Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Similaire à Stress detection using fluorescence, narrow-band spectral indices and thermal imagery acquired from manned and unmanned aerial vehicles (20)
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Stress detection using fluorescence, narrow-band spectral indices and thermal imagery acquired from manned and unmanned aerial vehicles
1. Beyond Diagnostics: Insights and Recommendations from Remote Sensing
CIMMYT – México, December 2013
Stress detection using fluorescence,
narrow-band spectral indices and thermal
imagery acquired from manned and
unmanned aerial vehicles
Pablo Zarco-Tejada (JRC IES & IAS-CSIC)
http://quantalab.ias.csic.es
pablo.zarco@csic.es / pablo.zarco@jrc.ec.europa.eu
2. Institute for Sustainable
Agriculture (IAS)
National Research Council,
Spain (CSIC)
40 tenured researchers
250 staff / 3 departments
Agronomy
Plant Protection
Plant Breeding
RS Laboratory:
7-10 staff members
3. Crop stress indicators from RS
T
• Transpiration and CO2
absorption reduction
• Photosynthesis
reduction
Under water stress:
Temperature increases
Under nutrient stress conditions:
Photosynthetic pigment
degradation
4. BOREAS – NASA
Project
Canadian contribution –
Airborne Hyperspectral
Imager
CASI hyperspectral imager –
228 spectral bands @ 2 m
spatial resolution
8. Questions
Are these platforms
and multi-million
sensors operational
for our purposes ?
Can we use less
expensive
approaches ?
From leaf to canopy
can we “map”
stress ? Scaling up ?
9. Objectives
1. Identify pre-visual indicators of stress related to
physiological status (i.e. not only structure)
2. Evaluate thermal and hyperspectral indices in the context
of Precision Agriculture (and Phenotyping studies)
3. Test methods using micro-sensors on board UAVs and
small manned aircraft platforms
4. Develop the facility to provide 24-hour turn-around times
for flights conducted over thousands of hectares
38. Conclusions
1. Micro-hyperspectral and thermal cameras on board UAVs
and manned aircrafts enable the generation of stress maps
2. F, T and narrow-band indices demonstrate good relationships
with physiological indicators such as Gs, x and Pn
3. F retrieval using the FLD principle from micro hyperspectral
cameras is feasible from manned and UAVs
4. Low-cost remote sensing platforms and sensors can be used
with success in precision farming, conservation agriculture
and phenotyping studies
39. The QuantaLab – IAS – CSIC Team
Manned aircraft
facility
David Notario – Flight Operations
UAV facility
Alberto Hornero – Software Engineer
Rafael Romero – Image Processing Analyst
Calibration Facility
Alfredo Gómez – Cartographic Engineer
Alberto Vera – Electronics IT
40. Beyond Diagnostics: Insights and Recommendations from Remote Sensing
CIMMYT – México, December 2013
Stress detection using fluorescence,
narrow-band spectral indices and thermal
imagery acquired from manned and
unmanned aerial vehicles
Pablo Zarco-Tejada (JRC IES & IAS-CSIC)
http://quantalab.ias.csic.es
pablo.zarco@csic.es / pablo.zarco@jrc.ec.europa.eu