Simón Sandoval Rocha

Áreas de Investigación

• Biometría Forestal

Líneas de Investigación

• Crecimiento y rendimiento de bosques
• Ciencia de datos
• Inventarios forestales LiDAR
• Biomasa y bioenergía

Proyectos de Investigación Destacados

Últimas Publicaciones

Sandoval S., Montes C., Mena-Quijada P., Acuña E., Olmedo F. Modeling above ground biomass in Pinus radiata trees with explicit multivariate uncertainty. Forestry (In press).

Sandoval S., Acuña E. 2021. Stem taper estimation using Artificial Neural Networks for Nothofagus tress in natural forests. Anaals of Forest Science (In press).

Sandoval S., Montes C., Wang M., Bullock B. 2021. Modeling basal area yield using simultaneous equations system incorporating uncertainty estimators. Forest Science (In press).

Sandoval S., Bustamante-Ortega R. 2020. Estimation of Uncertainty in Airborne LiDAR Inventories Using Approaches Based on Bootstrapping-Pairs Methods. Forests. 11:1305. https://doi.org/10.3390/f11121305.

Acevedo M., Rubilar R., Kasten R., Ovalle J., Sandoval S., Chassin-Trubert R. 2020. Nitrogen loading of Eucalyptus globulus seedlings: nutritional dynamics and influence on morphology and root growth potential. New Forest. https://doi.org/10.1007/s11056-020-09778-2.

Acuña E., Pinto A., Cancino J., Sandoval S. 2020. Fair value of standing timber in the context of IAS 41 implementation: a case study with Pinus radiata. Ciencia Florestal 30(4): 1217-1229. JCR: Q3. DOI: https://doi.org/10.5902/1980509824460.

Acuña E., Cancino J., Rubilar R., Sandoval S. 2017. Aboveground biomass growth and yield of first rotation cutting cycle of acacia and eucalyptus short rotation dendroenergy crops. Revista Árvore 41(6): 1-10. http://dx .doi.org/10.1590/1806-90882017000600008.

Barría C., Sandoval S., Rojas G. 2017. Using resistography method for prediction of wood basic density in standing trees of Pinus radiata. Maderas. Ciencia y tecnología 19(3): 349 – 362. DOI: 10.4067/S0718-221X2017005000030.