State of the art reviews of remote sensing change detection are becoming increasingly
complicated and disparate due to an ever growing list of techniques, algorithms and …

In their applications, both deep learning techniques and object-based image analysis (OBIA)
have shown better performance separately than conventional methods on change detection …

Exact land cover inventory data should be extracted for future landscape prediction and
seismic hazard assessment. This paper presents a comprehensive study towards the …

Multi-temporal remote sensing images are the primary sources for change detection.
However, it is difficult to obtain comparable multi-temporal images at the same season and …

Shifts from longer seasonal snowpacks to shorter, ephemeral snowpacks (snowpacks that
persist for< 60 days) due to climate change will alter the timing and rates of water …

Airborne Light Detection and Ranging (lidar) data provide useful measurements of forest
canopy structure but are often limited in spatial coverage. Satellite remote sensing data from …

The availability of a large amount of remote sensing data made Earth Observation
increasingly accessible and detailed. High temporal and spatial resolution sensors are …

In the context of a changing climate it is important to be able to monitor and map descriptors
of snow seasonality. Because of its relatively low elevation range, Australia's alpine …

Image matching is a vital process for many photogrammetric and remote sensing
applications such as image registration and aerial triangulation. In this paper, an accurate …

With the amount of multitemporal and multiresolution images growing exponentially, the
number of image segmentation applications is recently increasing and, simultaneously, new …