PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2019 | 28 | 4 |

Tytuł artykułu

Impact of land use/land cover changes on the thermal environment in urbanization: a case study of the natural wetlands distribution area in Minjiang River Estuary, China

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Under accelerated urbanization and high-intensity human activities, the natural wetlands distribution area (NWDA) in Minjiang River estuary faces the great challenge of a deteriorative urban thermal environment. This work aims to analyze the impact of land use/land cover (LULC) on the urban thermal environment and model wetland surface temperature disturbance characteristics during the process of urbanization. The study utilized the following methodological steps: (1) mapping of LULC spatial and temporal distribution through photo interpretation; (2) applying the mono-window algorithm to obtain the spatiotemporal patterns of land surface temperature (LST); (3) examining the correlation between LST and different LULC classes, normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), and normalized difference impervious surface index (NDISI); and (4) exploring wetland surface temperature characteristics based on profile analysis and regression models. The results showed that the LST pattern depended on the LULC distribution; the high LST zones were mainly observed in the center of Fuzhou city, and the low LST zones were mainly observed in forest and river areas. Moreover, the urban thermal environment was influenced by both LULC classes and urban growth types. Finally, the positive relationship between LST and NDISI indicated an amplifying effect of the impervious surface for wetland surface temperature, while vegetation with high liquid water attenuated the regional high temperature. The obtained conclusions are expected to be beneficial in improving the design and management of the urban thermal environment.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

28

Numer

4

Opis fizyczny

p.3025-3041,fig.,ref.

Twórcy

autor
  • College of the Environment and Resources, Fuzhou University, Shangjie Town, Minhou County, Fuzhou, Fujian, China
autor
  • Fuzhou University Zhicheng College, Gulou District, Fuzhou, Fujian, China
  • College of Geographical Sciences, Fujian Normal University, Cangshan District, Fuzhou, Fujian, China
autor
  • College of the Environment and Resources, Fuzhou University, Shangjie Town, Minhou County, Fuzhou, Fujian, China
autor
  • College of the Environment and Resources, Fuzhou University, Shangjie Town, Minhou County, Fuzhou, Fujian, China
autor
  • Fujian Environmental Protection Design Institute Co., Ltd., Jin’an District, Fuzhou, Fujian, China

