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1 ACTA ECOLOGICA SINICA Vol. 31 No. 14 Jul Xu H Q. Analysis on urban heat island effect based on the dynamics of urban surface biophysical descriptors. Acta Ecologica Sinica * Landsat a Analysis on urban heat island effect based on the dynamics of urban surface biophysical descriptors XU Hanqiu * College of Environment and Resources Fuzhou University Institute of Remote Sensing Information Engineering Fuzhou University Fuzhou China Abstract The dynamics of urban biophysical descriptors represented mainly by impervious surface vegetation and open water can affect the quality of urban thermal environment UTE. With the progress of urbanization Fuzhou City located in the coastal area of southeastern China has witnessed a significant UTE change which led the city to have been reputed by media as the top of the three new furnace cities in China in To investigate the process of the city from a nonfurnace city to a top furnace city in China the dynamics of urban biophysical components of Fuzhou and the associated UTE change between 1976 and 2006 have been analyzed. The study focuses on the quantitative relationship between impervious surface and land surface temperature LST because the impervious surface has for many years been recognized as an indicator of the intensity of the UTE and with the advent of urban sprawl become a key issue in urban habitat health. The city's biophysical properties e. g. impervious surface vegetation and water along with LST in and 2006 were retrieved from the Landsat MSS / TM images of the corresponding years. Three thematic indices Normalized Difference Impervious Surface Index NDISI Normalized Difference Vegetation Index NDVI and Modified Normalized Difference Water Index MNDWI were employed to extract features of impervious surface vegetation and open water respectively from the satellite images. The spatial overlay and correlation analysis of these land surface features were then carried out. The results reveal the dynamics of the urban biophysical properties of the city in the 30 study years and their quantitative relationship to the UTE change. The area of urban impervious surface has significantly increased by 329% over the 30 years which was only km 2 in 1976 but remarkably increased to km 2 in The cost of the increase in urban impervious surfaces is the considerable reduction of vegetation and open water coverage in the city area. The JK * Corresponding author. fdy@ public. fz. fj. cn

2 vegetation coverage in the urban area has decreased from 25% in 1976 to 9. 8% in The replacement of the natural vegetation-dominated land surfaces by the impervious materials would have an impact on thermal environment of the city due to modification of heat energy balance. The study shows that the impervious surface has a positive exponential relationship with LST rather than a simple linear one which suggests that the area with high percent impervious surface could accelerate LST rise and thus the urban heat island development. The study also found that the contribution of impervious surface to LST could equal or even exceed that of the sum of vegetation and water. On the whole the significant urban biophysicalcomponent changes of Fuzhou City during the study period have induced the strong urban heat island effect to the city which led the city to have become the hottest one in China. The analysis shows that the increase and amalgamation of impervious surface patches reduction and fragmentation of vegetation and water covers and poor urban ventilation are the main factors contributing to the formation of the furnace city of Fuzhou. Key Words urban expansion impervious surface urban heat island remote sensing Fuzhou City 50% 100a 15% 100a 40% % % d 35 10a d 30a Owen Centre 5 Weng TM K Nichol ASTER ETM + 9 Hardin LAI ASTER Terre Haute LAI NDVI Xu 19a 1 12

3892 31 30a 1 1. 1 600 1000m 1 2007 2008 187 290 1044km 2 1388km 2 1 3 1. 2 Fig.

3 a m km km Fig. 1 3D-perspective view of the Fuzhou Basin a a Landsat 1976 MSS TM NLCD Chander 13 Chavez 14 DN bit RMSE a NDISI NDISI TIR - NDISI = VIS 1 + NIR + MIR1 /3 TIR + VIS 1 + NIR + MIR1 /3 NIR MIR1 TIR TM4 TM5 TM6 VIS MSS 1 Carlson NDVI NDVI NIR - RED NDVI = NIR + Red 1 2

