An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images

Above-ground biomass (AGB) is an essential indicator for assessing ecosystem health and carbon storage in desert shrub-related research. Above-ground volume (AGV) of vegetation is a crucial parameter to estimate the AGB. In unmanned aerial vehicle (UAV) remote sensing, the AGV and AGB are mainly est...

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Autores principales:	Peng Mao, Longjun Qin, Mengyu Hao, Wenli Zhao, Jiechunyi Luo, Xu Qiu, Lijie Xu, Yujiu Xiong, Yili Ran, Chunhua Yan, Guo Yu Qiu
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Above-ground biomass (AGB) Above-ground volume (AGV) Unmanned aerial vehicle (UAV) Spectral indices Textural metrics Structural metrics Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/8f5efa79a0ce4658afb1fcc09040f605
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spelling	oai:doaj.org-article:8f5efa79a0ce4658afb1fcc09040f6052021-12-01T04:47:20ZAn improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images1470-160X10.1016/j.ecolind.2021.107494https://doaj.org/article/8f5efa79a0ce4658afb1fcc09040f6052021-06-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X2100159Xhttps://doaj.org/toc/1470-160XAbove-ground biomass (AGB) is an essential indicator for assessing ecosystem health and carbon storage in desert shrub-related research. Above-ground volume (AGV) of vegetation is a crucial parameter to estimate the AGB. In unmanned aerial vehicle (UAV) remote sensing, the AGV and AGB are mainly estimated by vegetation feature metrics (for example, spectral indices, textural, and structural metrics). However, there is limited study on the AGV and AGB estimation in desert shrub communities by using UAV, and it is difficult to determine the contribution of these metrics to AGV models under eliminating the influence of background factors. Taking a typical desert shrub area in Inner Mongolia, China as an example, this study develops an improved approach to extracted three types of feature metrics simultaneously using UAV RGB (Red, Green, Blue) images. First, digital orthophoto map (DOM) and digital surface model (DSM) were created through the photogrammetric procedure based on UAV RGB images. Second, the digital terrain model (DTM) for canopy height calculation was generated based on DOM and DSM by object-oriented image binary classification and ground elevation interpolation. Here, we recommended the ENVI Landsat Gap-fill tool to interpolate the ground elevation of vegetation areas. Meanwhile, 21 spectral indices, eight textural metrics, and five structural metrics were extracted. Finally, single-variable and multi-variable commonly used regression models were established based on these metrics and measured AGV with a leave-one-out cross-validation. Results showed that: (1) in the proposed model, the contribution of structural, textural, and spectral metric to shrub AGV models was 86.68, 7.08, and 6.24%, respectively. (2) The horizontal and vertical structural metrics, textural metrics, or spectral indices reflected the one-dimensional change of AGV, which had a saturation effect. (3) The canopy volume, combining the horizontal and vertical characteristics of vegetation canopy, could describe the overall change of AGV and played the most essential role in AGV modelling (R2 = 0.928, relative RMSE = 26.8%). The study findings provide a direct reference in determining suitable vegetation feature metrics for monitoring shrub AGV. The proposed approach for DTM generation and AGV estimation is more efficient, accurate and low-cost than before, and it can be a useful bridge between ground-based investigation and satellite remote sensing.Peng MaoLongjun QinMengyu HaoWenli ZhaoJiechunyi LuoXu QiuLijie XuYujiu XiongYili RanChunhua YanGuo Yu QiuElsevierarticleAbove-ground biomass (AGB)Above-ground volume (AGV)Unmanned aerial vehicle (UAV)Spectral indicesTextural metricsStructural metricsEcologyQH540-549.5ENEcological Indicators, Vol 125, Iss , Pp 107494- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Above-ground biomass (AGB) Above-ground volume (AGV) Unmanned aerial vehicle (UAV) Spectral indices Textural metrics Structural metrics Ecology QH540-549.5
spellingShingle	Above-ground biomass (AGB) Above-ground volume (AGV) Unmanned aerial vehicle (UAV) Spectral indices Textural metrics Structural metrics Ecology QH540-549.5 Peng Mao Longjun Qin Mengyu Hao Wenli Zhao Jiechunyi Luo Xu Qiu Lijie Xu Yujiu Xiong Yili Ran Chunhua Yan Guo Yu Qiu An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
description	Above-ground biomass (AGB) is an essential indicator for assessing ecosystem health and carbon storage in desert shrub-related research. Above-ground volume (AGV) of vegetation is a crucial parameter to estimate the AGB. In unmanned aerial vehicle (UAV) remote sensing, the AGV and AGB are mainly estimated by vegetation feature metrics (for example, spectral indices, textural, and structural metrics). However, there is limited study on the AGV and AGB estimation in desert shrub communities by using UAV, and it is difficult to determine the contribution of these metrics to AGV models under eliminating the influence of background factors. Taking a typical desert shrub area in Inner Mongolia, China as an example, this study develops an improved approach to extracted three types of feature metrics simultaneously using UAV RGB (Red, Green, Blue) images. First, digital orthophoto map (DOM) and digital surface model (DSM) were created through the photogrammetric procedure based on UAV RGB images. Second, the digital terrain model (DTM) for canopy height calculation was generated based on DOM and DSM by object-oriented image binary classification and ground elevation interpolation. Here, we recommended the ENVI Landsat Gap-fill tool to interpolate the ground elevation of vegetation areas. Meanwhile, 21 spectral indices, eight textural metrics, and five structural metrics were extracted. Finally, single-variable and multi-variable commonly used regression models were established based on these metrics and measured AGV with a leave-one-out cross-validation. Results showed that: (1) in the proposed model, the contribution of structural, textural, and spectral metric to shrub AGV models was 86.68, 7.08, and 6.24%, respectively. (2) The horizontal and vertical structural metrics, textural metrics, or spectral indices reflected the one-dimensional change of AGV, which had a saturation effect. (3) The canopy volume, combining the horizontal and vertical characteristics of vegetation canopy, could describe the overall change of AGV and played the most essential role in AGV modelling (R2 = 0.928, relative RMSE = 26.8%). The study findings provide a direct reference in determining suitable vegetation feature metrics for monitoring shrub AGV. The proposed approach for DTM generation and AGV estimation is more efficient, accurate and low-cost than before, and it can be a useful bridge between ground-based investigation and satellite remote sensing.
format	article
author	Peng Mao Longjun Qin Mengyu Hao Wenli Zhao Jiechunyi Luo Xu Qiu Lijie Xu Yujiu Xiong Yili Ran Chunhua Yan Guo Yu Qiu
author_facet	Peng Mao Longjun Qin Mengyu Hao Wenli Zhao Jiechunyi Luo Xu Qiu Lijie Xu Yujiu Xiong Yili Ran Chunhua Yan Guo Yu Qiu
author_sort	Peng Mao
title	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
title_short	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
title_full	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
title_fullStr	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
title_full_unstemmed	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
title_sort	improved approach to estimate above-ground volume and biomass of desert shrub communities based on uav rgb images
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8f5efa79a0ce4658afb1fcc09040f605
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An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images

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