Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing
Abstract
:1. Introduction
1.1. Studies on the Impact of Urban Spatial Morphology on LST
1.2. Studies on the Impact of Green and Blue Infrastructure’s Spatial Pattern on LST
1.3. Planning Orientation of Urban Thermal Environment Improvement Studies
2. Materials and Methods
2.1. Study Area and Block Units
2.2. Data Source and Processing
2.3. Characteristic Indicators of UHI Based on LST
2.4. Spatial Morphological Indicators of Urban Blocks
2.5. Relationship Analysis Methods
3. Results
3.1. Spatial Heterogeneity of UHI in Historical Downtown Blocks
3.2. Relationship between UHI and Block Morphology
3.3. Relationships between UHI and GBI in Different Spatial Morphological Blocks
3.4. Potential Adaptive UHI Mitigation Solutions for Historical Downtown Blocks with Different Spatial Morphology
- High GBI proportion and mid-rise blocks (HMB)
- Mid GBI proportion and high-rise blocks (MHB)
- Low GBI proportion and low-rise blocks (LLB)
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Category | Indicators | Formula | Note |
---|---|---|---|
Land cover characteristics | Impervious surface proportion (ISP) | % | , represents the area of impervious surface, vegetated area, water bodies, bare soil, respectively, A is block area. |
Vegetated area proportion (VP) | % | ||
Water proportion (WP) | % | ||
Soil proportion (SP) | % | ||
Normalized difference vegetation index (NDVI) | represents the reflection value in the NIR band, represents the reflection value in the red band [72]. | ||
Impervious surface area (ISA) | In this paper, ISA of urban area was extracted by linear spectral hybrid image element decomposition model. It mainly includes the minimum noise separation, pure image element processing, end element collection, linear spectral separation, result checking and correction of the pre-processed images [73,74] | ||
Urban spatial structure characteristics | Building coverage ratio (BCR) | % | refer to the height, volume, footprint and perimeter of the building No.i respectively, n is the number of buildings, A is the area of the block, C = 3.0 m is a constant, is the maximum height of the buildings in the block, is the minimum height of the buildings in the block [71]. |
Mean height (MH) | |||
Highest building index (HBI) | % | ||
Height fluctuation degree (HFD) | |||
Average Volume (AV) | |||
Space crowd degree (SCD) | |||
Floor area ratio (FAR) | |||
Building structural index (BSI) | |||
Building surface area (BSA) | |||
Sky view factor (SVF) | is the sky view stereo angle, is the effect of terrain height angle on azimuth; n is the number of calculated azimuths (n = 36), and the spatial resolution is 5 m [75,76]. |
Appendix B
Category | Indicators | Formula | Note |
---|---|---|---|
Patch Size | Mean patch size (AREA_MN) | is the number of GBI patches in a block. | |
Largest patch index (LPI) | is block area. | ||
Patch shape | Area-weighted fractal dimension index (FRAC_AM) | refers to the area of the GBI patch number i, n is the number of GBI patches in a block, is boundary length of GBI patch No.i. | |
Landscape shape index (LSI) | is total length of the boundary of GBI patches in a block, is coverage area of GBI in a block | ||
Fragmentation | Number of patches (NP) | is the number of GBI patches in a block. | |
Area-weighted Euclidean nearest neighbor distance (ENN_AM) | is the nearest distance between GBI patch No.i and No.j, n is the number of GBI patches in a block. | ||
Aggregation index (AI) | is the number of similar neighboring patches of GBI in a block. |
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Category | Indicators | Definition | Unit |
---|---|---|---|
Land cover characteristics | Impervious land proportion (IP) | The ratio of impervious area to block area. | % |
Vegetated land proportion (VP) | The ratio of vegetated area to block area. | % | |
Water proportion (WP) | The ratio of water area to block area. | % | |
Bare soil proportion (SP) | The ratio of bare soil area to block area. | % | |
Normalized Difference Vegetation Index (NDVI) | The vegetation index calculated by the near-infrared band and red band value of Landsat-8 OLI. [72] | - | |
Impervious Surface Area (ISA) | The impervious degree calculated by a linear spectral mixture decomposition model [73,74] | - | |
