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31 pages, 11659 KiB

Open AccessArticle

SAR Sentinel 1 Imaging and Detection of Palaeo-Landscape Features in the Mediterranean Area

by Abdelaziz Elfadaly, Nicodemo Abate, Nicola Masini and Rosa Lasaponara

Remote Sens. 2020, 12(16), 2611; https://doi.org/10.3390/rs12162611 - 13 Aug 2020

Cited by 29 | Viewed by 6450 | Correction

Abstract

The use of satellite radar in landscape archaeology offers great potential for manifold applications, such as the detection of ancient landscape features and anthropogenic transformations. Compared to optical data, the use and interpretation of radar imaging for archaeological investigations is more complex, due [...] Read more.

The use of satellite radar in landscape archaeology offers great potential for manifold applications, such as the detection of ancient landscape features and anthropogenic transformations. Compared to optical data, the use and interpretation of radar imaging for archaeological investigations is more complex, due to many reasons including that: (i) ancient landscape features and anthropogenic transformations provide subtle signals, which are (ii) often covered by noise; and, (iii) only detectable in specific soil characteristics, moisture content, vegetation phenomenology, and meteorological parameters. In this paper, we assessed the capability of SAR Sentinel 1 in the imaging and detection of palaeo-landscape features in the Mediterranean area of Tavoliere delle Puglie. For the purpose of our investigations, a significant test site (larger than 200 km²) was selected in the Foggia Province (South of Italy) as this area has been characterized for millennia by human frequentation starting from (at least) the Neolithic. The results from the Sentinel 1 (S-1) data were successfully compared with independent data sets, and the comparison clearly showed an excellent match between the S-1 based outputs and ancient anthropogenic transformations and landscape features. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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16 pages, 21722 KiB

Open AccessArticle

The UAS-Based 3D Image Characterization of Mozarabic Church Ruins in Bobastro (Malaga), Spain

by Carlos Enríquez, Juan Manuel Jurado, Alexandro Bailey, Danilo Callén, María José Collado, Gabriel Espina, Pablo Marroquín, Erick Oliva, Edgar Osla, María Isabel Ramos, Scarlett Sarceño and Francisco Ramón Feito

Remote Sens. 2020, 12(15), 2377; https://doi.org/10.3390/rs12152377 - 24 Jul 2020

Cited by 18 | Viewed by 3894

Abstract

In recent years, the application of geomatics tools in archaeology has proved to be very useful to obtain meaningful knowledge of the 3D reconstruction of archaeological remains and semantic classification of the 3D surface. These techniques have proven to be an effective solution [...] Read more.

In recent years, the application of geomatics tools in archaeology has proved to be very useful to obtain meaningful knowledge of the 3D reconstruction of archaeological remains and semantic classification of the 3D surface. These techniques have proven to be an effective solution for the 3D modeling and the extraction of many spatial features on an archaeological site. However, novel methodologies as well as new data exploitation strategies are required to exploit these geospatial data for natural and cultural heritage documentation, monitoring, and preservation. In this paper, we have studied unique archaeological ruins, a Mozarab church in Al-Andalus, using high-resolution RGB images, which was taken by a drone. Thus, a 3D reconstruction of the ruins and the surrounding environment is carried out in order to characterize it on a dense point cloud. Then, a digital elevation model (DEM) was calculated in order to identify critical slope lines, which are significant to determine where the structure of the church was built. Our results can be used for the development of an architectural project and thus a virtual recreation of these archaeological ruins was performed. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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27 pages, 10396 KiB

Open AccessArticle

Multitemporal 2016-2018 Sentinel-2 Data Enhancement for Landscape Archaeology: The Case Study of the Foggia Province, Southern Italy

by Nicodemo Abate, Abdelaziz Elfadaly, Nicola Masini and Rosa Lasaponara

Remote Sens. 2020, 12(8), 1309; https://doi.org/10.3390/rs12081309 - 21 Apr 2020

Cited by 40 | Viewed by 5792

Abstract

This paper is focused on the use of satellite Sentinel-2 data for assessing their capability in the identification of archaeological buried remains. We selected the “Tavoliere delle Puglie” (Foggia, Italy) as a test area because it is characterized by a long human frequentation [...] Read more.

This paper is focused on the use of satellite Sentinel-2 data for assessing their capability in the identification of archaeological buried remains. We selected the “Tavoliere delle Puglie” (Foggia, Italy) as a test area because it is characterized by a long human frequentation and is very rich in archaeological remains. The investigations were performed using multi-temporal Sentinel-2 data and spectral indices, commonly used in satellite-based archaeology, and herein analyzed in known archaeological areas to capture the spectral signatures of soil and crop marks and characterize their temporal behavior using Time Series Analysis and Spectral Un-mixing. Tasseled Cap Transformation and Principal Component Analysis have been also adopted to enhance archaeological features. Results from investigations were compared with independent data sources and enabled us to (i) characterize the spectral signatures of soil and crop marks, (ii) assess the performance of the diverse spectral channels and indices, and (iii) identify the best period of the year to capture the archaeological proxy indicators. Additional very important results of our investigations were (i) the discovery of unknown archaeological areas and (ii) the setup of a database of archaeological features devised ad hoc to characterize and categorize the diverse typologies of archaeological remains detected using Sentinel-2 Data. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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25 pages, 14879 KiB

