## 2 Methodology  
As was mentioned above, the objective of this paper is to determine and suggest the altitude of the sensor and minimum mapping size of pure chemical for finding traces of chemicals with an accuracy above 70%, as shown in conceptual Figure 2. The approach used to achieve this objective is shown in Figures 3 and 4. The experiments were conducted in outdoor conditions and suitable altitude and minimum mapping size of the chemicals were identified using the SVM model and spectral library developed in [19]. The principal component analysis and first derivative were used to select 22 optimal wavelengths out of 144 wavelengths in the range of 400-1000 nm. These selected wavelengths showed distinct spectral features and were input to the SVM model. The algorithm selects the most suitable hyperplane on the basis of maximum margin between each class. For classification of spectral data SVM has been proved as a reliable and efficient method. In this study, SVM was performed on R studio using a radial bias function along with 10-fold cross validation, which explain the relation between the target variable and independent variable, and grid search procedure. Classification accuracy is used to assess the performances of SVM models. Chemical samples of AN, TNT and C4 were prepared in different sizes which varied from 0.25*0.25 cm to 1 cm*1 cm as shown in Figure 3. The dimensions of the chemical samples were measured accurately using the measuring instruments and distributed over the soil, which acted as the background material. The experiment was performed on a bright sunny morning at 10 am, with sun azimuth equal to 94, and altitude above horizon equal to 53.6. The hyperspectral sensor was placed on the vehicle at different altitude varying from 40 cm to 150 cm. The speed of the vehicle is determined using the in-built software of the sensor (Cube Creator by BaySpec). The speed of the vehicle holding the sensor is suggested to user depending upon the side overlap the user has requested for the mentioned altitude. These chemical samples were placed over the soil samples and marked with different colors for accuracy assessment in later part of the experiment. The reflectance data was obtained by BaySpec OCI F hypespectral sensor, which consists of a charge coupled device that has a readout mode. The images were acquired by pushbroom scanning at 45 frames per second with a field of view of 22\({}^{\circ}\), focal length of 16 mm in 144 bands with spectral resolution of 4.16 nm from 400-1000 nm. Hyperspectral cube was created for the chemical samples at different heights using pushbroom scanning. To detect the traces of the chemicals, present in the hyperspectral cube, the image is converted into tiff format which goes as an input to the SVM model. The SVM model determines the traces of the chemical samples present and accuracy assessment is done for all the images acquired at different altitude of the sensor. The suitable altitude is selected for the next experiment where the altitude is fixed and the MMS size of the chemicals are varied. The hyperspectral cube is generated and the SVM model is used to determine how many samples of each MMS were detected correctly and incorrectly. The conceptual design of the experiment is shown in the Figure 4, which gives information on how the experiment was conducted in terms of varying the altitude of the sensor and size of the chemical samples.  
Figure 3: Steps for conducting experiment to suggest altitude of sensor in outdoor conditions.  
Figure 2: Conceptual design for the experiments to be conducted.