## 4 Discussion  
### Influence MMS and Altitude of Sensor  
The effect of the altitude of the sensor and spatial resolution on the overall accuracy of the SVM classification model has been shown in the previous section. Based on the results obtained from different experiments, conducted in this study, it was observed that the image with a finer resolution achieved higher accuracy but at a lower altitude which might not be feasible in real applicability. While, images collected at a coarser resolution, but at a height of 150 cm, achieved an accuracy of around 65% because the images contained traces of different chemical and soil as background. Therefore, with the increase in altitude, the dominance of the reflectance in the pixel was more from soil instead of pure chemicals, which leads to decrease in accuracy and misclassification. The misclassification error can be grouped as a pure pixel classification error or mixed pixel classification error. The mixed pixel between the soil and the chemical was the major reason for lower accuracy. To determine the suggested MMS for trace detection of chemicals the spatial resolution of the image was kept fixed and the pixels were subdivided into 0.5, 0.33 and 0.25 cm MMS. For studying the effect of MMS on the accuracy the image of chemical at resolution of 0.028 cm at an altitude of 90 cm, consisting of 38 pixels was reduced to 19, 13 and 9 pixels. As discussed earlier, the misclassification occurred due to mixed pixel where a pixel is made up of from two or more classes. This kind of error occurs often in the boundaries between two classes and is also referred to as boundary effect. From the results it can be seen and discussed that when the MMS was 1 cm in that case 30 pixels out of 38 pixels were correctly classified whereas the pixels around the boundary were misclassified. Similarly, for 0.5 MMS the 14 pixels out of 19 were misclassified and similarly pixels around the boundary which had dominance of soil were misclassified. However, when MMS was decreased to 0.25 cm 4 pixels out of 9 were only classified correctly. For practical applicability of the hyperspectral imaging system, the user needs to decide the altitude and MMS according the accuracy they want to achieve, which could be either the screening phase or critical phase. One of major factors that affects the real applicability is the amount of storage required, processing time for creation of hyperspectral cube. The speed of the vehicle mounted with sensor determines coverage area in a given time and number of raw images that would be acquired. From the experiment firstly suitable altitude was determined. A total of 90 cm is the suggested altitude for the user as it is easier to deploy a sensor at an altitude of 90 cm rather 40 cm, 60 cm in an automated vehicle. The coverage area or swath at 40 cm, 60 cm is comparatively low to 90 cm. At 90 cm the user can expect an accuracy of more than 75%, which would decrease if the altitude is increased to 150 cm. While, 90-120 cm can be suggested altitude for the sensor to be deployed in real ground application. After determining a suitable height of 90 cm, suitable MMS was determined (0.5 cm) as the accuracy achieved was more than 70% and it had minimal effect of mixed pixel problem if compared to 0.33 cm to 0.25 cm, later two MMS had a very low accuracy almost equal to 50%. For 90 cm height the speed can be varied from 3.5 cm/s to 17.5 cm/s depending upon the required overlapping by the user. The suggested overlap is 70%, which results in a uniform stitching in the raw images for creation of hyperspectral cube. For 70% overlap, the suggested speed is 10.5 cm/s, whereas it could be 17.5 cm/s for 50% overlap and 3.5 cm/s for 90% overlap. For real ground conditions controlling the automated vehicle at 3.5 cm/s is not feasible as it would a much higher time to cover the area of interest. If the vehicle is moving at a speed of 10.5 cm/s to cover an area of 10 m\({}^{2}\) at altitude of 90 cm, the system would acquire 285 raw images with storage of 3.5 GB.