STUDY ON URBAN TEMPERATURE AND LAND-USE IN GUANGZHOU BASED ON RS AND GIS. Relationship of Urban heat island effect and land-use trends

Similar documents
Applications of GIS and Remote Sensing for Analysis of Urban Heat Island

Analysis on Climate Change of Guangzhou in Nearly 65 Years

Dynamical Monitoring and Evaluation Methods to Urban Heat Island Effects Based on RS&GIS

CORRELATION BETWEEN URBAN HEAT ISLAND EFFECT AND THE THERMAL INERTIA USING ASTER DATA IN BEIJING, CHINA

1. Introduction. Chaithanya, V.V. 1, Binoy, B.V. 2, Vinod, T.R. 2. Publication Date: 8 April DOI: /cloud.ijarsg.

Percentage of Vegetation Cover Change Monitoring in Wuhan Region Based on Remote Sensing

ScienceDirect. Local Climate Zone Study for Sustainable Megacities Development by Using Improved WUDAPT Methodology A Case Study in Guangzhou

Using Geographic Information Systems and Remote Sensing Technology to Analyze Land Use Change in Harbin, China from 2005 to 2015

Urban Growth in South China and Impacts on Local Precipitation, Fifth Urban Research Symposium 2009

AssessmentofUrbanHeatIslandUHIusingRemoteSensingandGIS

MONITORING THE SURFACE HEAT ISLAND (SHI) EFFECTS OF INDUSTRIAL ENTERPRISES

SUPPORTING INFORMATION. Ecological restoration and its effects on the

Estimation of Land Surface Temperature of Kumta Taluk Using Remote Sensing and GIS Techniques

Critical review of the Climate Change Impact on urban areas by assessment of Heat Island effect

Atmospheric correction of HJ1-A/B images and the effects on remote sensing monitoring of cyanobacteria bloom

The Relationship between Vegetation Changes and Cut-offs in the Lower Yellow River Based on Satellite and Ground Data

Analysis of China s Haze Days in the Winter Half-Year and the Climatic Background during

Comparison between Land Surface Temperature Retrieval Using Classification Based Emissivity and NDVI Based Emissivity

Research Article A Quantitative Assessment of Surface Urban Heat Islands Using Satellite Multitemporal Data over Abeokuta, Nigeria

International Journal of Scientific & Engineering Research, Volume 4, Issue 12, December-2013 ISSN

Estimation of Wavelet Based Spatially Enhanced Evapotranspiration Using Energy Balance Approach

Numerical simulation of the low visibility event at the. Hong Kong International Airport on 25 December 2009

Landuse and Landcover change analysis in Selaiyur village, Tambaram taluk, Chennai

Investigation of the Effect of Transportation Network on Urban Growth by Using Satellite Images and Geographic Information Systems

EXTRACTION OF REMOTE SENSING INFORMATION OF BANANA UNDER SUPPORT OF 3S TECHNOLOGY IN GUANGXI PROVINCE

LAND USE LAND COVER, CHANGE DETECTION OF FOREST IN KARWAR TALUK USING GEO-SPATIAL TECHNIQUES

DROUGHT ASSESSMENT USING SATELLITE DERIVED METEOROLOGICAL PARAMETERS AND NDVI IN POTOHAR REGION

Spatial heterogeneity of urban land-cover landscape in Guangzhou from 1990 to 2005

Remote sensing Based Assessment of Urban Heat Island Phenomenon in Nagpur Metropolitan Area

VISUALIZATION URBAN SPATIAL GROWTH OF DESERT CITIES FROM SATELLITE IMAGERY: A PRELIMINARY STUDY

The Study of Dynamic Monitor of Rice Drought in Jiangxi Province with Remote Sensing

Tropical Climates Zone

Chapter 3: Temperature

Drought Estimation Maps by Means of Multidate Landsat Fused Images

Making Rain on Arid Regions The GESHEM Rain System

Joint International Mechanical, Electronic and Information Technology Conference (JIMET 2015)

Seasonal Variations of the Urban Heat Island Effect:

Interannual variation of MODIS NDVI in Lake Taihu and its relation to climate in submerged macrophyte region

Changes in Climate Factors and Extreme Climate Events in South China during

Mario Flores, Graduate Student Department of Applied Mathematics, UTSA. EES 5053: Remote Sensing

EFFECT OF ANCILLARY DATA ON THE PERFORMANCE OF LAND COVER CLASSIFICATION USING A NEURAL NETWORK MODEL. Duong Dang KHOI.

