Using techniques of data mining for detecting water-stressed and disease-infected potato crops

使命地理空间（MGeo）是一家在测量、遥感和地理空间信息系统（GIS）的不同领域提供专业和技术咨询服务的公司。他们正在寻求一种可行的、负担得起的和可持续的解决方案来监测马铃薯作物的健康状况。因此，MGeo联系了Shahbazi博士进行一个研究项目；本项目的目的是利用数据挖掘技术检测缺水和病虫害作物。输入数据包括在多个光谱波段捕获的图像和从图像重建的三维（3D）模型。该解决方案的优点有四：1)它不试图建立光谱信息与植物生物物理属性之间的直接数学关系；Ii)利用数据挖掘技术间接了解受胁迫或患病植物的特征及其生长的土壤；Iii)在这个学习过程中，土壤特征对植物的影响得到了承认；iv)利用三维信息，考虑了冠层结构和高度对结果的影响。为MGeo开发的解决方案将满足客户在效率（适用于大型工业规模），可负担性（适用于大型工业集团和小农）和精度（可靠且可重复，已知精度限制）方面的需求。此外，这种作物病害自动检测解决方案为可持续农业迈出了有希望的一步，既促进了加拿大农民的经济稳定，又促进了加拿大公民的粮食安全。

Mission Geospatial (MGeo) is a company with extensive experience in providing professional and technicalconsulting services in different domains of surveying, remote sensing, and geospatial information systems(GIS). They are seeking a feasible, affordable and sustainable solution for monitoring the health status ofpotato crops. Therefore, MGeo has contacted Dr. Shahbazi to conduct a research project; the aim of this projectis using techniques of data mining for detecting water-stressed and disease-infected crops. The input dataincludes imagery captured at multiple spectral bands and three-dimensional (3D) models reconstructed fromimages. The advantages of this solution are fourfold: i) it does not attempt to establish a direct mathematicalrelationship between spectral information and biophysical attributes of plants; ii) the characteristics of stressedor diseased plants and the soil in which they are growing are learnt indirectly using data-mining techniques; iii)the effect of soil features on the plants is acknowledged during this learning process; and iv) by utilizing 3Dinformation, the impact of canopy structure and height on the results is considered as well. The developedsolution for MGeo will meet their clients' needs in terms of efficiency (applicable in large industrial scales),affordability (accessible to both large industry groups and smallholder farmers) and precision (reliable andrepeatable with known accuracy limits). Also, this solution for automatic crop disease detection offers apromising step towards sustainable agriculture which promotes both economic stability for Canadian farmersand food security for Canadian citizens.