Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

Remote sensing imagery needs to be converted into tangible information which can be
utilised in conjunction with other data sets, often within widely used Geographic Information …

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 …

Transformer has been widely applied in image processing tasks as a substitute for
convolutional neural networks (CNNs) for feature extraction due to its superiority in global …

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 …

Land cover mapping via image classification is sometimes realized through object-based
image analysis. Objects are typically constructed by partitioning imagery into spatially …

Classification of very high resolution imagery (VHRI) is challenging due to the difficulty in
mining complex spatial and spectral patterns from rich image details. Various object-based …

The increasing volume of remote sensing data with improved spatial and temporal
resolutions generates unique opportunities for monitoring and mapping of crops. We …

Most object-based image analysis use parameters to control the size, shape, and
homogeneity of segments. Because each parameter may take a range of possible values …

In contrast to the many studies that use expert-based analysis of LiDAR derivatives for
landslide mapping in forested terrain, only few studies have attempted to develop (semi-) …