Bibliografia

  • 1. SUN R., CHEN A., CHEN L., Lü Y. Cooling effects of wetlands in an urban region: The case of Beijing. Ecological Indicators, 20 (9), 57, 2012.
  • 2. DU H., SONG X., JIANG H., KAN Z., WANG Z., CAI Y. Research on the cooling island effects of water body: A case study of Shanghai, China. Ecological Indicators, 67, 31, 2016.
  • 3. XU H., SHI T., WANG M., FANG C., LIN Z. Predicting effect of forthcoming population growth–induced impervious surface increase on regional thermal environment: Xiong'an New Area, North China. Building and Environment, 136, 98, 2018.
  • 4. SINGH P., KIKON N., VERMA P. Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustainable Cities and Society, 32, 100, 2017.
  • 5. QIAO Z., TIAN G., XIAO L. Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data. ISPRS Journal of Photogrammetry and Remote Sensing, 85 (2), 93, 2013.
  • 6. ZHANG H., QI Z., YE X., CAI Y., MA W., CHEN M. Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China. Applied Geography, 44 (4), 121, 2013.
  • 7. SUN R., CHEN L. Effects of green space dynamics on urban heat islands: Mitigation and diversification. Ecosystem Services, 23, 38, 2017.
  • 8. ZHANG B., XIE G., GAO J., YANG Y. The cooling effect of urban green spaces as a contribution to energy-saving and emission-reduction: A case study in Beijing, China. Building and Environment, 76 (76), 37, 2014.
  • 9. CAO X., ONISHI A., CHEN J., IMURA H. Quantifying the cool island intensity of urban parks using ASTER and IKONOS data. Landscape and Urban Planning, 96 (4), 224, 2010.
  • 10. MONDAL B., DOLUI G., PRAMANIK M., MAITY S., BISWAS S., PAL R. Urban expansion and wetland shrinkage estimation using a GIS-based model in the East Kolkata Wetland, India. Ecological Indicators, 83, 62, 2017.
  • 11. SICA Y., QUINTANA R., RADELOFF V., GAVIERPIZARRO G. Wetland loss due to land use change in the Lower Paraná River Delta, Argentina. Science of the Total Environment, 568, 967, 2016.
  • 12. ZHANG B., SHI Y., LIU J., XU J., XIE G. Economic values and dominant providers of key ecosystem services of wetlands in Beijing, China. Ecological Indicators, 77, 48, 2017.
  • 13. CAI Y., ZHANG H., ZHENG P., PAN W. Quantifying the impact of land use/land cover changes on the urban heat island: A case study of the natural wetlands distribution area of Fuzhou city, China. Wetlands, 36 (2), 285, 2016.
  • 14. WU W., ZHOU Y., TIAN B. Coastal wetlands facing climate change and anthropogenic activities: A remote sensing analysis and modelling application. Ocean & Coastal Management, 138, 1, 2017.
  • 15. MENG W., HE M., HU B., MO X., LI H., LIU B., WANG Z. Status of wetlands in China: A review of extent, degradation, issues and recommendations forimprovement. Ocean & Coastal Management, 146, 50, 2017.
  • 16. TIAN H., LINDENMAYER D., WONG G., Mao Z., HUANG Y., XUE X. A methodological framework for coastal development assessment: A case study of Fujian Province, China. Science of the Total Environment, 615, 572, 2017.
  • 17. DENG Y., WANG S., BAI X., TIAN Y., WU L., XIAO J., CHEN F., QIAN Q. Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, 8 (1), 641, 2018.
  • 18. DOS SANTOS A.R., De OLIVEIRA F.S., DA SILVA A.G., GLERIANI J.M., GONCALVES W., MOREIRA G.L., SILVA F.G., FIGUEIRA BRANCO E.R., MOURA M.M., DA SILVA R.G., JUVANHOL R.S., DE SOUZA K.B., SOARES RIBEIRO C.A.A., DE QUEIROZ V.T., COSTA A.V., LORENZON A.S., DOMINGUES G.F., MARCATTI G.E., DE CASTRO N.L.M., RESENDE R.T., GONZALES D.E., DE CASTRO N.L.M., RESENDE R.T., GONZALES D.E., DE ALMEIDA TELLES L.A., TEIXEIRA T.R., DOS SANTOS G.M.A.D.A., SANTOS MOTA P.H. Spatial and temporal distribution of urban heat islands. Science of the Total Environment, 605-606, 946, 2017.
  • 19. CHAUDHURI G., MISHRA N. Spatio-temporal dynamics of land cover and land surface temperature in Ganges-Brahmaputra delta: A comparative analysis between India and Bangladesh. Applied Geography, 68, 68, 2016.
  • 20. WANG S., MA Q., DING H., LIANG H. Detection of urban expansion and land surface temperature change using multi-temporal landsat images. Resources, Conservation and Recycling, 128, 526, 2018.
  • 21. QIN Z., ZHANG M., ARNON K., PEDRO B. Monowindow algorithm for retrieving land surface temperature from Lansat TM 6 data. Acta Geographica Sinica, 56 (4), 456, 2001.
  • 22. VOOGT J., OKE T. Thermal remote sensing of urban climates. Remote Sensing of Environment, 86 (3), 370, 2003.
