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BELAIR HESBANIA 2015 (R-6643)
The aim of the Belair - Hesbania project is to collect detailed field and Remote Sensing (UAV, airborne APEX, and spaceborne) data needed to improve the monitoring, steering and managing of capital intensive perennial fruit orchards and areal intensive potato fields. Special attention will be paid to the detection of nutrient stress in fruit crops. In addition various types of potatoes under different N fertilization regimes will be monitored. The collected data will be made available to, in first instance, partnering research institutions for (1) hyperspectral vegetation stress detection at field, airborne and spaceborne scale, and multitemporal unmixing from airborne and spaceborne imagery (VITO), (2) virtual orchard modelling to validate biophysical processes in a controlled environment and to mimic characteristics of future satellites, such as Sentinel-2 (KUL), (3) chlorophyll fluorescence image analysis combined with fast fluorescence induction kinetics and quenching analysis of vegetation (UHasselt), (4) user need definition and sharing of fruit orchard expertise (PcFruit), (5) algorithm development, data and decision fusion techniques (UA), (6) crop monitoring and modeling (CRA-w), soil organic carbon monitoring (UCL), and validation of PROBA-V imagery (VITO).
Date:1 Jun 2015 → 31 May 2016
Keywords:FRUIT QUALITY, IMAGE ANALYSIS
Disciplines:Plant biology, Agricultural plant production, Horticultural production