F. Chianucci, N. Puletti, M. Grotti, C. Bisaglia, F. Giannetti, E. Romano, M. Brambilla, W. Mattioli, Giovanna Cabassi, S. Bajocco, Linyuan Li, G. Chirici, P. Corona, C. Tattoni
{"title":"Influence of image pixel resolution on canopy cover estimation in poplar plantations from field, aerial and satellite optical imagery","authors":"F. Chianucci, N. Puletti, M. Grotti, C. Bisaglia, F. Giannetti, E. Romano, M. Brambilla, W. Mattioli, Giovanna Cabassi, S. Bajocco, Linyuan Li, G. Chirici, P. Corona, C. Tattoni","doi":"10.12899/ASR-2074","DOIUrl":null,"url":null,"abstract":"Accurate estimates of canopy cover (CC) are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used to estimate CC from the complement of gap fraction measurements obtained with restricted-view sensors. In this short note we evaluated the influence of the image pixel resolution (ground sampling distance; GSD) on CC estimation in poplar plantations obtained from field (cover photography; GSD < 1 cm), unmanned aerial (UAV; GSD <10 cm) and satellite (Sentinel-2; GSD = 10 m) imagery. The trial was conducted in poplar tree plantations in Northern Italy, with varying age and canopy cover. Results indicated that the coarser resolution available from satellite data is suitable to obtain estimates of canopy cover, as compared with field measurements obtained from cover photography; therefore, S2 isrecommended for larger scale monitoring and routine assessment of canopy cover in poplar plantations. The higher resolution of UAV compared with Sentinel-2 allows finer assessment of canopy structure, which could also be used for calibrating metrics obtained from coarser-scale remote sensing products, avoiding the need of ground measurements.","PeriodicalId":37733,"journal":{"name":"Annals of Silvicultural Research","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Silvicultural Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12899/ASR-2074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Accurate estimates of canopy cover (CC) are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used to estimate CC from the complement of gap fraction measurements obtained with restricted-view sensors. In this short note we evaluated the influence of the image pixel resolution (ground sampling distance; GSD) on CC estimation in poplar plantations obtained from field (cover photography; GSD < 1 cm), unmanned aerial (UAV; GSD <10 cm) and satellite (Sentinel-2; GSD = 10 m) imagery. The trial was conducted in poplar tree plantations in Northern Italy, with varying age and canopy cover. Results indicated that the coarser resolution available from satellite data is suitable to obtain estimates of canopy cover, as compared with field measurements obtained from cover photography; therefore, S2 isrecommended for larger scale monitoring and routine assessment of canopy cover in poplar plantations. The higher resolution of UAV compared with Sentinel-2 allows finer assessment of canopy structure, which could also be used for calibrating metrics obtained from coarser-scale remote sensing products, avoiding the need of ground measurements.