Open AccessEditor’s ChoiceArticle

Combining InfraRed Thermography and UAV Digital Photogrammetry for the Protection and Conservation of Rupestrian Cultural Heritage Sites in Georgia: A Methodological Application

by William Frodella, Mikheil Elashvili, Daniele Spizzichino, Giovanni Gigli, Luka Adikashvili, Nikoloz Vacheishvili, Giorgi Kirkitadze, Akaki Nadaraia, Claudio Margottini and Nicola Casagli

Remote Sens. 2020, 12(5), 892; https://doi.org/10.3390/rs12050892 - 10 Mar 2020

Cited by 51 | Viewed by 7399

Abstract

The rock-cut city of Vardzia is an example of the extraordinary rupestrian cultural heritage of Georgia. The site, Byzantine in age, was carved in the steep tuff slopes of the Erusheti mountains, and due to its peculiar geological characteristics, it is particularly vulnerable [...] Read more.

The rock-cut city of Vardzia is an example of the extraordinary rupestrian cultural heritage of Georgia. The site, Byzantine in age, was carved in the steep tuff slopes of the Erusheti mountains, and due to its peculiar geological characteristics, it is particularly vulnerable to weathering and degradation, as well as frequent instability phenomena. These problems determine serious constraints on the future conservation of the site, as well as the safety of the visitors. This paper focuses on the implementation of a site-specific methodology, based on the integration of advanced remote sensing techniques, such as InfraRed Thermography (IRT) and Unmanned Aerial Vehicle (UAV)-based Digital Photogrammetry (DP), with traditional field surveys and laboratory analyses, with the aim of mapping the potential criticality of the rupestrian complex on a slope scale. The adopted methodology proved to be a useful tool for the detection of areas of weathering and degradation on the tuff cliffs, such as moisture and seepage sectors related to the ephemeral drainage network of the slope. These insights provided valuable support for the design and implementation of sustainable mitigation works, to be profitably used in the management plan of the site of Vardzia, and can be used for the protection and conservation of rupestrian cultural heritage sites characterized by similar geological contexts. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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19 pages, 7182 KiB

Open AccessCommunication

A European-Scale Investigation of Soil Erosion Threat to Subsurface Archaeological Remains

by Athos Agapiou, Vasiliki Lysandrou and Diofantos G. Hadjimitsis

Remote Sens. 2020, 12(4), 675; https://doi.org/10.3390/rs12040675 - 18 Feb 2020

Cited by 15 | Viewed by 4635

Abstract

This communication emanates from the lack of a European-scale study for investigating the potential threats that subsurface archaeological remains face today due to soil loss by water. This research analyses the impact of soil loss on potential subsurface archaeological evidence by integrating open [...] Read more.

This communication emanates from the lack of a European-scale study for investigating the potential threats that subsurface archaeological remains face today due to soil loss by water. This research analyses the impact of soil loss on potential subsurface archaeological evidence by integrating open geospatial datasets deriving from two pertinent European studies. The first study’s dataset is related to soil erosion (soil loss provoked by water activity), which was reclassified into three groups alluding the level of threat on potential subsurface archaeological contexts, as follows: (1) areas presenting soil loss from 0 until 5 t/h per year, which are characterised as low threat areas; (2) areas presenting soil loss from 5 until 10 t/h per year, which are characterised as moderated threat; and (3) areas presenting soil loss beyond 10 t/h per year, which are considered as high-risk areas. The second study’s dataset refers to the capacity of soils to preserve specific archaeological materials, classified in four categories based on the properties of the archaeological material (bones, teeth, and shells (bones); organic materials (organics); metals (Cu, bronze, and Fe) (metals); and stratigraphic evidence (strati). Both datasets were imported into a Geographical Information System (GIS) for further synthesis and analysis, while the average threat of soil loss per year was evaluated in a country level (nomenclature of territorial units for statistics (NUTS) level 0). The overall results show that approximately 10% of European soils that potentially preserve archaeological remains are in high threat due to soil loss, while similar patterns—on a European level—are found for areas characterised with moderate to high risk from the soil loss. This study is the first attempt to present a proxy map for subsurface cultural material under threat due to soil loss, covering the entire European continent. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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28 pages, 22003 KiB

Open AccessArticle

Earth Stewardship Science—Transdisciplinary Contributions to Quantifying Natural and Cultural Heritage of Southernmost Africa

by Bastien Linol, Warren Miller, Cheryl Rensburg, Renee Schoeman, Lucian Bezuidenhout, Fabien Genin, Barry Morkel, Nyaradzo Dhliwayo, Keegan Jeppesen, Sinazo Dlakavu, Okuhle Poto, Gaathier Mahed, Natasha Gariremo, James Berkland, Debbie Claassen, Tebogo Sebake, Thulisile Kunjwa, Gregorio Guzzo, Maria Bobbio, Romain Pellen, Lizalise Mngcele, Manyano Makuzeni, Katherine Winkler, Thandeka Tembe, Sameera Musa, Khaya Valashiya, Vhuhwavhohau Nengovhela, Verouschka Sonn, Divan Stroebel, Nokuthua Kom, Philasande Mambalu, Taufeeq Dhansay, Thomas Muedi and Thakane Ntholi Show full author list Hide full author list

Remote Sens. 2020, 12(3), 420; https://doi.org/10.3390/rs12030420 - 28 Jan 2020

Cited by 6 | Viewed by 7263

Abstract

Evaluating anthropogenic changes to natural systems demand greater quantification through innovative transdisciplinary research focused on adaptation and mitigation across a wide range of thematic sciences. Southernmost Africa is a unique field laboratory to conduct such research linked to earth stewardship, with ‘earth’ as [...] Read more.

