Spatial Association Rules and Thermal Environment Differentiation Evaluation of Local Climate Zone and Urban Functional Zone
Abstract
:1. Introduction
2. Study Area and Data Collection
2.1. Study Area
2.2. Data Sources
3. Method
3.1. Local Climate Zones (LCZs) Classification
3.2. LCZ and UFZ Association Rule Mining
- (1)
- Overlay analysis was conducted by calculating the spatial overlap of the two systems. The urban function classification results of different systems were spatially superimposed. As shown in Figure 4, a local climate zone (LCZ1) intersects several functional zones (UFZa and UFZb). Their spatial overlap area can be expressed as LCZ1 ∩ UFZa and LCZ1 ∩ UFZb. The spatial correlation degree (SCD) of UFZa in the functional area to LCZ1 was calculated as follows: SCD (LCZ1|UFZa) = (LCZ1 ∩ UFZa)/UFZa (i.e., 100% in Figure 4). The SCD of LCZ1 to UFZa was calculated as follows: SCD (UFZa|LCZ1) = LCZ1 ∩ UFZa/LCZ1 (i.e., 40% in Figure 4).
- (2)
- Ranking the correlation degrees: a correlation degree of 70–100% is high; 30–70% is medium; and less than 30% is low.
- (3)
- According to the above two steps, we obtained the results regarding the degree of correlation of each block with other types of blocks. We filtered out all blocks with high correlation degrees, and used Apriori algorithm to mine the association rules of UFZ and LCZ.
3.3. Land Surface Temperature Retrieval
3.4. Geographic Detector Analysis
4. Results and Discussion
4.1. LCZ Classification Results
4.2. Surface Temperature Distribution
4.3. Association Rule Mining Results
4.4. Analysis of Thermal Environment Differentiation between UFZ and LCZ
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data Type | Detailed Information | |||
---|---|---|---|---|
Raster data | Data name | Region | Time | Row and path number |
Landsat8 image data | Beijing | 17 August 2019 | 123 32 | |
Harbin | 7 July 2017 | 118 28 | ||
Wuhan | 23 July 2016 | 123 39 | ||
Guangzhou | 20 August 2017 | 122 44 | ||
Vector data | Data name | Data source | ||
UFZ data | http://data.starcloud.pcl.ac.cn/ (accessed on 18 August 2023, Tsinghua University Public Data Set) | |||
Built-up area data | http://data.starcloud.pcl.ac.cn/ (accessed on 18 August 2023) | |||
Building base data | http://data.tpdc.ac.cn (accessed on 18 August 2023) |
UFZ | Guangzhou | Wuhan | Harbin | Beijing | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
LCZ with High Correlation | Support | Confidence | LCZ with High Correlation | Support | Confidence | LCZ with High Correlation | Support | Confidence | LCZ with High Correlation | Support | Confidence | |
101 Residential zone | LCZ2 Compact mid-rise | 0.172 | 0.220 | LCZ5 Open mid-rise | 0.228 | 0.417 | LCZ2Compact mid-rise | 0.124 | 0.297 | |||
201 Commercial office zone | LCZ1 Compact high-rise | 0.105 | 0.299 | LCZ2 Compact mid-rise | 0.173 | 0.293 | LCZ2 Compact mid-rise | 0.314 | 0.647 | |||
LCZ2 Compact mid-rise | 0.173 | 0.210 | LCZ5 Open middle-rise | 0.230 | 0.198 | |||||||
202 Business service zone | LCZ2 Compact mid-rise | 0.174 | 0.543 | LCZ3Compact low-rise | 0.214 | 0.225 | LCZ1 Compact high-rise | 0.105 | 0.325 | LCZ1 Compact high-rise | 0.144 | 0.671 |
LCZ8 Large low-rise | 0.146 | 0.153 | LCZ2 Compact mid-rise | 0.362 | 0.718 | |||||||
301 Industrial zone | LCZ8 Large low-rise | 0.148 | 0.224 | LCZ7Lightweight low-rise | 0.108 | 0.269 | LCZ3 Compact low-rise | 0.101 | 0.256 | LCZ3 Compact low-rise | 0.129 | 0.152 |
LCZ4 Open high-rise | 0.151 | 0.322 | LCZ8 Large low-rise | 0.169 | 0.333 | |||||||
402 Transport station | LCZ8 Large low-rise | 0.165 | 0.273 | |||||||||
LCZ9 sparsely built | 0.110 | 0.182 | ||||||||||
403 Airport facilities | LCZ9 Sparsely built | 0.132 | 0.500 | |||||||||
