FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2079797871> ?p ?o ?g. }

• W2079797871 endingPage "417" @default.
• W2079797871 startingPage "403" @default.
• W2079797871 abstract "There is an undisputed need to increase accuracy of Fractional Snow Cover (FSC) estimation in regions of complex terrain, especially in areas dependent on winter snow accumulation for a substantial portion of their water supply, such as the western United States. The main aim of this research is to develop FSC estimation in complex alpine-forested environments using an Artificial Neural Network (ANN) methodology as a fusion framework between multi-sensor remotely sensed data at medium temporal/spatial resolution (e.g.16-day revisit time; 30 m; Landsat), and high spatial resolutions (e.g.1 m; IKONOS). This research is the first known attempt to develop a multi-scale estimator of FSC from surface equivalent reference data derived from IKONOS multispectral data. It is also the first endeavor to estimate FSC values by combining terrain and snow/non-snow reflectance data. The plasticity of the developed ANN Landsat-FSC model accommodates alpine-forest heterogeneity, and renders unbiased, comprehensive, and precise FSC estimates. The accuracy of the ANN Landsat based FSC is characterized by: (1) very low error values (mean error ~ 0.0002; RMSE ~ 0.10; MAE ~ 0.08 FSC), (2) high correlation with the ground equivalent reference datasets derived from 1 m resolution IKONOS images (r2 ~ 0.9), and (3) robust FSC estimation that is independent of terrain/vegetation alpine heterogeneity. The latter is supported by a spatially uniform distribution of errors, and lack of correlation between terrain (slope, aspect, terrain shadow distribution), Normalized Difference Vegetation Index, and the error (r2 = 0)." @default.
• W2079797871 created "2016-06-24" @default.
• W2079797871 creator A5003990276 @default.
• W2079797871 creator A5017211285 @default.
• W2079797871 creator A5026716433 @default.
• W2079797871 creator A5041325286 @default.
• W2079797871 creator A5073060528 @default.
• W2079797871 date "2015-01-01" @default.
• W2079797871 modified "2023-10-16" @default.
• W2079797871 title "Fractional snow cover estimation in complex alpine-forested environments using an artificial neural network" @default.
• W2079797871 cites W1560807794 @default.
• W2079797871 cites W1752626349 @default.
• W2079797871 cites W1963700381 @default.
• W2079797871 cites W1964166287 @default.
• W2079797871 cites W1978125380 @default.
• W2079797871 cites W1979653734 @default.
• W2079797871 cites W1984177456 @default.
• W2079797871 cites W1985834113 @default.
• W2079797871 cites W1987352360 @default.
• W2079797871 cites W1987882549 @default.
• W2079797871 cites W1990226794 @default.
• W2079797871 cites W1993499995 @default.
• W2079797871 cites W1998952372 @default.
• W2079797871 cites W2002604925 @default.
• W2079797871 cites W2002867057 @default.
• W2079797871 cites W2007090431 @default.
• W2079797871 cites W2009026858 @default.
• W2079797871 cites W2014330917 @default.
• W2079797871 cites W2014978772 @default.
• W2079797871 cites W2017261638 @default.
• W2079797871 cites W2022106079 @default.
• W2079797871 cites W2024040169 @default.
• W2079797871 cites W2030214786 @default.
• W2079797871 cites W2033904036 @default.
• W2079797871 cites W2035308632 @default.
• W2079797871 cites W2035571004 @default.
• W2079797871 cites W2036045737 @default.
• W2079797871 cites W2037460094 @default.
• W2079797871 cites W2040001180 @default.
• W2079797871 cites W2044111667 @default.
• W2079797871 cites W2049628041 @default.
• W2079797871 cites W2055448925 @default.
• W2079797871 cites W2055970510 @default.
• W2079797871 cites W2061413577 @default.
• W2079797871 cites W2062459439 @default.
• W2079797871 cites W2063544218 @default.
• W2079797871 cites W2068753710 @default.
• W2079797871 cites W2079019836 @default.
• W2079797871 cites W2079454091 @default.
• W2079797871 cites W2080281207 @default.
• W2079797871 cites W2082003047 @default.
• W2079797871 cites W2082456610 @default.
• W2079797871 cites W2082776805 @default.
• W2079797871 cites W2085335861 @default.
• W2079797871 cites W2086418724 @default.
• W2079797871 cites W2087070363 @default.
• W2079797871 cites W2088292560 @default.
• W2079797871 cites W2090407929 @default.
• W2079797871 cites W2091397530 @default.
• W2079797871 cites W2094087960 @default.
• W2079797871 cites W2094158326 @default.
• W2079797871 cites W2096842752 @default.
• W2079797871 cites W2099577969 @default.
• W2079797871 cites W2100794131 @default.
• W2079797871 cites W2100861890 @default.
• W2079797871 cites W2103475795 @default.
• W2079797871 cites W2103497845 @default.
• W2079797871 cites W2103794190 @default.
• W2079797871 cites W2106363631 @default.
• W2079797871 cites W2108238008 @default.
• W2079797871 cites W2108478886 @default.
• W2079797871 cites W2110456190 @default.
• W2079797871 cites W2111747718 @default.
• W2079797871 cites W2117396433 @default.
• W2079797871 cites W2117706739 @default.
• W2079797871 cites W2122172326 @default.
• W2079797871 cites W2124195644 @default.
• W2079797871 cites W2125368795 @default.
• W2079797871 cites W2128462828 @default.
• W2079797871 cites W2130269771 @default.
• W2079797871 cites W2132060408 @default.
• W2079797871 cites W2134721717 @default.
• W2079797871 cites W2137340504 @default.
• W2079797871 cites W2137597204 @default.
• W2079797871 cites W2139094401 @default.
• W2079797871 cites W2142800341 @default.
• W2079797871 cites W2144120083 @default.
• W2079797871 cites W2144841545 @default.
• W2079797871 cites W2151456308 @default.
• W2079797871 cites W2152228856 @default.
• W2079797871 cites W2152509385 @default.
• W2079797871 cites W2155482699 @default.
• W2079797871 cites W2155529731 @default.
• W2079797871 cites W2156730686 @default.
• W2079797871 cites W2164453447 @default.
• W2079797871 cites W2165383220 @default.
• W2079797871 cites W2168360065 @default.
• W2079797871 cites W2170505850 @default.

• next