The Self-adaptive Adjustment Method of Clustering Center in Multi-spectral Remote Sensing Image Classification of Land Use

APPLICATION OF LAND CHANGE MODELER FOR PREDICTION OF FUTURE LAND USE LAND COVER A CASE STUDY OF VIJAYAWADA CITY

Aniekan Eyoh 1* Department of Geoinformatics & Surveying, Faculty of Environmental Studies, University of Uyo, Nigeria

URBAN CHANGE DETECTION OF LAHORE (PAKISTAN) USING A TIME SERIES OF SATELLITE IMAGES SINCE 1972

Measurement and Analysis of the Vertical Distribution Characteristic of the Atmospheric Particle Concentration in Beijing District

Definitions Weather and Climate Climates of NYS Weather Climate 2012 Characteristics of Climate Regions of NYS NYS s Climates 1.

Application of ZY-3 remote sensing image in the research of Huashan experimental watershed

Land cover/land use mapping and cha Mongolian plateau using remote sens. Title. Author(s) Bagan, Hasi; Yamagata, Yoshiki. Citation Japan.

Synoptic Analysis of Total Rainfall Patterns at Azerbaijan District.

Modeling Study of A Typical Summer Ozone Pollution Event over Yangtze River Delta

Abstract: Introduction: 10 th ESRI India User Conference 2009 Geography in Action

Indian National (Weather) SATellites for Agrometeorological Applications

West meets East: Monitoring and modeling urbanization in China Land Cover-Land Use Change Program Science Team Meeting April 3, 2012

Droughts are normal recurring climatic phenomena that vary in space, time, and intensity. They may affect people and agriculture at local scales for

Analysis of Industrialization, Urbanization and Land-use Change in East Asia According to the DPSER Framework

Quick Response Report #126 Hurricane Floyd Flood Mapping Integrating Landsat 7 TM Satellite Imagery and DEM Data

Urbanization in China A synthesis of local and regional case studies on land cover change

An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

Spatial Geotechnologies and GIS tools for urban planners applied to the analysis of urban heat island. Case Caracas city, Venezuela Contribution 115.

Geography Class XI Fundamentals of Physical Geography Section A Total Periods : 140 Total Marks : 70. Periods Topic Subject Matter Geographical Skills

Drought Monitoring Based on the Vegetation Temperature Condition Index by IDL Language Processing Method

Preliminary Research on Grassland Fineclassification

Seasonal Aerosol Vertical Distribution and Optical Properties over North China Xing-xing GAO, Yan CHEN, Lei ZHANG * and Wu ZHANG

A Method to Improve the Accuracy of Remote Sensing Data Classification by Exploiting the Multi-Scale Properties in the Scene

DROUGHT RISK EVALUATION USING REMOTE SENSING AND GIS : A CASE STUDY IN LOP BURI PROVINCE

Reprint 850. Within the Eye of Typhoon Nuri in Hong Kong in C.P. Wong & P.W. Chan

PAUL RUDOLPH Oriental Masonic Gardens

Spatio-temporal dynamics of the urban fringe landscapes

Urban-rural humidity and temperature differences in the Beijing area

GLOBAL/CONTINENTAL LAND COVER MAPPING AND MONITORING

Over the course of this unit, you have learned about different

DISTRIBUTION AND DIURNAL VARIATION OF WARM-SEASON SHORT-DURATION HEAVY RAINFALL IN RELATION TO THE MCSS IN CHINA

THE STRUCTURE OF THE ATMOSPHERIC BOUNDARYLAYER DURING FOGGY DAYS IN WINTER AND SPRING SEASONS AT SOUTHERT OF BEIJING

Learning Objectives. Thermal Remote Sensing. Thermal = Emitted Infrared

Small- and large-current cloud-to-ground lightning over southern China

IMPACT OF URBAN EVOLUTION ON LAND-USE CHANGE OF SARGODHA CITY, PAKISTAN

Climates of Earth. Lesson Outline LESSON 1. A. What is climate? 1. is the long-term average weather conditions that occur in a particular region.

CHAPTER 2 REMOTE SENSING IN URBAN SPRAWL ANALYSIS

IAP Dynamical Seasonal Prediction System and its applications

Lecture 4 Air Temperature. Measuring Temperature. Measuring Temperature. Surface & Air Temperature. Environmental Contrasts 3/27/2012

DEPENDENCE OF URBAN TEMPERATURE ELEVATION ON LAND COVER TYPES. Ping CHEN, Soo Chin LIEW and Leong Keong KWOH

Impact of urbanization on boundary layer structure in Beijing

Reassessing the conservation status of the giant panda using remote sensing

Hong Kong Meteorological Society 香港氣象學會.

