Reference number : GC-2017-Q4-01628, amendment number : , agreement type : G, recipient legal name : Shahbazi, Mozhdeh (University of Calgary), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Mission Geospatial (MGeo) is a company with extensive experience in providing professional and technical_x000D_
consulting services in different domains of surveying, remote sensing, and geospatial information systems_x000D_
(GIS). They are seeking a feasible, affordable and sustainable solution for monitoring the health status of_x000D_
potato crops. Therefore, MGeo has contacted Dr. Shahbazi to conduct a research project; the aim of this project_x000D_
is using techniques of data mining for detecting water-stressed and disease-infected crops. The input data_x000D_
includes imagery captured at multiple spectral bands and three-dimensional (3D) models reconstructed from_x000D_
images. The advantages of this solution are fourfold: i) it does not attempt to establish a direct mathematical_x000D_
relationship between spectral information and biophysical attributes of plants; ii) the characteristics of stressed_x000D_
or diseased plants and the soil in which they are growing are learnt indirectly using data-mining techniques; iii)_x000D_
the effect of soil features on the plants is acknowledged during this learning process; and iv) by utilizing 3D_x000D_
information, the impact of canopy structure and height on the results is considered as well. The developed_x000D_
solution for MGeo will meet their clients' needs in terms of efficiency (applicable in large industrial scales),_x000D_
affordability (accessible to both large industry groups and smallholder farmers) and precision (reliable and_x000D_
repeatable with known accuracy limits). Also, this solution for automatic crop disease detection offers a_x000D_
promising step towards sustainable agriculture which promotes both economic stability for Canadian farmers_x000D_
and food security for Canadian citizens., program purpose french : Mission Geospatial (MGeo) is a company with extensive experience in providing professional and technical_x000D_
consulting services in different domains of surveying, remote sensing, and geospatial information systems_x000D_
(GIS). They are seeking a feasible, affordable and sustainable solution for monitoring the health status of_x000D_
potato crops. Therefore, MGeo has contacted Dr. Shahbazi to conduct a research project; the aim of this project_x000D_
is using techniques of data mining for detecting water-stressed and disease-infected crops. The input data_x000D_
includes imagery captured at multiple spectral bands and three-dimensional (3D) models reconstructed from_x000D_
images. The advantages of this solution are fourfold: i) it does not attempt to establish a direct mathematical_x000D_
relationship between spectral information and biophysical attributes of plants; ii) the characteristics of stressed_x000D_
or diseased plants and the soil in which they are growing are learnt indirectly using data-mining techniques; iii)_x000D_
the effect of soil features on the plants is acknowledged during this learning process; and iv) by utilizing 3D_x000D_
information, the impact of canopy structure and height on the results is considered as well. The developed_x000D_
solution for MGeo will meet their clients' needs in terms of efficiency (applicable in large industrial scales),_x000D_
affordability (accessible to both large industry groups and smallholder farmers) and precision (reliable and_x000D_
repeatable with known accuracy limits). Also, this solution for automatic crop disease detection offers a_x000D_
promising step towards sustainable agriculture which promotes both economic stability for Canadian farmers_x000D_
and food security for Canadian citizens., agreement title english : Using techniques of data mining for detecting water-stressed and disease-infected potato crops, agreement title french : Using techniques of data mining for detecting water-stressed and disease-infected potato crops, agreement number : EGP, agreement value : 25000.0, agreement start date : 2018-03-07, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada