**4. Detection of archaeological sites based on remote sensing techniques**

massol Castle found that for the majority of the time periods, the PM10 readings exceeded the

**Figure 10.** AOT levels in the Limassol area. High AOT levels are noted in the area near the Limassol Castle.

**0**

**200**

**400**

**600**

**800**

**1000**

**1200**

A similar approach was followed for the Paphos town using daily MODIS AOT data. The re‐ sults have shown that 54% of the measurements for air quality was above the threshold of AOT 300 (AOT 0.300) (see Figure 11). This analysis suggest that cultural heritage sites near the Pa‐ phos town (e.g. *Nea Paphos, Tombs of the Kings* etc) are exposed to air pollutants half the time.

**Paphos AOT values**

**Figure 11.** Paphos AOT values (sample = 109 measurements) in blue. In red circle is the threshold air quality limit of 300 (AOT 0.300). In the y-axis, AOT value is multiplied by 1000 (to match MODIS data) (Themistocleous et al., 2012a).

**Paphos AOT Air Quality Threshold**

limit value (50 μg/m3), indicating a high level of air pollution in the area.

72 Remote Sensing of Environment: Integrated Approaches

Several Neolithic settlements ("magoules") are located in the Thessalian plain in central Greece. These sites are typically found as low hills raised up to 5-10 m. Alexakis et al., (2009; 2011) has recently shown that the detection of several unknown sites is possible based on remote sensing and GIS analysis. The study aimed to combine several types of remote sens‐ ing data (e.g. Landsat TM/ETM+, ASTER, Hyperion, IKONOS) and DEM in order to im‐ prove the detection of these subsurface remains (Figure 12). The satellite data were statistically analyzed, together with other environmental parameters, to examine any kind of correlation between environmental, archaeological and satellite data. Moreover, different methods were compared for the detection of Neolithic settlements. The results of the study suggested that the complementary use of different imagery can provide more satisfactory results.

Further to the Alexakis study, Agapiou et al., (2012a) argued that the detection of the settle‐ ments is possible based on ground spectroradiometric measurements. Several spectroradio‐ metric measurements have indicated that each magoula has its own spectral characteristics related to its own morphological characteristics. The study has found that the highest peak of the magoula tends to give high NDVI and SR values (similar to the flat – healthy regions) while the slope of the magoula has lowest NDVI and SR values (and for the other indices as well). The extraction of each magoula requires further analysis and enhancement techniques in cases where the spatial resolution of the satellite image used is low. Local histogram en‐ hancements can identify magoules as a small difference of NDVI values at the same parcel (Figure 13).

**Figure 12.** Magoula *Neraida* using ASTER image (left). Magoula *Melissa 1* using IKONOS image (RGB - 321) (right).

Similar results were found following the application of the Tasselled Cap algorithm (Figure 14 to a series of Landsat TM/ETM+ multispectral images. The Tasselled Cap transformation is used to enhance spectral information for Landsat images, and it was specially developed for vegetation studies. The first three bands of the Tasseled Cap algorithm result are charac‐ terized as follow: band 1: brightness (measure of soil); band 2: greenness (measure of vegeta‐ tion); band 3: wetness (interrelationship of soil and canopy moisture).

Phenological studies of crops for the detection of buried archaeological remains were al‐ so evaluated (Agapiou et al., 2012b) It was found that the phenological cycle of crops for 'archaeological' and 'non archaeological areas' can be used as a "remote" approach in or‐ der to locate buried architecture remains. In Figure 15, the phenological cycle of an ar‐ chaeological site (*Almyros II*) and the phenological cycle of a healthy site (Site 3) are examined. A small NDVI difference is evident (Case A, Figure 15) which is associated with buried archaeological remains. This is due to the fact that soil over the archaeologi‐ cal remains seems to have a different moisture content compared to their surroundings. Therefore, although there exist similar climate characteristics and crop cultivation techni‐ ques, there is a difference in amplitude of the NDVI cycle of the archaeological and non-

Remote Sensing for Archaeological Applications: Management, Documentation and Monitoring

http://dx.doi.org/10.5772/39306

75

**Figure 15.** Phenological cycle of the Neolithic settlement (solid line) and the healthy site 3 (dashed line) (Agapiou et

Contemporary techniques and methods such as computer graphics, virtual reality, multime‐ dia technology, and information technology can be integrated in Web GIS technologies, in order to act as a uniform digital tool for documentation, protection and preservation of cul‐ tural heritage (Agapiou et al., 2010c; Hadjimitsis et al., 2006). In order to document and map known archaeological sites and monuments, several techniques may be used, including la‐ ser scanning, 3D modelling and GIS. In this section, applications from several monuments in

**5. Documentation of cultural heritage sites using remote sensing**

**techniques, GIS and laser scanning**

archaeological areas.

al., 2012b)

Cyprus are presented.

**Figure 13.** NDVI results for *Prodromos II* site (in green circle). (a) Raw satellite image without any radiometric enhancements, (b) satellite image with a linear max-min enhancement applied to all image, (c) max-min enhancement applied to the area around *Prodromos II* and (d) modified max-min enhancement applied to the area around *Prodromos II*. The magoula is indicated with the red arrow (Agapiou et al., 2012c).

**Figure 14.** Tasseled Cap results for *Nikaia 16* site (in red circle), (a) Brightness, (b) greenness, (c) wetness and (d) RGB of the first three components of the T-K algorithm (Agapiou et al., 2012c).

Phenological studies of crops for the detection of buried archaeological remains were al‐ so evaluated (Agapiou et al., 2012b) It was found that the phenological cycle of crops for 'archaeological' and 'non archaeological areas' can be used as a "remote" approach in or‐ der to locate buried architecture remains. In Figure 15, the phenological cycle of an ar‐ chaeological site (*Almyros II*) and the phenological cycle of a healthy site (Site 3) are examined. A small NDVI difference is evident (Case A, Figure 15) which is associated with buried archaeological remains. This is due to the fact that soil over the archaeologi‐ cal remains seems to have a different moisture content compared to their surroundings. Therefore, although there exist similar climate characteristics and crop cultivation techni‐ ques, there is a difference in amplitude of the NDVI cycle of the archaeological and nonarchaeological areas.

**Figure 13.** NDVI results for *Prodromos II* site (in green circle). (a) Raw satellite image without any radiometric enhancements, (b) satellite image with a linear max-min enhancement applied to all image, (c) max-min enhancement applied to the area around *Prodromos II* and (d) modified max-min enhancement applied to the area around *Prodromos II*. The

**Figure 14.** Tasseled Cap results for *Nikaia 16* site (in red circle), (a) Brightness, (b) greenness, (c) wetness and (d) RGB

magoula is indicated with the red arrow (Agapiou et al., 2012c).

74 Remote Sensing of Environment: Integrated Approaches

of the first three components of the T-K algorithm (Agapiou et al., 2012c).

**Figure 15.** Phenological cycle of the Neolithic settlement (solid line) and the healthy site 3 (dashed line) (Agapiou et al., 2012b)
