No abstract available.

This study investigates the surroundings of Munigua (municipium Flavium Muniguense), a small Roman town in the ancient province of Hispania Baetica (SW Spain). The city's economy was based primarily on copper and iron mining, which brought financial prosperity to its citizens. Local production of agricultural goods is thought to have been of little importance, as the regional soil conditions do not seem to be suitable for extensive agriculture. To evaluate the recent soil agro-potential and to find evidence for prehistoric and historic land use in the surroundings of Munigua, we applied a pedo-geomorphological approach based on the physico-chemical analysis of 14 representative soil and sediment exposures. Selected samples were analyzed for bulk chemistry, texture and phytoliths. The chronostratigraphy of the sequences was based on radiocarbon dating of charcoal samples. The site evaluation of the present-day soil agro-potential was carried out according to standard procedures and included evaluation of potential rootability, available water-storage capacity and nutrient budget within the uppermost 1 m. The results show that moderate to very good soil agro-potential prevails in the granitic and floodplain areas surrounding Munigua. Clearly, recent soil agro-potential in these areas allows the production of basic agricultural goods, and similar limited agricultural use should also have been possible in ancient times. In contrast, weak to very weak present-day soil agro-potential prevails in the metamorphic landscape due to the occurrence of shallow and sandy to stony soils. In addition, the study provides pedo-geomorphological evidence for prehistoric and historic land use in pre-Roman, Roman and post-Roman times. Catenary soil mapping in the vicinity of a Roman house complex reveals multi-layered colluvial deposits. They document phases of hillslope erosion mainly triggered by human land use between 4063 ± 82 and 3796 ± 76 cal BP, around 2601 ± 115 cal BP, and between 1424 ± 96 and 421 ± 88 cal BP. Moreover, geochemical and phytolith analyses of a Roman hortic Anthrosol indicate the local cultivation of agricultural products that contributed to the food supply of Munigua. Overall, the evidence of Roman agricultural use in the Munigua area indicates that the city's economy was by no means focused solely on mining. The production of basic agricultural products was also part of Munigua's economic portfolio. Our geoarcheological study thus supports the archeological concept of economically diversified Roman cities in the province of Baetica and in Hispania.

Snow cover (SC) and timing of snowmelt are key regulators of a wide range of Arctic ecosystem functions. Both are strongly influenced by the amplified Arctic warming and essential variables to understand environmental changes and their dynamics. This study evaluates the potential of Sentinel-1 (S-1) synthetic aperture radar (SAR) time series for monitoring SC depletion and snowmelt with high spatiotemporal resolution to capture their understudied small-scale heterogeneity. We use 97 dual-polarized S-1 SAR images acquired over northeastern Greenland and 94 over southwestern Greenland in the interferometric wide swath mode from the years 2017 and 2018. Comparison of S-1 intensity against SC fraction maps derived from orthorectified terrestrial time-lapse imagery indicates that SAR backscatter can increase before a decrease in SC fraction is observed. Hence, the increase in backscatter is related to changing snowpack properties during the runoff phase as well as decreasing SC fraction. We here present a novel empirical approach based on the temporal evolution of the SAR signal to identify start of runoff (SOR), end of snow cover (EOS) and SC extent for each S-1 observation date during melt using backscatter thresholds as well as the derivative. Comparison of SC with orthorectified time-lapse imagery indicates that HV polarization outperforms HH when using a global threshold. The derivative avoids manual selection of thresholds and adapts to different environmental settings and seasonal conditions. With a global configuration (threshold: 4 dB; polarization: HV) as well as with the derivative, the overall accuracy of SC maps was in all cases above 75 % and in more than half of cases above 90 %. Based on the physical principle of SAR backscatter during snowmelt, our approach is expected to work well in other low-vegetation areas and, hence, could support large-scale SC monitoring at high spatiotemporal resolution (20 m, 6 d) with high accuracy.

Digital platforms, understood as multi-sided matchmakers, have amassed huge power, reimagining the role of consumers, producers, and even ownership. They increasingly dictate the way the economy and urban life is organized. Yet, despite their influential and far-reaching role in shaping our economic as well as sociocultural world, our understanding of their embeddedness, namely how their activities are embedded in systems of social and societal relationships and how they conceptualize their main functions and actions in relation to their wider setting, remains rudimentary. Consequently, the purpose of this frontier paper is threefold. Firstly, it reveals the need to discuss and evaluate (dis-)embedding processes in platform urbanism in order to understand the underlying dynamics of platform power and urban transformation. Secondly, it aims to reveal the main reasons in regard to the difficulties in pinpointing digital platforms embeddedness. Thirdly, it seeks to propose future research unravelling the (dis-)embeddedness of the platform economy. This paper argues for three main reasons namely unawareness, unaccountability and non-transparency of digital platforms that drive the lack of embeddedness and reaffirms platform power. This is mainly based on the configuration of new commodities, platforms’ strategic avoidance of labour protections and other regulatory frameworks as well as platforms’ secrecy in which they operate. This frontier paper argues that transferring the concept of embeddedness to the platform economy might serve as a valuable tool to understand and pinpoint essential dynamics and relationships at play, therefore proposing embeddedness as a basis for future research on the platform economy. It strongly argues that a more detailed understanding is urgently needed, in order to be able to understand, accompany and actively influence the development of the platform economy in regulatory terms.

Remote sensing time series is the collection or acquisition of remote sensing data in a fixed equally spaced time period over a particular area or for the whole world. Near daily high spatial resolution data is very much needed for remote sensing applications such as agriculture monitoring, phenology change detection, environmental monitoring and so on. Remote sensing applications can produce better and accurate results if they are provided with dense and accurate time series of data. The current remote sensing satellite architecture is still not capable of providing near daily or daily high spatial resolution images to fulfill the needs of the above mentioned remote sensing applications. Limitations in sensors, high development, operational costs of satellites and presence of clouds blocking the area of observation are some of the reasons that makes near daily or daily high spatial resolution optical remote sensing data highly challenging to achieve. With developments in the optical sensor systems and well planned remote sensing satellite constellations, this condition can be improved but it comes at a cost. Even then the issue will not be completely resolved and thus the growing need for high temporal and high spatial resolution data cannot be fulfilled entirely. Because the data collection process relies on satellites which are physical system, these can fail unpredictably due to various reasons and cause a complete loss of observation for a given period of time making a gap in the time series. Moreover, to observe the long term trend in phenology change due to rapidly changing environmental conditions, the remote sensing data from the present is not just sufficient, the data from the past is also important. A better alternative solution for this issue can be the generation of remote sensing time series by fusing data from multiple remote sensing satellite which has different spatial and temporal resolutions. This approach will be effective and efficient. In this method a high temporal low spatial resolution image from a satellite such as Sentinel-2 can be fused with a low temporal and high spatial resolution image from a satellite such as the Sentinel-3 to generate a synthetic high temporal high spatial resolution data. Remote sensing time series generation by data fusion methods can be applied to the satellite images captured currently as well as the images captured by the satellites in the past. This will provide the much needed high temporal and high spatial resolution images for remote sensing applications. This approach with its simplistic nature is cost effective and provides the researchers the means to generate the data needed for their application on their own from the limited source of data available to them. An efficient data fusion approach in combination with a well planned satellite constellation can offer a solution which will ensure near daily time series of remote sensing data with out any gap. The aim of this research work is to develop an efficient data fusion approaches to achieve dense remote sensing time series.