Ebenezer yemi ogunbadewa (6 Ergebnisse)
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Taschenbuch. Zustand: Neu. Evaluating micro-satellite data for monitoring environmental dynamics | Advances in micro-satellite remote sensing | Ebenezer Yemi Ogunbadewa | Taschenbuch | 196 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838386348 | Verantwortliche Person für die EU: BoD - Books on Demand, In de…Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Quantitative monitoring of vegetation change over time is essential in understanding the environmental processes of which are importance in climate change and global warming models. However, obtaining such information has been a chall…enge especially for vegetation phenology due to the lack of appropriate methods for quantitative assessment.The aim of this research was to test the relationships between ground-based measurement of leaf area index (LAI) and vegetation indices (VI) derived from satellite remote sensing instruments to quantitatively monitor vegetation dynamics in a broadleaf and coniferous forest in the UK. A regression model was used to predict LAI at both sites and the resulting estimates of LAI had a root mean square error of 0.51 at the broadleaf site and 1.1 at the coniferous forest site. Improvements in the accuracy of ground-based LAI measurements and radiometric and atmospheric correction of the data are expected to increase the accuracy of such LAI estimates in future. 196 pp. Englisch.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: OGUNBADEWA Ebenezer YemiEbenezer Yemi Ogunbadewa,PhD: A senior lecturer in remote sensing (RS) and geographical information systems(GIS) at Adekunle Ajasin University, Nigeria. He holds B.Sc and M.Sc Geog…raphy from Ilorin and Lagos U.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Quantitative monitoring of vegetation change over time is essential in understanding the environmental processes of which are importance in climate change and global warming models. However, obtaining such information has been a challenge… especially for vegetation phenology due to the lack of appropriate methods for quantitative assessment.The aim of this research was to test the relationships between ground-based measurement of leaf area index (LAI) and vegetation indices (VI) derived from satellite remote sensing instruments to quantitatively monitor vegetation dynamics in a broadleaf and coniferous forest in the UK. A regression model was used to predict LAI at both sites and the resulting estimates of LAI had a root mean square error of 0.51 at the broadleaf site and 1.1 at the coniferous forest site. Improvements in the accuracy of ground-based LAI measurements and radiometric and atmospheric correction of the data are expected to increase the accuracy of such LAI estimates in future.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch.
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Quantitative monitoring of vegetation change over time is essential in understanding the environmental processes of which are importance in climate change and global warming models. However, obtaining such information has been a challenge…especially for vegetation phenology due to the lack of appropriate methods for quantitative assessment.The aim of this research was to test the relationships between ground-based measurement of leaf area index (LAI) and vegetation indices (VI) derived from satellite remote sensing instruments to quantitatively monitor vegetation dynamics in a broadleaf and coniferous forest in the UK. A regression model was used to predict LAI at both sites and the resulting estimates of LAI had a root mean square error of 0.51 at the broadleaf site and 1.1 at the coniferous forest site. Improvements in the accuracy of ground-based LAI measurements and radiometric and atmospheric correction of the data are expected to increase the accuracy of such LAI estimates in future.
