title: Robustness of model-based high-resolution prediction of forest biomass against different field plot designs.
abstract: BACKGROUND
  Participatory forest monitoring has been promoted as a means to engage local forest-dependent communities in concrete climate mitigation activities as it brings a sense of ownership to the communities and hence increases the likelihood of success of forest preservation measures. However, sceptics of this approach argue that local community forest members will not easily attain the level of technical proficiency that accurate monitoring needs. Thus it is interesting to establish if local communities can attain such a level of technical proficiency. This paper addresses this issue by assessing the robustness of biomass estimation models based on air-borne laser data using models calibrated with two different field sample designs namely, field data gathered by professional forester teams and field data collected by local communities trained by professional foresters in two study sites in Nepal. The aim is to find if the two field sample data sets can give similar results (LiDAR models) and whether the data can be combined and used together in estimating biomass.
  
  
  RESULTS
  Results show that even though the sampling designs and principles of both field campaigns were different, they produced equivalent regression models based on LiDAR data. This was successful in one of the sites (Gorkha). At the other site (Chitwan), however, major discrepancies remained in model-based estimates that used different field sample data sets. This discrepancy can be attributed to the complex terrain and dense forest in the site which makes it difficult to obtain an accurate digital elevation model (DTM) from LiDAR data, and neither set of data produced satisfactory results.
  
  
  CONCLUSIONS
  Field sample data produced by professional foresters and field sample data produced by professionally trained communities can be used together without affecting prediction performance provided that the correlation between LiDAR predictors and biomass estimates is good enough.
authors.affiliation: Department of Mathematics and Physics, Lappeenranta University of Technology, P.O.Box 20, 53851 Lappeenranta, Finland.
authors.forename: Virpi
authors.initials: V
authors.lastname: Junttila
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Basanta
authors.initials: B
authors.lastname: Gautam
authors.affiliation: International Centre for Integrated Mountain Development (ICIMOD), G.P.O. Box 3226, Khumaltar, Lalitpur, Kathmandu, Nepal.
authors.forename: Bhaskar Singh
authors.initials: BS
authors.lastname: Karky
authors.affiliation: Department of Mathematics and Physics, Lappeenranta University of Technology, P.O.Box 20, 53851 Lappeenranta, Finland ; Mzumbe University, P.O. Box 1, Mzumbe, Morogoro, Tanzania.
authors.forename: Almasi
authors.identifier: 0000-0002-1345-121X
authors.initials: A
authors.lastname: Maguya
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Katri
authors.initials: K
authors.lastname: Tegel
authors.affiliation: Department of Mathematics and Physics, Lappeenranta University of Technology, P.O.Box 20, 53851 Lappeenranta, Finland ; Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Tuomo
authors.initials: T
authors.lastname: Kauranne
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Katja
authors.initials: K
authors.lastname: Gunia
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Jarno
authors.initials: J
authors.lastname: Hämäläinen
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Petri
authors.initials: P
authors.lastname: Latva-Käyrä
authors.affiliation: Department of Mathematics and Physics, Lappeenranta University of Technology, P.O.Box 20, 53851 Lappeenranta, Finland.
authors.forename: Ekaterina
authors.initials: E
authors.lastname: Nikolaeva
authors.affiliation: Arbonaut Ltd, Kaislakatu 2, 80130 Joensuu, Finland.
authors.forename: Jussi
authors.initials: J
authors.lastname: Peuhkurinen
keywords: Above-ground biomass; LiDAR; Participatory forest monitoring; REDD+