Influence of drone altitude, image overlap, and optical sensor resolution on multi-view reconstruction of forest images

Seifert, Erich ; Seifert, Stefan ; Vogt, Holger ; Drew, David ; Van Aardt, Jan ; Kunneke, Anton ; Seifer, Thomas (2019)

CITATION: Seifert, E., et al. 2019. Influence of drone altitude, image overlap, and optical sensor resolution on multi-view reconstruction of forest images. Remote Sensing, 11(10):1252, doi:10.3390/rs11101252.

The original publication is available at http://www.mdpi.com

Publication of this article was funded by the Stellenbosch University Open Access Fund

Article

Recent technical advances in drones make them increasingly relevant and important toolsfor forest measurements. However, information on how to optimally set flight parameters and choosesensor resolution is lagging behind the technical developments. Our study aims to address this gap,exploring the effects of drone flight parameters (altitude, image overlap, and sensor resolution) onimage reconstruction and successful 3D point extraction. This study was conducted using video footageobtained from flights at several altitudes, sampled for images at varying frequencies to obtain forwardoverlap ratios ranging between 91 and 99%. Artificial reduction of image resolution was used to simulatesensor resolutions between 0.3 and 8.3 Megapixels (Mpx). The resulting data matrix was analysed usingcommercial multi-view reconstruction (MVG) software to understand the effects of drone variables on(1) reconstruction detail and precision, (2) flight times of the drone, and (3) reconstruction times duringdata processing. The correlations between variables were statistically analysed with a multivariategeneralised additive model (GAM), based on a tensor spline smoother to construct response surfaces.Flight time was linearly related to altitude, while processing time was mainly influenced by altitudeand forward overlap, which in turn changed the number of images processed. Low flight altitudesyielded the highest reconstruction details and best precision, particularly in combination with high imageoverlaps. Interestingly, this effect was nonlinear and not directly related to increased sensor resolution athigher altitudes. We suggest that image geometry and high image frequency enable the MVG algorithmto identify more points on the silhouettes of tree crowns. Our results are some of the first estimates ofreasonable value ranges for flight parameter selection for forestry applications.

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