Urban heat island and ecological condition modeling using thermal remote sensing in Tigray-Northern Ethiopia

被引:0
|
作者
Hishe, Solomon [1 ]
Gidey, Eskinder [2 ]
Zenebe, Amanuel [2 ]
Girma, Atkilt [2 ]
Dikinya, Oagile [3 ]
Sebego, Reuben [3 ]
Lyimo, James [4 ]
机构
[1] Mekelle Univ, Coll Social Sci & Languages, Dept Geog & Environm Studies, POB 231, Mekelle, Tigray, Ethiopia
[2] Mekelle Univ, Coll Dryland Agr & Nat Resources, Dept Land Resources Management & Environm Protect, POB 231, Mekelle, Tigray, Ethiopia
[3] Univ Botswana, Fac Sci, Dept Environm Sci, Private Bag 00704, Gaborone, Botswana
[4] Univ Dar es Salaam, Inst Resource Assessments, Dar Es Salaam, Tanzania
关键词
LST; NDBI; UHI; UHS; UTFVI; Thermal InfraRed Sensor (TIRS-1); Mekelle; Tigray; LAND-SURFACE TEMPERATURE; BUILT-UP; NDVI; INDEX; CITY; VALIDATION; HEALTH; AREA; UHI; LST;
D O I
10.1007/s40808-023-01804-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The detection of Urban Thermal Field Variance Index and Ecological condition was generally conducted based on the thermal remote sensing. This study aims to model the Land Surface Temperature (LST), Urban Heat Island (UHI), Urban Heat Hotspot (UHS), Normalized Difference Built-Up Index (NDBI), Enhanced Built-Up and Bareness Index (EBBI), Ecological Evaluation Index (EEI), Urban Thermal Field Variance Index (UTFVI) of Mekelle city, Tigray-Northern Ethiopia. The Landsat 8 Operational Land Imager (OLI) and Thermal InfraRed sensor (TIRS-1) bands were used. The results indicated that the mean LST was highest (38.69 degrees C) in the Semen sub-city. A total area of 33.4 Km(2) (30.56%) was classified as UHI dominantly located in the Semen sub-city. Moreover, about 38 Km(2) (34.61%) was characterized with the worst EEI. The UHS zones were covering a total area of 3.03 Km(2) (2.8%) and it is mainly concentrated in the Semen sub-city. In addition, the statistical relationship between LST and NDBI is negative and moderately strong (r = - 0.51, p < 0.001) due to the fact that most of the built-up area in the city is mixed with vegetation cover that cools the environment. We also found that an R-2 of 0.997 (p < 0.001) in all UTFVI indices. The multiple regression model result indicated that Pv, NDBI, and EBBI control LST negatively, whereas the LST, UTFVI, EEI and NDVI influences LST positively.
引用
收藏
页码:735 / 749
页数:15
相关论文
共 50 条
  • [31] Research On Seasonal Change Of Beijing Urban Heat Island By Satellite Remote Sensing
    Hu Jiacong
    Wei Xin
    [J]. EPLWW3S 2011: 2011 INTERNATIONAL CONFERENCE ON ECOLOGICAL PROTECTION OF LAKES-WETLANDS-WATERSHED AND APPLICATION OF 3S TECHNOLOGY, VOL 3, 2011, : 473 - 476
  • [32] Study on the Urban Heat Island Effect based on Quantitative Remote Sensing Technology
    Nie, Yunju
    Tong, Chengzhuo
    Cheng, Penggen
    Chen, Xiaoyong
    Zhou, Mengyu
    [J]. INTERNATIONAL CONFERENCE ON INTELLIGENT EARTH OBSERVING AND APPLICATIONS 2015, 2015, 9808
  • [33] Remote sensing of the urban heat island effect across biomes in the continental USA
    Imhoff, Marc L.
    Zhang, Ping
    Wolfe, Robert E.
    Bounoua, Lahouari
    [J]. REMOTE SENSING OF ENVIRONMENT, 2010, 114 (03) : 504 - 513
  • [34] Remote sensing for urban heat island research: Progress, current issues, and perspectives
    Diem, Phan Kieu
    Nguyen, Can Trong
    Diem, Nguyen Kieu
    Diep, Nguyen Thi Hong
    Thao, Pham Thi Bich
    Hong, Tran Gia
    Phan, Thanh Noi
    [J]. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2024, 33
  • [35] Microclimatic modeling of the urban thermal environment of Singapore to mitigate urban heat island
    Priyadarsini, Rajagopalan
    Hien, Wong Nyuk
    David, Cheong Kok Wai
    [J]. SOLAR ENERGY, 2008, 82 (08) : 727 - 745
  • [36] A study of urban heat island effects using remote sensing and GIS techniques in Kancheepuram, Tamil Nadu, India
    Bagyaraj, Murugesan
    Senapathi, Venkatramanan
    Karthikeyan, Sivakumar
    Chung, Sang Yong
    Khatibi, Rahman
    Nadiri, Ata Allah
    Lajayer, Behnam Asgari
    [J]. URBAN CLIMATE, 2023, 51
  • [37] The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data
    Peres, Leonardo de Faria
    de Lucena, Andrews Jose
    Rotunno Filho, Otto Correa
    de Almeida Franca, Jose Ricardo
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2018, 64 : 104 - 116
  • [38] A New Framework for Studying Urban Heat Island and Surface Energy Budget Using Remote Sensing and Ground Observations
    Bah, Abdou
    Norouzi, Hamid
    Blake, Reginald
    Valentine, Makini
    [J]. GEO-EXTREME 2021: CASE HISTORIES AND BEST PRACTICES, 2021, 328 : 304 - 310
  • [39] Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China
    Zhou, Decheng
    Bonafoni, Stefania
    Zhang, Liangxia
    Wang, Ranghui
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 628-629 : 415 - 429
  • [40] Mesoscale modeling of thermal circulation forced by airflow and urban heat island
    Kurbatskiy, A. F.
    Kurbatskaya, L. I.
    [J]. FOURTEENTH INTERNATIONAL SYMPOSIUM ON ATMOSPHERIC AND OCEAN OPTICS/ATMOSPHERIC PHYSICS, 2008, 6936