Characterizing urban growth and land surface temperature in the western himalayan cities of India using remote sensing and spatial metrics

被引:4
|
作者
Gupta, Rajman [1 ]
Sharma, Mani [1 ]
Singh, Garima [1 ]
Joshi, Rajendra Kr [1 ]
机构
[1] Jawaharlal Nehru Univ, Sch Environm Sci, New Delhi, India
关键词
urban sprawl; normalized difference vegetation index (NDVI); normalized difference water index (NDWI); normalized difference built-up index (NDBI); land surface temperature (LST); spatial metrics; BUILT-UP INDEX; LANDSCAPE METRICS; COVER CHANGES; HEAT-ISLAND; IMPERVIOUS SURFACE; PATTERN; DYNAMICS; GIS; DELHI; FRAGMENTATION;
D O I
10.3389/fenvs.2023.1122935
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Urban heat islands (UHI) are developing due to increasing urbanization and loss of vegetation in major cities in India. Increased urbanization modifies the urban microclimate that leads to significant land-use changes resulting in surface conversion and heat release, which poses serious risks to human health, environment and the ecosystem of the Himalayan ecosystem. Hence, mitigating UHI becomes important and requires a better understanding of underlying associated biophysical processes. In the study an attempt has been made to demonstrate the impact of urbanization on land surface temperature (LST) in Shimla and Dehradun, capitals of the Western Himalayan states, India using satellite data and spatial metrics. The process was analyzed using urban coverage patterns obtained from Landsat 5, 7, and 8 and corresponding sensors from TM, ETM+, and OLI. The Built-up and Non-Built-up areas were extracted and the biophysical parameters NDVI, NDBI, NDWI and LST were calculated to capture different features of urban growth. The result indicated, that the built-up area increased from 32.19 km(2) (2000) to 68.37 km(2) (2016) in Dehradun and from 12.38 km(2) (2000) to 29.47 km(2) (2016) in Shimla during the study period, resulting in an increase in NDBI and LST and Reduction and NDVI and NDWI. Results showed that temperature hotspots were largest in urban areas, followed by vegetation and water bodies. A significant correlation (p < 0.05) was observed between LST and biophysical parameters -NDVI, NDBI, NDWI. Spatial metrics at the class and landscape levels show that increased urban growth from 2000 to 2016 has made the landscape fragmented and more heterogeneous. The Identified trends and changes in landscape patterns and their impact on heterogeneous urban areas suggest that the study is feasible to estimate LST, NDVI, NDBI and NDWI with reasonable accuracy that will likely have influence on policy interventions.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] URBAN HEAT ISLANDS AND REMOTE SENSING: CHARACTERIZING LAND SURFACE TEMPERATURE AT THE NEIGHBORHOOD SCALE
    Liebowitz, Anna
    Sebastian, Elizabeth
    Yanos, Claudia
    Bilik, Matthew
    Blake, Reginald
    Norouzi, Hamidreza
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 4407 - 4409
  • [2] Efficiency of landscape metrics characterizing urban land surface temperature
    Liu, Yanxu
    Peng, Jian
    Wang, Yanglin
    LANDSCAPE AND URBAN PLANNING, 2018, 180 : 36 - 53
  • [3] GIS and remote sensing based analysis for monitoring urban growth dynamics in Western Himalayan city of Dharamshala, India
    Nishant Mehra
    Janaki Ballav Swain
    Urban Lifeline, 3 (1):
  • [4] Urban Growth of Palembang and Its Impact on Land Surface Temperature Using Remote Sensing and GIS Technique
    Adiyanto, Johannes
    Atyanta, Adhika
    PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND SUSTAINABLE DEVELOPMENT (ICESSD 2019), 2020,
  • [5] Modeling the internal structure, dynamics and trends of urban sprawl in Ghanaian cities using remote sensing, spatial metrics and spatial analysis
    Kpienbaareh, Daniel
    Luginaah, Isaac
    AFRICAN GEOGRAPHICAL REVIEW, 2020, 39 (03) : 189 - 207
  • [6] Characterizing Urban Growth of Nanjing, China, by Using Multi-stage Remote Sensing Images and Landscape Metrics
    Wang, Jun
    Ju, Weimin
    Li, Manchun
    2009 JOINT URBAN REMOTE SENSING EVENT, VOLS 1-3, 2009, : 123 - 128
  • [7] Mapping Urban Land Use at Street Block Level Using OpenStreetMap, Remote Sensing Data, and Spatial Metrics
    Grippa, Tais
    Georganos, Stefanos
    Zarougui, Soukaina
    Bognounou, Pauline
    Diboulo, Eric
    Forget, Yann
    Lennert, Moritz
    Vanhuysse, Sabine
    Mboga, Nicholus
    Wolff, Eleonore
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2018, 7 (07)
  • [8] A case study on the relation between city planning and urban growth using remote sensing and spatial metrics
    Hai Minh Pham
    Yamaguchi, Yasushi
    Thanh Quang Bui
    LANDSCAPE AND URBAN PLANNING, 2011, 100 (03) : 223 - 230
  • [9] Characterizing urban area dynamics in historic city of Kurukshetra, India, using remote sensing and spatial metric tools
    Anees, Mangalasseril Mohammad
    Sajjad, Shafa
    Joshi, Pawan Kumar
    GEOCARTO INTERNATIONAL, 2019, 34 (14) : 1584 - 1607
  • [10] Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices
    Filiz Bektaş Balçik
    Environmental Monitoring and Assessment, 2014, 186 : 859 - 872