Abstract
Remotely sensed imagery is an attractive source of information for mapping and monitoring land cover. Fine spatial resolution imagery is typically acquired infrequently, but fine temporal resolution systems commonly provide coarse spatial resolution imagery. Sub-pixel land cover change mapping is a method that aims to use the advantages of these multiple spatial and temporal resolution sensing systems. This method produces fine spatial and temporal resolution land cover maps, by updating fine spatial resolution land cover maps using coarse spatial resolution remote sensing imagery. A critical issue for sub-pixel land cover change mapping is downscaling coarse spatial resolution fraction maps estimated by soft classification to a fine spatial resolution land cover map. The relationship between a historic fine spatial resolution map and a contemporary fine spatial resolution map to be estimated at a more recent date plays an important role in the downscaling procedure. A change strategy based on the assumption that the change for each land cover class in a coarse spatial resolution pixel is unidirectional was shown to be a promising means to describe this relationship. This paper aims to assess this change strategy by analyzing the factors that affect the accuracy of the change strategy, using six subsets of the National Land Cover Database (NLCD) of USA. The results show that the spatial resolution of coarse pixels, the time interval of the previous fine resolution land cover map and the current coarse spatial resolution images, and the thematic resolution of the used land cover class scheme have considerable influence on the accuracy of the change strategy. The accuracy of the change strategy decreases with the coarsening of spatial resolution, an increase of time interval, and an increase of thematic resolution. The results also indicate that, when the historic land cover map has a 30 m resolution, like the NLCD, the average accuracy of the change strategy is still as high as 92% when the coarse spatial resolution data used had a resolution of ~1000 m, confirming the effectiveness of the change strategy used in sub-pixel land cover change mapping for use with popular remote sensing systems.
Highlights
Land cover change has been considered as one of the most important drivers of the global environmental change [1,2,3]
The unidirectional change strategy is a popular method to describe the relationship between the historic fine resolution map and current coarse resolution fraction images, and to construct the temporal model in sub-pixel land cover change mapping
The factors that affect the accuracy of the unidirectional change strategy were analyzed, in order to provide guidance for the practical application of the approach to sub-pixel land cover change mapping from multi-scale remote sensing images
Summary
Land cover change has been considered as one of the most important drivers of the global environmental change [1,2,3]. Remote sensing provides the ability to acquire images of the Earth’s surface at a range of scales, notably in the spatial and temporal domains. Systems such as the Moderate Resolution Imaging. By using a variety of remote sensing systems it should be possible to use multi-scale data to monitor land cover at fine spatial and temporal scales [7]. Once a baseline fine spatial resolution land cover map has been generated from fine spatial resolution images, it should be possible to update it in a timely manner through the use of coarse spatial resolution images, if the limitation of their coarse spatial resolution can be reduced
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