A malarial-ridden swamp: using Google Earth Pro and Corona to access the southern Balikh valley, Syria

Hritz, Carrie

doi:10.1016/j.jas.2012.11.017

Cited by 32 publications

(19 citation statements)

References 45 publications

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“…These advances were mostly developed within the framework of archaeological research, predominantly in the semi‐arid regions of the Near East (Philip et al, ; Galiatsatos et al, ; Alizadeh and Ur, ; Casana and Cothren, ; Bitelli and Girelli, ; Hall, ; Beck and Philip, ; Ur, ; see also references from the CORONA Atlas Project in Casana and Cothren, ) and temperate areas of North/Central Asia (Gheyle et al, ; Goossens et al, ; Rondelli et al, ). Most of these studies aimed at the detection of archaeological features at landscape level, such as tells or ancient hollow roads and pathways, especially in landscapes where features have been damaged or no longer survive (Kennedy, ; Ur, , ; Wilkinson, ; Comfort et al, ; Wilkinson et al, ; Hritz, ; Palmer, ). Furthermore, CORONA images have been compared with multispectral signatures from very high‐resolution Ikonos imagery for detecting non‐tell archaeological sites (Wilkinson et al, ; Beck et al, ) and crop marks (Fowler and Fowler, ).…”

Section: Corona Reconnaissance Photographsmentioning

confidence: 99%

“…Orthorectified datasets can be easily integrated into Google Earth Pro to improve archaeological surveys in areas where maps or aerial photographs are difficult to access or that have problems of logistical or political access, such as in present‐day Syria (Hritz, ), Afghanistan (Thomas et al, ) and many parts of South Asia (Beck et al, ). Although Google Earth has become a tool commonly used to obtain a first glance into archaeological landscapes and planning field surveys (Beck, ; Ur, ; Myers, ; Kaimaris et al, ), its application in developing countries such India has only recently been utilized (Balbo et al, ; Thakuria et al, ).…”

Section: Data Integration: Improving Surveys In Real‐timementioning

confidence: 99%

“…Ur, ; Alizadeh and Ur, ); addressing navigation and mapping in remote areas (such as the alluvial landscape of the Balikh valley in Syria; e.g. Hritz, ); and improving photointerpretation and time‐change analysis in eroded or damaged landscapes (e.g. Challis et al, ; Casana et al, ).…”

Section: Introductionmentioning

confidence: 99%

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CORONA Photographs in Monsoonal Semi‐arid Environments: Addressing Archaeological Surveys and Historic Landscape Dynamics over North Gujarat, India

Conesa

Madella

Galiatsatos

et al. 2014

Archaeological Prospection

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Here we illustrate a ground map approach that uses orthorectified CORONA KH4B images and declassified topographical maps to study historical land-use dynamics and to help planning archaeological survey in the monsoonal semi-arid alluvial plains of North Gujarat, India. In spite of its generalized use in archaeological applications, CORONA photographs have rarely been used in Indian archaeological contexts. The methods discuss a cost-effective and integrated protocol for: (i) obtaining ground control points (GCPs) and orthorectify CORONA photographs when very high-resolution imagery or detailed topographic maps are not available; and (ii) evaluating the integration of declassified datasets into Google Earth Pro for addressing archaeological surveys in remote areas. The merging of CORONA imagery with declassified USA and the former USSR historical military maps provided a picture of the human-environment interaction in North Gujarat of the past 40 years, prior to the intense development of mechanical agriculture and regional irrigation channels. We conclude by identifying the human and climate-induced taphonomical processes that are obliterating a fragile landscape characterized by archaeological scatters located in fossilized sand dunes.The land-use patterns that were earlier determined by the availability of surface water (stored in seasonal flooded interdunes or village ponds, in close relation

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Section: Corona Reconnaissance Photographsmentioning

confidence: 99%

Section: Data Integration: Improving Surveys In Real‐timementioning

confidence: 99%

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CORONA Photographs in Monsoonal Semi‐arid Environments: Addressing Archaeological Surveys and Historic Landscape Dynamics over North Gujarat, India

Conesa

Madella

Galiatsatos

et al. 2014

Archaeological Prospection

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“…Although it is widely acknowledged that it is essential to validate Sentinel-2 products using field data in order to reinforce and validate its findings, accessing field data can at times prove to be a daunting task as is the case for Liberia and Somalia. In such cases, the use of alternative approaches such as Google Earth Pro has been shown to be reasonable, see, e.g., Hritz (2013). Google Earth Pro provides high-resolution imagery from several commercial satellites from 2000 to the present, see, e.g., Kennedy and Bishop (2011) and Sadr and Rodier (2012).…”