Research on Climate of Typhoons Affecting China

Extremes Events in Climate Change Projections Jana Sillmann

Evaluation of SEBAL Model for Evapotranspiration Mapping in Iraq Using Remote Sensing and GIS

3.3 AN OBSERVATIONAL ANALYSIS OF VERTICAL DISTRIBUTIONS OF SO 2 IN THE SURFACE LAYER OF BEIJING DURING COLD WAVE PASSING IN WINTER

RESEARCH ON TEMPORAL AND SPATIAL VARIATION OF HEAT ISLAND EFFECT IN XI'AN, CHINA

Quantifying the influence of wind advection on the urban heat island for an improvement of a climate change adaptation planning tool

Sensitivity Analysis on Sea Surface Temperature Estimation Methods with Thermal Infrared Radiometer Data through Simulations

URBAN HEAT ISLAND IN SEOUL

Results of the ESA-DUE UHI project

2.2 Geographic phenomena

Effect of land use/land cover changes on runoff in a river basin: a case study

What do we think of our cities?

Meteorology. Circle the letter that corresponds to the correct answer

METRIC tm. Mapping Evapotranspiration at high Resolution with Internalized Calibration. Shifa Dinesh

Atmospheric Composition and Structure

Transcription:

M. A. Schnabel (ed.), Cutting Edge: 47 th International Conference of the Architectural Science Association, pp. 301 310. 2013, The Architectural Science Association (ANZAScA), Australia STUDY ON URBAN TEMPERATURE AND LAND-USE IN GUANGZHOU BASED ON RS AND GIS Relationship of Urban heat island effect and land-use trends CHEN-YANG LI, JING-YU ZHENG, YING YAO and LU YU Center for Housing Innovations, The Chinese University of Hong Kong, China chenyang.kenyon@gmail.com, zhengjyu1989@hotmail.com yaoying082008@sina.com, luee.yu@gmail.com 1. Introduction Abstract. It has been known that rapid urbanization has caused the raising urban warming phenomenon, which had been named ad Urban Heat Island Effect (UHI). By static analysis and dynamic analysis based on RS and GIS method, this paper revealed the relationship of UHI and land-use trends of Guangzhou between 2001 and 2009. To conclude, temperature distribution and land-use condition of Guangzhou had been plotted. Quantificationally, on static analysis, land-use has a close positive correlation relationship with urban temperature, from the aspects of land-use types and the intensive degree of utilize. Meanwhile, on dynamic analysis, this research proved that unbalanced extreme temperature distribution had been intensified, which means UHI had been exacerbated in relativity level. Keywords. UHI; GIS; RS; Guangzhou; Land-use. In 20th century, urbanization had huge impacts on human society (Berry, 1981). With booming of population and economy, cities assemble everincreasing social resources. Meanwhile conversely, series of negative effects, which had been known as City Disease (UPADIFU, 2012), had been exposed extensively, including Urban Heat Island Effect (UHI). 1.1. URBAN HEAT ISLAND EFFECT (UHI) Since 1960s, when urban area in a city expanded largely with high density development, UHI started to trouble those people who lived there. It is often

302 C.Y. LI, J.Y. ZHENG, Y. YAO AND L. YU referred to the phenomenon that urban and suburban temperatures are hotter than nearby rural areas (Zhang and Wang, 2010). In Figure 1, it shows the temperature difference between urban area and rural area (USEPA, 2013). For example, in relative meteorological record of Shanghai city (Xu et al, 2011), the temperature difference between urban area and rural area can even reach to 6 C. It is worth mentioning that UHI Effect is highly related with climate conditions in different seasons. For example, in Beijing, UHI effect strongly in winter, particularly from October to March (Song et al, 2003). Generally, UHI impacts in 2 main aspects. Firstly, aside from the effect on temperature, UHI can produce secondary effects on local meteorology, including the altering of local wind patterns, the development of clouds and fog, the humidity, and the rates of precipitation (ABR, 2007). It also can cause various microscopic meteorological disasters, such as rainstorms and thunderstorms. In Spain, rainfall rates of cities are increased between 48% and 116% due to UHI (Fuchs, 2005). Secondly, many health issues on urban residents had been caused by UHI, particularly by secondary induced heat and rainfall. Within the United States alone, an average of 1,000 people died each year due to extreme urban heat (Changnon, 1996). UHI is caused by excessive human activities on urban areas. Basically, there are 5 main reasons that can cause UHI (Yip 2011): Heat radiating from human activities, vehicles, etc. Heat absorbing by thermal properties of surface materials. Heat gathering by lack of evapotranspiration due to vegetation reducing. Heat transforming from polluted atmosphere. Heat distributing through urban canyon effect. Figure 1 & 2. Temperature Comparison (USEPA, 2013) & Location of Guangzhou.

