Data extraction from digital repeat photography using xROI: An interactive framework to facilitate the process

Bijan Seyednasrollah, Thomas Milliman, Andrew D. Richardson

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)132-144
Number of pages13
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume152
DOIs
StatePublished - Jun 2019

Keywords

  • Digital repeat photography
  • PhenoCam
  • Phenology
  • ROI
  • Time-series
  • xROI

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences

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