501 Administrative zone | LCZ4 Open high-rise | 0.120 | 0.420 | LCZ5 Open mid-rise | 0.166 | 0.429 | LCZ5 Open mid-rise | 0.317 | 0.750 | LCZ1 Compact high-rise | 0.428 | 0.913 |
502 Education zone | LCZ4 Open high-rise | 0.154 | 0.576 | LCZ2 Compact mid-rise | 0.101 | 0.186 | LCZ2 Compact mid-rise | 0.106 | 0.462 | LCZ1 Compact high-rise | 0.345 | 0.724 |
LCZ5 Open middle-rise | 0.253 | 0.464 | LCZ9 Sparsely built | 0.132 | 0.429 | LCZ4 Open high-rise | 0.127 | 0.157 | ||||
503 Medical zone | LCZ2 Compact middle-rise | 0.100 | 0.340 | LCZ2 Compact mid-rise | 0.115 | 0.308 | LCZ2 Compact mid-rise | 0.489 | 0.838 | LCZ1 Compact high-rise | 0.462 | 0.920 |
LCZ2 Compact mid-rise | 0.140 | 0.163 | ||||||||||
504 Sports and cultural | LCZ6 Open low-rise | 0.255 | 0.163 | LCZ9 Sparsely built | 0.111 | 0.364 | ||||||
505 Parks and green | LCZT Trees and plants | 0.364 | 0.509 | LCZT Trees and plants | 0.151 | 0.329 | LCZ6 Open low-rise | 0.150 | 0.491 | LCZW Water | 0.241 | 0.354 |
LCZT Trees and plants | 0.445 | 0.650 | ||||||||||
LCZW Water | 0.352 | 0.455 |
LCZ | Guangzhou | Wuhan | Harbin | Beijing | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
UFZ with High Correlation | Support | Confidence | UFZ with High Correlation | Support | Confidence | UFZ with High Correlation | Support | Confidence | UFZ with High Correlation | Support | Confidence | |
LCZ1 Compact high-rise | 502 Education zones | 0.206 | 0.395 | 101 Residential zones | 0.105 | 0.519 | ||||||
LCZ2 Compact mid-rise | 503 Medical zones | 0.102 | 0.475 | 101 Residential zones | 0.151 | 0.557 | 502 Education zones | 0.212 | 0.356 | 101 Residential zones | 0.126 | 0.696 |
LCZ3 Compact low-rise | 301 Industrial zones | 0.178 | 0.402 | 202 Business service zones | 0.237 | 0.587 | ||||||
LCZ4 Open high-rise | 201 Commercial office zones | 0.189 | 0.320 | |||||||||
LCZ5 Open mid-rise | 101 Residential zones | 0.108 | 0.281 | 504 Sports and cultural | 0.110 | 0.433 | 101 Residential zones | 0.187 | 0.415 | 502 Education zones | 0.229 | 0.368 |
LCZ6 Open low-rise | 301 Industrial zones | 0.270 | 0.466 | 101 Residential zones | 0.241 | 0.530 | 101 Residential zones | 0.127 | 0.274 | 403 Airport facilities | 0.257 | 0.643 |
403 Airport facilities | 0.135 | 0.233 | 504 Sports and cultural areas | 0.120 | 0.553 | |||||||
LCZ7 Lightweight low-rise | 301 Industrial zones | 0.237 | 0.489 | |||||||||
LCZ8 Large low-rise | 504 Sports and cultural | 0.349 | 0.596 | 403 Airport facilities | 0.144 | 0.780 | ||||||
LCZ9 Sparsely built | 403 Airport facilities | 0.176 | 0.651 | 403 Airport facilities | 0.621 | 0.840 | ||||||
LCZ10 Heavy industry | 301 Industrial zones | 0.403 | 0.760 | 301 Industrial zones | 0.208 | 0.632 | ||||||
LCZT Trees and plants | 505 Parks and green areas | 0.105 | 0.193 | 101 Residential zones | 0.116 | 0.277 | 101 Residential zones | 0.111 | 0.333 | |||
505 Parks and green areas | 0.455 | 0.520 | 505 Parks and green areas | 0.306 | 0.211 | |||||||
LCZW Water | 504 Sports and cultural areas | 0.127 | 0.200 |
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Xu, Y.; Hou, W.; Zhang, C. Spatial Association Rules and Thermal Environment Differentiation Evaluation of Local Climate Zone and Urban Functional Zone. Land 2023, 12, 1701. https://doi.org/10.3390/land12091701
Xu Y, Hou W, Zhang C. Spatial Association Rules and Thermal Environment Differentiation Evaluation of Local Climate Zone and Urban Functional Zone. Land. 2023; 12(9):1701. https://doi.org/10.3390/land12091701
Chicago/Turabian StyleXu, Yinuo, Wei Hou, and Chunxiao Zhang. 2023. "Spatial Association Rules and Thermal Environment Differentiation Evaluation of Local Climate Zone and Urban Functional Zone" Land 12, no. 9: 1701. https://doi.org/10.3390/land12091701