Evaluating anthropogenic changes to natural systems demand greater quantification through innovative transdisciplinary research focused on adaptation and mitigation across a wide range of thematic sciences. Southernmost Africa is a unique field laboratory to conduct such research linked to earth stewardship, with ‘earth’ as in our Commons. One main focus of the AEON’s Earth Stewardship Science Research Institute (ESSRI) is to quantify the region’s natural and cultural heritage at various scales across land and its flanking oceans, as well as its time-scales ranging from the early Phanerozoic (some 540 million years) to the evolution of the Anthropocene (changes) following the emergence of the first human-culture on the planet some 200 thousand years ago. Here we illustrate the value of this linked research through a number of examples, including: (i) geological field mapping with the aid of drone, satellite and geophysical methods, and geochemical fingerprinting; (ii) regional ground and surface water interaction studies; (iii) monitoring soil erosion, mine tailing dam stability and farming practices linked to food security and development; (iv) ecosystem services through specific biodiversity changes based on spatial logging of marine (oysters and whales) and terrestrial (termites, frogs and monkeys) animals. We find that the history of this margin is highly episodic and complex by, for example, the successful application of ambient noise and groundwater monitoring to assess human-impacted ecosystems. This is also being explored with local Khoisan representatives and rural communities through Citizen Science. Our goal is to publicly share and disseminate the scientific and cultural data, through initiatives like the Africa Alive Corridor 10: ‘Homo Sapiens’ that embraces storytelling along the entire southern coast. It is envisioned that this approach will begin to develop the requisite integrated technological and societal practices that can contribute toward the needs of an ever-evolving and changing global ‘village’. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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15 pages, 4981 KiB

Open AccessArticle

Characterisation of Terrain Variations of an Underwater Ancient Town in Qiandao Lake

by Fanlin Yang, Fangzheng Xu, Kai Zhang, Xianhai Bu, Hao Hu and Michael Anokye

Remote Sens. 2020, 12(2), 268; https://doi.org/10.3390/rs12020268 - 14 Jan 2020

Cited by 15 | Viewed by 3441

Abstract

The underwater ancient town of Chunan is of great importance in archaeology and tourism. Hence, the efficient mapping and monitoring of the topographical changes in this town are essential. An attractive choice for the efficient mapping of underwater archaeology is the multibeam echo [...] Read more.

The underwater ancient town of Chunan is of great importance in archaeology and tourism. Hence, the efficient mapping and monitoring of the topographical changes in this town are essential. An attractive choice for the efficient mapping of underwater archaeology is the multibeam echo sounder system (MBES). The MBES has several advantages including noncontact survey, high precision, and low cost. In this study, the topographical changes of the ancient town under Qiandao Lake were quantitatively assessed on the basis of time-series MBES data collected in 2002 and 2015. First, the iterative closest point (ICP) algorithm was applied to eliminate the coordinate deviations between two point sets. Second, the robust estimation method was used to analyse the characterisations of the terrain variations of the town on the basis of the differences between the two matched point sets. Obvious topographical changes ranging from −0.89 m to 0.88 m were observed in a number of local areas in the town. On the global scale, the mean absolute value of the depth change in the town was merely 0.12 m, which indicated a weak global deformation pattern. The experiment proved the effectiveness of applying MBES data to analyse the deformation of the ancient town. The results are beneficial to the study of underwater ancient towns and the development of protection strategies. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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25 pages, 7504 KiB

Open AccessArticle

Discovering Potential Settlement Areas around Archaeological Tells Using the Integration between Historic Topographic Maps, Optical, and Radar Data in the Northern Nile Delta, Egypt

by Abdelaziz Elfadaly, Mohamed A. R. Abouarab, Radwa R. M. El Shabrawy, Wael Mostafa, Penelope Wilson, Christophe Morhange, Jay Silverstein and Rosa Lasaponara

Remote Sens. 2019, 11(24), 3039; https://doi.org/10.3390/rs11243039 - 16 Dec 2019

Cited by 18 | Viewed by 6992

Abstract

The primary objective of this study is to leverage the integration of surface mapping data derived from optical, radar, and historic topographical studies with archaeological sampling to identify ancient settlement areas in the Northern Nile Delta, Egypt. This study employed the following methods: [...] Read more.

