Results 51 to 60 of about 7,186,066 (138)

Constraints and Opportunities for Detecting Land Surface Phenology in Drylands

Journal of Remote Sensing, 2021
Land surface phenology (LSP) enables global-scale tracking of ecosystem processes, but its utility is limited in drylands due to low vegetation cover and resulting low annual amplitudes of vegetation indices (VIs).
Shawn D. Taylor, Dawn M. Browning, Ruben A. Baca, Feng Gao   +3 more
doaj   +1 more source

Comparisons of Global Land Surface Seasonality and Phenology Derived from AVHRR, MODIS and VIIRS data

, 2017
The data set in this collection is for the paper Comparisons of Global Land Surface Seasonality and Phenology Derived from AVHRR, MODIS and VIIRS Data which will be published in the Journal of Geophysical Research ...
Zhang, Xiaoyang
core   +1 more source

The Coexistence of Trees, Shrubs, and Grasses Creates a Complex Picture of Land Surface Phenology in Dry Tropical Ecosystems

Remote Sensing
The use of digital cameras to monitor vegetation phenology (phenocams) has become increasingly common as a means of ground truthing estimates of land surface phenology from Earth observation data.
Stephanie P. Koolen, John L. Godlee, Bruna Alberton, Desirée Marques Ramos, Magna Soelma Beserra Moura, Leonor Patricia C. Morellato, Kyle G. Dexter   +6 more
doaj   +1 more source

Tree species diversity drives the land surface phenology of seasonally dry tropical woodlands [PDF]

Seasonal foliage display (leaf phenology) is a key determinant of ecosystem function. Variation in land surface phenology, observed via space-borne remote sensing, can be explained at broad spatial scales by climate, but we lack understanding of how ...
School of GeoSciences, Siampale, Abel, Godlee, John   +2 more
core   +2 more sources

Relative influence of timing and accumulation of snow on alpine land surface phenology [PDF]

, 2018
Timing and accumulation of snow are among the most important phenomena influencing land surface phenology in mountainous ecosystems. However, our knowledge on their influence on alpine land surface phenology is still limited, and much remains unclear as ...
Schaepman, Michael E; https://orcid.org/, Xie, Jing; https://orcid.org/, Garonna, Irene, De Gregorio, Ludovica, de Jong, Rogier, Notarnicola, Claudia, Kneubühler, Mathias; https://orcid.org/, Rogier de Jong, Claudia Notarnicola, Mathias Kneubühler, Michael E. Schaepman, Xie, Jing, Schaepman, Michael E., Kneubühler, Mathias, Jing Xie, Ludovica De Gregorio, Irene Garonna   +16 more
core   +1 more source

CLM output for "A Comparison of Land Surface Phenology in the Northern Hemisphere Derived from Satellite Remote Sensing and the Community Land Model"

, 2022
This data set includes the Leaf Area Index (LAI) and net primary production (NPP) outputs from two data atmosphere forced CLM-only simulations. The manuscript titled "A Comparison of Land Surface Phenology in the Northern Hemisphere Derived from ...
Peter Lawrence (12507317), David M Lawrence (8021006), Mark A. Friedl (12507326), Xiaolu Li (4820067), Toby Ault (4875742), Eli Melaa (12507308), Bijan Seyednasrollah (7463491), Andrew D. Richardson (6066404), Carlos M. Carrillo (12507311), Adam M. Young (3286260)   +9 more
core   +1 more source

Atmospheric teleconnection influence on North American land surface phenology

Environmental Research Letters, 2018
Short-term forecasts of vegetation activity are currently not well constrained due largely to our lack of understanding of coupled climate-vegetation dynamics mediated by complex interactions between atmospheric teleconnection patterns.
Matthew P Dannenberg, Erika K Wise, Mark Janko, Taehee Hwang, W Kolby Smith   +4 more
doaj   +1 more source

Supplemental Online Materials of Trends in Land Surface Phenology across the Conterminous United States (1982-2016) Analyzed by NEON Domains [PDF]

, 2020
This research investigated land surface phenology trends across the conterminous United States (1982-2016) by National Ecological Observatory Network (NEON) domains. The Supplemental Online Materials (SOM) contain two Appendices.
Liang, Liang, Henebry, Geoffrey M., Liu, Lingling, Zhang, Xiaoyang, Hsu, Li-Chih   +4 more
core   +1 more source

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology [PDF]

Geoscientific Model Development
Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface
G. Liu, G. Liu, M. Migliavacca, C. Reimers, B. Kraft, M. Reichstein, A. D. Richardson, L. Wingate, N. Delpierre, H. Yang, A. J. Winkler   +10 more
doaj   +1 more source

Spatial-temporal dynamics of land surface phenology over Africa for the period of 1982-2015. [PDF]

Heliyon, 2023
Shi S, Yang P, van der Tol C.
europepmc   +1 more source