Landscape pattern and driving forces in the upper reaches of Minjiang River, China

Based on field investigation and social-economical data, in combination with the 1992 and 2007 Landsat TM remote sensing images of Coastal Urban Belt in Liaoning, this paper analyzed the dynamic changes of landscape pattern at both class and landscape levels and their driving forces in the study area. From 1992 to 2007, the landscape pattern in the study area experienced a significant change. At class level, the area of farmland, forestland, wetland, grassland, and abandoned land decreased, while the area of residential area, salt pan, and water area increased. At landscape level, both total number of patches and patch density increased significantly, while the largest patch index decreased, and the complication of landscape shape intensified.

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Landscape pattern and eco-hydrological characteristics at the upstream of Minjiang River, China

Frontiers of Biology in China ◽

10.1007/s11515-006-0062-3 ◽

2006 ◽

Vol 1 (4) ◽

pp. 455-462 ◽

Cited By ~ 4

Author(s):

Chongwei Li ◽

Jianping Ge ◽

Shirong Liu ◽

Pengsen Sun

Keyword(s):

Landscape Pattern ◽

Hydrological Characteristics ◽

Minjiang River ◽

Upstream Of Minjiang River

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The relation between soil erosion dynamics and landscape pattern variation in the Minjiang River headwaters in Sichuan, China

Water-Rock Interaction ◽

10.1201/noe0415451369.ch90 ◽

2007 ◽

Author(s):

C Li ◽

H Jiang ◽

O Luukkanen ◽

Y Liu

Keyword(s):

Soil Erosion ◽

Landscape Pattern ◽

Minjiang River

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The Driving Forces of Landscape Pattern in Coastal Urban Belt in Liaoning

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.610-613.3771 ◽

2012 ◽

Vol 610-613 ◽

pp. 3771-3775

Author(s):

Hai De Hu

Keyword(s):

Remote Sensing ◽

Economic Development ◽

Population Growth ◽

Landscape Pattern ◽

Driving Forces ◽

Landscape Fragmentation ◽

Field Investigation ◽

Rapid Population Growth ◽

Remote Sensing Images ◽

Growth Economic

Based on field investigation and social-economical data, in combination with the 1992 and 2007 Landsat TM remote sensing images of Coastal Urban Belt in Liaoning, this paper analyzed the driving forces of landscape pattern in the study area. From 1992 to 2007, the landscape pattern in the study area experienced a significant change. The rapid population growth, economic development and infrastructure construction had exerted strong influences on these changes of landscape pattern, and thus leading to a deeper level of landscape fragmentation

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Landscape Pattern Change of Impervious Surfaces and Its Driving Forces in Shanghai during 1965–2010

Water ◽

10.3390/w13141956 ◽

2021 ◽

Vol 13 (14) ◽

pp. 1956

Author(s):

Yang Yao ◽

Sen Zhang ◽

Yuqing Shi ◽

Mengqi Xu ◽

Jiaquan Zhang ◽

...

Keyword(s):

Water Quality ◽

Landscape Pattern ◽

Driving Forces ◽

Surface Water Quality ◽

Water Area ◽

Impervious Surfaces ◽

Rapid Urbanization ◽

The Past ◽

Pattern Change ◽

Quality Variation

Rapid urbanization influences the landscape pattern of impervious surfaces, and potentially affects surface water quality. Using ArcGIS and Fragstats, this study analyzed the temporal change of the landscape pattern of impervious surfaces in Shanghai over the past 45 years, and its driving forces and impact on water quality were also analyzed. The results show that both low and high impervious surfaces showed different degrees of expansion, and as a result, the pervious surfaces and water area reduced by 40.1% and 13.8%, respectively. It proves that the fragmentation and diversity of impervious surfaces in Shanghai notably increased in the past decades, and especially the low and high impervious surfaces show substantial changes. The primary driving forces of the landscape pattern change are population density, unit area Gross Domestic Product (GDP), and the percentage of primary industry. The result of Redundancy analysis (RDA) is that the explanatory ability of landscape pattern to water quality variations decreased from 68.7% to 46.4% in the period 2000–2010. It should be stressed that the contribution of the configuration of impervious surfaces to water quality variation is less than that of the percentage of impervious surfaces.

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