title: Choice of satellite imagery and attribution of changes to disturbance type strongly affects forest carbon balance estimates.
abstract: BACKGROUND
  Remote sensing products can provide regular and consistent observations of the Earth´s surface to monitor and understand the condition and change of forest ecosystems and to inform estimates of terrestrial carbon dynamics. Yet, challenges remain to select the appropriate satellite data source for ecosystem carbon monitoring. In this study we examine the impacts of three attributes of four remote sensing products derived from Landsat, Landsat-SPOT, and MODIS satellite imagery on estimates of greenhouse gas emissions and removals: (1) the spatial resolution (30 vs. 250 m), (2) the temporal resolution (annual vs. multi-year observations), and (3) the attribution of forest cover changes to disturbance types using supplementary data.
  
  
  RESULTS
  With a spatially-explicit version of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), we produced annual estimates of carbon fluxes from 2002 to 2010 over a 3.2 million ha forested region in the Yucatan Peninsula, Mexico. The cumulative carbon balance for the 9-year period differed by 30.7 million MgC (112.5 million Mg CO2e) among the four remote sensing products used. The cumulative difference between scenarios with and without attribution of disturbance types was over 5 million Mg C for a single Landsat scene.
  
  
  CONCLUSIONS
  Uncertainty arising from activity data (rates of land-cover changes) can be reduced by, in order of priority, increasing spatial resolution from 250 to 30 m, obtaining annual observations of forest disturbances, and by attributing land-cover changes by disturbance type. Even missing a single year in the land-cover observations can lead to substantial errors in ecosystems with rapid forest regrowth, such as the Yucatan Peninsula.
authors.affiliation: Faculty of Forestry, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4 Canada.
authors.forename: Vanessa S
authors.initials: VS
authors.lastname: Mascorro
authors.affiliation: Faculty of Forestry, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4 Canada.
authors.forename: Nicholas C
authors.initials: NC
authors.lastname: Coops
authors.affiliation: Canadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5 Canada.
authors.forename: Werner A
authors.initials: WA
authors.lastname: Kurz
authors.affiliation: Proyecto Mexico-Noruega, Comision Nacional Forestal, Coyoacán, D.F. Col. del Carmen Coyoacán, CP 04100 Mexico, Mexico.
authors.forename: Marcela
authors.initials: M
authors.lastname: Olguín
keywords: Activity data; CBM-CFS3; Carbon modeling; Forest disturbance; MRV; Mexico; REDD+