Temporal and Spatial Analyses of the Landscape Pattern of Wuhan City Based on Remote Sensing Images
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.2. Study Method
2.2.1. Texture-Based Back Propagation (BP) Neural Network Classification
- Forest landscape cluster, including landscape units such as woodland, garden, and grassland.
- Agricultural landscape cluster, including landscape units such as dry land and vegetable plots.
- Water landscape cluster, including landscape units such as the Yangtze River, lakes, and rivers.
- Urban landscape cluster: including landscape units, such as houses, roads, and rural settlements.
2.2.2. Analytical Method of Landscape Metrics
2.2.3. Urban Density Curve
3. Results
3.1. Analyses of the Temporal and Spatial Features of Landscape Metrics
3.2. Urban Land Density Distribution Pattern
3.3. Spatial and Temporal Evolution of the Development Direction Gradient
4. Discussion and Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Image Type | Acquisition Date (Month/Year) |
---|---|
Landsat-5 | 2/1989 |
4/1995 | |
4/2001 | |
4/2004 | |
5/2007 | |
5/2010 | |
Landsat-8 | 4/2013 |
5/2016 |
Year | 1989 | 1995 | 2001 | 2004 | 2007 | 2010 | 2013 | 2016 |
---|---|---|---|---|---|---|---|---|
Kappa coefficient | 0.8854 | 0.8063 | 0.7924 | 0.7928 | 0.8178 | 0.8056 | 0.8236 | 0.8389 |
Year | PD | SHDI |
---|---|---|
1989 | 3.6556 | 0.904 |
1995 | 3.4896 | 0.9064 |
2001 | 3.801 | 0.9257 |
2004 | 3.2578 | 0.956 |
2007 | 2.8566 | 0.971 |
2010 | 2.4352 | 1.004 |
2013 | 2.6703 | 0.9998 |
2016 | 2.2976 | 1.0166 |
Year | α | c | D | k |
---|---|---|---|---|
1989 | 2.479 | 0.036 | 15.554 | 0.53 |
1995 | 2.493 | 0.041 | 18.528 | 0.48 |
2001 | 2.486 | 0.033 | 19.733 | 0.50 |
2004 | 2.481 | 0.029 | 22.672 | 0.44 |
2007 | 2.496 | 0.022 | 25.468 | 0.41 |
2010 | 2.507 | 0.021 | 26.732 | 0.39 |
2013 | 2.510 | 0.019 | 28.354 | 0.36 |
2016 | 2.894 | 0.006 | 30.366 | 0.31 |
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Lv, J.; Ma, T.; Dong, Z.; Yao, Y.; Yuan, Z. Temporal and Spatial Analyses of the Landscape Pattern of Wuhan City Based on Remote Sensing Images. ISPRS Int. J. Geo-Inf. 2018, 7, 340. https://doi.org/10.3390/ijgi7090340
Lv J, Ma T, Dong Z, Yao Y, Yuan Z. Temporal and Spatial Analyses of the Landscape Pattern of Wuhan City Based on Remote Sensing Images. ISPRS International Journal of Geo-Information. 2018; 7(9):340. https://doi.org/10.3390/ijgi7090340
Chicago/Turabian StyleLv, Jianjun, Teng Ma, Zhiwen Dong, Yao Yao, and Zehao Yuan. 2018. "Temporal and Spatial Analyses of the Landscape Pattern of Wuhan City Based on Remote Sensing Images" ISPRS International Journal of Geo-Information 7, no. 9: 340. https://doi.org/10.3390/ijgi7090340