Open Access
Issue |
E3S Web Conf.
Volume 472, 2024
International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2023)
|
|
---|---|---|
Article Number | 02003 | |
Number of page(s) | 11 | |
Section | Green Computing | |
DOI | https://doi.org/10.1051/e3sconf/202447202003 | |
Published online | 05 January 2024 |
- https://en.wikipedia.org/wiki/Hyderabad [Google Scholar]
- https://en.wikipedia.org/w/index.php?search=Hyderabad+ORR& title=Special%3ASearch& ns0=1 [Google Scholar]
- https://www.usgs.gov/landsat-missions/landsat-5 [Google Scholar]
- https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-8-olioperational-land-imager. [Google Scholar]
- Adnan, Nor Aizam, et al. “Utilizing Landsat imageries for land surface temperature (LST) analysis of the Penang Island.” 2015 International Conference on Space Science and Communication (IconSpace). IEEE, 2015. [Google Scholar]
- Avdan, U. and Jovanovska, J. (2016) “Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data”. Journal of Sensors, 2016, ArticleID:1480307. [PubMed] [Google Scholar]
- Chander G., Markham B.L., Barsi J.A. “Revised landsat-5 thematic mapper radiometric calibration”. J IEEE Geoscince and Remote Sens Letters 2007; 4 (3): 490–494. DOI: 10.1109/LGRS.2007.898285 [CrossRef] [Google Scholar]
- [USGS] United State Geological Survey. Landsat 7 science data users handbook [internet]. [cited by 2014 January 12]. From: http://landsathandbook.gsfc.nasa.gov/pdfs/Landsat7_Handbook.pdf; 2013. [Google Scholar]
- H.-Q. Xu and B.-Q. Chen, “Remote sensing of the urban heat island and its changes in Xiamen City of SE China,” Journal of Environmental Sciences, vol. 16, no. 2, pp. 276–281, 2004. [Google Scholar]
- Gao B. NDWI - “A normalized difference water index for remote sensing of vegetation liquid water from space”. J Remote Sens Environ 1996; 58: 257–266. [CrossRef] [Google Scholar]
- Ho L.T.K., Umitsu M., Yamaguchi Y. “Flood hazard mapping by satellite images and SRTM DEM in the Vu Gia-Thu Bon Alluvial Plain, Central Vietnam”. J International Archive of Photogrammetry, Remote Sensing and Spatial Information Science 2010; 38 (8): 275–280. [Google Scholar]
- Annisa Nurdianaa, Idung Risdiyantob “Indicator determination of forest and land fires vulnerability using Landsat-5 TM data (case study: Jambi Province)”, 1878-0296 © 2015 The Authors. Published by Elsevier B.V [Google Scholar]
- Rouse J.W., Haas R.H., Schell J.A., Deering D.W. “Monitoring vegetation systems in the great plain with ERTS”. In: Proceedings of the third ERTS Symposium. Washington DC: US Government Printing Office NASA; 1973. [Google Scholar]
- Thoha A.S. “Assessment of forest fire danger by using keetch byram drought index in Sumberkima Bali Province”. Thesis. Bogor: Bogor Agricultural University; 1998. [Google Scholar]
- Niladri Das, Prolay Mondal, Subhasish Sutradhar, Ranajit Ghosh, “Assessment of variation of land use/land cover and its impact on land surface temperature of Asansol subdivision”, The Egyptian Journal of Remote Sensing and Space Science, Volume 24, Issue 1, 2021, Pages 131–149, ISSN 1110-9823, https://doi.org/10.1016/j.ejrs.2020.05.001. [CrossRef] [Google Scholar]
- USGS, 2013, http://landsat.usgs.gov/Landsat8UsingProduct.php. [Google Scholar]
- H.-Q. Xu and B.-Q. Chen, “Remote sensing of the urban heat island and its changes in Xiamen City of SE China,” Journal of Environmental Sciences, vol. 16, no. 2, pp. 276–281, 2004. [Google Scholar]
