Modeling plant phenology database: Blending near-surface remote phenology with on-the-ground observations

• Autor(a) principal: Mariano, Greice C.
• Data de Publicação: 2016
• Outros Autores: Morellato, Leonor Patricia C. [UNESP], Almeida, Jurandy, Alberton, Bruna [UNESP], de Camargo, Maria Gabriela G. [UNESP], Torres, Ricardo da S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.ecoleng.2016.03.001; http://hdl.handle.net/11449/177870
• topic: Database design; Digital images; Image-based phenological indices; Leafing; Modeling; Remote phenology

Phenology research handles multifaceted information that needs to be organized and made promptly accessed by scientific community. We propose the conceptual design and implementation of a database to store, manage, and manipulate phenological time series and associated ecological information and environmental data. The database was developed in the context of the e-phenology project and integrates ground-based conventional plant phenology direct observations with near-surface remote phenology using repeated images from digital cameras. It also includes site-base information, sensor derived data from the study site weather station and plant ecological traits (e.g., pollination and dispersal syndrome, flower and fruit color, and leaf exchange strategy) at individual and species level. We validated the database design through the implementation of a Web application that generates the time series based on queries, exemplified in two case studies investigating: the relationship between flowering phenology and local weather; and the consistency between leafing patterns derived from ground-based phenology on leaf flush and from vegetation image indices (%Green). The database will store all the information produced in the e-phenology project, monitoring of 12 sites from cerrado savanna to rainforest, and will aggregate the legacy information of other studies developed in the Phenology Laboratory (UNESP, Rio Claro, Brazil) over the last 20 years. We demonstrate that our database is a powerful tool that can be widely used to manage complex temporal datasets, integrating legacy and live phenological information from diverse sources (e.g., conventional, digital cameras, seed traps) and temporal scales, improving our capability of producing scientific and applied information on tropical phenology.