Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone Camera Sensors

Version 1 : Received: 16 January 2017 / Approved: 17 January 2017 / Online: 17 January 2017 (09:59:36 CET)

How to cite: Qu, Y.; Wang, J.; Song, J.; Wang, J. Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone Camera Sensors. Preprints 2017, 2017010077. https://doi.org/10.20944/preprints201701.0077.v1 Qu, Y.; Wang, J.; Song, J.; Wang, J. Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone Camera Sensors. Preprints 2017, 2017010077. https://doi.org/10.20944/preprints201701.0077.v1

Abstract

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Keywords

leaf area index; smartphone camera sensor; conifer forest; canopy gap fraction

Subject

Engineering, Control and Systems Engineering

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