Ripe with possibilities offered by deep-learning techniques and useful in applications
related to remote sensing, computer vision, and robotics, 3D point cloud semantic …

Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …

Nowadays, and more than a decade after the first steps towards autonomous driving, we
keep heading to achieve fully autonomous vehicles on our roads, with LiDAR sensors being …

The optical illusion affects depth‐sensing due to the limited and specific light‐field
information acquired by single‐lens imaging. The incomplete depth information or visual …

This article brings together the advances of multisource and multitemporal data fusion
approaches with respect to the various research communities and provides a thorough and …

As a revolutionary technology, terrestrial laser scanning (TLS) is attracting increasing
interest in the fields of architecture, engineering and construction (AEC), with outstanding …

Landslide, one of the most critical natural hazards, is caused due to specific compositional
slope movement. In the past decades, due to inflation of urbanized area and climate change …

Plant phenomics is a new avenue for linking plant genomics and environmental studies,
thereby improving plant breeding and management. Remote sensing techniques have …

Ecosystem structure, especially vertical vegetation structure, is one of the six essential
biodiversity variable classes and is an important aspect of habitat heterogeneity, affecting …

Ideal for both undergraduate and graduate students in the fields of geography, forestry,
ecology, geographic information science, remote sensing, and photogrammetric …