- Q. H. Weng, D. S. Lu, and J. Schubring, “Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies,” Remote Sensing of Environment, vol. 89, no. 4, pp. 467–483, 2004. [CrossRef] [Google Scholar]
- F. Wang, Z. Qin, C. Song, L. Tu, A. Karnieli, and S. Zhao, “An improved mono-window algorithm for land surface temperature retrieval from landsat 8 thermal infrared sensor data,” Remote Sensing, vol. 7, no. 4, pp. 4268–4289, 2015. [CrossRef] [Google Scholar]
- F. Wang, Z. Qin, C. Song, L. Tu, A. Karnieli, and S. Zhao, “An improved mono-window algorithm for land surface temperature retrieval from landsat 8 thermal infrared sensor data,” Remote Sensing, vol. 7, no. 4, pp. 4268–4289, 2015. [CrossRef] [Google Scholar]
- J. A. Sobrino, J.C. Jim’enez-Mu’noz, and L. Paolini, “Land surface temperature retrieval from LANDSAT TM 5,” Remote Sensing of Environment, vol. 90, no. 4, pp. 434–440, 2004. [CrossRef] [Google Scholar]
- J. C. Jim’enez-Mu’noz, J. A. Sobrino, A. Plaza, L. Guanter, J. Moreno, and P. Mart’inez, “Comparison between fractional vegetation cover retrievals from vegetation indices and spectral mixture analysis: case study of PROBA/CHRIS data over an agricultural area,” Sensors, vol. 9, no. 2, pp. 768–793, 2009. [CrossRef] [PubMed] [Google Scholar]
- J. C. Jimenez-Munoz, J. A. Sobrino, A. Gillespie, D. Sabol, and W. T. Gustafson, “Improved land surface emissivities over agricultural areas using ASTER NDVI,” Remote Sensing of Environment, vol. 103, no. 4, pp. 474–487, 2006. [CrossRef] [Google Scholar]
- Dash P., Gottsche F.M., Olesen F.S., Fischer H., (2002), “Land surface temperature and emissivity estimation from passive sensor data: theory and practice - current trends”, International Journal of Remote Sensing, 23, 2563–2594. [CrossRef] [Google Scholar]
- Sobrino J.A., Jimenez-Munoz J.C., Paolini L., (2004), “Land surface temperature retrieval from Landsat TM 5”, Remote Sensing of Environment, 90, 434–440. [CrossRef] [Google Scholar]
- Ugur Avdan and Gordana Jovanovska “Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data”, Hindawi Publishing Corporation Journal of Sensors Volume 2016, Article ID 1480307, 8 pages http://dx.doi.org/10.1155/2016/1480307 [Google Scholar]
- Xiao, R., Weng, Q., Ouyang, Z., Li, W., Schienke, E.W. and Zhang, Z. (2008) “Land Surface Temperature Variation and Major Factors in Beijing, China”. Photogrammetric Engineering & Remote Sensing, 74, 451–461. https://doi.org/10.14358/PERS.74.4.451 [CrossRef] [Google Scholar]
- Barsi, J.A., Lee, K., Kvaran, G., Markham, B.L. and Pedelty, J.A. (2014) “The Spectral Response of the Landsat-8 Operational Land Imager. Remote Sensing”, 6, 10232–10251. https://doi.org/10.3390/rs61010232 [Google Scholar]
- Azua, S., Nnah, S.I. and Ikwueze, H.U. (2020) “Spatio-Temporal Variability of Land-use Landcover and Its Impact on Land Surface Temperature in Zaria Metropolis, Nigeria”. FUTY Journal of the Environment, 14, 1–11. [Google Scholar]
- Xu, H.Q. and Chen, B.Q. (2004) “Remote Sensing of the Urban Heat Island and Its Changes in Xiamen City of SE China”. Journal of Environmental Sciences, 16, 276–281. [Google Scholar]
- Ek Bahadur Kshetri, “Geo world, Volume II, NDVI, NDBI and NDWI calculation using Landsat 7 and 8, 2022” [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.