Urban spatial structure characteristics | Building coverage ratio (BCR) | The ratio of building coverage to block area. | % |
Mean height (MH) | The average height of buildings in the block. | m | |
Highest building index (HBI) | The ratio of the tallest building’s height to the sum of all buildings’ heights in the block. [71] | - | |
Height fluctuation degree (HFD) | The difference between the height of the tallest and shortest building in the block [71] | - | |
Average Volume (AV) | The average volume of buildings in the block. | m3 | |
Space crowd degree (SCD) | The ratio of the sum of all buildings’ volumes to the potential largest building volume in the block [71] | - | |
Floor area ratio (FAR) | The ratio of total above-ground floor area to block area. | - | |
Building structural index (BSI) | The average ratio of each building’s covered area to its height in the block [71] | - | |
Building surface area (BSA) | The surface area of buildings in the block. | m2 | |
Sky view factor (SVF) | The average sky openness among buildings in the block [75,76] | - |
Category | Indicators | Definition | Unit | |
---|---|---|---|---|
Composition | Trees and shrubs proportion (TP) | The ratio of tree and shrub covered area to block area. | % | |
Grass proportion (GP) | The ratio of grass covered area to block area. | % | ||
Water proportion (WP) | The ratio of water area to block area. | % | ||
Configuration | Patch Size | Mean patch size (AREA_MN) | Average area of all GBI patches within the block | Ha |
Largest patch index (LPI) | Ratio of the area of the largest GBI patch to the total area of GBI within the block | % | ||
Patch shape | Area-weighted fractal dimension index (FRAC_AM) | The fractal dimension weighted by its area of individual GBI patches in the block | - | |
Landscape shape index (LSI) | Modified perimeter-area ratio of GBI patches in the block | - | ||
Fragmentation Connectivity Aggregation | Number of patches (NP) | The number of GBI patches in the block | - | |
Area-weighted Euclidean nearest neighbor distance (ENN_AM) | The ENN-MN weighted by the area of GBI patches in the block | % | ||
Aggregation index (AI) | A measure of aggregation between GBI patches within blocks, obtained by dividing number of joins by the maximum possible umber of joins among GBI patches in the block | m |
Region | The LST Indicator/°C | The Spatial Characteristic Indicator | |||||
---|---|---|---|---|---|---|---|
LSTmean | LSTstd | LSTrange | Area/km2 | Proportion/ % | Cohesion | Aggregation | |
Whole City of Beijing | 27.09 | 3.22 | 32.07 | / | / | / | / |
Central urban area of Beijing | 31.15 | 2.74 | 27.66 | / | / | / | / |
Beijing Old Town (BOT) | 33.06 | 2.09 | 25.25 | 62.28 | 100 | / | / |
Cold area | 29.92 | 1.37 | 17.47 | 12.42 | 19.95 | 82.27 | 88.56 |
Warm area | 33.19 | 0.86 | 3.88 | 36.27 | 58.23 | 94.17 | 91.10 |
Hot area | 35.61 | 0.86 | 4.95 | 13.59 | 21.82 | 82.80 | 89.57 |
Indicators | Mean Value | LSTmean | LSTstd | LSTrange | |||
---|---|---|---|---|---|---|---|
C | S | C | S | C | S | ||
Impervious surface proportion (ISP) | 67.86% | 0.717 ** | 0.000 | −0.529 ** | 0.000 | −0.446 ** | 0.000 |
Vegetation proportion (VP) | 27.74% | −0.675 ** | 0.000 | 0.390 ** | 0.000 | 0.358 ** | 0.000 |
Water proportion (WP) | 3.20% | −0.466 ** | 0.000 | 0.583 ** | 0.000 | 0.451 ** | 0.000 |
Bare soil proportion (BP) | 1.19% | −0.114 | 0.208 | 0.026 | 0.778 | −0.001 | 0.993 |
Indicators | LSTmean | LSTstd | LSTrange | |||
---|---|---|---|---|---|---|
C | S | C | S | C | S | |
Building coverage ratio (BCR) | 0.543 ** | 0.000 | −0.203 * | 0.026 | −0.145 | 0.113 |
Mean height (MH) | −0.785 ** | 0.000 | 0.100 | 0.280 | 0.042 | 0.653 |
Highest building index (HBI) | −0.361 ** | 0.000 | −0.161 | 0.080 | −0.236 ** | 0.009 |
Height fluctuation degree (HFD) | −0.411 ** | 0.000 | 0.144 | 0.117 | 0.139 | 0.129 |
Space crowd degree (SCD) | 0.464 ** | 0.000 | −0.080 | 0.387 | −0.129 | 0.160 |
Floor area ratio (FAR) | 0.020 | 0.829 | 0.078 | 0.396 | 0.023 | 0.800 |
Sky view factor (SVF) | 0.237 ** | 0.009 | 0.033 | 0.721 | 0.028 | 0.764 |
Category | Indicators | HMB | MHB | LLB | |||
---|---|---|---|---|---|---|---|
LSTmean | LSTstd | LSTmean | LSTstd | LSTmean | LSTstd | ||
