Abstract

Land cover maps are fundamental materials for resource management and change detection. Remote sensing technology is crucial for fast mapping with low cost. However, besides the inherent classification errors in the land cover products, numerous illogical transitions exist between the neighboring time points. In this study, we introduce a series of logical codes for all the land cover types according to the ecological rules in the study area. The codes represent the transformational logicality of species between different seasons. The classification performance and the codes for all the seasons are imposed on the initial land cover maps which have been produced independently by the conventional hierarchical strategy. We exploit the proposed modified hierarchical mapping strategy to map the land cover of Poyang Lake Basin area, Middle China. The illogical transitions between neighboring seasons and the accuracies based on the labeled samples are calculated for both the initial and modified strategies. The number of illogical pixels have been reduced by 13%–35% for different seasons and the average accuracy has been improved by 9.7% for the specific land cover maps. The accuracy of land cover changes has also presented great improvement of the proposed strategy. The experimental results have suggested the scheme is effective.

Highlights

  • The Global Land Cover (GLC) is fundamental for land resource management, environmental protection, and sustainable development [1]

  • We have introduced a seasonal land cover mapping strategy taking into account temporal transitions

  • The proposed strategy aims to reduce the unphysical disagreements between neighboring seasons by modifying the initial results, so as to produce rational and accurate land cover maps

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Summary

Introduction

The Global Land Cover (GLC) is fundamental for land resource management, environmental protection, and sustainable development [1]. The development of satellite technology makes it possible to acquire sufficient remote sensing data with finer spatial resolution. The multi-temporal land cover maps make especially great contributions in acquiring the long-term land cover information [22,23]. The post-classification comparison effectively examines the changes between the land cover maps with different time points, which makes it possible to quickly assess the spatial and temporal dynamics of the study areas [24,25]. It is quite convenient to acquire highly temporal remote sensing images for a certain area, which makes it feasible to produce regional land cover maps quarterly

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