Determination of Riparian Vegetation Biomass from an Unmanned Aerial Vehicle (UAV)

编号 030032402

推送时间 20220103

研究领域 森林经理 

年份 2022 

类型 期刊 

语种 英语

标题 Determination of Riparian Vegetation Biomass from an Unmanned Aerial Vehicle (UAV)

来源期刊 Forests

期 第324期

发表时间 20211112

关键词 precision forestry;  unmanned aerial vehicle;  image analysis;  crown detection;  biomass;  river analysis; 

摘要 The need to rely on accurate information about the wood biomass available in riparian zones under management, inspired the land reclamation authority of southern Tuscany to develop a research based on the new remote sensing technologies. With this aim, a series of unmanned aerial vehicle (UAV) flight campaigns flanked by ground-data collection were carried out on 5 zones and 15 stream reaches belonging to 3 rivers and 7 creeks, being representative of the whole area under treatment, characterized by a heterogeneous spatial distribution of trees and shrubs of different sizes and ages, whose species’ mix is typical of this climatic belt. A careful preliminary analysis of the zones under investigation, based on the available local orthophotos, followed by a quick pilot inspection of the riverbank segments selected for trials, was crucial for choosing the test sites. The analysis of a dataset composed of both measured and remotely sensed acquired parameters allowed a system of four allometric models to be built for estimating the trees’ biomass. All four developed models showed good results, with the highest correlation found in the fourth model (Model 4, R2?= 0.63), which also presented the lowest RMSE (0.09 Mg). The biomass values calculated with Model 4 were in line with those provided by the land reclamation authority for selective thinning, ranging from 38.9 to 70.9 Mg ha?1. Conversely, Model 2 widely overestimated the actual data, while Model 1 and Model 3 offered intermediate results. The proposed methodology based on these new technologies enabled an accurate estimation of the wood biomass in a riverbank environment, overcoming the limits of a traditional ground monitoring and improving management strategies to benefit the river system and its ecosystems.

服务人员 付贺龙

服务院士 唐守正

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