Effects of grain size on landscape patterns in mineral resource zones: a case study of Wu’an, China

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.

Landscape Pattern Evolution in a Mining City: An Urban Life Cycle Perspective

“…This study selects 15 indicators that can reflect the changes of landscape pattern in mining cities, including terrain area (TA), patch number (NP), patch density (PD), largest patch index (LPI), mean patch area (AREA_MN), fractal patch (PAFRAC), contagion index (CONTAG), interspersion and juxtaposition index (IJI), cohesion index (COHESION), division index (DIVISION), split index (SPLIT), patch richness (PR), Shannon's diversity index (SHDI), Shannon's evenness index (SHEI), and aggregation index (AI). In determining these indexes, the choice of grain size has a decisive effect [46][47][48]. We determined the optimum analytical grain size based on an analytical approach to the way that grain size affects landscape pattern indexes and by using the information loss method.…”