Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest

Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data

Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...

Comparative Evaluation of Image Fusion Methods for Hyperspectral and Panchromatic Data Fusion in Agricultural and Urban Areas

Nowadays remote sensing plays a key role in the field of earth science studies due to some of the advantages, including data collection at a very low cost and time on a very large scale. Meanwhile, using hyperspectral data is of great importance due to the high spectral resolution. Because of some limitations, such as hyperspectral imaging technology, it suffers from a reduction in the spatial ...

Urban tree species mapping using hyperspectral and lidar data fusion

Adaptive Fusion of Inertial Navigation System and Tracking Radar Data

Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the fil...

Fusion of hyperspectral and LIDAR remote sensing data for the classification of complex forest areas

In this paper we propose an analysis on the joint effect of hyperspectral and LIDARdata for the classification of complex forest areas. In greater detail, we describe an advanced system for LI-DAR and hyperspectral image analysis and investigate the effectiveness of Support Vector Ma-chine and Gaussian Maximum Likelihood (with Leave-One-Out-Covariance estimation) classifi-cation techniques in c...