGIS 10.8.2 tools.Cluster and Outlier Analysis creates z-scores and p-values attributes, which are measures of statistical significance.They will tell you whether or not to reject the null hypothesis, feature by feature.They indicate whether the apparent similarity (a spatial clustering of either high or low values) or dissimilarity (a spatial outlier) is more pronounced than one would expect in a random distribution.
Data collection through interviews was also carried out to strengthen the discussion regarding the existing conditions and plans for enhancing ecosystem services in one of the micro areas in the study area (Figure 1).The micro area is Mojo village, one of the sub-districts in Surakarta City, where a settlement revitalization program is being implemented.The revitalization located in the river basin of Bengawan Solo river across the village.Interviews have been conducted in 2023 with revitalization actors and the Surakarta city government.

Land Surface Temperature characteristic
The LST aggregation results for 2022 show that the surface temperature of Surakarta City is between 36 and 45 Celsius.High surface temperatures spread throughout the city of Surakarta.However, the majority of low temperatures can be seen on the north side of Surakarta (Figure 3).Apart from that, it can also be seen that low temperatures are also found in the river border area, which stretches in the middle of the city.Low temperatures are also seen in the city center, which is in urban green open space areas such as parks and riverside.

Urban Heat Island spatial cluster
LST data for Surakarta City were then analyzed for patterns using ArcGIS tools for Cluster and Outlier Analysis (Anselin Local Moran's I).The analysis resulted in z-scores for each feature at a 95% statistical confidence level.A high positive z-score for a feature indicates that the surrounding features have similar values (either high values or low values).Otherwise, a low negative z-score for a feature indicates a statistically significant spatial data outlier.The cluster/outlier type (COType) was categorized as High-High, Low-Low, High-Low, Low-High, and Not Significant.The result will be High-High for a statistically significant cluster of high values of LST, which means both the LST of the block and its surroundings are higher than the average LST of the whole zone.The Low-Low COType results were for statistically significant clusters of low values of LST.This indicated that both the LST of the block and its adjacent blocks were lower than the average LST of the whole study area.The COType in the results will also indicate if the feature has a high value of LST and is surrounded by features with low values of LST (High-Low) or if the feature has a low value of LST and is surrounded by features with high values of LST (Low-High).Not significant indicated that there was a random spatial pattern of LST distribution without a clustering structure.The cluster map of Surakarta LST can be seen in Figure 4.These results represent the characteristics of the UHI spatial pattern.The High-High LST cluster represents an area with a high intensity of UHI.Those areas are located in the city center and south area of Surakarta, with large built-up areas and high density of buildings.While the Low-Low LST cluster represents an area with a low intensity of UHI, we can also see that the majority of these areas are on the north side of the city.Areas with Low-High and High-Low COType results are indicated by green open space areas in the middle of urban areas, such as parks and riverside.The area has a low LST, but is in between areas with a high LST, which is also an area with a high density of buildings.
According to the findings, even if people were more concerned about environmental and health conditions during the pandemic, UHI was still occurring.Even after the pandemic had been controlled (perhaps by vaccination, lockdowns, and public health initiatives), continuous climate change continued to cause the global surface temperature to increase.Social and economic activities continue to emit significant quantities of carbon emissions, particularly in urban areas, as the economy recovers.If cities in the post-pandemic era cannot balance economic and environmental activity, humanity will confront bigger issues and challenges [13].Research that has proven that the lockdown from COVID-19 leads to a significant decrease in UHI recommends that post-pandemic human habits should be improved in order to mitigate climate change [14].Seeing the results of the study, at a time when post-pandemic UHI in Surakarta City is still high, the lifestyle of the people and economic activity need to be a concern, especially by the government.The inventions need to be made on ecosystem services to get the effect of urban cooling to lower LST in urban areas.It is also critical to support the services provided by various urban green and open spaces, as well as to rethink urban planning in order to adapt to new behaviors and requirements resulting from the COVID-19 epidemic [15].The microarea of the case study, Mojo Village, was chosen to take a closer look at UHI patterns in a dense urban area.Mojo Village received a settlement revitalization program for its river basin area.It can be seen in Figure 5 that the area in Mojo Village is a significant UHI cluster area, even after the revitalization program.The river basin area, which is the focus of the revitalization, even has a high temperature.This is due to the fact that the area for the revitalization program is still narrow and surrounded by areas that also require revitalization.Similar factors that lead to high surface temperatures exist in the surrounding areas that also need revitalization, such as a lack of green space and inappropriate settlement planning.All of these factors contribute to the "heat spillover" effect, whereby high temperatures in one area may have an impact on nearby neighborhoods.The changes made within the revitalized area might not be sufficient to compensate for the broader environmental issues causing high surface temperatures.
Based on interviews with the local government, the revitalization program will be improved gradually.Green open space is not a priority in the first stage of the program because the basic issue of this program is land ownership legality.Therefore, in the early stages of the program, priority is given to the fulfilment of habitable housing buildings and the ownership of legal land.The next stage of the program is the completion of the settlement infrastructure, one of which is the green open space that has been prepared for construction at the next stage.It is critical to complete infrastructure for urban cooling since UHI connects with regional vulnerability to other disasters.This is because multi-hazard risk hotspots occur in low-income areas with the highest COVID-19 infection rates and surface temperatures [16].

Conclusions
The research shows that the city of Surakarta still has high surface temperatures, even though people have changed their minds and lifestyles after the pandemic.The economic activity in the wake of the pandemic is also occuring, especially in developing countries, which produce more emissions than before.Even in a revitalized neighborhood that has recovered from the pandemic, the surface temperature was still high.The narrow broadness of the revitalization initiative and the interconnectedness of urban surroundings may be responsible to the continued existence of high surface temperatures in the neighborhood.A more comprehensive, city-wide strategy to urban planning and environmental improvements may be necessary to address this issue and enhance the ecosystem services.Therefore, infrastructure improvements still need to be made in clusters with high UHI, especially urban parks and forest to enhance urban cooling ecosystem services benefits.