This article presents the use of new remote sensing data acquired from airborne full-waveform lidar systems. They are active sensors which record altimeter profiles. This paper introduces a set of methodologies for processing these data. These techniques are then applied to a particular landscape, the badlands, but the methodologies are designed to be applied to any other landscape. Indeed, the...

In this paper, a thorough analysis on automatic DSM generation from imagery, acquired by the airborne pushbroom sensor ADS40, is presented. At first, the algorithmic approach is described, focusing on its essential key components that exploit the special geometric and radiometric characteristics of the sensor and thus facilitate automatic extraction of 3D information. The novel algorithm makes ...

Landcover classification is an important application in remote sensing, but it always a challenge to distinguish different features with similar characteristics or large-scale differences. Some deep learning networks, such as UperNet, PSPNet, and DANet, use pyramid pooling attention mechanisms improve their abilities multi-scale extraction. However, due the neglect of low-level contained underl...

Manifold learning methods have widely used in ordinary image processing domain. It has many advantages, depending on the different formulation of the manifold. Hyperspectral images are kind of images acquired by air-borne or space-born platforms. This paper introduces a novel manifold learning based dimension reduction (DR) method for hyperspectral classification. The purpose is to fully utiliz...