Abstract

A mineral resource zone, rich in resources and energy, is intensively developed and disturbed by human activities, which causes an obvious change of landscapes. Taking Wu’an of Hebei Province, China, as a case study, this paper extracts landscape information of mineral resource zones through overlapping mineral resources distribution map and landscape pattern map. And then, various landscape indices are selected for analyzing the effects of grain size (30, 60, 90, 120, 150, 180, 210, 240, 270 and 300 m) on landscape patterns. Due to different kinds of landscape information transmitted by indices, the changing trends vary with the increase of grain sizes. Accordingly the landscape indices are classified into three types of effects: disturbance, continuity and sustainability, and each type of effect has its own optimal range for grain sizes. Then the optimal range of grain size on landscape patterns in mineral resource zones is gained through a comparison of the effects in various grain sizes of landscape indices. The best first domain of scale covers 30–90 m, with a suitable grain size of 30–60 m before intensive mining and a suitable grain size of 60–90 m after intensive mining. Besides, the suitable grain sizes for reflecting disturbance, continuity and sustainability before intensive mining are 30–60, 30–60 and 30–90 m, respectively, however, the sizes are changed to 60–90, 60–90 and 30–90 m, respectively, after intensive mining. The results are helpful for rational land use and optimal landscape allocation.

Highlights

  • Population, resources and environments have significantly impacted the development of human society

  • Due to different kinds of landscape information transmitted by indices, the changing trends vary with the increase of grain sizes

  • The landscape indices are classified into three types of effects: disturbance, continuity and sustainability, and each type of effect has its own optimal range for grain sizes

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Summary

Introduction

As a measurement of spatial allocation and structure of land use patterns, landscape indices has become a useful tool in the study of land uses and landscapes. The calculation of landscape indices takes raster data as sources, and the size of grid cells may impact calculated results. In the areas composed of a great number of small and smart patches, which may be ‘‘swallowed up’’ by dominant landscapes. For this scientific problem, some scholars did some research and concluded that landscape indices change with different grain sizes (grid cells) (Turner et al 1989; Qi and Wu 1996). Inspired from theories and methods above, mining activities may be more sensitive to changes of

General situation of study area
Selection of data
Results
Disturbance
Continuity
Limitations and uncertainty
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