ARTÍCULO
TITULO

High-Resolution Remote Sensing Data Classification over Urban Areas Using Random Forest Ensemble and Fully Connected Conditional Random Field

Xiaofeng Sun    
Xiangguo Lin    
Shuhan Shen and Zhanyi Hu    

Resumen

No disponible

 Artículos similares

       
 
Yulu Hao, Mengdi Li, Jianyu Wang, Xiangyu Li and Junmin Chen    
The development and functional perfection of urban areas have led to increasingly severe fire risks in recent decades. Previous urban fire risk assessment methods relied on subjective judgment, rough data collection, simple linear statistical methods, et... ver más

 
Vahid Nasiri, Seyed Mohammad Moein Sadeghi, Fardin Moradi, Samaneh Afshari, Azade Deljouei, Verena C. Griess, Carmen Maftei and Stelian Alexandru Borz    
Forest canopy cover (FCC) is one of the most important forest inventory parameters and plays a critical role in evaluating forest functions. This study examines the potential of integrating Sentinel-1 (S-1) and Sentinel-2 (S-2) data to map FCC in the het... ver más

 
Zehra Cetin and Naci Yastikli    
Trees are the key components of urban vegetation in cities. The timely and accurate identification of existing urban tree species with their location is the most important task for improving air, water, and land quality; reducing carbon accumulation; mit... ver más

 
Grayson R. Morgan, Cuizhen Wang, Zhenlong Li, Steven R. Schill and Daniel R. Morgan    
Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments, in comparison with the popularly of applied machine le... ver más

 
Yinzhi Zhao, Jingui Zou, Jiming Guo, Gege Huang and Lixian Cai    
Ultra-wideband (UWB) technology is suitable for indoor positioning owing to its high resolution and penetration. However, the current UWB positioning methods not only fail to fully analyze errors, but do not have the ability to eliminate gross and large ... ver más