- A researcher collected information from four forest using sensors to assess their green cover. Observed average spectral values from each of the forest are given in the table below:
The forest cover in the order of highest to lowest is
(1) A>C>B>D (2) A>D>C>B
(3) B>C>D>A (4) D>A>B>CIntroduction
Remote sensing is a powerful tool for assessing forest green cover. By analyzing spectral data collected from sensors, researchers can estimate vegetation density and health. This article explains how to interpret spectral values to rank forest green cover, and why having the correct data is crucial for accurate results.
How Spectral Data Reflects Green Cover
Vegetation reflects and absorbs light in specific ways. Healthy, dense forests absorb more red light and reflect more near-infrared (NIR) light, resulting in higher values for vegetation indices like the Normalized Difference Vegetation Index (NDVI)67. These indices are widely used to assess green cover.
Ranking Forest Green Cover
To rank forests from highest to lowest green cover using spectral data:
-
Collect spectral values for each forest (e.g., NDVI, EVI, or raw reflectance).
-
Compare the values for each forest.
-
Rank the forests from highest to lowest based on the values.
Example (hypothetical):
Forest NDVI Value A 0.8 B 0.5 C 0.7 D 0.6 Ranking: A > C > D > B
Why the Table Is Essential
Without the actual spectral values or index, it is impossible to determine the correct ranking. The answer depends on the specific data collected for each forest671.
Conclusion
To accurately rank forest green cover using spectral sensor data, the spectral values for each forest must be provided. Higher values indicate greater green cover. Always ensure you have the correct data before making conclusions.
-
