A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern classification. Very recently, deep learning (DL) models ha...

Full description

Bibliographic Details
Main Authors: Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Remote Sensing
Subjects:
convolutional neural network
cross-validation
deep learning
land use classification
land cover classification
remote sensing
statistical analysis
Online Access:https://www.mdpi.com/2072-4292/11/3/274

Internet

https://www.mdpi.com/2072-4292/11/3/274

Similar Items