Field experiments to test the use of the normalized-difference vegetation index for phenology detection.

By S. Nagai, K. Nasahara, Hiroyuki Muraoka, T. Akiyama, S. Tsuchida. 2010

101 citations recorded by the source corpus.

Some previous studies have detected the timing of leaf expansion and defoliation using the normalized-difference vegetation index (NDVI), but to examine tree phenology using satellite data, NDVI results should be confirmed using ground-truthing. We examined the relationship between NDVI and tree phenology during leaf expansion and defoliation by simultaneously observing the spectral reflectance of the canopy surface and canopy surface images in a cool-temperate deciduous broad-leaved forest. To define the timing of leaf expansion and defoliation using NDVI, the index should meet three criteria: (1) NDVI should exhibit a monotonous increase or decrease (monotonicity). (2) The relationship between NDVI and the forest canopy's status should be unique (uniqueness). (3) The method is robust against the systematic noise (bias) (robustness). In the spring, NDVI values of 0.2-0.3 (relative values: 0.15-0.28) and 0.6-0.7 (relative values: 0.65-0.78) satisfied all three criteria. NDVI values of 0.6-0.7 can serve as potential criteria for detecting the timing of leaf expansion. In autumn, no NDVI values satisfied all three criteria. Thus, NDVI does not appear to be useful for detecting the timing of defoliation. For an area where evergreen vegetation or snow covers the forest floor in winter, our results suggest that previous uses of NDVI to identify the timing of leaf expansion and defoliation on the basis of the date of the maximum rate of growth or reduction of NDVI and the date with a value midway between the year's maximum and minimum values are misleading.

Subfields: Ecology, Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/f8376e0bced416082d7b795d3d6287e4fa47e8ce

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Markus Metz
2. A. Gutierrez
3. Harini Nagendra
4. Carlo Ricotta
5. Kate S. He
6. Duccio Rocchini
7. Markus Neteler
8. Thomas W. Gillespie

In Global and Planetary Change

1. A. Gutierrez
2. Harini Nagendra
3. Carlo Ricotta
4. Kate S. He
5. Duccio Rocchini
6. Markus Neteler
7. Luigi Ponti

In Plant Science

1. Carlo Ricotta
2. Kate S. He
3. Duccio Rocchini
4. Thomas W. Gillespie

Citations in the corpus

• Applicability of Green-Red Vegetation Index for Remote Sensing of Vegetation Phenology (2010, background): “[13] have reported, the canopy condition of autumn coloring corresponded to different NDVI values from year to year.”
• Potential of remote sensing to predict species invasions (2015, background): “Different models have been developed to understand the nature of the geometry of vegetation in relation to its spectral behaviour (see Eastman et al., 2013; Förster et al., 2010; Nagai et al., 2010).”