Using and comparing two nonparametric methods (CART and RF) and SPOT-HRG satellite data to predictive tree diversity distribution
Kalbi S, Fallah A, Hojjati SM. 2014. Using and comparing two nonparametric methods (CART and RF) and SPOT-HRG satellite data to predictive tree diversity distribution. Nusantara Bioscience 6: 57-62. The prediction of spatial distributions of tree species by means of survey data has recently been use...
Main Authors: | SIAVASH KALBI, ASGHAR FALLAH, SEYED MOHAMMAD HOJJATI |
---|---|
Format: | Article |
Language: | English |
Published: |
MBI & UNS Solo
2014-05-01
|
Series: | Nusantara Bioscience |
Subjects: | |
Online Access: | http://biosains.mipa.uns.ac.id/N/N0601/N060110.pdf |
Similar Items
-
Evaluation of the capability of SPOT5-HRG data for predicting tree density in the northern Zagros forests
by: Mahtab Pir Bavaghar, et al.
Published: (2011-06-01) -
Determining Pleiades satellite data capability for tree diversity modeling
by: Akbari H, et al.
Published: (2017-02-01) -
Empirical Investigation of CART and Decision Tree Extraction from Neural Networks
by: Hari, Vijaya
Published: (2009) -
Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes
by: Rachmadania Irmanita, et al.
Published: (2021-02-01) -
Performance Evaluation of Deep Learning-Based Gated Recurrent Units (GRUs) and Tree-Based Models for Estimating ETo by Using Limited Meteorological Variables
by: Mohammad Taghi Sattari, et al.
Published: (2020-06-01)