Wu J; Wolfe B; Serbin S; Ely K; Rogers A
Parque Natural Metropolitano; Bosque Protector San Lorenzo (Fort Sherman)
Dec. 20, 2016
May 9, 2019
Tropical forest phenology monitoring undertaken by use of Wingscapes timelapse cameras (phenocams) at three tropical evergreen forests in Panama: San Lorenzo (PA-SLZ), Parque Natural Metropolitano (PA-PNM), and Barro Colorado Island (PA-BCI). Following installation in December 2016, images were acquired every 10 minutes from 10 am to 2 pm daily, ending in May 2019. A total of 37 cameras were mounted on towers and tree branches, and view sunlit canopy or understory forest as follows: PA-SLZ, 11 canopy, 14 understory; PA-PNM, 6 canopy, 2 understory, PA-BCI, 4 canopy (trees also monitored for sap flow). This data package contains a full data description, metadata, species identification guides and summary files showing example fields of view from each camera location as csv and pdf files. The data description provides instructions for download of the full resolution image files, and other summary data products stored on external servers.
Images recorded by Wingscapes timelapse pro cameras, generally acquiring images from 10 am to 2 pm Panama local time (UTC-5:00) in 10 minutes intervals.
Cameras were mostly attached to towers, with a small number attached to branches within the canopy. Most cameras capture a top of canopy field of view, a small number have understory fields of view.
QC: Image collections were reviewed for data quality. In most cases, images recorded during installation that are not representative of the intended field of view have been deleted. In some cases camera clock errors led to image capture during the night; completely dark images have been deleted where they were noted. In some cases image quality varies due to camera fogging. To allow for various analysis types these images have generally been retained, but fall outside of the “End dates” noted in the metadata. Some image sets include intermittent periods of foggy images. Change of field of view occurs within some photo sets, either as a rapid shift or slow drift. Where noted, these changes are documented in the metadata, along with other errors including clock corruption, incorrect location imprinting and missing data.
Brookhaven National Laboratory; Smithsonian Tropical Research Institute
U.S. Department of Energy Office of Science Office of Biological and Environmental Research
Serbin, Shawn - Brookhaven National Laboratory ([email protected])
Wu J; Wolfe B; Serbin S; Ely K; Rogers A (2022): Panama tropical forest digital camera imagery for vegetation phenology, Dec2016-May2019, PA-SLZ, PA-PNM, PA-BCI. 1.0. NGEE Tropics Data Collection. (dataset). http://dx.doi.org/10.15486/ngt/1770776
This research was supported as part of NGEE-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under contract no. DE-SC0012704.
Data Link: Download Dataset
Guangqin Song, Shengbiao Wu, Calvin K.F. Lee, Shawn P. Serbin, Brett T. Wolfe, Michael K. Ng, Kim S. Ely, Marc Bogonovich, Jing Wang, Ziyu Lin, Scott Saleska, Bruce W. Nelson, Alistair Rogers, Jin Wu (2022). Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 183, 19-33, https://doi.org/10.1016/j.isprsjprs.2021.10.023