| publications-2201 |
Peer reviewed articles |
2020 |
Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Daniela Langhans, Max Tegmark, Francesco Fuso Nerini |
The role of artificial intelligence in achieving the Sustainable Development Goals |
Nature Communications |
10.1038/s41467-019-14108-y |
Simulation & Modeling |
Precipitation & Ecological Systems |
|
AbstractThe emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. However, current research foci overlook important aspects. The fast development of AI needs to be supported by the necessary regulatory insight and oversight for AI-based technologies to enable sustainable development. Failure to do so could result in gaps in transparency, safety, and ethical standards. |
748625 |
|
|
|
| publications-2202 |
Peer reviewed articles |
2019 |
Simone D. Langhans, Sonja C. Jähnig, Manuel Lago, Astrid Schmidt-Kloiber, Thomas Hein |
The potential of ecosystem-based management to integrate biodiversity conservation and ecosystem service provision in aquatic ecosystems |
Science of The Total Environment |
10.1016/j.scitotenv.2019.04.025 |
Uncategorized |
Hydropower Dams & reservoirs |
|
No abstract available |
748625 |
|
|
|
| publications-2203 |
Peer reviewed articles |
2019 |
Nele Schuwirth, Florian Borgwardt, Sami Domisch, Martin Friedrichs, Mira Kattwinkel, David Kneis, Mathias Kuemmerlen, Simone D. Langhans, Javier Martínez-López, Peter Vermeiren |
How to make ecological models useful for environmental management |
Ecological Modelling |
10.1016/j.ecolmodel.2019.108784 |
Simulation & Modeling |
Precipitation & Ecological Systems |
|
No abstract available |
748625 |
|
|
|
| publications-2204 |
Peer reviewed articles |
2019 |
Ana Barbosa, Beatriz Martín, Virgilio Hermoso, Juan Arévalo-Torres, Julian Barbière, Javier Martínez-López, Sami Domisch, Simone D. Langhans, Stefano Balbi, Ferdinando Villa, Gonzalo Delacámara, Heliana Teixeira, Antonio J.A. Nogueira, Ana I. Lillebø, Yolanda Gil-Jiménez, Hugh McDonald, Alejandro Iglesias-Campos |
Cost-effective restoration and conservation planning in Green and Blue Infrastructure designs. A case study on the Intercontinental Biosphere Reserve of the Mediterranean: Andalusia (Spain) – Morocco |
Science of The Total Environment |
10.1016/j.scitotenv.2018.10.416 |
Uncategorized |
Wastewater Treatment Plants |
|
No abstract available |
748625 |
|
|
|
| publications-2205 |
Peer reviewed articles |
2019 |
Cameron Petrie, Hector Orengo, Adam Green, Joanna Walker, Arnau Garcia, Francesc Conesa, J. Knox, Ravindra Singh |
Mapping Archaeology While Mapping an Empire: Using Historical Maps to Reconstruct Ancient Settlement Landscapes in Modern India and Pakistan |
Geosciences |
10.3390/geosciences9010011 |
Control Systems |
Wastewater Treatment Plants |
|
A range of data sources are now used to support the process of archaeological prospection, including remote sensed imagery, spy satellite photographs and aerial photographs. This paper advocates the value and importance of a hitherto under-utilised historical mapping resource—the Survey of India 1” to 1-mile map series, which was based on surveys started in the mid–late nineteenth century, and published progressively from the early twentieth century AD. These maps present a systematic documentation of the topography of the British dominions in the South Asian Subcontinent. Incidentally, they also documented the locations, the height and area of thousands of elevated mounds that were visible in the landscape at the time that the surveys were carried out, but have typically since been either damaged or destroyed by the expansion of irrigation agriculture and urbanism. Subsequent reanalysis has revealed that many of these mounds were actually the remains of ancient settlements. The digitisation and analysis of these historic maps thus creates a unique opportunity for gaining insight into the landscape archaeology of South Asia. This paper reviews the context within which these historical maps were created, presents a method for georeferencing them, and reviews the symbology that was used to represent elevated mound features that have the potential to be archaeological sites. This paper should be read in conjunction with the paper by Arnau Garcia et al. in the same issue of Geosciences, which implements a research programme combining historical maps and a range of remote sensing approaches to reconstruct historical landscape dynamics in the Indus River Basin. |