The primary objective of this study is to leverage the integration of surface mapping data derived from optical, radar, and historic topographical studies with archaeological sampling to identify ancient settlement areas in the Northern Nile Delta, Egypt. This study employed the following methods: digitization of topographic maps, band indices techniques on optical data, the creation of a 3D model from SRTM data, and Sentinel-1 interferometric wide swath (IW) analysis. This type of study is particularly relevant to the search for evidence of otherwise hidden ancient settlements. Due to its geographical situation and the fertility of the Nile, Egypt witnessed the autochthonous development of predynastic and dynastic civilizations, as well as an extensive history of external influences due to Greek, Roman, Coptic, Islamic, and Colonial-era interventions. Excavation work at Buto (Tell el-Fara’in) in 2017–18, carried out by the Kafrelsheikh University (KFS) in cooperation with the Ministry of Antiquities, demonstrated that remote sensing data offers considerable promise as a tool for developing regional settlement studies and excavation strategies. This study integrates the mission work in Buto with the satellite imagery in and around the area of the excavation. The results of the initial Buto area research serve as a methodological model to expand the study area to the North Delta with the goal of detecting the extent of the ancient kingdoms of Buto and Sakha. The results of this research include the creation of a composite historical database using ancient references and early topographical maps (1722, 1941, 1950, and 1997), Optical Corona (1965), Landsat MSS (Multispectral Scanner System) (1973, 1978, and 1988), TM (Thematic Mapper) (2005) data, and Radar SRTM (2014) and Sentinel1 (2018 and 2019) data. The data in this study have been analyzed using the ArcMap, Envi, and SNAP software. The results from the current investigation highlight the rapid changes in the land use/land cover in the last century in which many ancient sites were lost due to agriculture and urban development. Three potential settlement areas have been identified with the Sentinel1 Radar data, and have been integrated with the early maps. These discoveries will help develop excavation strategies aimed at elucidating the ancient settlement dynamics and history of the region during the next phase of research. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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23 pages, 34308 KiB

Open AccessArticle

Remotely-Sensed Identification of a Transition for the Two Ecosystem States Along the Elevation Gradient: A Case Study of Xinjiang Tianshan Bogda World Heritage Site

by Hong Wan, Xinyuan Wang, Lei Luo, Peng Guo, Yanchuang Zhao, Kai Wu and Hongge Ren

Remote Sens. 2019, 11(23), 2861; https://doi.org/10.3390/rs11232861 - 2 Dec 2019

Cited by 3 | Viewed by 3920

Abstract

The alpine treeline, as an ecological transition zone between montane coniferous forests and alpine meadows (two ecosystem states), is a research hotspot of global ecology and climate change. Quantitative identification of its elevation range can efficiently capture the results of the interaction between [...] Read more.

The alpine treeline, as an ecological transition zone between montane coniferous forests and alpine meadows (two ecosystem states), is a research hotspot of global ecology and climate change. Quantitative identification of its elevation range can efficiently capture the results of the interaction between climate change and vegetation. Digital extraction and extensive analysis in such a critical elevation range crucially depend on the ability of monitoring ecosystem variables and the suitability of the experimental model, which are often restricted by the weak intersection of disciplines and the spatial-temporal continuity of the data. In this study, the existence of two states was confirmed by frequency analysis and the Akaike information criterion (AIC) as well as the Bayesian information criterion (BIC) indices. The elevation range of a transition for the two ecosystem states on the northern slope of the Bogda was identified by the potential analysis. The results showed that the elevation range of co-occurrence for the two ecosystem states was 2690–2744 m. At the elevation of 2714 m, the high land surface temperature (LST) state started to exhibit more attraction than the low LST state. This elevation value was considered as a demarcation where abrupt shifts between the two states occurred with the increase of elevation. The identification results were validated by a field survey and unmanned aerial vehicle data. Progress has been made in the transition identification for the ecosystem states along the elevation gradient in mountainous areas by combining the remotely-sensed index with a potential analysis. This study also provided a reference for obtaining the elevation of the alpine tree line quickly and accurately. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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22 pages, 37980 KiB

Open AccessArticle

Identifying Linear Traces of the Han Dynasty Great Wall in Dunhuang Using Gaofen-1 Satellite Remote Sensing Imagery and the Hough Transform

by Lei Luo, Nabil Bachagha, Ya Yao, Chuansheng Liu, Pilong Shi, Lanwei Zhu, Jie Shao and Xinyuan Wang

Remote Sens. 2019, 11(22), 2711; https://doi.org/10.3390/rs11222711 - 19 Nov 2019

Cited by 20 | Viewed by 5438

Abstract

The Han Dynasty Great Wall (GH), one of the largest and most significant ancient defense projects in the whole of northern China, has been studied increasingly not only because it provides important information about the diplomatic and military strategies of the Han Empire [...] Read more.

The Han Dynasty Great Wall (GH), one of the largest and most significant ancient defense projects in the whole of northern China, has been studied increasingly not only because it provides important information about the diplomatic and military strategies of the Han Empire (206 B.C.–220 A.D.), but also because it is considered to be a cultural and national symbol of modern China as well as a valuable archaeological monument. Thus, it is crucial to obtain the spatial pattern and preservation situation of the GH for next-step archaeological analysis and conservation management. Nowadays, remote sensing specialists and archaeologists have given priority to manual visualization and a (semi-) automatic extraction approach is lacking. Based on the very high-resolution (VHR) satellite remote sensing imagery, this paper aims to identify automatically the archaeological features of the GH located in ancient Dunhuang, northwest China. Gaofen-1 (GF-1) data were first processed and enhanced after image correction and mathematical morphology, and the M-statistic was then used to analyze the spectral characteristics of GF-1 multispectral (MS) data. In addition, based on GF-1 panchromatic (PAN) data, an auto-identification method that integrates an improved Otsu segmentation algorithm with a Linear Hough Transform (LHT) is proposed. Finally, by making a comparison with visual extraction results, the proposed method was assessed qualitatively and semi-quantitatively to have an accuracy of 80% for the homogenous background in Dunhuang. These automatic identification results could be used to map and evaluate the preservation state of the GH in Dunhuang. Also, the proposed automatic approach was applied to identify similar linear traces of other generations of the Great Wall of China (Western Xia Dynasty (581 A.D.–618 A.D.) and Ming Dynasty (1368 A.D.–1644 A.D.)) in various geographic regions. Moreover, the results indicate that the computer-based automatic identification has great potential in archaeological research, and the proposed method can be generalized and applied to monitor and evaluate the state of preservation of the Great Wall of China in the future. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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21 pages, 37154 KiB

