Evaluation of image-assisted forest monitoring: A simulation

Abstract

Fiscal uncertainties can sometimes affect national continuous forest monitoring efforts. One solution of interest is to lengthen the time it takes to collect a “full set” of plot data from five to 10 years in order to reduce costs. Here, we investigate using ancillary information to partially offset this proposed solution’s negative effects. We focus our discussion on the corresponding number of years between measurements of each plot while we investigate how thoroughly the detrimental effects of the reduced sampling effort can be ameliorated with change estimates obtained from temporally-dense remotely-sensed images. We simulate measured plot data under four sampling error structures, and we simulate remotely-sensed change estimates under three reliability assumptions, integrated with assumptions about the additional unobserved growth resulting from the lengthened bservation window. We investigate a number of estimation systems with respect to their ability to provide compatible annual estimates of the components of change during years spanned by at least half of the full set of plot observations. We show that auxiliary data with shorter observation intervals can contribute to a significant improvement in estimation.

  • Citation: Roesch, Francis; Coulston, John; Van Deusen, Paul; Podlaski, Rafal 2015. Evaluation of image-assisted forest monitoring: A simulation. Forests, Vol. 6(9): 21 pages.: 2897-2917. DOI:10.3390/f6092897
  • Keywords: forest monitoring; sample design; estimation; auxiliary information; remote sensing
  • Posted Date: August 4, 2016
  • Modified Date: March 22, 2017
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