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Journal of Arid Land

, Volume 6, Issue 1, pp 80–96 | Cite as

Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

  • Carlos A. Aguirre-SaladoEmail author
  • Eduardo J. Treviño-Garza
  • Oscar A. Aguirre-Calderón
  • Javier Jiménez-Pérez
  • Marco A. González-Tagle
  • José R. Valdéz-Lazalde
  • Guillermo Sánchez-Díaz
  • Reija Haapanen
  • Alejandro I. Aguirre-Salado
  • Liliana Miranda-Aragón
Article

Abstract

As climate change negotiations progress, monitoring biomass and carbon stocks is becoming an important part of the current forest research. Therefore, national governments are interested in developing forest-monitoring strategies using geospatial technology. Among statistical methods for mapping biomass, there is a nonparametric approach called k-nearest neighbor (kNN). We compared four variations of distance metrics of the kNN for the spatially-explicit estimation of aboveground biomass in a portion of the Mexican north border of the intertropical zone. Satellite derived, climatic, and topographic predictor variables were combined with the Mexican National Forest Inventory (NFI) data to accomplish the purpose. Performance of distance metrics applied into the kNN algorithm was evaluated using a cross validation leave-one-out technique. The results indicate that the Most Similar Neighbor (MSN) approach maximizes the correlation between predictor and response variables (r=0.9). Our results are in agreement with those reported in the literature. These findings confirm the predictive potential of the MSN approach for mapping forest variables at pixel level under the policy of Reducing Emission from Deforestation and Forest Degradation (REDD+).

Keywords

k-nearest neighbor Mahalanobis most similar neighbor MODIS BRDF-adjusted reflectance forest inventory the policy of Reducing Emission from Deforestation and Forest Degradation 

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Copyright information

© Science Press, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Carlos A. Aguirre-Salado
    • 1
    • 2
    Email author
  • Eduardo J. Treviño-Garza
    • 1
  • Oscar A. Aguirre-Calderón
    • 1
  • Javier Jiménez-Pérez
    • 1
  • Marco A. González-Tagle
    • 1
  • José R. Valdéz-Lazalde
    • 3
  • Guillermo Sánchez-Díaz
    • 2
  • Reija Haapanen
    • 4
  • Alejandro I. Aguirre-Salado
    • 3
  • Liliana Miranda-Aragón
    • 5
  1. 1.Faculty of Forest SciencesAutonomous University of Nuevo LeonLinaresMexico
  2. 2.Faculty of EngineeringAutonomous University of San Luis PotosiSan Luis PotosíMexico
  3. 3.Forestry ProgramPostgraduate CollegeMontecilloMexico
  4. 4.Haapanen Forest ConsultingKärjenkoskentieFinland
  5. 5.Faculty of Agronomy and VeterinaryAutonomous University of San Luis PotosíSan Luis PotosíMexico

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