Title | What would it take to detect land surface phenology in sparsely vegetated drylands? |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Taylor SD, Browning DM, Baca R |
Conference Name | Ecological Society of American Conference 2021 |
Date Published | 3/3/2021 |
ARIS Log Number | 382757 |
Abstract | Land surface phenology (LSP) enables ecosystem scale tracking of the drivers and consequences of a changing climate, but it’s useability is limited in some areas. In dryland ecosystems low vegetation cover is the primary limitation in LSP detection. Low vegetation cover can cause the growing season vegetation index (VI) to be indistinguishable from the dormant season VI, making phenology extraction impossible. Here, using both simulated data and multi-temporal drone imagery of a desert shrubland, we explore the feasibility of detecting LSP with respect to fractional vegetation cover, plant functional types, and sensor observation error. We found that plants with distinct VI signals, such as deciduous shrubs with a high leaf area index, require at least 30-40% fractional cover on the landscape to consistently detect pixel level phenology. Evergreen plants, which have lower VI amplitude between dormant and growing seasons, require considerably higher cover and can sometimes have undetectable phenology even with 100% fractional cover. We also found that even with adequate cover, biases in phenological metrics can still be up to 20 days, and can never be 100% accurate due to observation error from shadows, viewing angle, and atmospheric interference. Our work also highlights some understudied limitations in drylands LSP. For example some areas may have the occasional season which meets a minimum VI threshold for detecting phenology, potentially indicating a higher than normal productive year. Our results show that these years may happen solely due to chance as opposed to increased productivity. |