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Phenology: Refers to the study of cyclic and seasonal natural phenomena, especially in relation to climate and plant and animal life. In the context of Landsat data, phenology affects the imagery because different seasons show varying characteristics of vegetation, water bodies, and other land features. For instance, trees may be leafless in winter but fully leafed in summer, affecting the interpretation of satellite images.
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Sun Angle Differences: This pertains to the varying positions of the sun at different times of the year. The sun angle influences the illumination and shadows in the imagery captured by Landsat satellites. A low sun angle can cause long shadows, while a high sun angle reduces shadows but may increase the glare. These variations can significantly affect the visual characteristics of the satellite imagery, impacting the analysis and interpretation of the data.
Implications in Landsat Data Analysis:
- Consistency in Data Collection: For accurate change detection using Landsat images, it is crucial to minimize the effects of phenology and sun angle differences. Using images from the same season across different years helps in maintaining consistency, as it reduces variations caused by seasonal changes in vegetation and illumination.
- Challenges in Algorithm Development: Developing algorithms for change detection over short intervals is challenging due to these natural variations. Algorithms need to account for these factors to avoid misinterpreting natural seasonal changes as significant land cover changes.