diff --git a/Heatwaves_NewDataSource/README.md b/Heatwaves_NewDataSource/README.md new file mode 100644 index 0000000..64a32be --- /dev/null +++ b/Heatwaves_NewDataSource/README.md @@ -0,0 +1,157 @@ +**Improving Land Surface Temperature (LST) Maps Using Nighttime Images** + +Land Surface Temperature (LST) is a key indicator for analyzing +heatwaves and the urban heat island (UHI) effect, which refers to higher +surface and air temperatures in urban areas compared to their rural +surroundings. + +In the CLIMAAX Heatwave Risk Assessment Workflow, satellite-based LST +images as the exposure component is analysed. The workflow currently +defines the Landsat 8 image downloading methodology and related codes. + +At the **Şanlıurfa and Mersin Metropolitan Municipalites**, Landsat 8 +datasets for daytime observations during the summer season have been +already applied. However, since daytime land surface temperatures often +exceed 60°C and are distributed relatively homogeneously across the city +center, it was not possible to effectively visualize temperature +variations or the urban heat island effect. + +Therefore, as joint working group from Mersin and Şanlıurfa Metropolitan +Municipalities, we searched for another data source providing nighttime +LST images. Two of the most widely used satellite sources for LST data +are Terra ASTER (Advanced Spaceborne Thermal Emission and Reflection +Radiometer) and Landsat 8 (Thermal Infrared Sensor – TIRS). + +Below is a comparison of their sensor and data characteristics: + +| **Feature** | **Terra ASTER** | **Landsat 8 (TIRS)** | +|----|----|----| +| Satellite Platform | Terra (NASA, launched 1999) | Landsat 8 (NASA/USGS, launched 2013) | +| Spatial Resolution | 90 meters | 30 or 100 meters | +| Day/Night Imagery | Day or Night | Daytime only | +| Data format | GeoTiff/HDF | GeoTiff | +| LST Unit | Kelvin | Degrees Celcius | +| Data-Source | NASA Earthdata Search | RSLab Landsat LST | +| URL | | | + +**Why Terra ASTER Instead of Landsat 8?** + +Landsat 8 offers consistent global coverage and good temporal +consistency but has fewer thermal bands and generally only provides +daytime acquisitions. For city-scale UHI studies, ASTER’s 90 m thermal +data is better suited to detect local temperature variations between +urban structures and vegetated areas. ASTER’s ability to acquire both +daytime and nighttime thermal images is a major advantage. Nighttime LST +helps capture residual heat storage in built-up areas and provides +clearer contrasts between urban and rural surfaces. This makes ASTER +data more convenient and reliable for visualizing and quantifying the +urban heat island effect, especially in densely built city centers. + +**Main disadvantages of ASTER Data** + +- Data analysis is more complex than for Landsat 8. + +- A simple additional code is required to convert the LST unit from + Kelvin to degrees Celsius. + +- Preloaded “granules”should be clipped for desired area of concern. + +In Şanlıurfa, we compared both data sources over the same location using +ASTER night-time and Landsat 8 daytime maps. The results clearly +demonstrated that night-time ASTER imagery provides a more effective +visualization of the urban heat island effect. + + + +We have improved the Climaax Heatwave Risk Map of Şanlıurfa MM and +Mersin MM city centres by applying ASTER’s night-time LST data-sets: + + + + + +**Step by Step Data Processing (We applied)** + +1\. Go to : + +2\. Sign in. + +3\. Search data source “ASTER Surface Kinetic Temperature” + +4\. Select data source “ASTER L2 Surface Kinetic Temperature V003” + +5\. “Spatial” function: Navigate in the map, locate the Region and draw +a polygon or circle. + +6\. “Temporal” function: Define the temporal period as 01.07 to 31.08 of +e.g. 2020-2025 (tick «Use a recurring date range» box) + +7\. Select «Night» + +8\. Select the best preloaded «granule» covering our region. Probably +much bigger than our area of interest. Select «GeoTiff» as file format. +“Download” the selected granule (image). Requested image data will be +sent via e-mail within a day + +9\. The incoming ASTER image file cannot be used directly in the +workflow. + +The following pre-processing steps are required: + +- Convert the temperature values from Kelvin to Celsius. + +- Since the file covers a very large area, it needs to be clipped to the + study area. + +The software we used for this study is ArcMAP version 10.8. It is a +desktop GIS software developed by Esri. This screen shows the appearance +of the Aster satellite image within the software. + +10\. Since the surface temperature of the downloaded satellite image is +in Kelvin, we need to convert it to Celsius. To do this, we use the +Raster Calculator tool. After opening the tool, in the calculation field +we enter: + +```("file_name.tif" * 0.1) - 273.15``` + +and then select the folder where the new file will be saved. + +11\. Since the obtained image is very large, we need to cut it according +to our study area. To do this, we created a shapefile (shp) centered on +our study area. The square visible on the screen is centered on +Şanlıurfa. In ArcMap, we open the Image Analysis tool. we select our +study area. In the Image Analysis tool, we choose the image we want to +clip (After conversion). Then, in the Processing section, the desired +area is clipped. + +12\. Change the coordinate system of the clipped image. The reason for +this step is to align it with the coordinate system of the population +data in the workflow, ensuring that the workflow functions correctly. To +do this, we used the Project Raster tool to change the image’s +coordinate system. The output coordinate system is GCS_WGS_1984. + +13\. If the image name is incorrect, it causes an error in the workflow. +Therefore, the image name needs to be changed. All files should be saved +under the LST Folder. + +14\. The file — the updated ASTER image — is now ready and working +properly in the workflow. + +**Conclusion** + +The results clearly demonstrated that night-time ASTER imagery provides +a more effective visualization of the urban heat island effect. But, +data analysis is more complex than for Landsat 8. + +We hope that, temperature conversion from Kelvin to Celsius and clipping +operation can be performed within in the workflow by means of additional +codes instead of manual ArcGIS operations. + +**For further explanation and contact:** + +**İhsan Topallı- MersinMM:** + +**İzzettin Karabulut-Sanliurfa MM:** + +**Tamer Atalay- Atalay Climate Consulting:** tamer@atalayconsulting.com diff --git a/Heatwaves_NewDataSource/media/image1.png b/Heatwaves_NewDataSource/media/image1.png new file mode 100644 index 0000000..0457467 Binary files /dev/null and b/Heatwaves_NewDataSource/media/image1.png differ diff --git a/Heatwaves_NewDataSource/media/image2.png b/Heatwaves_NewDataSource/media/image2.png new file mode 100644 index 0000000..bfdf833 Binary files /dev/null and b/Heatwaves_NewDataSource/media/image2.png differ diff --git a/Heatwaves_NewDataSource/media/image3.png b/Heatwaves_NewDataSource/media/image3.png new file mode 100644 index 0000000..c441277 Binary files /dev/null and b/Heatwaves_NewDataSource/media/image3.png differ