4 Red Xu MNDWI 18 McFeeters NDWI MNDWI Green - MIR1 MNDWI = Green + MIR1 Green USGS Ji 19 Soti MNDWI MSS McFeeters NDWI NASA Landsat 21 L 6 = gain DN + bias L 6 TM 6 DN gain bias 6 K2 T = ln K1 /L T K1 K2 TM 6 K1 = W / m 2 ster μm K2 = K 7 5 T 10 LST T LST = 1 + λt /ρ lnε λ TM μm ρ = h c / σ = m K - σ = J /K h = J s c = m /s ε MSS NDVI URI 8 URI 12 LST' = LST - LST min LST max - LST min URI = 1 100mi n w i p i = 1 LST' min LST max m n i i w i p i URI 0 1 URI 1 0 URI

5 SPOT-Pan 10m % 96. 7% a 1 2 Item 1976 Area /km 2 % 1 Table 1 Various thematic information of biophysical components /km Area /km 2 % 1996 Area /km 2 % 2006 Area /km 2 % /% /% Increase Increase rate rate /% Increase rate Study area Impervious surface Vegetation Water URI Urban area Study area Urban area Study area Urban area Study area Urban area / UHI intensity Urban area /km Study area /km a km km km km a 994km 2 822km % 74. 1% 61. 3% % % a 6. 3km % %

6 Fig. 2 2 Spatiotemporal distribution of main urban biophysical components in Fuzhou's main urban area DUM URI

3896 31 2. 2 Veldkamp R 25 R = N2 - N1 N1-1 T - 1 100 N1 N2 T a 10a 1 1 2 1986 1996 1976 1986 1 3 10a 9 Fig.

7 Veldkamp R 25 R = N2 - N1 N1-1 T N1 N2 T a 10a a 9 Fig. 3 3 Digital UHI Model of the study area a 49% 17% 2 30a 4a 4b d a a a 10a 5 4d a b 5c d 4d 4d 30a 4b 4d 4d 1986

1976 and 2006 Level Area /km 2 /% Percentage /% Total percentage Lowering - 3 0. 51 0. 42 17. 04-2 2. 45 2.

8 e f 4b d Fig. 4 4 Difference image of UHI in Fuzhou main urban area LST Table 2 LST level variations between 1976 and 2006 Level Area /km 2 /% Percentage /% Total percentage Lowering Constant Raising Total Fig. 5 Typical UHI change areas 2. 3

9 Table 3 3 Regression models between impervious surface vegetation water and LST Univariate regression 1976 LST = e NDISI LST = NDVI LST = NDWI R 2 = R = R = R = LST = e NDISI LST = NDVI LST = MNDWI R 2 = R = R = R = LST = e NDISI LST = NDVI LST = MNDWI R 2 = R = R = R = Multivariate stepwise regression LST = NDISI NDVI MNDWI LST = NDISI NDVI MNDWI LST = NDISI NDVI MNDWI LST = e NDISI LST = NDVI LST = MNDWI LST = NDISI NDVI MNDWI R 2 = R = R = R = % Table 4 Impervious surface level and its corresponding LST in 2006 NDISI LST / Increased LST / Fig. 6 6 LST Exponential relationship between impervious surface and

10 a 64. 5% 73. 4% 25% 9. 8% 8. 7% 2. 6% a Imperviousness UHI Vegetation Water Table 5 5 Characteristics of urban biophysical components in the main urban area Patch number Mean area /km % Percentage of urban area Fragmentation degree Patch number Mean area /km URI Fragmentation degree Patch number Mean area /km Percentage of urban area Fragmentation degree Patch number Mean area /km Percentage of urban area /% Fragmentation degree F i = n i / a i n i i a i i d

