Interactive Web Tools for Visualizing Land Surface Anomalies

Land surface parameters derived from remote sensing offer extensive spatial coverage and frequent temporal sampling. They are crucial for research, as they establish complex relationships with each other and serve as indicators of both current and historical environmental and climate conditions. These measurements, along with their corresponding anomalies derived from historical averages, help researchers identify and understand changes in climate, ecology, biodiversity, and more. By focusing on land surface changes, we aim to better understand our living environment and capture rapid disturbances. Based on long-term accumulated data, we have developed a website to facilitate users in understanding land surface changes from three dimensions: time, space, and multiple parameters. Researchers can use this website to investigate and analyze land surface anomalies. By comparing current anomalies to historical data, users can identify patterns, assess severity, and explore potential relationships with other environmental factors. For example, researchers studying NDVI (Normalized Difference Vegetation Index) changes might correlate these with LST (Land Surface Temperature) anomalies, as higher temperatures often coincide with shifts in vegetation growth. Understanding these relationships is essential for effective environmental management and conservation.

Our website primarily focuses on tracking heat and cold events using LST data. We offer tools for both daily and monthly anomaly analysis in order to support rapid response and long-term trend assessment. The monthly scale is characterized by multi-parameter relationships, while the daily scale focuses on rapid responses to heatwaves and cold spells. By incorporating population data, we aim to quantify the human impact of these extreme weather events.

Our web platform offers an interactive map interface that enables researchers to overlay and visualize various land surface parameters and their respective anomalies. It facilitates the exploration of complex relationships between different variables. For instance, researchers can analyze the correlation between NDVI and ET (Evapotranspiration) anomalies by overlaying them on the map and selecting specific dates or time periods. The platforms also provide user-friendly features such as customizable date ranges, data animation, downloadable visualizations, among others.

Our goal is to provide researchers with tools for enhanced visualization of land surface anomalies, especially during heat/cold events. This work also paves the way for future expansion to track a broader range of natural disasters.