Validating remotely sensed land surface phenology with leaf out records from a citizen science network
Vegetation phenology indices derived from multispectral remote sensing data are used to estimate primary productivity, track impacts of climate change and predict fire seasons. Such indices may, however, lack accuracy due to effects of snow and water, different vegetation types, and parameter choice...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-02-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843222003363 |