Influence of Accessibility on Land Use and Landscape Pattern Based on Mapping Knowledge Domains: Review and Implications
Table 2
Statistics on high-frequency keywords.
Keywords
Frequency
Centralitya
Year
land use change
61
0.18
2003
pattern
52
0.17
2000
urbanization
47
0.12
2004
driving force
41
0.08
2009
china
40
0.12
2008
land use
37
0.1
2006
city
37
0.06
2003
growth
35
0.16
2006
dynamics
34
0.06
2002
gi
31
0.16
2004
impact
29
0.05
2009
model
29
0.12
2004
fragmentation
26
0.1
2002
expansion
24
0.05
2013
region
24
0.04
2007
landscape
23
0.03
2005
cover change
23
0.04
2004
accessibility
22
0.03
2005
road
21
0.07
2007
urban growth
21
0.06
2013
logistic regression
20
0.02
2007
deforestation
20
0.17
2000
landscape pattern
18
0.07
2004
area
16
0.05
2009
land cover change
13
0.02
2007
cellular automata
12
0.03
2016
urban expansion
12
0.04
2016
transportation
12
0.04
2013
conservation
12
0.11
2007
landscape metrics
12
0.01
2006
united states
11
0.06
2005
landscape change
11
0.01
2005
remote sensing
11
0
2013
biodiversity
10
0.02
2014
density
9
0.06
2000
scale
9
0.02
2002
determinant
9
0.07
2016
ecology
8
0.01
2014
metropolitan area
8
0
2015
management
8
0.04
2013
aBetweenness centrality of a node, which captures the number of times the node is included in the shortest paths of any pair of nodes in the keyword network. The larger the value of betweenness centrality, the higher the influence of one specific keyword [49].