STUDY ON URBAN TEMP. AND LAND-USE IN GUANGZHOU 303 1.2. RESEARCH REGION - GUANGZHOU Guangzhou is the capital of Guangdong Province and the regional centre in the Pearl River Delta (PRD) of South China. Thus, relevant research on urban condition of Guangzhou is significant and irradiative, including this research on UHI. Figure 2 mapped the location of Guangzhou City and Central District, and Table 1 listed Basic information of Guangzhou. In The General Land Use Planning of Guangzhou (2010-2020) published by Guangzhou Government, it is divided into 1 core urban district (Central Districts) and 5 functional sub-districts, named as East Sub-district, Conghua, Zengcheng, Huadu and Nansha. In Figure 3 and Figure 4, the detail social and corresponding development conditions of these 6 districts had been listed contrastively. For example, Central District is the main urban area with 75% of total population living and working in 25% of total boundary areas. Thus Central District is a high-density urban living area. Table 1. Basic information of Guangzhou. Coordinates 23 08 N 113 16 E Area: 7,434 km2 (Urban: 3,843 km2 ) Population (2010): 12,700,800 (Urban: 11,070,654) Density: 1,708/km2 Climate Type Ocean subtropical monsoon climate Extreme Temperature 0 C to 39.1 C Annual Mean Temperature 22.6 C Figure 3 & 4. Urban Spatial Structure Plan & Urban Functional Structure Plan.

304 C.Y. LI, J.Y. ZHENG, Y. YAO AND L. YU 2. Methodology 2.1 RESEARCH FRAMEWORK Our research processes mainly include five parts, data collection, data preprocess, data process, result analysis and conclusion (Figure 5). Firstly, by data collection and data pre-process, we obtain the maps of Guangzhou in 2001 and 2009. Secondly, data process contains two sections, land use classification and temperature information extraction. 2.2 DATA PROCESS 2.2.1 Data source Figure 5. Research framework. The data we use in the project are Pearl River Delta (PRD) images got from Landsat 5, TM (Table 2). Considering the features of Urban Heat Island (UHI) and the impacts of cloud cover, we select the similar time of December 30 th and January 2 nd in 2001 and 2009, to have comparative analysis. Table 2. Basic data information. Name Pearl River Delta 2001 Pearl River Delta 2009 Sensor Landsat 5, TM Spatial 30 x 30 meters Temporal 30 December, 2001 2 January, 2009 Spectral (micrometres) Band 1 = Blue (.45-.52) Band 2 = Green (.52-.6) Band 3 = Red (.63-.69) Band 4 = NIR (.76-.9) Band 5 = SWIR (1.55-1.75) Band 6 = TIR (10.4-12.5) Band 7 = SWIR (2.08-2.35)

STUDY ON URBAN TEMP. AND LAND-USE IN GUANGZHOU 305 2.2.2 Land use classification Five kinds of land types have been defined: new urban land, old urban land, cultivated land, forest and water. We differentiate these land types according to their different features of surface and materials. ROI Tool is used to classify these land types, and by Support Vector Machine, we obtain the land use maps of Guangzhou in 2001 and 2009 (Figure 7 and Figure 8). Figure 7 & 8. Temperature map in 2001 & Temperature map in 2009 2.2.3 Temperature Information Extraction In this section, several indexes including Normalized Difference Vegetation Index (NDVI), Vegetation Fraction (FV), Surface Emissivity and Brightness Temperature (TB), should be calculated step by step to get the final temperature information (Figure 6).

