Your search found 5 records
1 Soeharso, H. P.; Murty, V. V. M.; Enclona, E. A.. 1995. A procedure for studying environmental issues in large irrigation systems. VISI Irigasi Indonesia, 11(5):53-69.
Irrigation systems ; Large-scale systems ; Environmental effects ; Irrigation effects ; Assessment ; Water balance ; Models / Indonesia
(Location: IWMI-HQ Call no: P 4194 Record No: H018016)
2 Thenkabail, P. S.; Hall, J.; Lin, T.; Ashton, M. S.; Harris, D.; Enclona, E. A.. 2003. Detecting floristic structure and pattern across topographic and moisture gradients in a mixed species Central African forest using IKONOS and Landsat - 7 ETM + images. International Journal of Applied Earth Observation, 4:255-270.
(Location: IWMI-HQ Call no: P 6620 Record No: H033320)
3 Enclona, E. A.; Thenkabail, P. S.; Celis, D.; Diekmann, J. 2003. Within-field wheat yield prediction from IKONOS data: a new matrix approach. International Journal of Remote Sensing, 25(2):377-388.
(Location: IWMI-HQ Call no: P 6622 Record No: H033322)
This study demonstrates a unique matrix approach to determine within-field variability in wheat yields using fine spatial resolution 4m IKONOS data. The matrix approach involves solving a system of simultaneous equations based on IKONOS data and post-harvest yields available at entire field scale.This approach was compared with a regression-based modelling approach involving field-sensor measured yields and the corresponding IKONOS
measured indices and wavebands. The IKONOS data explained 74–78% variability in wheat yield. This is a significant result since the finer spatial resolution leads to capturing greater spatial variability and detail in landscape
relative to coarser spatial resolution data. A pixel-by-pixel mapping of wheat yield variability highlights the fine spatial detail provided by IKONOS data for precision farming applications.
measured indices and wavebands. The IKONOS data explained 74–78% variability in wheat yield. This is a significant result since the finer spatial resolution leads to capturing greater spatial variability and detail in landscape
relative to coarser spatial resolution data. A pixel-by-pixel mapping of wheat yield variability highlights the fine spatial detail provided by IKONOS data for precision farming applications.
4 Thenkabail, Prasad S.; Enclona, E. A.; Ashton, M. S.; Legg, C.; de Dieu, M. J. 2004. Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests. Remote Sensing of Environment, 90(1):23-43.
(Location: IWMI-HQ Call no: IWMI 634.9 G100 THE Record No: H033904)
5 Thenkabail, Prasad S.; Enclona, E. A.; Ashton, M. S.; Van Der Meer, B. 2004. Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications. Remote Sensing of Environment, 91(3-4):354-376.
(Location: IWMI-HQ Call no: IWMI 621.3678 G190 THE Record No: H034569)
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