Section: Sensormentioning

confidence: 99%

Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products

Saleem

Awange

2019

CATENA

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In most developing countries, coastline shift monitoring using in-situ (ground-based) data faces challenges due, e.g., to data unreliability, inconsistency, deficiency, inaccessibility or incompleteness. Even where practically applicable, the traditional "boots on the ground" methods are labour intensive and expensive, thus imposing burden on poor countries struggling to meet other urgent pressing daily needs, i.e., food and medicine. Remote sensing (RS) techniques provide a more efficient and effective way of collecting data for coastline shift analysis. However, moderate spatio-temporal resolution RS products such as the widely used Landsat products (30 m and 16 days) may be insufficient where high accuracy is desired. In 2015, Sentinel-2 Multi-Spectral Instrument (MSI) remotely sensed products with higher spatio-temporal resolution (10 m and 5 days) and high spectral resolution (13 bands), which promises to improve coastline movement monitoring to high accuracy, was launched. Using two war-impacted countries (Liberia and Somalia) as case studies of regions with data deficiency or of poor quality, for the period 2015-2018, this contribution aims at (i) assessing the suitability of the new freely available high spatio-temporal Sentinel-2 products to monitor coastline shift, (ii) assessing the possibility of filling the missing Sentinel-2 gaps with Landsat 8 panchromatic band (15 m) products to provide alternative data source for mapping of coastline movements where Sentinel-2 data is unusable, e.g., due to cloud cover, and (iii), undertake a comparative analysis between Sentinel-2 (10 m), Landsat panchromatic (15 m), and Landsat multi-spectral (30 m). The results of the evaluation indicate 23% (on average) improvement gained by using Sentinel-2 compared to the traditional Landsat 30 m resolution data (i.e., 32% for Liberia and 14% for Somalia). A comparison of 100 check points from Google Earth Pro (i.e., surrogate in-situ reference data) show 91% agreement for Liberia and 85% for Somalia, indicating the potential of using Sentinel-2 data for future coastal shift studies, particularly for the data deficient regions. The results of comparative studies for Sentinel-2, Landsat panchromatic (PAN), and Landsat multi-spectral (MS) show that the percentages of Sentinel-2 and Landsat PAN that falls within 10 m threshold is much higher than Landsat MS by 35% and 26%, respectively, and for the 2016-2017 period, they provide more detailed mapping of the Liberian coastline compared to Landsat MS (30 m). Finally, panchromatic Landsat data with 15 m resolution are found to be capable of filling the missing Sentinel-2 gaps, i.e., where cloud cover hampers its usability.

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“…Such images are very important for archaeological research since they capture landscape prior to recent changes (Hritz, ). The high spatial resolution of aerial imagery enables the identification of archaeological marks linked to the presence of buried structures.…”

Section: Introductionmentioning

confidence: 99%

Colour to Greyscale Pixels: Re‐seeing Greyscale Archived Aerial Photographs and Declassified Satellite CORONA Images Based on Image Fusion Techniques

Αγαπίου

Alexakis

Sarris

et al. 2016

Archaeological Prospection

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To date, archived aerial photographs or recently declassified satellite CORONA images have been used to support archaeological research. However the use of such images is limited to the interpretation of greyscale images, which can be improved by image analysis processes including filters, edge detection techniques, etc. This article presents a methodology to improve the interpretation of these images by adding colour from recently acquired satellites or airborne sensors. The methodology followed in this article, is based on the use of pan-sharpening algorithms which are applied to a set of an archived greyscale image and a recently colour image taken over the same area. These two images are geometrically corrected while their histograms are matched. Then, the two images are merged based on different pan-sharpening techniques such as Brovey transformation, high pass filters, multiplicative transformation, principal component analysis and wavelet decomposition. The final result is a colour image which can be further studied for interpretation purposes. A coherence image is also calculated since differences due to time might be also observed in the images (e.g. land use changes). The results presented here from different cases studies of Cyprus indicate that the proposed methodology may be applied in any other greyscale archive dataset. From the results is was shown that Brovey and high pass filter transform seem to be able to support better the interpretation of such archive information. Figure 3. CORONA and Landsat 8 LDCM images used over the 'Kourion' archaeological site (34°40.367ʹN; 32°51.830ʹE, WGS 84, 36 N). Fusion results based on Brovey, PCA, and wavelet transformations are also presented. This figure is available in colour online at wileyonlinelibrary.com/journal/arp Figure 4. CORONA and Landsat 8 LDCM images used over the 'Palaepaphos' archaeological site (34°42.357ʹN; 32°34.867ʹE; WGS 84, 36 N). Fusion results based on Brovey, PCA, and wavelet transformations are also presented. This figure is available in colour online at wileyonlinelibrary.com/journal/arp 235 Colour to Greyscale Pixels Based on Image Fusion Techniques

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A malarial-ridden swamp: using Google Earth Pro and Corona to access the southern Balikh valley, Syria

Cited by 32 publications

References 45 publications

CORONA Photographs in Monsoonal Semi‐arid Environments: Addressing Archaeological Surveys and Historic Landscape Dynamics over North Gujarat, India

CORONA Photographs in Monsoonal Semi‐arid Environments: Addressing Archaeological Surveys and Historic Landscape Dynamics over North Gujarat, India

Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products

Colour to Greyscale Pixels: Re‐seeing Greyscale Archived Aerial Photographs and Declassified Satellite CORONA Images Based on Image Fusion Techniques

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