Open AccessEditor’s ChoiceArticle

Extracting Khmer Rouge Irrigation Networks from Pre-Landsat 4 Satellite Imagery Using Vegetation Indices

by Corrine Coakley, Mandy Munro-Stasiuk, James A. Tyner, Sokvisal Kimsroy, Chhunly Chhay and Stian Rice

Remote Sens. 2019, 11(20), 2397; https://doi.org/10.3390/rs11202397 - 16 Oct 2019

Cited by 8 | Viewed by 4721

Abstract

Often discussed, the spatial extent and scope of the Khmer Rouge irrigation network has not been previously mapped on a national scale. Although low resolution, early Landsat images can identify water features accurately when using vegetation indices. We discuss the methods involved in [...] Read more.

Often discussed, the spatial extent and scope of the Khmer Rouge irrigation network has not been previously mapped on a national scale. Although low resolution, early Landsat images can identify water features accurately when using vegetation indices. We discuss the methods involved in mapping historic irrigation on a national scale, as well as comparing the performance of several vegetation indices at irrigation detection. Irrigation was a critical component of the Communist Part of Kampuchea (CPK)’s plan to transform Cambodia into an ideal communist society, aimed at providing surplus for the nation by tripling rice production. Of the three indices used, normalized difference, corrected transformed, and Thiam’s transformed vegetation indexes, (NDVI, CTVI, and TTVI respectively), the CTVI provided the clearest images of water storage and transport. This method for identifying anthropogenic water features proved highly accurate, despite low spatial resolution. We were successful in locating and identifying both water storage and irrigation canals from the time that the CPK regime was in power. In many areas these canals and reservoirs are no longer visible, even with high resolution modern satellites. Most of the structures built at this time experienced some collapse, either during the CPK regime or soon after, however many have been rehabilitated and are still in use, in at least a partial capacity. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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26 pages, 12730 KiB

Open AccessArticle

Re-Discovering Ancient Landscapes: Archaeological Survey of Mound Features from Historical Maps in Northwest India and Implications for Investigating the Large-Scale Distribution of Cultural Heritage Sites in South Asia

by Adam S. Green, Hector A. Orengo, Aftab Alam, Arnau Garcia-Molsosa, Lillian M. Green, Francesc Conesa, Amit Ranjan, Ravindra N. Singh and Cameron A. Petrie

Remote Sens. 2019, 11(18), 2089; https://doi.org/10.3390/rs11182089 - 6 Sep 2019

Cited by 23 | Viewed by 9079

Abstract

Incomplete datasets curtail the ability of archaeologists to investigate ancient landscapes, and there are archaeological sites whose locations remain unknown in many parts of the world. To address this problem, we need additional sources of site location data. While remote sensing data can [...] Read more.

Incomplete datasets curtail the ability of archaeologists to investigate ancient landscapes, and there are archaeological sites whose locations remain unknown in many parts of the world. To address this problem, we need additional sources of site location data. While remote sensing data can often be used to address this challenge, it is enhanced when integrated with the spatial data found in old and sometimes forgotten sources. The Survey of India 1” to 1-mile maps from the early twentieth century are one such dataset. These maps documented the location of many cultural heritage sites throughout South Asia, including the locations of numerous mound features. An initial study georeferenced a sample of these maps covering northwest India and extracted the location of many potential archaeological sites—historical map mound features. Although numerous historical map mound features were recorded, it was unknown whether these locations corresponded to extant archaeological sites. This article presents the results of archaeological surveys that visited the locations of a sample of these historical map mound features. These surveys revealed which features are associated with extant archaeological sites, which were other kinds of landscape features, and which may represent archaeological mounds that have been destroyed since the maps were completed nearly a century ago. Their results suggest that there remain many unreported cultural heritage sites on the plains of northwest India and the mound features recorded on these maps best correlate with older archaeological sites. They also highlight other possible changes in the large-scale and long-term distribution of settlements in the region. The article concludes that northwest India has witnessed profound changes in its ancient settlement landscapes, creating in a long-term sequence of landscapes that link the past to the present and create a foundation for future research and preservation initiatives. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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21 pages, 21384 KiB

Open AccessArticle

Measuring and Predicting Urban Expansion in the Angkor Region of Cambodia

by Jie Liu, Hongge Ren, Xinyuan Wang, Zeeshan Shirazi and Bin Quan

Remote Sens. 2019, 11(17), 2064; https://doi.org/10.3390/rs11172064 - 2 Sep 2019

Cited by 7 | Viewed by 7251

Abstract

Recent increases in urbanization and tourism threaten the viability of UNESCO world heritage sites across the globe. The Angkor world heritage site located in southern Cambodia is now facing such a challenge. Over the past two decades, Angkor has seen over 300,000% growth [...] Read more.