11 hm hm hm 2 29 Nichol hm a References 1 Sterling S Ducharne A. Comprehensive data set of global land cover change for land surface model applications. Global Biogeochemical Cycles GB3017 doi /2007GB Xinhua Net. China's urbanization level increased by more than 5 times during the last 60 years since the foundation of the P. R. China http / /news. xinhuanet. com /fortune. 3 Gao H Y Cai X L He G Wang L H Kou X L Zhang H. The impact of urbanization on the surface temperature in Xi'an. Acta Geographica Sinica Xie Z Q Du Y Zeng Y Shi Y F Wu J G. Impact of urban expansion on regional temperature change in the Yangtze River Delta. Acta Geographica Sinica Owen T W Carlson T N Gillies R R. An assessment of satellite remotely sensed land cover parameters in quantitatively describing the climate effect of urbanization. International Journal of Remote Sensing Weng Q. A remote sensing-gis evaluation of urban expansion and its impact on surface temperature in the ZhujiangDelta China. International Journal of Remote Sensing Chen Y H Li X B Shi P J He C Y. Study on spatial pattern of urban heat environment in Shanghai City. Scientia Geographica Sinica Xu H Q Chen B Q. Remote sensing of the urban heat island and its changes in Xiamen City of SE China. Journal of Environmental Sciences Nichol J. Remote sensing of urban heat islands by day and night. Photogrammetric Engineeringand Remote Sensing Hardin P J Jensen R R. The effect of urban leaf area on summertime urban surface kinetic temperatures a Terre Haute case study. Urban Forestry

12 and Urban Greening Gong A D Chen Y H Li J Hu H L. Study on relationship between urban heat island and urban land use and cover change in Beijing. Journal of Image and Graphics XuH Q Ding F Wen X L. Urban expansion and heat island dynamics in the Quanzhou region China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Chander G Markham B. Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing Chavez P S Jr. Image-based atmospheric corrections revisited and revised. Photogrammetric Engineering and Remote Sensing Xu H Q. Quantitative analysis on the relationship of urban impervious surface with other components of the urban ecosystem. Acta Ecologica Sinica Xu H Q. Analysis of impervious surface and its impact on urban heat environment using the Normalized Difference Impervious Surface Index. Photogrammetric Engineering and Remote Sensing Carlson T N Arthur S T. The impact of landuse land cover changes due to urbanization on surface microclimate and hydrology a satellite perspective. Global and Planetary Change / Xu H Q. Modification of normalised difference water index NDWI to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing Ji L Zhang L Wylie B. Analysis of dynamic thresholds for the normalized difference water index. Photogrammetric Engineeringand Remote Sensing Soti V Tran A Bailly J S Puech C Lo S D Bégue A. Assessing optical earth observation systems for mapping and monitoring temporary ponds in arid areas. International Journal of Applied Earth Observation and Geoinformation Irish R. Landsat 7 Science Data Users Handbook http / /ltpwww. gsfc. nasa. gov /IAS /handbook /handbook_toc. html. 22 Agam N Kustas W P Anderson M C Li F Q Neale C M U. A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sensing of Environment Rajasekar U Weng Q H. Spatio-temporal modelling and analysis of urban heat islands by using Landsat TM and ETM + imagery. International Journal of Remote Sensing Melesse A M. Spatiotemporal dynamics of land surface parameters in the Red River of the North Basin. Physics and Chemistry of the Earth / Valdkamp E Weitz A M Staritsky I G Huising E J. Deforestation trends in the Atlantic Zone of Costa Rica a case study. Land Degradation and Rehabilitation Goetz S J Wright R K Smith A J Zinecker E Schaub E. IKONOS imagery for resource management tree cover impervious surfaces and riparian buffer analyses in the mid-atlantic region. Remote Sensing of Environment / Liu L C Lu S H Gao J X Lu X S. Spatial-temporal landscape dynamics in the Hulunbeir forest-steppe ecotone. Acta Ecologica Sinica Wang W K. Studies on the green patterns of Fuzhou City with the high resolution patches. Fujian Architecture and Construction Li Y M Zhang J H Gu R Z. Research on the relationship between urban greening and the effect of urban heat island. Journal of Chinese Landscape Architecture http / /news. xinhuanet. com /fortune /

% GIS / / Fig. 1 Characteristics of flood disaster variation in suburbs of Shang

% GIS / / Fig. 1 Characteristics of flood disaster variation in suburbs of Shang 20 6 2011 12 JOURNAL OF NATURAL DISASTERS Vol. 20 No. 6 Dec. 2011 1004-4574 2011 06-0094 - 05 200062 1949-1990 1949 1977 0. 8 0. 03345 0. 01243 30 100 P426. 616 A Risk analysis of flood disaster in Shanghai