The Experts below are selected from a list of 180 Experts worldwide ranked by ideXlab platform
Budiman Minasny - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of iron forms and Features in the dried lake bed of Urmia Lake of Iran
Geoderma Regional, 2020Co-Authors: Amin Mousavi, Farzin Shahbazi, Shahin Oustan, Ali Asghar Jafarzadeh, Budiman MinasnyAbstract:Abstract Urmia Lake, located in Iran, has a unique Pedological Feature as fresh soil materials are being exposed as the lake is shrinking. Overuse of its water resources has caused its water level to drop, particularly in the east shore of that lake. This consequence has caused a serious environmental risk, but created a rare opportunity to investigate the spatial distribution of six iron forms and Features, i.e., total iron (Fet); dithionite-extractable iron (Fed); oxalate-extractable iron (Feo); crystalline iron (Fed-Feo); activity ratio (Feo/Fed) and crystallinity ratio (Fed-Feo/Fet). In total, 130 soil samples were taken from three strata based on their proximity to the lake. Spectral indices derived from Landsat-8 OLI imagery acquired in July 2017 were used as environmental covariates in spatial models using Random Forests (RF) technique. The calibrated RF model for 2017 allowed us to backcast data for 2013 and 2015. The results showed that the iron forms and Features varied primarily as a function of distance from the shore. Soil ripening process was also demonstrated in the east shore of Urmia Lake. Overall, this study showed the possibility of a combination of spectral imageries and spatial models to predict the dynamic environment of iron forms.
Amin Mousavi - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of iron forms and Features in the dried lake bed of Urmia Lake of Iran
Geoderma Regional, 2020Co-Authors: Amin Mousavi, Farzin Shahbazi, Shahin Oustan, Ali Asghar Jafarzadeh, Budiman MinasnyAbstract:Abstract Urmia Lake, located in Iran, has a unique Pedological Feature as fresh soil materials are being exposed as the lake is shrinking. Overuse of its water resources has caused its water level to drop, particularly in the east shore of that lake. This consequence has caused a serious environmental risk, but created a rare opportunity to investigate the spatial distribution of six iron forms and Features, i.e., total iron (Fet); dithionite-extractable iron (Fed); oxalate-extractable iron (Feo); crystalline iron (Fed-Feo); activity ratio (Feo/Fed) and crystallinity ratio (Fed-Feo/Fet). In total, 130 soil samples were taken from three strata based on their proximity to the lake. Spectral indices derived from Landsat-8 OLI imagery acquired in July 2017 were used as environmental covariates in spatial models using Random Forests (RF) technique. The calibrated RF model for 2017 allowed us to backcast data for 2013 and 2015. The results showed that the iron forms and Features varied primarily as a function of distance from the shore. Soil ripening process was also demonstrated in the east shore of Urmia Lake. Overall, this study showed the possibility of a combination of spectral imageries and spatial models to predict the dynamic environment of iron forms.
Ali Asghar Jafarzadeh - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of iron forms and Features in the dried lake bed of Urmia Lake of Iran
Geoderma Regional, 2020Co-Authors: Amin Mousavi, Farzin Shahbazi, Shahin Oustan, Ali Asghar Jafarzadeh, Budiman MinasnyAbstract:Abstract Urmia Lake, located in Iran, has a unique Pedological Feature as fresh soil materials are being exposed as the lake is shrinking. Overuse of its water resources has caused its water level to drop, particularly in the east shore of that lake. This consequence has caused a serious environmental risk, but created a rare opportunity to investigate the spatial distribution of six iron forms and Features, i.e., total iron (Fet); dithionite-extractable iron (Fed); oxalate-extractable iron (Feo); crystalline iron (Fed-Feo); activity ratio (Feo/Fed) and crystallinity ratio (Fed-Feo/Fet). In total, 130 soil samples were taken from three strata based on their proximity to the lake. Spectral indices derived from Landsat-8 OLI imagery acquired in July 2017 were used as environmental covariates in spatial models using Random Forests (RF) technique. The calibrated RF model for 2017 allowed us to backcast data for 2013 and 2015. The results showed that the iron forms and Features varied primarily as a function of distance from the shore. Soil ripening process was also demonstrated in the east shore of Urmia Lake. Overall, this study showed the possibility of a combination of spectral imageries and spatial models to predict the dynamic environment of iron forms.
Shahin Oustan - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of iron forms and Features in the dried lake bed of Urmia Lake of Iran
Geoderma Regional, 2020Co-Authors: Amin Mousavi, Farzin Shahbazi, Shahin Oustan, Ali Asghar Jafarzadeh, Budiman MinasnyAbstract:Abstract Urmia Lake, located in Iran, has a unique Pedological Feature as fresh soil materials are being exposed as the lake is shrinking. Overuse of its water resources has caused its water level to drop, particularly in the east shore of that lake. This consequence has caused a serious environmental risk, but created a rare opportunity to investigate the spatial distribution of six iron forms and Features, i.e., total iron (Fet); dithionite-extractable iron (Fed); oxalate-extractable iron (Feo); crystalline iron (Fed-Feo); activity ratio (Feo/Fed) and crystallinity ratio (Fed-Feo/Fet). In total, 130 soil samples were taken from three strata based on their proximity to the lake. Spectral indices derived from Landsat-8 OLI imagery acquired in July 2017 were used as environmental covariates in spatial models using Random Forests (RF) technique. The calibrated RF model for 2017 allowed us to backcast data for 2013 and 2015. The results showed that the iron forms and Features varied primarily as a function of distance from the shore. Soil ripening process was also demonstrated in the east shore of Urmia Lake. Overall, this study showed the possibility of a combination of spectral imageries and spatial models to predict the dynamic environment of iron forms.
Farzin Shahbazi - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of iron forms and Features in the dried lake bed of Urmia Lake of Iran
Geoderma Regional, 2020Co-Authors: Amin Mousavi, Farzin Shahbazi, Shahin Oustan, Ali Asghar Jafarzadeh, Budiman MinasnyAbstract:Abstract Urmia Lake, located in Iran, has a unique Pedological Feature as fresh soil materials are being exposed as the lake is shrinking. Overuse of its water resources has caused its water level to drop, particularly in the east shore of that lake. This consequence has caused a serious environmental risk, but created a rare opportunity to investigate the spatial distribution of six iron forms and Features, i.e., total iron (Fet); dithionite-extractable iron (Fed); oxalate-extractable iron (Feo); crystalline iron (Fed-Feo); activity ratio (Feo/Fed) and crystallinity ratio (Fed-Feo/Fet). In total, 130 soil samples were taken from three strata based on their proximity to the lake. Spectral indices derived from Landsat-8 OLI imagery acquired in July 2017 were used as environmental covariates in spatial models using Random Forests (RF) technique. The calibrated RF model for 2017 allowed us to backcast data for 2013 and 2015. The results showed that the iron forms and Features varied primarily as a function of distance from the shore. Soil ripening process was also demonstrated in the east shore of Urmia Lake. Overall, this study showed the possibility of a combination of spectral imageries and spatial models to predict the dynamic environment of iron forms.