Recent increases in urbanization and tourism threaten the viability of UNESCO world heritage sites across the globe. The Angkor world heritage site located in southern Cambodia is now facing such a challenge. Over the past two decades, Angkor has seen over 300,000% growth in international tourist arrivals, which has led to uncontrolled development of the nearby city of Siem Reap. This study uses remote sensing and GIS to comprehend the process of urban expansion during the past 14 years, and has applied the CA-Markov model to predict future urban expansion. This paper analyzes the urban pressure on the Angkor site at different scales. The results reveal that the urban area of Siem Reap city increased from 28.23 km² in 2004 to 73.56 km² in 2017, an increase of 160%. Urban growth mainly represented a transit-oriented pattern of expansion, and it was also observed that land surfaces, such as arable land, forests, and grasslands, were transformed into urban residential land. The total constructed land area in the core and buffer zones increased by 12.99 km² from 2004 to 2017, and 72% of the total increase was in the buffer zone. It is predicted that the built-up area in Siem Reap is expected to cover 135.09 km² by 2025 and 159.14 km² by 2030. The number of monuments that are most likely be affected by urban expansion is expected to increase from 9 in 2017 to 14 in 2025 and 17 in 2030. The urban area in Siem Reap has increased dramatically over the past decade and monuments continue to be decimated by urban expansion. This paper urges closer attention and urgent actions to minimize the urban pressure on the Angkor site in the future. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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31 pages, 68268 KiB

Open AccessArticle

Monitoring Land Cover Change and Disturbance of the Mount Wutai World Cultural Landscape Heritage Protected Area, Based on Remote Sensing Time-Series Images from 1987 to 2018

by Xuyu Bai, Peijun Du, Shanchuan Guo, Peng Zhang, Cong Lin, Pengfei Tang and Ce Zhang

Remote Sens. 2019, 11(11), 1332; https://doi.org/10.3390/rs11111332 - 3 Jun 2019

Cited by 29 | Viewed by 6156

Abstract

The contextual-based multi-source time-series remote sensing and proposed Comprehensive Heritage Area Threats Index (CHATI) index are used to analyze the spatiotemporal land use/land cover (LULC) and threats to the Mount Wutai World Heritage Area. The results show disturbances, such as forest coverage, vegetation [...] Read more.

The contextual-based multi-source time-series remote sensing and proposed Comprehensive Heritage Area Threats Index (CHATI) index are used to analyze the spatiotemporal land use/land cover (LULC) and threats to the Mount Wutai World Heritage Area. The results show disturbances, such as forest coverage, vegetation conditions, mining area, and built-up area, in the research area changed dramatically. According to the CHATI, although different disturbances have positive or negative influences on environment, as an integrated system it kept stable from 1987 to 2018. Finally, this research uses linear regression and the F-test to mark the remarkable spatial-temporal variation. In consequence, the threats on Mount Wutai be addressed from the macro level and the micro level. Although there still have some drawbacks, the effectiveness of threat identification has been tested using field validation and the results are a reliable tool to raise the public awareness of WHA protection and governance. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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21 pages, 5729 KiB

Open AccessArticle

3D-Modelling of Charlemagne’s Summit Canal (Southern Germany)—Merging Remote Sensing and Geoarchaeological Subsurface Data

by Johannes Schmidt, Johannes Rabiger-Völlmer, Lukas Werther, Ulrike Werban, Peter Dietrich, Stefanie Berg, Peter Ettel, Sven Linzen, Andreas Stele, Birgit Schneider and Christoph Zielhofer

Remote Sens. 2019, 11(9), 1111; https://doi.org/10.3390/rs11091111 - 9 May 2019

Cited by 9 | Viewed by 4734

Abstract

The Early Medieval Fossa Carolina is the first hydro-engineering construction that bridges the Central European Watershed. The canal was built in 792/793 AD on order of Charlemagne and should connect the drainage systems of the Rhine-Main catchment and the Danube catchment. In this [...] Read more.

The Early Medieval Fossa Carolina is the first hydro-engineering construction that bridges the Central European Watershed. The canal was built in 792/793 AD on order of Charlemagne and should connect the drainage systems of the Rhine-Main catchment and the Danube catchment. In this study, we show for the first time, the integration of Airborne LiDAR (Light Detection and Ranging) and geoarchaeological subsurface datasets with the aim to create a 3D-model of Charlemagne’s summit canal. We used a purged Digital Terrain Model that reflects the pre-modern topography. The geometries of buried canal cross-sections are derived from three archaeological excavations and four high-resolution direct push sensing transects. By means of extensive core data, we interpolate the trench bottom and adjacent edges along the entire canal course. As a result, we are able to create a 3D-model that reflects the maximum construction depth of the Carolingian canal and calculate an excavation volume of approx. 297,000 m³. Additionally, we compute the volume of the present dam remnants by Airborne LiDAR data. Surprisingly, the volume of the dam remnants reveals only 120,000 m³ and is much smaller than the computed Carolingian excavation volume. The difference reflects the erosion and anthropogenic overprint since the 8th century AD. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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16 pages, 5046 KiB

Open AccessArticle

The Development of a GIS Methodology to Identify Oxbows and Former Stream Meanders from LiDAR-Derived Digital Elevation Models

by Courtney L. Zambory, Harvest Ellis, Clay L. Pierce, Kevin J. Roe, Michael J. Weber, Keith E. Schilling and Nathan C. Young

Remote Sens. 2019, 11(1), 12; https://doi.org/10.3390/rs11010012 - 21 Dec 2018

Cited by 9 | Viewed by 4874

Abstract

Anthropogenic development of floodplains and alteration to natural hydrological regimes have resulted in extensive loss of off-channel habitat. Interest has grown in restoring these habitats as an effective conservation strategy for numerous aquatic species. This study developed a process to reproducibly identify areas [...] Read more.

