Estimation Of Annual Average Soil Loss: An Application Of Remote Sensing And Gis. Este artículo no está disponible.
Idioma: inglés
Editorial: Lap Lambert Academic Publishing, 2013
- Tapa blanda
- Nuevo
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Descripción del artículo del vendedor
68 pages. 8.66x5.91x0.16 inches. In Stock.
N° de ref. del artículo 3659466204
- Título
- Estimation Of Annual Average Soil Loss: An Application Of Remote Sensing And Gis
- Autor
- Mandal, Sakti; Mandal, Sakti
- Editorial
- Lap Lambert Academic Publishing
- Año de publicación
- 2013
- Estado
- Brand New
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 3659466204
- ISBN 13
- 9783659466205
- Peso del artículo
- 0,15 kilogramos
Remote Sensing (RS) and Geographic Information Systems (GIS) are useful tools in hydrological analysis and natural resource management. The application of RS and GIS techniques leads to estimate soil loss based on different parameters. RUSLE (Revised Universal Soil Loss Equation) model is used for soil loss estimation. Different parameters, namely the rainfall and runoff factor (R), soil erodibility factor (K), slope length and steepness factor (LS), crop management factor (C) and conservation practice factor (P), that are the mandatory inputs to RUSLE, have been either derived from remote sensing data or through conventional data collection systems.
“Sinopsis” puede pertenecer a otra edición de este título.
Reseña del editor
Remote Sensing (RS) and Geographic Information Systems (GIS) are useful tools in hydrological analysis and natural resource management. The application of RS and GIS techniques leads to estimate soil loss based on different parameters. RUSLE (Revised Universal Soil Loss Equation) model is used for soil loss estimation. Different parameters, namely the rainfall and runoff factor (R), soil erodibility factor (K), slope length and steepness factor (LS), crop management factor (C) and conservation practice factor (P), that are the mandatory inputs to RUSLE, have been either derived from remote sensing data or through conventional data collection systems.
“Acerca de” puede pertenecer a otra edición de este título.