15 datasets found

The CDD dataset contains 11 pairs of bi-temporal images obtained from Google Earth in different seasons with a spatial resolution ranging from 3 to 100 cm per pixel.

Change detection is a crucial but extremely challenging task in remote sensing image analysis, and much progress has been made with the rapid development of deep learning....

Change detection in high-resolution remote sensing images using a bitemporal image transformer (BIT)

The Vaihingen dataset consists of 1440 scenes with a size of 250×250 pixels. Each scene is a colour-infrared (CIR) true orthophoto and a height grid (digital surface model; DSM)...

The DSIFN-CD dataset is a collection of high-resolution images with seasonal changes in different cities.

The proposed SMDNet model is used for change detection in high-resolution remote sensing images.

The CDD dataset is a collection of remote sensing images with seasonal changes and different lighting conditions.

The Sardinia dataset consists of bi-temporal SAR images, acquired by the RADARSAT at the area of Sardinia in September 1995 and July 1996, respectively.

The Yellow River dataset consists of bi-temporal SAR images, acquired by Radarsat-2 at the region of Yellow River Estuary in China in June 2008 and June 2009, respectively.

The Bern dataset consists of bi-temporal SAR images, acquired by the European Remote Sensing 2 satellite SAR sensor at the region of Bern, Switzerland, in April and May 1999,...

The Ottawa dataset consists of bi-temporal SAR images, acquired by the RADARSAT at the area of Ottawa in May 1997 and August 1997, respectively.

Building change detection using multi-temporal airborne LiDAR data

DE-CD(3.3×) is a dataset for cross-resolution change detection.

SV-CD(8×) is a dataset for cross-resolution change detection.

LEVIR-CD(4×) is a dataset for cross-resolution change detection.