Anthropogenic development of floodplains and alteration to natural hydrological regimes have resulted in extensive loss of off-channel habitat. Interest has grown in restoring these habitats as an effective conservation strategy for numerous aquatic species. This study developed a process to reproducibly identify areas of former stream meanders to assist future off-channel restoration site selections. Three watersheds in Iowa and Minnesota where off-channel restorations are currently being conducted to aid the conservation of the Topeka Shiner (Notropis topeka) were selected as the study area. Floodplain depressions were identified with LiDAR-derived digital elevation models, and their morphologic and topographic characteristics were described. Classification tree models were developed to distinguish relic streams and oxbows from other landscape features. All models demonstrated a strong ability to distinguish between target and non-target features with area under the receiver operator curve (AUC) values ≥ 0.82 and correct classification rates ≥ 0.88. Solidity, concavity, and mean height above channel metrics were among the first splits in all trees. To compensate for the noise associated with the final model designation, features were ranked by their conditional probability. The results of this study will provide conservation managers with an improved process to identify candidate restoration sites. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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21 pages, 4808 KiB

Open AccessArticle

Partitioning of Terrain Features Based on Roughness

by Jiang Wu, Qinke Yang and Yuru Li

Remote Sens. 2018, 10(12), 1985; https://doi.org/10.3390/rs10121985 - 7 Dec 2018

Cited by 18 | Viewed by 5888

Abstract

Surface roughness is a key parameter that reflects topographic characteristics and influences surface processes, and characterization of surface roughness is a fundamental problem in geoscience. In recent years, although there have been basic studies on roughness, few studies have compared the concept and [...] Read more.

Surface roughness is a key parameter that reflects topographic characteristics and influences surface processes, and characterization of surface roughness is a fundamental problem in geoscience. In recent years, although there have been basic studies on roughness, few studies have compared the concept and quantification of roughness, and there have been few studies that have evaluated the ability of partition terrain features. Based on 1″ resolution Shuttle Radar Topography Mission (SRTM) data and previous studies, we selected the Qinba Mountain region of China and its adjacent areas as our study area, and used 13 different roughness algorithms to extract roughness in this study. Using spatial patterns and statistical distributions, the results were analyzed, and the best algorithm suited to partitioning terrain features was selected. We then evaluated the ability of the algorithm to distinguish the terrain morphology. The results showed the following: (1) The 13 algorithms were able to be classified into four types, that is, gradient (SLOPE), relief (root mean squared height, RMSH), local vector (directional cosine eigenvalue, DCE) and power-spectral (two-dimensional continuous wavelet transform, 2D CWT). (2) The SLOPE and RMSH algorithms were better able to express and distinguish terrain, as they were able to macroscopically distinguish between four types of terrain in the study areas. Based on power-spectral methods, 2D CWT had the same discrimination ability as the first two methods following a normalization transform, whereas the DCE method had a general effect and could only distinguish two types of terrain. (3) Different roughness algorithms had their own applicability for different terrain areas and application directions. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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22 pages, 8267 KiB

Open AccessArticle

Beyond GIS Layering: Challenging the (Re)use and Fusion of Archaeological Prospection Data Based on Bayesian Neural Networks (BNN)

by Athos Agapiou and Apostolos Sarris

Remote Sens. 2018, 10(11), 1762; https://doi.org/10.3390/rs10111762 - 8 Nov 2018

Cited by 10 | Viewed by 4134

Abstract

Multisource remote sensing data acquisition has been increased in the last years due to technological improvements and decreased acquisition cost of remotely sensed data and products. This study attempts to fuse different types of prospection data acquired from dissimilar remote sensors and explores [...] Read more.

Multisource remote sensing data acquisition has been increased in the last years due to technological improvements and decreased acquisition cost of remotely sensed data and products. This study attempts to fuse different types of prospection data acquired from dissimilar remote sensors and explores new ways of interpreting remote sensing data obtained from archaeological sites. Combination and fusion of complementary sensory data does not only increase the detection accuracy but it also increases the overall performance in respect to recall and precision. Moving beyond the discussion and concerns related to fusion and integration of multisource prospection data, this study argues their potential (re)use based on Bayesian Neural Network (BNN) fusion models. The archaeological site of Vésztő-Mágor Tell in the eastern part of Hungary was selected as a case study, since ground penetrating radar (GPR) and ground spectral signatures have been collected in the past. GPR 20 cm depth slices results were correlated with spectroradiometric datasets based on neural network models. The results showed that the BNN models provide a global correlation coefficient of up to 73%—between the GPR and the spectroradiometric data—for all depth slices. This could eventually lead to the potential re-use of archived geo-prospection datasets with optical earth observation datasets. A discussion regarding the potential limitations and challenges of this approach is also included in the paper. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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16 pages, 20897 KiB

Open AccessTechnical Note

A Pilot Study on Remote Sensing and Citizen Science for Archaeological Prospection

by Christopher Stewart, Georges Labrèche and Daniel Lombraña González

Remote Sens. 2020, 12(17), 2795; https://doi.org/10.3390/rs12172795 - 28 Aug 2020

Cited by 16 | Viewed by 6658

Abstract

Cost-effective techniques for systematic archaeological prospection are essential to improve the efficiency of preventive archaeology and the preservation of cultural heritage. Web Mapping Services, such as Microsoft Bing Maps, provide imagery covering extensive areas at high resolution. These can, in some cases, reveal [...] Read more.

