URBAN OBJECT EXTRACTION FROM DIGITAL SURFACE MODEL AND DIGITAL AERIAL IMAGES

Urban Object Extraction from Digital Surface Model and Digital Aerial Images

The paper describes two different methods for extraction of two types of urban objects from lidar digital surface model (DSM) and digital aerial images. Within the preprocessing digital terrain model (DTM) and orthoimages for three test areas were generated from aerial images using automatic photogrammetric methods. Automatic building extraction was done using DSM and multispectral orthoimages....

Automatic Urban Road Extraction from Digital Surface Model and Aerial Imagery

Automatic linear feature extraction has a long history but still it is one of the challenging topics in photogrammetry and computer vision. In this paper, we describe an automatic road extraction process suitable for urban areas with high buildings. The proposed road extraction process has roughly three steps. The first step is generating an obstacle map to get road primitives from the digital ...

Road Extraction from Digital Aerial Imagery

Building Detection Using Aerial Images and Digital Surface Models

In this paper a method for building detection in aerial images based on variational inference of logistic regression is proposed. It consists of three steps. In order to characterize the appearances of buildings in aerial images, an effective bag-of-Words (BoW) method is applied for feature extraction in the first step. In the second step, a classifier of logistic regression is learned using th...

Object-Based Mangrove Species Classification Using Unmanned Aerial Vehicle Hyperspectral Images and Digital Surface Models

Mangroves are one of the most important coastal wetland ecosystems, and the compositions and distributions of mangrove species are essential for conservation and restoration efforts. Many studies have explored this topic using remote sensing images that were obtained by satellite-borne and airborne sensors, which are known to be efficient for monitoring the mangrove ecosystem. With improvements...