  • 23. WARD K., LAUF S., KLEINSCHMIT B., ENDLICHER W. Heat waves and urban heat islands in Europe: A review of relevant drivers. Science of the Total Environment, 569-570, 527, 2016.
  • 24. JAGANMOHAN M., KNAPP S., BUCHMANN C.M., SCHWARZ N. The bigger, the better? The influence of urban green space design on cooling effects for residential areas. Journal of Environmental Quality, 45 (1), 134, 2016.
  • 25. XU H., LIN D., TANG F. The impact of impervious surface development on land surface temperature in a subtropical city: Xiamen, China. International Journal of Climatology, 33 (8), 1873, 2013.
  • 26. ZHANG Y., ODEH I.O.A., HAN C. Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a subpixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 11 (4), 256, 2009.
  • 27. PENG J., XIE P., LIU Y., MA J. Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region. Remote Sensing of Environment, 173, 145, 2016.
  • 28. SONG J., DU S., FENG X., GUO L. The relationships between landscape compositions and land surface temperature: Quantifying their resolution sensitivity with spatial regression models. Landscape and Urban Planning, 123 (1), 145, 2014.
  • 29. WU H., YE L., SHI W., CLARKE K. Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China. International Journal of Applied Earth Observation and Geoinformation, 32 (1), 67, 2014.
  • 30. GUO G., WU Z., XIAO R., CHEN Y., LIU X., ZHANG X. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape and Urban Planning, 135, 1, 2015.
  • 31. MALLICK J., SINGH C.K., SHASHTRI S., RAHMAN A., MUKHERJEE S. Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city. International Journal of Applied Earth Observation and Geoinformation, 19 (10), 348, 2012.
  • 32. LI B., WANG H., QIN M., ZHANG P. Comparative study on the correlations between NDVI, NDMI and LST. Progress in Geography, 36 (5), 585, 2017.
  • 33. XU H. Analysis of impervious surface and its impact on urban heat environment using the normalized difference impervious surface index (NDISI). Photogrammetric Engineering and Remote Sensing, 76 (5), 557, 2010.
  • 34. TRAN D.X., PLA F., LATORRE-CARMONA P., MYINT S.W., CAETANO M., KIEU H.V. Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119, 2017.
  • 35. TU L., QIN Z., LI W., GENG J., YANG L., ZHAO S., ZHAN W., WANG F. Surface urban heat island effect and its relationship with urban expansion in Nanjing, China. Journal of Applied Remote Sensing, 10 (2), 026037, 2016.
  • 36. LI X., ZHOU Y., ASRAR G.R., IMHOFF M., LI X. The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States. Science of the Total Environment, 605-606, 426, 2017.
  • 37. LIU X., LI X., CHEN Y., TAN Z., LI S., AI B. A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data. Landscape Ecology, 25 (5), 671, 2010.
  • 38. MUSHORE T.D., ODINDI J., DUBE T., MUTANGA O. Prediction of future urban surface temperatures using medium resolution satellite data in Harare metropolitan city, Zimbabwe. Building and Environment, 122, 397, 2017.
  • 39. YU X., GUO X., WU Z. Land surface temperature retrieval from Landsat 8 TIRS – Comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote Sensing, 6 (10), 9829, 2014.
  • 40. Landsat 7 science data users handbook. Washington, DC: Goddard Space Flight Center, NASA. Available online: http://landsathandbook.gsfc.nasa.gov/handbook.html (accessed on 2011).
  • 41. Landsat 8 (L8) data users handbook. Washington, DC: Goddard Space Flight Center, NASA. Available online: http://landsathandbook.gsfc.nasa.gov/handbook.html (accessed on 2016).
  • 42. BARSI J.A., SCHOTT J.R., PALLUCONI F.D., HOOK S.J. Validation of a web-based atmospheric correction tool for single thermal band instruments. Proceedings of SPIE - The International Society for Optical Engineering, 5882, 58820E, 2005.
  • 43. HAN L., DAI X., SHAO H., WANG H. An improved method for atmospheric transmissivity inversion based on field atmospheric modes. Remote Sensing for Land & Resources, 28 (4), 88, 2016.
  • 44. QIN Z., LI W., ZHANG M., KARNIELI A., BERLINER P. Estimating of the essential atmospheric parameters of mono-window algorithm for land surface temperature retrieval from Landsat TM 6. Remote Sensing for Land & Resources, 56 (2), 37, 2003.
  • 45. SOBRINO J.A., JIMENEZ-MUNOZ J.C., PAOLINI L. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90 (4), 434, 2004.
