**3.2 Image maps**

*Military Engineering*

**Figure 3.**

*during phenological cycle for EVI.*

**96**

**Figure 4.**

*during phenological cycle for SR.*

a different response at different phenological stages. It may be seen clearly in the Flowering stage that there is a distinction between area (a) and area (b). **Figure 2** presents a typical example of the spectral profile of area (a) and area (b) using the NDVI. There is an upward trend of area (b) (blue line) compared with area (a) (red line) in which there is a downward trend, throughout the phenological

*Vegetation values for area (a) for (buried structure, red dots) and area (b) for (vegetated area, blue line)* 

*Vegetation values for area (a) for (buried structure, red dots) and area (b) for (vegetated area, blue line)* 

Ground spectroradiometric measurements can provide the spectral response of the vegetation in detail [29]. The analysis of the spectral data shows the maps of vegetation indices (NDVI, EVI, and SR) for area (a) (**Figure 5**) and area (b) (**Figure 6**), during Flag Leaf Emerging stage. Comparing area (a) with area (b) using NDVI (**Figure 5**), it appears that area (b) obtains lower values due to the nonexistence of underground structures, while area (a) has similar vegetation but higher NDVI values due to the existence of underground structures. In addition, using the EVI (**Figure 6**), area (a) has higher values due to the existence of underground structures, while area (b) has lower values due to nonexistence of structures. Similarly, using the SR vegetation index (**Figure 6**), area (b) has clearly lower values due to the existence of underground structures, while area (a) (**Figure 5**) has higher values due to nonexistence of structures. The green color illustrates high value of indices that distinguish the existence of structures. The existence of underground structure can be clearly seen by comparing area (a) with area (b), during the Head Emerging stage. The analysis of the spectral data shows the maps of vegetation indices (NDVI, EVI, and SR) for area (a) (**Figure 7**) and area (b)

**Figure 5.** *Image maps showing NDVI, EVI, and SR field data for area (a) during Flag Leaf Emerging stage.*

**Figure 6.** *Image maps showing NDVI, EVI, and SR field data for area (b) during Flag Leaf Emerging stage.*

**Figure 7.** *Image maps showing NDVI, EVI, and SR field data for area (a) during Head Emerging Stage.*

(**Figure 8**). In comparing area (a) with area (b) using the NDVI (**Figure 8**), area (b) has higher values due to the nonexistence of underground structures, while area (a) (**Figure 7**) has similar vegetation but lower NDVI values due to the existence of underground structures. Likewise, using the EVI, area (a) (**Figure 7**) has lower values due to the existence of underground structures, while area (b) (**Figure 8**) has higher values due to nonexistence of structures.

Using the SR vegetation index (**Figure 7**), area (a) tends to exhibit a difference with respect to area (b) (**Figure 8**). More specifically, in target area (a) (**Figure 7**), the reflectance response is lower than area (b) (**Figure 8**), which indicates that the

**99**

*Detecting Underground Military Structures Using Field Spectroscopy*

resulting differences reinforce the existence/nonexistence of underground structures. It can be argued that soil also contributed to the reflectance measurements. The variations between the two cases, namely, in the presence and in the absence of military underground structures, can result in better interpretations of images for

*Image maps showing NDVI, EVI, and SR field data for area (b) during Head Emerging Stage.*

Field spectroscopy can support satellite remote sensing studies for monitoring systematically critical areas of interest including the detection of underground

The application of remote sensing in defense and security merges the technological improvements of remote sensing sensors with military needs to improve the quality of information retrieved from remote sensing data. Indeed, decision-making authorities can benefit from such efficient space imaging technology of underground targets. The advantages of using vegetation indices as proxy variables for intercalibration among existing sensors are the low sensitivity to the uncertainties in atmospheric correction and the variation in the satellite viewing angle [30]. As shown in this paper, vegetation indices can corroborate areas of possible military underground structure. In comparing the two areas, the spatial distributions of VIs exhibit no table differences (**Figures 7** and **8**). This is clear in **Figure 8**, where image maps illustrate the differences between the two areas using NDVI, EVI and SR Vegetation Indices. Mostly SR vegetation index is used for defining areas where military underground

Consequently, the near-infrared (NIR) band of Landsat 8 sensor could be useful to identify the underground structure. It is apparent that the waveband analysis of the Landsat 8 sensor distinguishes between the two study sites. Monitoring variations of the NIR spectrum during the life cycle of vegetation is a key parameter for the field spectroscopy for the detection of military underground structures using

*DOI: http://dx.doi.org/10.5772/intechopen.86690*

the detection and identification of crop marks.

**4. Conclusions**

structures are present.

remote sensing techniques.

bunkers.

**Figure 8.**

*Detecting Underground Military Structures Using Field Spectroscopy DOI: http://dx.doi.org/10.5772/intechopen.86690*

**Figure 8.** *Image maps showing NDVI, EVI, and SR field data for area (b) during Head Emerging Stage.*

resulting differences reinforce the existence/nonexistence of underground structures. It can be argued that soil also contributed to the reflectance measurements. The variations between the two cases, namely, in the presence and in the absence of military underground structures, can result in better interpretations of images for the detection and identification of crop marks.
