Detection of Firmiana danxiaensis Canopies by a Customized Imaging System Mounted on an UAV Platform

Abstract

The objective of this study was to test the effectiveness of mapping the canopies of Firmiana danxiaensis (FD), a rare and endangered plant species in China, from remotely sensed images acquired by a customized imaging system mounted on an unmanned aerial vehicle (UAV). The work was conducted in an experiment site (approximately 10 km 2 ) at the foot of Danxia Mountain in Guangdong Province, China. The study was conducted as an experimental task for a to-be-launched large-scale FD surveying on Danxia Mountain (about 200 km 2 in area) by remote sensing on UAV platforms. First, field-based spectra were collected through hand-held hyperspectral spectroradiometer and then analyzed to help design a classification schema which was capable of differentiating the targeted plant species in the study site. Second, remote-sensed images for the experiment site were acquired and calibrated through a variety of preprocessing steps. Orthoimages and a digital surface model (DSM) were generated as input data from the calibrated UAV images. The spectra and geometry features were used to segment the preprocessed UAV imagery into homogeneous patches. Lastly, a hierarchical classification, combined with a support vector machine (SVM), was proposed to identify FD canopies from the segmented patches. The effectiveness of the classification was evaluated by on-site GPS recordings. The result illustrated that the proposed hierarchical classification schema with a SVM classifier on the remote sensing imagery collected by the imaging system on UAV provided a promising method for mapping of the spatial distribution of the FD canopies, which serves as a replacement for field surveys in the attempt to realize a wide-scale plant survey by the local governments.

No place to hide: Rare plant detection through remote sensing

“…Likewise, the rare plant Firmiana danxiaensis H.H.Hsue & H.S.Kiu, J. S. was detected in Danxia Mountain (China) using multispectral bands and RS-derived vegetation, topographic, texture and geometric indices (Liu et al, 2018).…”

“…Direct detection can be carried out either by visual identification or by image classification methods that allow the detection of distinctive spectral features of the target species. Specifically, Fletcher and Erskine (2012) and Rominger and Meyer (2019) indices, has proven to be an effective alternative approach for their direct detection (Liu et al, 2018). For instance, the endangered Allium tricoccum Aiton (wild leek) and the endemic Agathis australis (D.Don) Lindl.…”

“…in the Tehuacan‐Cuicatlan Valley in Mexico with high validation accuracy (0.95; López‐Jiménez et al., 2019). When morphological features extracted from traditional colour imagery are not enough to discriminate rare plants, spectral bands and derived indices, either alone or in combination with other types of RS indices, has proven to be an effective alternative approach for their direct detection (Liu et al., 2018). For instance, the endangered Allium tricoccum Aiton (wild leek) and the endemic Agathis australis (D.Don) Lindl.…”

A Tree Species Mapping Method from UAV Images over Urban Area Using Similarity in Tree-Crown Object Histograms

“…UAV multispectral images and derived DSM data were used in this study. The UAV images were collected using a customized multispectral imaging system [29], in September, 2016, when the weather was fine and the trees flourished in the study area. The spatial resolution of the UAV multispectral images is about 4 cm.…”

“…The UAV multispectral images collected were processed to generate ortho-image and DSM image. First, optical and radiometric calibrations were carried out on the UAV images using the methods presented in Reference [29]. The optical calibration corrected the geometric distortion and removed the vignetting effect, while the radiometric calibration transformed the digital numbers to radiance.…”