%0 Journal Article %T Mapeo del ¨ªndice de ¨¢rea foliar y cobertura arb¨®rea mendiante fotograf¨ªa hemisf¨¦rica y datos SPOT 5 HRG: regresi¨®n y k-nn %A Aguirre-Salado %A Carlos A. %A Valdez-Lazalde %A Jos¨¦ R. %A ¨¢ngeles-P¨¦rez %A Gregorio %A de los Santos-Posadas %A H¨¦ctor M. %A Aguirre-Salado %A Alejandro I. %J Agrociencia %D 2011 %I Colegio de Postgraduados %X leaf area index (lai) is a useful variable for characterizing the dynamics and productivity of forest ecosystems. canopy cover (cob), on the other hand, regulates the amount of penetrating light that controls certain light-dependent processes, and promotes the infiltration of rainfall as an environment hydrological service. this paper addresses the estimation of lai and cob (%) using multispectral data from spot 5 satellite in stands of different ages in a managed forest of pinus patula in zacualtip¨¢n, hidalgo, m¨¦xico. the lai was obtained by the allometric calibration of optical measurements taken with hemispherical photographs (pseudo r2=0.79). geospatial estimates were made using two methods: the multiple linear regression analysis and the nonparametric estimator of the nearest neighbor (k-nn). the analysis of the results showed a high ratio between lai calibrated (r2=0.93, rmse=0.50; coefficient of determination and root mean squared error) and the cob (r2=0.96, rmse=4.57 %), with the bands and spectral indices constructed from them. the average estimates for forested stands were: lai = 6.5; cob=80 %. the estimates per hectare of both methods (regression and k-nn) were comparable between them; however, k-nn required a considerable computational effort in calculating the spectral distances between the target pixel and the pixels in the sample. %K pinus patula %K applied geomatics %K satellite image %K vegetation index %K forest inventory %K hidalgo %K m¨¦xico. %U http://www.scielo.org.mx/scielo.php?script=sci_abstract&pid=S1405-31952011000100010&lng=en&nrm=iso&tlng=en