TY - JOUR
T1 - Data extraction from digital repeat photography using xROI
T2 - An interactive framework to facilitate the process
AU - Seyednasrollah, Bijan
AU - Milliman, Thomas
AU - Richardson, Andrew D.
N1 - Funding Information:
Support for the development and maintenance of PhenoCam network infrastructure has come from the National Science Foundation , through the Macrosystems Biology program, awards EF-1065029 and EF-1702697. The tools described here were developed to facilitate processing of image data from the National Ecological Observatory Network, under agreement 18-0080 between Battelle Memorial Institute and the Arizona Board of Regents. A.D.R. acknowledges support from NASA through the AIST program (award 80NSSC17K0582). The armoklahoma images were provided courtesy of the Atmospheric Radiation Measurement (ARM) Climate Research Facility, Billings, Oklahoma. The bartlettir images from the Bartlett Experimental Forest tower were supported by the National Science Foundation (grant DEB-1114804 ) and the USDA Forest Service's Northern Research Station . The boundarywaters images from Superior National Forest were provided courtesy of the USDA Forest Service Air Resources Management Program. The harvardhemlock images from Harvard Forest were partially supported through the National Science Foundation’s LTER program (DEB-1237491), and Department of Energy Office of Science (BER). The pasayten images from the Okanogan National Forest were provided courtesy of the USDA Forest Service Air Resources Management Program. The images from proctor site were supported by the Agricultural Experiment Station of the University of Vermont. The sherman images were provided courtesy of the Berkeley Biometeorology Lab at University of California Berkeley. Imagery from the PhenoCam network is made publicly available under a fair use agreement ( https://phenocam.sr.unh.edu/webcam/fairuse_statement/ ). We thank our many site collaborators for their efforts in support of PhenoCam.
Funding Information:
Support for the development and maintenance of PhenoCam network infrastructure has come from the National Science Foundation, through the Macrosystems Biology program, awards EF-1065029 and EF-1702697. The tools described here were developed to facilitate processing of image data from the National Ecological Observatory Network, under agreement 18-0080 between Battelle Memorial Institute and the Arizona Board of Regents. A.D.R. acknowledges support from NASA through the AIST program (award 80NSSC17K0582). The armoklahoma images were provided courtesy of the Atmospheric Radiation Measurement (ARM) Climate Research Facility, Billings, Oklahoma. The bartlettir images from the Bartlett Experimental Forest tower were supported by the National Science Foundation (grant DEB-1114804) and the USDA Forest Service's Northern Research Station. The boundarywaters images from Superior National Forest were provided courtesy of the USDA Forest Service Air Resources Management Program. The harvardhemlock images from Harvard Forest were partially supported through the National Science Foundation's LTER program (DEB-1237491), and Department of Energy Office of Science (BER). The pasayten images from the Okanogan National Forest were provided courtesy of the USDA Forest Service Air Resources Management Program. The images from proctor site were supported by the Agricultural Experiment Station of the University of Vermont. The sherman images were provided courtesy of the Berkeley Biometeorology Lab at University of California Berkeley. Imagery from the PhenoCam network is made publicly available under a fair use agreement (https://phenocam.sr.unh.edu/webcam/fairuse_statement/). We thank our many site collaborators for their efforts in support of PhenoCam. The authors declared that there is no conflict of interest.
Publisher Copyright:
© 2019 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
PY - 2019/6
Y1 - 2019/6
N2 - Digital repeat photography and near-surface remote sensing have been used by environmental scientists to study environmental change for nearly a decade. However, a user-friendly, reliable, and robust platform to extract color-based statistics and time series from a large stack of images is still lacking. Here, we present an interactive open-source toolkit, called xROI, that facilitates the process of time series extraction and improves the quality of the final data. xROI provides a responsive environment for scientists to interactively (a) delineate regions of interest (ROI), (b) handle field of view (FOV) shifts, and (c) extract and export time series data characterizing color-based metrics. The software gives user the opportunity to adjust mask files or draw new masks, every time an FOV shift occurs. Utilizing xROI can significantly facilitate data extraction from digital repeat photography and enhance the accuracy and continuity of extracted data.
AB - Digital repeat photography and near-surface remote sensing have been used by environmental scientists to study environmental change for nearly a decade. However, a user-friendly, reliable, and robust platform to extract color-based statistics and time series from a large stack of images is still lacking. Here, we present an interactive open-source toolkit, called xROI, that facilitates the process of time series extraction and improves the quality of the final data. xROI provides a responsive environment for scientists to interactively (a) delineate regions of interest (ROI), (b) handle field of view (FOV) shifts, and (c) extract and export time series data characterizing color-based metrics. The software gives user the opportunity to adjust mask files or draw new masks, every time an FOV shift occurs. Utilizing xROI can significantly facilitate data extraction from digital repeat photography and enhance the accuracy and continuity of extracted data.
KW - Digital repeat photography
KW - PhenoCam
KW - Phenology
KW - ROI
KW - Time-series
KW - xROI
UR - http://www.scopus.com/inward/record.url?scp=85064604224&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064604224&partnerID=8YFLogxK
U2 - 10.1016/j.isprsjprs.2019.04.009
DO - 10.1016/j.isprsjprs.2019.04.009
M3 - Article
AN - SCOPUS:85064604224
SN - 0924-2716
VL - 152
SP - 132
EP - 144
JO - ISPRS Journal of Photogrammetry and Remote Sensing
JF - ISPRS Journal of Photogrammetry and Remote Sensing
ER -