306 C.Y. LI, J.Y. ZHENG, Y. YAO AND L. YU Figure 6. Process of temperature information extraction. The equations are as below: FV = (NDVI - NDVIS) / (NDVIV - NDVIS) (1) NDVIS means pure vegetation, NDVIV means pure soil εsurface = 0.9625+0.0614FV 0.0461FV 2 (2) εbuilding = 0.9589+0.086FV 0.0671FV 2 (3) εsurface means Natural Surface Emissivity, εbuilding means Urban Surface Emissivity B(TS) = [L λ -L U -T*(1-ε)L d ]/T*ε (4) B(TS) means the radiance value of the object with the temperature of T, Lλ means Calibration value, Lu means upwards radiance, Ld means downwards radiance, and T means transmittance TS = K 2 / ln(k 1 / B(TS) + 1) (5) K 1 = 607.66W/(m 2 sr μm), K 2 =1260.56W/(m 2 sr μm) After the calculation in ENVI, we acquire Guangzhou temperature maps in 2001 and 2009 (Figure 9 and Figure 10). These two temperature maps had been transformed from ENVI to ArcGIS, with the tool box of raster calculate, the temperature change map from 2001 to 2009 is plotted (Figure 11). Figure 9 & 10. Temperature map in 2001 & Temperature map in 2009

STUDY ON URBAN TEMP. AND LAND-USE IN GUANGZHOU 307 3. Data Analysis 3.1. STATIC ANALYSIS Figure 11. Temperature change map from 2001 to 2009. 3.1.1 UHI effect and land-use conditions of Guangzhou in 2001 From temperature classification map of Guangzhou on January, 2001(Figure 9), the temperature distribution law can be found. The main temperature change region is from 8 to 18. the change trend can be recognized that it increased from Conghua and Zengcheng in north to Huadu and East Subdistrict in middle, reached the maximum in Central Districts, which is metropolitan area of Guangzhou, and then decreased toward to Nansha in the south. Statistically, the average minimum, median and maximum temperature in January from 1960 to 1990 is 9.8, 13.3 and 18.3 (Hong Kong Observatory, 2012). Figure 12 illustrates area percentage ratio of different temperature intervals, which is divided into <8, 8-11, 11-14, 14-18 and >18. Obviously, temperature of over 70% area distributes at 14-18. In the other hand, the land use conditions of Guangzhou in 2001 (Table 3). Construction land, including new and old urban area, only cover 14.7% of total city area. And meanwhile over half part is occupied by forest. Secondly, 27.8% of total city area identified as cultivated land. Comparing the TB distribution with the land cover classification map in 2001, we can find the consistency of TB distribution and land cover. The high temperature section was concentrated in urban area and consistent with

308 C.Y. LI, J.Y. ZHENG, Y. YAO AND L. YU the city silhouette in the detailed maps. The temperature was obviously higher than surrounding areas. The low temperature sections mainly distributed in high vegetation overcast area in the north and along the water area. TB is proportional to the urban scale and has the negative correlation with NDVI. 3.1.2 UHI effect and land-use conditions of Guangzhou in 2009 In Figure 10, the temperature classification map of Guangzhou on January, 2009 had been plotted. It has the same change region and trend as in 2001. Similarly with 2001, area percentage ratio of different temperature intervals of 2009 can be seen in Figure 12. 14-18 region still appears in over 50% area. Extreme temperature distribution (<8 and >18 ) began to increase. Table 3 also lists land use conditions in 2009, new urban land had been expanded to 23.8%, which is 3 times of old urban land. Meanwhile, cultivate land had been decreased sharply. Table 3. Land cover condition of Guangzhou. Year 2001 2009 Land cover type Area 2001 Area 2009 Change Ratio Old urban land 482,087,700.00 6.70% 1,453,683,600.0 6.70% 0.00% New urban land 572,139,900.00 8.00% 1,707,766,200.0 23.80 % 15.80% Cultivated land 1,989,455,400.00 27.80% 723,490,200.0 10.10 % -17.70% Forest 3,723,451,200.00 52.00% 2,875,102,200.0 40.10 % -11.90% Water 393,874,200.00 5.50% 400,971,600.0 5.60% 0.10% 7,161,008,400.00 7,161,013,800.00 3.2. DYNAMIC ANALYSIS 3.2.1 Land-use change in Guangzhou 2001-2009 From the land cover change chart (Figure 13), we can find that Guangzhou is booming in urbanization, city scale and urban population density rises sharply. The Urban Land in 2001(including old and new construction land) is 14.7% in total. But it expanded to 30.5% in 2009. Thus, the urban area growth rate is 199.9%. Guangzhou encountered quite a significant urban sprawl during these years. The urban land has almost two times increased.