  • 46. LIU Y., PENG J., WANG Y. Diversification of land surface temperature change under urban landscape renewal: A case study in the main city of Shenzhen, China. Remote Sensing, 9 (9), 919, 2017.
  • 47. CARLSON T.N., RIPLEY D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62 (3), 241, 1997.
  • 48. SOBRINO J.A., CASELLES V., BECKER F. Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard. ISPRS Journal of Photogrammetry and Remote Sensing, 44 (6), 343, 1990.
  • 49. MAJUMDAR D.D., BISWAS A. Quantifying land surface temperature change from LISA clusters: An alternative approach to identifying urban land use transformation. Landscape and Urban Planning, 153, 51, 2016.
  • 50. GAO B. NDWI – A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257, 1996.
  • 51. SUN Z., WANG C., GUO H., SHANG R. A modified normalized difference impervious surface index (MNDISI) for automatic urban mapping from Landsat imagery. Remote Sensing, 9 (9), 942, 2017.
  • 52. EI-DERENY M., RASHWAN N.I. Solving multicollinearity problem using ridge regression models. Int.J.Contemp.Math.Sciences, 6 (12), 585, 2011.
  • 53. ESTOQUE R.C., MURAYAMA Y., MYINT S.W. Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349, 2017.
  • 54. XIAO F., LI Y., DU Y., LING F., YAN Y., FENG Q., BAN X. Monitoring perennial sub-surface waterlogged croplands based on MODIS in Jianghan plain, middle reaches of the Yangtze River. Journal of Integrative Agriculture, 13 (8), 1791, 2014.
  • 55. ZHAO Z., HE B., LI L., WANG H., DARKO A. Profile and concentric zonal analysis of relationship between land use/land cover and land surface temperature: Case study of Shenyang, China. Energy and Buildings, 155, 282, 2017.
  • 56. CAI Y., ZHANG H., PAN W., CHEN Y., WANG X. Urban expansion and its influencing factors in natural wetland distribution area in Fuzhou city, China. Chinese Geographical Science, 22 (5), 568, 2012.
  • 57. CAI Y., ZHANG H., PAN W. Detecting urban growth patterns and wetland conversion processes in a natural wetlands distribution area. Polish Journal of Environment Studies, 24 (5), 1919, 2015 [In Polish].
  • 58. FENG H., LIU H., WU L. Monitoring the relationship between the land surface temperature change and urban growth in Beijing, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7 (10), 4010, 2014.
  • 59. CAI Y., LI H., YE X., ZHANG H. Analyzing threedecadal patterns of land use/land cover change and regional ecosystem services at the landscape level: Case study of two coastal metropolitan regions, eastern China. Sustainability, 8 (8), 773, 2016.
  • 60. GONG J., HU Z., CHEN W., LIU Y., WANG J. Urban expansion dynamics and modes in metropolitan Guangzhou, China. Land Use Policy, 72, 100, 2018.
  • 61. ESTOQUE R.C., MURAYAMA Y. Intensity and spatial pattern of urban land changes in the megacities of Southeast Asia. Land Use Policy, 48, 213, 2015.
  • 62. MCCONNELL V., WILEY K. Infill development: Perspectives and evidence from economics and planning. In The Oxford Handbook of Urban Economics and Planning; Brooks N., Donaghy K., Knaap G., Eds.; Oxford University Press: New York, USA, 473, 2011.
  • 63. ZHANG X., ESTOQUE R.C., MURAYAMA Y. An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables. Sustainable Cities and Society, 32, 557, 2017.
  • 64. LU Y., FENG X., XIAO P., SHEN C. Urban heat island in summer of Nanjing based on TM data. Urban Remote Sensing Event, 1, 2009.
  • 65. LIU Y., PENG J., WANG Y. Application of partial least squares regression in detecting the important landscape indicators determining urban land surface temperature variation. Landscape Ecology, 33 (7), 1133, 2018.
  • 66. PENG J., MA J., LIU Q., LIU Y., HU Y., LI Y., YUE Y. Spatial-temporal change of land surface temperature across 285 cities in China: An urban-rural contrast perspective. Science of the Total Environment, 635, 487, 2018.
  • 67. RUIZ M.A., SOSA M.B., Correa Cantaloube E.N., Canton M.A. Suitable configurations for forested urban canyons to mitigate the UHI in the city of Mendoza, Argentina. Urban Climate, 14, 197, 2015.
  • 68. PENG J., JIA J., LIU Y., LI H., WU J. Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas. Remote Sensing of Environment 215, 255, 2018.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-a04c91e7-2557-4fee-a251-ebcba3b3a6d9
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.