Paper Info
Title
Super-Resolution Land Cover Mapping with Spatial–Temporal Dependence by Integrating a Former Fine Resolution Map
Abstract
Super-resolution mapping (SRM) is a technique to predict spatial locations of land cover classes at the subpixel scale within coarse resolution remotely sensed image pixels. Due to the lack of information about the spatial pattern of land covers, uncertainty always exists in resultant fine-resolution land cover maps. In the present work, by integrating a former fine-resolution land cover map, the spatial dependence used in existing SRM algorithms is extended into a novel spatial-temporal dependence used in the SRM algorithm (SRM_STD). The spatial-temporal dependence consists of the spatial dependences of former fine-resolution land cover map, the spatial dependences of latter coarse resolution fraction images, and the corresponding dependence between former and latter land cover maps. By considering the spatial-temporal dependences of subpixels, SRM_STD can inherit valuable land cover information from the former fine-resolution land cover map, and reduce the uncertainty of SRM to a large extent. The performance of the proposed SRM_STD algorithm is assessed using a subset of the National Land Cover Database datasets and land cover maps produced by Landsat imagery in an area of rapid urban expansion. The results of two experiments show that the former dependence has little influence on the result, whereas the corresponding dependence plays a crucial role on the result. With a large weight of corresponding dependence, the proposed SRM_STD algorithm can produce fine-resolution land cover maps with higher accuracy than those of hard classification and the pixel swapping algorithm.
Year
DOI
Venue
2014
10.1109/JSTARS.2014.2320256
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  
Keywords
Field
DocType
geophysical image processing,image classification,image resolution,land cover,terrain mapping,landsat imagery,national land cover database datasets,srm_std algorithm,coarse resolution fraction images,coarse resolution remotely sensed image pixels,fine-resolution land cover maps,hard classification,land cover classes,land cover information,pixel swapping algorithm,rapid urban expansion,spatial locations,spatial pattern,spatial-temporal dependence,subpixel scale,super-resolution land cover mapping,super-resolution mapping algorithms,land cover change,spatial–temporal dependence,spatial??temporal dependence,super-resolution mapping (srm),transfer matrix,earth,spatial resolution,uncertainty,remote sensing,accuracy,simulated annealing
Common spatial pattern,Simulated annealing,Fine resolution,Spatial dependence,Remote sensing,Pixel,Subpixel rendering,Image resolution,Land cover,Mathematics
Journal
Volume
Issue
ISSN
7
5
1939-1404
Citations 
PageRank 
References 
3
0.40
11
Authors
4
Name
Order
Citations
PageRank
Feng Ling120921.29
Xiaodong Li217116.82
Yun Du315316.11
Fei Xiao4513.27