STUDY ON URBAN TEMP. AND LAND-USE IN GUANGZHOU 309 The old urban area was mainly concentrated in the centre part. The new urban areas developed northwards to Huadu and southwards to Nansha, while the forest was still mainly distributed in Conghua Subdistrict. Meanwhile, the cultivated land and forest existing around urban land is rapidly replaced due to urbanization. During the process, in order to meet the increasing needs for construction lands, the cultivated land and forest have decreased separately by 17.70% and 11.90% from 2001 to 2009. Figure 12 & 13. Temperature classification 2001-2009 & Land covers change 2001-2009 3.2.2 Temperature change in Guangzhou 2001-2009 As seen in Figure 12, the overall trend is still the surface brightness temperature decreased from the metropolitan area to the periphery. The warming trend is most obviously in Nansha and Huadu (Figure 9 and Figure 10). 3.2.3 Relationship between land-use and temperature change According to dynamic analysis hereinbefore, particularly in Figure 12 and 13, it had been proved that with the decreasing of forest and cultivate land (from 79.8% to 50.2%) and the increasing of urban land (from 14.7% to 30.5%), the urban brightness temperature difference increase obviously from 2001 to 2009. Unbalanced extreme temperature distribution had been intensified, which means UHI had been exacerbated in relativity level. With the expansion of urban areas, the scope of heat island is gradually expanding. The general outline of localised warming part and added urban land were similar. 4. Conclusion Using RS and GIS, by comparing the TB distribution and land cover in 2001 and 2009, it indicates that TB is proportional to the urban scale and has positive correlation with NDVI. With the expansion of urban areas, the scope of UHI is gradually expanding. The consequent eco-environmental problems,

310 C.Y. LI, J.Y. ZHENG, Y. YAO AND L. YU such as landscape fragmentation, environmental pollution, have negative effects on UHI. However, there still are some limitations should be taken seriously. Firstly, the insufficiency of data, cloud cover can influenced accuracy. Secondly, in data pre-processing, atmosphere correction is ignored. The research indicates that the precision will be improved if NDVI is adopted, which is counted through the image of atmosphere correction. Acknowledgements We would like to extend our thanks and appreciation to Prof. Jin-yeu, TSOU and Prof. Yuanzhi ZHANG of Center for Housing Innovations, The Chinese University of Hong Kong for providing us relevant high quality academic education. Reference Arizona Board of Regents (ABR): 2007, Urban Climate-Climate Study and UHI via the Internet Wayback Machine, Arizona State University Press, Tempe, 36-42. Berry, Brian J.L.: 1981, Comparative Urbanization, Palgrave Macmillan, London, 54-59. Changnon, S. A., Jr., Kunkel, K. E. and Reinke, B. C.: 1996, Impacts and responses to the 1995 heat wave: A call to action. Bulletin of the American Meteorological Society, New York, 77 (7): 1497 1506 Rongbao, Z., Jianshun Z. and Jinqian Z.; 2008, The Relationship between NDVI Change and Land Use in Guangzhou City. Remote Sensing for Land & Resources, Beijing, 4(2): 89-101 Song, Y. L. and Zhang, S. Y.: 2003, The study on heat island effect in Beijing during last 40 years. CJEA, Beijing, ll(4): 126-129. UPADIFU: 2012, Urban Planning-City Disease, China Building Industry Press, Beijing. USEPA: 2013, Reducing Urban Heat Islands: Compendium of Strategies-Urban Heat Island Basics. USEPA, New York, 3-5. Yip, Z. D.: 2011, Low-carbon Eco Space: Rethincking of Planning, Dalian University of Technology Press, Dalian, 211-224. Xu, H., Chen, Y., Dan, S. and Qiu, W.: 2011, Dynamical Monitoring and Evaluation Methods to Urban Heat Island Effects Based on RS&GIS. Procedia Environmental Sciences, Elsevier, Rotterdam, 237-249. Zhang, H.X. and Wang, P.: 2010, Urban Heat Island Effect Based on RS: A Case study of Guangzhou City. Journal of Hengyang. Normal University, Hengyang, 9(2): 255-264. Dale Fuchs, Spain goes hi-tech to beat drought. 2005. Accessed May 14, 2013. <http://www.guardian.co.uk/world/2005/jun/28/spain.weather> Guangzhou Climate Data : 2012. Accessed June 1, 2013. <http://www.hko.gov.hk/wxinfo/climat/world/chi/asia/china/guangzhou_c.htm>