Assessing the impact of urban growth on Land Surface Temperature (LST) over the past 40 years involves integrating Local Climate Zones (LCZs) and Intensity Analysis Techniques. This approach provides a structured framework to evaluate how urbanization influences thermal characteristics in a rapidly developing area.

1. Local Climate Zones (LCZs):

LCZs offer a standardized classification system that delineates urban and natural landscapes based on factors like land cover, structure, and function. This classification aids in understanding the spatial distribution of thermal properties across different urban forms.

Steps to Utilize LCZs:

• Classification: Employ remote sensing data to categorize the study area into various LCZs, such as compact high-rise, open low-rise, and natural landscapes.
• Temporal Analysis: Analyze historical satellite imagery to observe transitions between LCZs over the 40-year period, identifying areas of significant urban expansion.

2. Intensity Analysis Techniques:

Intensity Analysis provides a quantitative method to assess land use and land cover changes, focusing on the rate and extent of these transformations.

Steps to Apply Intensity Analysis:

• Change Detection: Utilize satellite imagery from different time points to detect changes in land cover, particularly the conversion of natural areas to urban uses.
• Quantification: Measure the intensity of these changes to determine the degree of urbanization and its correlation with LST variations.

Integrating LCZs and Intensity Analysis:

• Spatial Correlation: Examine the relationship between specific LCZ types and corresponding LST data to identify which urban forms contribute most to temperature increases.
• Temporal Trends: Assess how changes in LCZ distribution over time correlate with LST trends, providing insights into the thermal impact of urban growth.

Case Study Reference:

A study titled "Determining the Influence of Long Term Urban Growth on Surface Urban Heat Islands Using Local Climate Zones and Intensity Analysis Techniques" exemplifies this integrated approach. The research highlights how combining LCZ classification with intensity analysis can effectively quantify the impact of urbanization on LSt.

Conclusion:

By merging LCZ classification with intensity analysis, researchers can systematically assess the effects of urban growth on land surface temperatures. This methodology enables the identification of critical areas where urban planning interventions can mitigate adverse thermal impacts, promoting sustainable urban development.

To assess the impact of urban growth on land surface temperature (LST) using Local Climate Zones (LCZs) and Intensity Analysis Techniques, you can follow several key steps. First, gather multi-temporal Landsat imagery spanning the last 40 years (e.g., from the 1980s to the present) to analyze changes in LST over time. It's essential to obtain high-resolution urban land use data and meteorological records for validation. Additionally, generate Local Climate Zones (LCZs) maps using methods like WUDAPT or manual classification to categorize different urban types within your study area.

Once you have your data, extract the land surface temperature (LST) from the thermal bands of your Landsat images (eg: Landsat 5 Band 6 and Landsat 8 Band 10). Apply radiance and emissivity corrections to accurately convert these thermal bands into LST values. Normalize and compare LST trends across various LCZ classes, such as compact urban, open low-rise, water, and vegetation, to understand how urbanization affects temperature variations.

Next, conduct a Land Use/Land Cover (LULC) classification for each time period using Supervised Classification techniques like Support Vector Machines or Random Forests. Utilize Intensity Analysis (IA) to quantify urban expansion rates, land cover transitions, and persistence over time. By comparing LST variations with urban expansion intensity in different LCZs, you can determine patterns of heat concentration and urban heat island (UHI) effects.

Accordingly, perform statistical analyses, such as correlation analysis (Pearson, regression, or machine learning models), to measure the relationship between urban growth and LST changes. Spatial clustering techniques, like Hot Spot Analysis or Getis-Ord Gi*, can help identify UHI intensification patterns. Based on your findings, assess how different LCZs influence LST variations and propose mitigation strategies, such as implementing green infrastructure and reflective materials, to reduce heat stress and improve urban climate resilience.