Estimating biomass and carbon sequestration of plantations around industrial areas using very high resolution stereo satellite imagery

• Published in: IForest (Viterbo) Vol. 12; no. 6; pp. 533 - 541
• Main Authors: Hosseini, Z, Naghavi, H, Latifi, H, Bakhtiari Bakhtiarvand, S
• Format: Journal Article
• Language: English
• Published: Potenza The Italian Society of Silviculture and Forest Ecology (SISEF) 01-12-2019; Italian Society of Silviculture and Forest Ecology (SISEF)
• Subjects: Accuracy; Algorithms; Aridity; Bias; Biomass; Carbon dioxide; Carbon sequestration; Climate change; Forest biomass; Forests; Global positioning systems; GPS; Greenhouse effect; Greenhouse gases; High resolution; Image resolution; Industrial areas; Industrial pollution; Lasers; Megacities; Monoculture; plantation; Plantations; Pollutants; Pollution monitoring; Regression analysis; Regression models; Remote sensing; Satellite imagery; Satellites; Trees; Vegetation; vhr stereo images; Water pollution; Iran
• ISSN: 1971-7458; 1971-7458
• DOI: 10.3832/ifor3155-012

Plantations established in highly-pollutant industrial areas have a crucial role to absorb greenhouse gases, particularly CO2. A thorough monitoring of their aboveground biomass and carbon balance is essential to ensure their beneficial effects. This can be operationally supported by using a combination of field and multispectral stereo remote sensing data to provide surface height information with high resolution and wide coverage. We estimated the fresh and dry aboveground biomass and the carbon sequestration from pairs of Pléiades satellite imagery of 25-year-old monoculture plantations of Pinus eldarica Medw., Cupressus arizonica Greene, Morus alba L. and Robinia pseudoacacia L., around the Mobarakeh Steel Complex near the megacity Isfahan. This complex is the largest-scale of its kind in semi-arid Iran. Tree heights were derived from a Canopy height model (CHM) at plantation management unit level. Parsimonious regression models were developed, and the accuracy was assessed by the coefficient of determination, bias and root mean square errors (RMSEs) at plot level. This resulted in R2 of total biomass, dry biomass, carbon sequestration, tree height and tree count of 0.90, 0.90, 0.91, 0.89, and 0.88, respectively. Moreover, mixed bias (with lowest value of -0.12 m for tree height) and NRMSE% (with lowest value of 5.93 % for tree carbon sequestration) values were obtained. The results demonstrated that pairs of stereo imageries can be effectively used for predicting forest biomass and carbon sequestration across semi-arid plantations, hence enabling a continuous monitoring of vegetation established around pollutant industrial areas.