| Título: | Improved Agricultural Management Using Remote Sensing to Estimate Water Stress Indices |
| Autores: | Cagatay Tanriverdi |
| Fecha: | 2010-08-10 |
| Publicador: | Applied Remote Sensing |
| Fuente: |
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| Tipo: |
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| Tema: |
Precision farming (PF); Crop water stress index (CWSI); Water deficit index (WDI) |
| Descripción: | Irrigation water is a principal issue for agricultural management throughout the world. Precision farming (PF) is a method that facilitates better agricultural management. Global positioning systems (GPS), geographic information systems (GIS), remote sensing (RS) and variable rate application (VRA) are components of PF. RS has the potential to be an important source of spatial data, which is very important in representative information of the field. Water Stress Indices (WSI), namely Crop Water Stress Index (CWSI) and Water Deficit Index (WDI), are useful tools for optimizing irrigation time. The effect of areas of bare soil on remotely-sensed canopy temperature (Ts) data is a major problem in establishing CWSI during the early stages of growth. Thus, WDI is a better index when compared with CWSI. Both CWSI and WDI can be determined by two different techniques. These may be measured using conventional methods and estimated by applying PF components to collect the relevant remotely sensed data to determine CWSI and WDI. Estimating these indices using remote technique has many advantages, including cost, time and labor savings, especially for large agricultural fields, due to the reduction in fieldwork |
| Idioma: | Inglés |
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