- LST (Land Surface Temperature): The measure of how hot the Earth's surface would feel to the touch in a particular location, measured by satellites.
- Infrared Radiation: Heat energy that satellites can detect from space, which the Earth's surface naturally emits.
- Resolution: The size of each data point in satellite images. For example: at 500m resolution, each data point covers an area of 500m x 500m (about 5 football fields). Just like a higher resolution photo shows more detail, higher resolution satellite data gives us more detailed temperature information.
- Microclimate: Small areas where the weather conditions are different from the surrounding area. For example, a valley might be cooler than the nearby hilltop.
- Urban-Wildland Interface: Places where cities or towns meet natural areas like forests, creating unique fire risks.
- Hotspot: An area that shows much higher temperatures than the areas around it, which could indicate fire risk.
- Resampling: The process of taking satellite data that shows temperature every 1km and making it show temperature every 500m instead, giving us more detailed information.
- EDA (Exploratory Data Analysis): The initial investigation of data to discover patterns, spot anomalies, and test assumptions using statistical summaries and visualizations.
Land Surface Temperature (LST) comes from satellites that measure heat energy coming from Earth's surface. This tells us how hot different surfaces are, whether they're forests, empty fields, or city buildings.
LST measures surface temperature, not air temperature. Think of how a parking lot feels much hotter than the air around it on a sunny day - LST measures that surface heat rather than the air temperature you'd feel standing there.
Satellites don't use thermometers like we do on Earth. Instead, they detect heat energy (infrared radiation) coming from the Earth's surface and convert this information into temperature measurements.
Satellites can only measure the temperature of what they can see from above. In a forest, they measure the treetops' temperature, not the ground beneath. In a city, they measure rooftops and roads.
The temperature of surfaces often differs from air temperature because:
- Plants and trees affect surface temperature differently than bare ground
- Wet soil is usually cooler than dry soil
- Different materials heat up and cool down at different rates
- Temperatures change throughout the day and night
- Local conditions like shade or wind affect surface temperatures
We use LST to find areas that might affect fire spread by:
- Finding places that heat up quickly, like dry grasslands
- Identifying areas that stay hot for long periods
- Watching how cities and natural areas store heat differently
We track temperature patterns by:
- Measuring how areas heat up during the day
- Seeing how quickly or slowly areas cool at night
- Finding places that stay unusually warm
LST helps us understand:
- Which areas have dry soil based on how hot they get
- When plants are stressed from heat and might catch fire easily
- How heat moves across different types of landscape
Temperature data comes in a special scientific unit (Kelvin) and needs conversion:
- First multiply the satellite data by 0.02 to get Kelvin
- Then subtract 273.15 from Kelvin to get Celsius
Our project makes temperature data more detailed by:
- Taking measurements every 500m instead of every 1km
- Creating clearer pictures of temperature changes in mountain areas like Uttarakhand
- Helping us spot small but important temperature changes
- Making our fire risk predictions more accurate in complex terrain
This detailed temperature information helps us:
- Find specific areas with high fire risk
- Tell emergency teams exactly where to focus
- Plan better fire prevention strategies
- Watch for dangerous conditions in real time
- Understand how fire risk changes with seasons
Using more detailed temperature measurements helps us:
- See four times more detail than before
- Spot small areas that might be dangerous
- Find potential fire spread paths earlier
Better detail is especially important in areas with varied landscape because we can:
- See temperature differences between valleys and ridges
- Understand where forests meet developed areas
- Track how heat behaves in complex mountain terrain
More detailed measurements help us tell the difference between:
- Different types of forest areas
- Open fields versus wooded areas
- Bare ground versus developed areas
- Where cities meet natural areas
With more detailed data, we can:
- Find small areas with unusual temperature patterns
- Spot places where fires might spread more quickly
- Identify natural features that might affect fire spread
- Higher resolution data helps us better understand temperature patterns across different landscapes.
- By examining temperature readings every 500m instead of every 1km, we can see how temperature varies within smaller areas.
- More detailed data allows us to examine relationships between temperature and other environmental factors more precisely.
- We can better analyze how temperature patterns change across different types of terrain and vegetation.
- Understanding detailed temperature patterns helps us plan how to build a better prediction model.
- Analyzing temperature variations at 500m resolution shows us which features might be most important for fire spread prediction.
- This detailed analysis helps us identify which areas need more careful monitoring in the future model.
- The insights from this analysis will guide decisions about what type of prediction model might work best.