Composition | TP | −0.531 ** | 0.111 | −0.033 | −0.067 | −0.353 * | −0.109 |
GP | −0.050 | 0.021 | −0.313 * | 0.234 | −0.274 | −0.032 | |
WP | −0.520 ** | 0.565 ** | −0.314 * | 0.112 | −0.145 | −0.031 | |
Patch Size | LPI | −0.702 ** | 0.403 * | −0.182 | 0.110 | −0.401 ** | −0.047 |
AREA_MN | −0.729 ** | 0.303 | −0.323 * | 0.312 * | −0.600 ** | −0.117 | |
Shape Complexity | LSI | 0.153 | 0.191 | 0.339 * | 0.060 | 0.060 | 0.037 |
FRAC_AM | −0.693 ** | 0.219 | −0.168 | 0.046 | −0.616 ** | −0.077 | |
Fragmentation Connectivity Aggregation | NP | −0.035 | 0.265 | 0.312 * | 0.061 | 0.131 | 0.047 |
ENN_AM | 0.456 * | −0.295 | 0.011 | 0.285 | 0.483 ** | 0.082 | |
AI | −0.764 ** | 0.480 ** | −0.267 | 0.442 ** | −0.570 ** | 0.028 |
Direction 1: Improvement for Construction of Urban Green and Blue Space System | ||
Key Points | Requirements | Sources |
Promoting street shading | Improve the construction of boulevard system, promote the transformation of street shading facilities. | Regulatory plan, 2020. |
Optimize plant communities and improve the quality of street shade. | Regulatory plan, 2020. | |
Increasing the area and accessibility of green space | Promote greening coverage, green space per capita, etc. | Regulatory plan, 2020. |
Constructing both community parks and small pocket green spaces on marginal land, unused land and etc. | Regulatory plan, 2020; Design guideline, 2019. | |
Enhancing the quality of green space | Improve the level of green vision ratio in various urban spaces. | Regulatory plan, 2020. |
Improve the three-dimensional greening scenery by reasonably vertical and roof greening. | Regulatory plan, 2020; Design guideline, 2019. | |
Improve greening construction mechanism | Promote public participation in greening construction and education. | Regulatory plan, 2020 |
Carry out public participation in greening construction activities of hutongs and courtyard. | Regulatory plan, 2020; Design guideline, 2019. | |
Optimize plant species selection | Select native plants such as acacia, mulberry, willow, pomegranate, begonia, etc. | Design guideline, 2019. |
Direction 2: Preservation of urban spatial matrix and historical features | ||
Key Points | Requirements | Sources |
Promoting the tree protection | Integrate trees preservation with street greening or public space design programs, strictly implement the protection of famous trees, large trees, old and historic trees. | Regulatory plan, 2020; Design guideline, 2019. |
Carry out the “one tree for one courtyard” replanting program. | Regulatory plan, 2020. | |
Promoting shading transformation of checkerboard-shaped street network | Enhance the proportion of boulevards, improve greening rate of street network by increasing the green space on both sides of streets. | Regulatory plan, 2020. |
Strengthening preservation and maintenance of traditional buildings and alleys | Strictly implement the requirements of historical buildings or buildings with traditional features can no longer be demolished. | Master plan, 2017; Regulatory plan, 2020. |
Promote housing decrement renewal, carry out retreatment and renovation of illegal or makeshift buildings. | Regulatory plan, 2020 | |
Regulating population density | Control resident density integrated with economic and social planning. | Regulatory plan, 2020. |
Reinforce street characteristics and features | Select the materials (e.g., greenery, wall, and pavement and etc.) consistent with historical features in design and management works. | Regulatory plan, 2020; Design guideline, 2019. |
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Zhang, L.; Shi, X.; Chang, Q. Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing. Land 2022, 11, 544. https://doi.org/10.3390/land11040544
Zhang L, Shi X, Chang Q. Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing. Land. 2022; 11(4):544. https://doi.org/10.3390/land11040544
Chicago/Turabian StyleZhang, Liukuan, Xiaoxiao Shi, and Qing Chang. 2022. "Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing" Land 11, no. 4: 544. https://doi.org/10.3390/land11040544
APA StyleZhang, L., Shi, X., & Chang, Q. (2022). Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing. Land, 11(4), 544. https://doi.org/10.3390/land11040544