Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Abdollah A. Jarihani"'
Autor:
Abdollah A. Jarihani, Tim R. McVicar, Thomas G. Van Niel, Irina V. Emelyanova, John N. Callow, Kasper Johansen
Publikováno v:
Remote Sensing, Vol 6, Iss 10, Pp 9213-9238 (2014)
The objective of this paper was to evaluate the accuracy of two advanced blending algorithms, Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to downscale M
Externí odkaz:
https://doaj.org/article/90efee06112341898cfb57946b0170e1
Publikováno v:
Journal of Hydrology. 529:1511-1529
Summary Drylands cover approximately one-third of the Earth’s surface, are home to nearly 40% of the Earth’s population and are characterised by limited water resources and ephemeral river systems with an extremely variable flow regime and high t
Publikováno v:
Journal of Hydrology. 524:489-506
Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modelling of environmental processes. Topographic accuracy, methods of preparation and grid size are all important for hydrodynamic mo
Publikováno v:
Journal of Hydrology. 505:78-90
Satellite altimeters have been launched with the objective to monitor changes in sea level and glacial ice sheet topography. More recently, their potential to monitor inland water bodies such as lakes, rivers and wetlands has been recognised. The obj
Autor:
Abdollah Asadzadeh Jarihani
Drylands occupy one third of the Earth’s surface and are home to around 400 million people, yet the water resources of these regions are often poorly understood because of a lack of fundamental hydrological data. Rivers are often low-gradient with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c42e3a5c092a3b4afc9b5fef3dcc41aa
https://doi.org/10.14264/uql.2015.920
https://doi.org/10.14264/uql.2015.920
Autor:
Irina Emelyanova, Tom Van Niel, J. N. Callow, Kasper Johansen, Abdollah A. Jarihani, Tim R. McVicar
Publikováno v:
Remote Sensing; Volume 6; Issue 10; Pages: 9213-9238
Remote Sensing, Vol 6, Iss 10, Pp 9213-9238 (2014)
Remote Sensing, Vol 6, Iss 10, Pp 9213-9238 (2014)
The objective of this paper was to evaluate the accuracy of two advanced blending algorithms, Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to downscale M