746446 |
|
|
|
| publications-2206 |
Peer reviewed articles |
2019 |
H.A. Orengo, A. Garcia-Molsosa |
A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery |
Journal of Archaeological Science |
10.1016/j.jas.2019.105013 |
Simulation & Modeling |
Groundwater |
|
No abstract available |
746446 |
|
|
|
| publications-2207 |
Peer reviewed articles |
2021 |
Garcia‐Molsosa, Arnau; Orengo, Hector A.; Lawrence, Dan; Philip, Graham; Hopper, Kristen; Petrie, Cameron A. |
Potential of deep learning segmentation for the extraction of archaeological features from historical map series. |
Archaeological Prospection |
10.17863/cam.63954 |
Simulation & Modeling |
Groundwater |
|
No abstract available |
746446 |
|
|
|
| publications-2208 |
Peer reviewed articles |
2019 |
Arnau Garcia, Hector Orengo, Francesc Conesa, Adam Green, Cameron Petrie |
Remote Sensing and Historical Morphodynamics of Alluvial Plains. The 1909 Indus Flood and the City of Dera Ghazi Khan (Province of Punjab, Pakistan) |
Geosciences |
10.3390/geosciences9010021 |
Simulation & Modeling |
Groundwater |
|
This paper explores the historical inundation of the city of Dera Ghazi Kkan (Punjab, Pakistan) in 1909. The rich documentation about this episode available—including historic news reports, books and maps—is used to reconstruct the historical dynamics between an urban settlement and the river morphodynamics in the Indus alluvial plain. Map and document-based historical regressive analysis is complemented with the examination of images obtained through different Remote Sensing techniques, including the use of new algorithms specifically developed for the study of topography and seasonal water availability which make possible to assess long-term changes in the Indus River basin. This case of study provides an opportunity to examine: (1) how historical hydrological dynamics are reflected in RS produced images; (2) the implications of river morphodynamics in the interpretation of settlement patterning; and (3) the documented socio-political responses to such geomorphological change. The results of this analysis are used to consider the long-term dynamics that have influenced the archaeo/cultural landscapes of the Indus River basin. This assessment provides critical insights for: (1) understanding aspects of the formation, preservation of representation of the archaeological record; (2) identifying traces of morphodynamics and their possible impact over the cultural heritage; and (3) offering insights into the role that recent historical documents can have in the interpretation of RS materials. This paper should be read in conjunction with the paper by Cameron Petrie et al. in the same issue of Geosciences, which explores the Survey of India 1” to 1-mile map series and outlines methods for using these historical maps for research on historical landscapes and settlement distribution. |
746446 |
|
|
|
| publications-2209 |
Peer reviewed articles |
2019 |
Green, Orengo, Alam, Garcia-Molsosa, Green, Conesa, Ranjan, Singh, Petrie |
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 |
Remote Sensing |
10.3390/rs11182089 |
Simulation & Modeling |
Groundwater |
|
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. |
746446 |
|
|
|
| publications-2210 |
Peer reviewed articles |
2020 |
Hector A. Orengo, Francesc C. Conesa, Arnau Garcia-Molsosa, Agustín Lobo, Adam S. Green, Marco Madella, Cameron A. Petrie |
Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data |
Proceedings of the National Academy of Sciences |
10.1073/pnas.2005583117 |
Uncategorized |
Groundwater |
|
Significance This paper illustrates the potential of machine learning-based classification of multisensor, multitemporal satellite data for the remote detection and mapping of archaeological mounded settlements in arid environments. Our research integrates multitemporal synthetic-aperture radar and multispectral bands to produce a highly accurate probability field of mound signatures. The results largely expand the known concentration of Indus settlements in the Cholistan Desert in Pakistan ( ca . 3300 to 1500 BC), with the detection of hundreds of new sites deeper in the desert than previously suspected including several large-sized (>30 ha) urban centers. These distribution patterns have major implications regarding the influence of climate change and desertification in the collapse of the largest of the Old-World Bronze Age civilizations. |
746446 |
|
|
|
