Abstract
Land Surface Temperature (LST) is a basic determinant of terrestrial thermal behavior. It is an important climatic parameter to access the heat of the earth's surface. Soil moisture, water, vegetation cover, and settlement have some strong effects to balance the LST. The heating of the earth's surface is increasing consistently with the passage of time and is a threat to human, animal and plant life. The changes in land cover, especially newly built-up areas create an impact on the variation of LST and soil moisture. Almost all cities of the world are getting warmer today than in the past. The present study analyses the LST of Kamrup Metropolitan district of Assam, along with the Normalized difference water index (NDWI), Normalized difference vegetation index (NDVI), Normalized difference built-up index (NDBI), and soil moisture index (SMI) of the study area for a period of 19 years i.e. 2000 to 2019 using remote sensing (RS) and Geographic information system (GIS) techniques. ENVI 5.1 was used to analyze Landsat satellite imagery, namely Enhanced Thematic Mapper (ETM) & Operational Land Imager (OLI) images. The results of the analysis were imported to ArcGIS 10.2 (www.esri.com) for final layout and map generation. Thermal band (TM) imageries (band 6 & band 10) were additionally used to perform the band math operation to obtain the results. Comparison of all the indices with LST was carried out to ascertain the impact of LST on the environment in the study area.
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References
Abdullah S, Barua D (2022) modeling land surface temperature with a mono-window algorithm to estimate urban heat Island intensity in an expanding Urban Area. Environ Proces 9(1):14
Balew A, Korme T (2020) Monitoring land surface temperature in Bahir Dar city and its surrounding using Landsat images. Egypt J Remote Sens Space Sci 23(3):371–386. https://doi.org/10.1016/j.ejrs.2020.02.001
Chetia S, Saikia A, Basumatary M, Sahariah D (2020) When the heat is on: urbanization and land surface temperature in Guwahati. India. Acta Geophysica 68(3):891–901
Chi Y, Sun J, Sun Y, Liu S, Fu Z (2020) Multi-temporal characterization of land surface temperature and its relationships with normalized difference vegetation index and soil moisture content in the Yellow River Delta. China. Global Ecol Conser 23:e01092. https://doi.org/10.1016/j.gecco.2020.e01092
Gandhi GM, Parthiban S, Thummalu N, Christy A (2015) Ndvi: vegetation change detection using remote sensing and GIS—a case study of Vellore District. Procedia Comput Sci 57:1199–1210. https://doi.org/10.1016/j.procs.2015.07.415
Khandelwal S, Goyal R, Kaul N, Mathew A (2018) Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. Egypt J Remote Sens Space Sci 21(1):87–94. https://doi.org/10.1016/j.ejrs.2017.01.005
Macarof P, Statescu F (2017) Comparison of NDBI and NDVI as indicators of surface urban heat island effect in landsat 8 imagery: a case study of Iasi. Present Environ Sustain Develop 11(2):141–150. https://doi.org/10.1515/pesd-2017-0032
Mohamed ES, Ali A, El-Shirbeny M, Abutaleb K, Shaddad SM (2020) Mapping soil moisture and their correlation with crop pattern using remotely sensed data in arid region. Egypt J Remote Sens Space Sci 23(3):347–353. https://doi.org/10.1016/j.ejrs.2019.04.003
Neog R (2022a) Evaluation of temporal dynamics of land use and land surface temperature (LST) in Agartala city of India. Environ Dev Sustain 24(3):3419–3438
Neog R (2022b) Monitoring land use dynamics, urban sprawl, and land surface temperature in Dimapur urban area, Nagaland, India. Int J Environ Sci Technol
Neog R (2021) Analyzing dynamic behavior of land use and land surface temperature in the city of Imphal, India. Acta Geophysica 69(6):2275–2290
Njoku EA, Tenenbaum DE (2022) Quantitative assessment of the relationship between land use/land cover (LULC), topographic elevation and land surface temperature (LST) in Ilorin, Nigeria. Remote Sens Appl Soc Environ 27:100780
Pablos M, Martinez Fernandez J, Piles M, Sánchez N, Vall-llossera M, Camps A (2016) Multi-temporal evaluation of soil moisture and land surface temperature dynamics using in situ and satellite observations. Remote Sens 8(7):587. https://doi.org/10.3390/rs8070587
Pawe CK, Saikia A (2020) Decumbent development: urban sprawl in the Guwahati metropolitan area. India. Singapore J Tropical Geogr 41(2):226–247
Raj Sharath B et al (2021) Groundwater drought index, temporal NDVI and LST comparison of Raichur District, Karnataka, India: Insight to the Intensifying Drought. In: Simhachalam DA (ed) Application of geo-spatial technologies in natural resource management. Akansha publishing house, New Delhi, pp 105–117
Saha A, Patil M, Goyal VC, Rathore DS (2018) Assessment and impact of soil moisture index in agricultural drought estimation using remote sensing and GIS techniques. Proceedings 7(1):2. https://doi.org/10.3390/ecws-3-05802
See L, Fritz S, Perger C, Changkakati T, Obersteiner M et al. (2016) Mapping human impact using crowdsourcing. In: Carver SJ, Fritz S (eds) Mapping wilderness: concepts, techniques and applications. Dordrecht, Springer, pp 89–101
Sekertekin A, Bonafoni S (2020) Land surface temperature retrieval from landsat 5, 7, and 8 over Rural areas: assessment of different retrieval algorithms and emissivity models and toolbox implementation. Remote Sens 12(2):294. https://doi.org/10.3390/rs12020294
Suresh DS et al (2021) LULC changes and LST dynamics in Davangere city, Karnataka India: inferences from landsat data. In: Simhachalam A (ed) Application of geo-spatial technologies in natural resource management. Akansha publishing house, New Delhi, pp 235–245
Tripathi R, Rahman MP, Abdul S (2017) Estimation of land surface temperature using geoinformatics technique, a case study of Dindigul city, Tamilnadu, India. In: Muthukumer DM (ed) Geospatial technology for rural development. Shanlax publications, Madurai, pp 133–138
Xu H (2006) Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033. https://doi.org/10.1080/01431160600589179
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Sharma, N., Arote, G. (2022). Mercury Rising: Examining LST Links with NDVI, NDWI, NDBI & SMI in the Kamrup Metropolitan District, India Using Geospatial Technologies. In: Saikia, A., Thapa, P. (eds) Environmental Change in South Asia. Springer, Cham. https://doi.org/10.1007/978-3-030-47660-1_5
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