The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in
almost every application (eg, agriculture, forestry, and mining) that needs observed …

Object-based image classification for land-cover map** purposes using remote-sensing
imagery has attracted significant attention in recent years. Numerous studies conducted over …

Object detection in optical remote sensing images, being a fundamental but challenging
problem in the field of aerial and satellite image analysis, plays an important role for a wide …

The appetite for up-to-date information about earth's surface is ever increasing, as such
information provides a base for a large number of applications, including local, regional and …

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

We introduce a new automated approach to parameterising multi-scale image segmentation
of multiple layers, and we implemented it as a generic tool for the eCognition® software …

Pixel-based and object-based image analysis approaches for classifying broad land cover
classes over agricultural landscapes are compared using three supervised machine …

The spatial resolution of imaging sensors has increased dramatically in recent years, and so
too have the challenges associated with extracting meaningful information from their data …

Landslide inventories are in high demand for risk assessment of this natural hazard,
particularly in tropical mountainous regions. This research designed residual networks for …

In this study, a multi-scale approach is used to improve the segmentation of a high spatial
resolution (30 cm) color infrared image of a residential area. First, a series of 25 image …