Open Access
Issue |
E3S Web Conf.
Volume 386, 2023
Annual International Scientific Conferences: GIS in Central Asia – GISCA 2022 and Geoinformatics – GI 2022 “Designing the Geospatial Ecosystem”
|
|
---|---|---|
Article Number | 04008 | |
Number of page(s) | 10 | |
Section | GIS in Geodesy and Cartography | |
DOI | https://doi.org/10.1051/e3sconf/202338604008 | |
Published online | 12 May 2023 |
- A. Lefebvre, C. Sannier, T. Corpetti, Monitoring urban areas with Sentinel-2A data: Application to the update of the Copernicus High Resolution Layer Imperviousness Degree, J. Remote Sens. 8, 1-21 (2016) [Google Scholar]
- R. K. Oymatov, Z. J. Mamatkulov, M.P. Reimov, R.I. Makhsudov, R.N. Jaksibaev, Methodology development for creating agricultural interactive maps, J. IOP Conf. Ser. Earth Environ. Sci., 868 (2021) [Google Scholar]
- N. Teshaev, B. Mamadaliyev, A. Ibragimov, S. Khasanov, The soil-adjusted vegetation index for soil salinity assessment in Uzbekistan, Conference: GI support of sustainable development of territories: Proceedings of the International conference (2020) [Google Scholar]
- T. Dong, J. Meng, J. Shang, J. Liu, B. Wu, Evaluation of Chlorophyll-Related Vegetation Indices Using Simulated Sentinel-2 Data for Estimation of Crop Fraction of Absorbed Photosynthetically Active Radiation, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8, 4049-59, (2015) [CrossRef] [Google Scholar]
- B.Y. Tam, W.A. Gough, T. Mohsin, The impact of urbanization and the urban heat island effect on day to day temperature variation, J. Urban Clim., 12, 1-10 (2015) [CrossRef] [Google Scholar]
- K. Yu, V. L. Wiedemann, X. Chen, G. Bareth, Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects, ISPRS J. Photogramm. Remote Sens., 97, 58-77 (2014) [CrossRef] [Google Scholar]
- S. Roy, S. Pandit, E. A. Eva, M.S. Bagmar, M. Papia, L. Banik, T. Dube, F. Rahman, M. Razi, Examining the nexus between land surface temperature and urban growth in Chattogram Metropolitan Area of Bangladesh using long term Landsat series data, J. Urban Clim., 32, 100593 (2020) [CrossRef] [Google Scholar]
- R. Oymatov, S. Safayev, Creation of a complex electronic map of agriculture and agro-geo databases using GIS techniques, J. E3S Web of Conferences, 258 (2021) [Google Scholar]
- D. Bazarov, S. Umarov, R. Oymatov, F. Uljaev, K. Rayimov, I. Raimova, Hydraulic parameters in the area of the main dam intake structure of the river, J. E3S Web of Conferences, 264 (2021) [Google Scholar]
- N.T. Tam, H.T Dat, P.M. Tam, V.T. Trinh, N.T. Hung, Agricultural Land-Use Mapping with Remote Sensing Data, 2(020) [Google Scholar]
- A.M. Youssef, M.A. Hegab, Flood-Hazard Assessment Modeling Using Multicriteria Analysis and GIS (Elsevier Inc., 2019) [Google Scholar]
- J. Jiang, W. Cai, H. Zheng, T. Cheng, Y. Tian, Y. Zhu, R. Ehsani, Y. Hu, Q. Niu, L. Gui, X. Yao, Using digital cameras on an unmanned aerial vehicle to derive optimum color vegetation indices for leaf nitrogen concentration monitoring in winter wheat, J. Remote Sens., 11 (2019) [Google Scholar]
- R. K. Oymatov, Z.J. Mamatkulov, M.P. Reimov, R.I. Makhsudov, R.N. Jaksibaev, Methodology development for creating agricultural interactive maps, J. IOP Conf. Ser. Earth Environ. Sci., 868, (2021) [Google Scholar]
- S. Khidirov, R. Oymatov, B. Norkulov, F. Musulmanov, I. Rayimova, I. Raimova, Exploration of the hydraulic structure of the water supply facilities operation mode and flow, J. E3S Web Conf., 264, 1-10 (2021). [Google Scholar]
- R. Cioffi, M. Travaglioni, G. Piscitelli, A. Petrillo, F.D. Felice, Artificial intelligence and machine learning applications in smart production: Progress, trends, and directions, J. Sustain., 12 (2020) [Google Scholar]
- M. Wojtaszek, L. Ronczyk, Z. Mamatkulov, M. Reimov, Object-Based Approach for Urban Land Cover Mapping Using High Spatial Resolution Data, J. E3S Web Conf. 227, (2021) [Google Scholar]
- B. Saipova, Z. Mamatkulov, A. Altiev, M. Rajapbaev, B. Kabulov, Importance of land use and land cover change analyze in land resource management, J. AIP Conference Proceedings, 2432(1), 040038 (2022). [CrossRef] [Google Scholar]
- Z. Mamatkulov, K. Abdivaitov, S. Hennig, E. Safarov, Int. J. Geoinformatics. 18(1), (2022) [Google Scholar]
- N. A. Mfondoum, S. Hakdaoui, R. Batcha, Landsat 8Bands’ 1 to 7 spectral vectors plus machine learning to improve land use/cover classification using Google Earth Engine, J. Ann. GIS, 00. 1-24 (2022) [Google Scholar]
- M.V. Wojtaszek, I. Abdurahmanov, Crop water condition mapping by optical remote sensing, Int. J. Geoinformatics, 17, 11-7 (2021) [CrossRef] [Google Scholar]
- Z. Mamatkulov, E. Safarov, R. Oymatov, I. Abdurahmanov, M. Rajapbaev, Application of GIS and RS in real time crop monitoring and yield forecasting: A case study of cotton fields in low and high productive farmlands, J. E3S Web Conf., 227, (2021) [Google Scholar]
- S. Khasanov, R. Oymatov, R. Kulmatov, Canopy temperature: as an indicator of soil salinity (a casestudy in Syrdarya province, Uzbekistan), J. IOP Conf. Series: Earth and Environmental Science, 1142, 012109 (2023) [CrossRef] [Google Scholar]
- S. Egamberdiev, M Kholmurotov, E. Berdiev, T. Ochilov, R. Oymatov, Z. Abdurakhmonov, Determination of substrate composition, light, and temperature for interior plant growth, J. E3S Web of Conferences, 284, 03015 (2021) [CrossRef] [EDP Sciences] [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.