Cost-effective techniques for systematic archaeological prospection are essential to improve the efficiency of preventive archaeology and the preservation of cultural heritage. Web Mapping Services, such as Microsoft Bing Maps, provide imagery covering extensive areas at high resolution. These can, in some cases, reveal cropmarks of buried historical structures. Given that archaeological prospection is not generally the priority of most common Web Mapping Services, the conditions under which images are acquired are not always suitable for the appearance of cropmarks. Therefore, their detection is typically serendipitous. This pilot project attempts to assess the potential to use the Microsoft Bing Maps Bird’s Eye service within a crowdsourcing platform to systematically search for archaeological cropmarks in the surroundings of the city of Rome in Italy. On this platform, which is hosted by the company Scifabric (Southampton, UK) and based on PyBossa, an Open Source framework for crowdsourcing, members of the public are invited to interpret oblique air photo tiles of Bing Maps Bird’s Eye. While the project is still on-going, at least one seamless coverage of tiles in the area of interest has been interpreted. For each tile, the Bing Maps Bird’s Eye service provides oblique air photo coverage in up to four possible orientations. As of 5 July 2020, 18,765 of the total 67,014 tasks have been completed. Amongst these completed tasks, positive detections of cropmarks were recorded once for 1447 tasks, twice for 57 tasks, and three or more times for 10 tasks. While many of these detections may be erroneous, some correspond with archaeological cropmarks of buried remains of buildings, roads, aqueducts, and urban areas from the Roman period, as verified by comparison with archaeological survey data. This leads to the conclusion that the Bing Maps Bird’s Eye service contains a wealth of information useful for archaeological prospection, and that to a certain extent citizen researchers could help to mine this information. However, a more thorough analysis would need to be carried out on possible false negatives and biases related to the varying ease of interpretation of residues of different archaeological structures from multiple historical periods. This activity forms the first part of a research project on the systematic prospection of archaeological cropmarks. The ultimate aim is to reach a critical mass of training data through crowdsourcing which can be augmented and used as input to train a machine learning algorithm for automatic detection on a larger scale. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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14 pages, 21401 KiB

Open AccessLetter

Deciphering Circular Anthropogenic Anomalies in PALSAR Data—Using L-Band SAR for Analyzing Archaeological Features on the Steppe

by Gino Caspari, Jegor Blochin, Timur Sadykov and Timo Balz

Remote Sens. 2020, 12(7), 1076; https://doi.org/10.3390/rs12071076 - 27 Mar 2020

Cited by 6 | Viewed by 3854

Abstract

Synthetic aperture radar has been employed for archaeological purposes for nearly forty years: nonetheless, its application among archaeological practitioners has remained limited. We analyzed circular anthropogenic anomalies in a steppe environment in PALSAR-2 data, which appeared as a homogeneous group of signatures. Each [...] Read more.

Synthetic aperture radar has been employed for archaeological purposes for nearly forty years: nonetheless, its application among archaeological practitioners has remained limited. We analyzed circular anthropogenic anomalies in a steppe environment in PALSAR-2 data, which appeared as a homogeneous group of signatures. Each anomaly was examined using additional SAR and optical data, as well as investigated through extensive ground truth and, in one case, excavation. We found the anomalies to originate from a wide range of processes and structural characteristics showing the non-intuitive complexity of SAR data interpretation. We found that this is likely the reason for the limited application SAR has seen within the archaeological community. In order to improve the usage of SAR for archaeological purposes beyond change detection and digital elevation models, specific products that are more readily understandable and superior to optical data in a narrow frame of application should be developed. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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10 pages, 24996 KiB

Open AccessLetter

Mapping and Damage Assessment of “Royal” Burial Mounds in the Siberian Valley of the Kings

by Gino Caspari

Remote Sens. 2020, 12(5), 773; https://doi.org/10.3390/rs12050773 - 28 Feb 2020

Cited by 34 | Viewed by 5901

Abstract

The Valley of the Kings in Tuva Republic, southern Siberia, is arguably one of the most important archaeological landscapes in the eastern Eurasian steppes. Nonetheless, little information exists about the spatial characteristics and preservation conditions of this burial ground consisting of large “royal” [...] Read more.

The Valley of the Kings in Tuva Republic, southern Siberia, is arguably one of the most important archaeological landscapes in the eastern Eurasian steppes. Nonetheless, little information exists about the spatial characteristics and preservation conditions of this burial ground consisting of large “royal” mounds. We map the large monuments of the Uyuk Valley’s northern river terrace and assess their state of preservation based on high-resolution optical satellite data. The burial site consists of several hundred mounds, over 150 of them with diameters of more than 25 m, the largest monuments are bigger than 100 m in diameter. This makes the Valley of the Kings in Tuva Republic one of the largest Early Iron Age burial sites in the Eurasian steppes. Unfortunately, around 92% of the large monuments are in bad condition, mostly due to looting. Full article

(This article belongs to the Special Issue Remote Sensing, Spatial Analysis, and GIS for Natural and Cultural Heritage Documentation, Monitoring, and Preservation)

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