Temporal Growth Analysis
This page visualizes hyperspectral vegetation index changes over time to support growth monitoring and early stress pattern analysis.
Temporal Analysis Goal
The goal of this analysis is to track how hyperspectral plant features change across dates. Instead of looking at one image at a time, temporal analysis helps show how vegetation indices move through the experiment timeline.
Time Based Tracking
Vegetation index values are compared across multiple dates to observe plant response over time.
Hyperspectral Features
The analysis focuses on VOG1 and NDVI, two indices used to summarize spectral plant response.
Growth and Stress Patterns
Tracking values across days helps reveal patterns that may not be obvious from a single image.
Interactive Hyperspectral Trends
This interactive chart shows Lia’s temporal hyperspectral outputs for VOG1 and NDVI across selected experiment dates.
VOG1 and NDVI Over Time
The chart allows users to hover over each date and compare how both hyperspectral indices changed through the timeline.
VOG1 Temporal Evolution
This plot shows the raw daily VOG1 mean, variation range, and smoothed mean. It gives a clearer view of how VOG1 changed over the selected dates.
Temporal Evolution of VOG1
The VOG1 plot shows raw daily mean values, standard deviation range, and a smoothed trend line across the experiment dates.
Summary Metrics
These summary values give a quick view of how much each index changed over the selected temporal window.
Highest VOG1
Highest VOG1 value occurred on January 31, 2026.
Lowest VOG1
Lowest VOG1 value occurred on February 12, 2026.
Highest NDVI
Highest NDVI value occurred on January 31, 2026.
Lowest NDVI
Lowest NDVI value occurred on February 9, 2026.
Observed Temporal Pattern
Both VOG1 and NDVI start higher at the beginning of the selected window and then generally decrease over time, with small recoveries or fluctuations on some dates. This supports the idea that temporal hyperspectral features can help summarize changes in plant condition across the experiment.
Why Temporal Analysis Matters
A single image can show plant condition at one moment, but temporal analysis shows how the plant changes across days. This makes it easier to observe gradual changes in vegetation index values and connect those changes to growth or stress progression.
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