干旱区生态环境知识资源中心(Arid): Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery

Arid

DOI	10.1093/forestry/cpaa028
	Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery
	Hosseini, Zahra; Latifi, Hooman; Naghavi, Hamed; Bakhtiari, Siavash Bakhtiarvand; Fassnacht, Fabian Ewald
通讯作者	Naghavi, H (corresponding author), Lorestan Univ, Fac Agr & Nat Resources, Dept Forestry, Khorramabad 6815144316, Iran.
来源期刊	FORESTRY
ISSN	0015-752X
EISSN	1464-3626
出版年	2021
卷号	94 期号:2 页码:278-291
英文摘要	Regular biomass estimations for natural and plantation forests are important to support sustainable forestry and to calculate carbon-related statistics. The application of remote sensing data to estimate biomass of forests has been amply demonstrated but there is still space for increasing the efficiency of current approaches. Here, we investigated the influence of field plot and sample sizes on the accuracy of random forest models trained with information derived from Pleiades very high resolution (VHR) stereo images applied to plantation forests in an arid environment. We collected field data at 311 Locations with three different plot area sizes (100, 300 and 500 m(2)). In two experiments, we demonstrate how plot and sample sizes influence the accuracy of biomass estimation models. In the first experiment, we compared model accuracies obtained with varying plot sizes but constant number of samples. In the second experiment, we fixed the total area to be sampled to account for the additional effort to collect Large field plots. Our results for the first experiment show that model performance metrics Spearman's r, RMSErel and RMSEnor improve from 0.61, 0.70 and 0.36 at a sample size of 24-0.79, 0.51 and 0.15 at a sample size of 192, respectively. In the second experiment, highest accuracies were obtained with a plot size of 100 m(2) (most samples) with Spearman's r = 0.77, RMSErel = 0.59 and RMSEnor = 0.15. Results from an analysis of variance type-II suggest that the overall most important factors to explain model performance metrics for our biomass models is sample size. Our results suggest no clear advantage for any plot size to reach accurate biomass estimates using VHR stereo imagery in plantations. This is an important finding, which partly contradicts the suggestions of earlier studies but requires validation for other forest types and remote sensing data types (e.g. LiDAR).
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000637092800009
WOS关键词	CARBON SEQUESTRATION ; AIRBORNE LIDAR ; STAND DENSITY ; VOLUME ; HEIGHT ; PREDICTION ; INVENTORY ; PRECISION ; SELECTION ; STOCKS
WOS类目	Forestry
WOS研究方向	Forestry
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/367879
作者单位	[Hosseini, Zahra; Naghavi, Hamed] Lorestan Univ, Fac Agr & Nat Resources, Dept Forestry, Khorramabad 6815144316, Iran; [Latifi, Hooman] KN Toosi Univ Technol, Dept Photogrammetry & Remote Sensing, 1346 Valiasr Str, Tehran 1996715433, Iran; [Latifi, Hooman] Univ Wurzburg, Dept Remote Sensing, Campus Hubland Nord 86, D-97074 Wurzburg, Germany; [Bakhtiari, Siavash Bakhtiarvand] Shahrekord Univ, Fac Nat Resources & Earth Sci, Dept Forestry, Shahrekord 8818634141, Iran; [Fassnacht, Fabian Ewald] Karlsruhe Inst Technol, Inst Geog & Geoecol, Kaiserstr 12, D-76131 Karlsruhe, Germany
推荐引用方式 GB/T 7714	Hosseini, Zahra,Latifi, Hooman,Naghavi, Hamed,et al. Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery[J],2021,94(2):278-291.
APA	Hosseini, Zahra,Latifi, Hooman,Naghavi, Hamed,Bakhtiari, Siavash Bakhtiarvand,&Fassnacht, Fabian Ewald.(2021).Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery.FORESTRY,94(2),278-291.
MLA	Hosseini, Zahra,et al."Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery".FORESTRY 94.2(2021):278-291.