Historical Maps Research Articles

An iterative and subsequent proximation method to map historical crop information with satellite images

Mapping agricultural information such as cropping area and type is of great significance for land use and food security and a common method to retrieve such information is satellite imagery classification. The current image classification techniques require a statistically large number of training samples to obtain representative spectral signatures, ideally collected during the satellite overpass time/date. Although this prerequisite sounds simple and easy in principle, it is extremely challenging and sometimes impossible when classifying historical satellite images, as one simply cannot go back in time to collect training datasets or ground truthing. In this paper, we introduce an iterative and subsequent proximation (ISP) method to circumvent this problem for historical image classifications for historical crop mapping. This method assumes that the same crops grown two years apart have similar spectral properties within the same growing season, with limited variation. This allows the use of the crop information classified in any given year (n) to be used as training samples for the next year (n + 1) or the previous year (n-1). Iteratively repeating n-1, n-2… process leads to the mapping of historical cropping information without a priori ground truthing data. To demonstrate the ISP feasibility, we first used the historical Landsat time-series data to map four major stable crops (rice, maize, soybean, and wheat) in Hailun County, Heilongjiang Province, China, and then further expanded the ISP application to the entire Heilongjiang Province to map cropping areas from 1982 to 2020, using the classification and regression trees (CART) algorithm. The results were validated for those years when actual cropping measurement data were available and further verified with statistical data for other years. The results indicated that the proposed ISP method was appropriate for the historical mapping of four major crops, with a mapping accuracy of approximately 80 % when validated with field data, and correlation coefficients of 0.86, 0.85, 0.91, and 0.94, respectively when compared with historical statistical cropping data. The crop mapping results showed distinct trends of northward expansion in each of the four crops in Heilongjiang Province, which agreed well with previous studies. In conclusion, the ISP method is quick, easy, and convenient for historical crop mapping, which is important in understanding the agricultural production history.

Systematics, distribution patterns and historical biogeography of the Central America wandering spider genus Kiekie Polotow & Brescovit, 2018 (Araneae: Ctenidae).

Kiekie Polotow & Brescovit, 2018 is a Neotropical genus of Ctenidae, with most of its species occuring in Central America. In this study, we review the systematics of Kiekie and describe five new species and the unknown females of K. barrocolorado Polotow & Brescovit, 2018 and K. garifuna Polotow & Brescovit, 2018, and the unknown male of K. verbena Polotow & Brescovit, 2018. In addition, we described the female of K. montanense which was wrongly assigned as K. griswoldi Polotow & Brescovit, 2018 (both species are sympatric). We provided a modified diagnosis for previously described species based on the morphology of the newly discovered species and in situ photographs of living specimens. We inferred a molecular phylogeny using four nuclear (histone H3, 28S rRNA, 18S rRNA and ITS-2) and three mitochondrial genes (cytochrome c oxidase subunit I or COI, 12S rRNA and 16S rRNA) to test the monophyly of the genus and the evolutionary relationships of its species. Lastly, we reconstruct the historical biogeography and map diversity and endemism distributional patterns of the different species. This study increased the number of known species of Kiekie from 13 to 18, and we describe a new genus, Eldivo which is sister lineage of Kiekie. Most of the diversity and endemism of the genus Kiekie is located in the montane ecosystems of Costa Rica followed by the lowland rainforest of the Pacific side (Limon Basin). Kiekie originated in the North America Tropical region, this genus started diversifying in the Late Miocene and spread to Lower Central America and South America. In that region, Kiekie colonized independently several times the montane ecosystems corresponding to periods of uplifting of Talamanca and Central Cordilleras.

Exploration of Genome-Wide Recombination Rate Variation Patterns at Different Scales in Pigs.

Meiotic recombination is a prevalent process in eukaryotic sexual reproduction organisms that plays key roles in genetic diversity, breed selection, and species evolution. However, the recombination events differ across breeds and even within breeds. In this study, we initially computed large-scale population recombination rates of both sexes using approximately 52 K SNP genotypes in a total of 3279 pigs from four different Chinese and Western breeds. We then constructed a high-resolution historical recombination map using approximately 16 million SNPs from a sample of unrelated individuals. Comparative analysis of porcine recombination events from different breeds and at different resolutions revealed the following observations: Firstly, the 1Mb-scale pig recombination maps of the same sex are moderately conserved among different breeds, with the similarity of recombination events between Western pigs and Chinese indigenous pigs being lower than within their respective groups. Secondly, we identified 3861 recombination hotspots in the genome and observed medium- to high-level correlation between historical recombination rates (0.542~0.683) and estimates of meiotic recombination rates. Third, we observed that recombination hotspots are significantly far from the transcription start sites of pig genes, and the silico-predicted PRDM9 zinc finger domain DNA recognition motif is significantly enriched in the regions of recombination hotspots compared to recombination coldspots, highlighting the potential role of PRDM9 in regulating recombination hotspots in pigs. Our study analyzed the variation patterns of the pig recombination map at broad and fine scales, providing a valuable reference for genomic selection breeding and laying a crucial foundation for further understanding the molecular mechanisms of pig genome recombination.

Explaining the spatial segregation of ethnic groups in an early industrial city: the case of Vyborg

Abstract An early industrial town’s spatial segregation is studied using empirical data concerning the Russian population of the town of Vyborg. Several hypotheses for explaining segregation are considered using spatial analysis. The spatial data are derived from historical maps and demographic data from various tax records. Socioeconomic segregation is studied as a possible cause of ethnic segregation. The main drivers of spatial segregation were the explicit policies of segregation enforced by both the Russian military administration and the town’s civilian administration. While the effects of segregation gradually diminished due to social diffusion, the impact of policy decisions driving segregation in the 18th and early 19th centuries was still visible in the population’s later 19th-century segregation. Yet neither the different preferences of Russians and others nor the income differences between areas explains the distribution of Russians. Segregation based on the membership of a guild was insignificant, with a few exceptions. Other factors such as discrimination, prejudice, and differences in housing market information probably contributed to segregation, but they cannot be studied with the data used.

Monitoring of toxic cyanobacterial blooms in Lalla Takerkoust reservoir by satellite imagery and microcystin transfer to surrounding farms

Cyanobacterial harmful algal blooms (CyanoHABs) threaten public health and freshwater ecosystems worldwide. In this study, our main goal was to explore the dynamics of cyanobacterial blooms and how microcystins (MCs) move from the Lalla Takerkoust reservoir to the nearby farms. We used Landsat imagery, molecular analysis, collecting and analyzing physicochemical data, and assessing toxins using HPLC. Our investigation identified two cyanobacterial species responsible for the blooms: Microcystis sp. and Synechococcus sp. Our Microcystis strain produced three MC variants (MC-RR, MC-YR, and MC-LR), with MC-RR exhibiting the highest concentrations in dissolved and intracellular toxins. In contrast, our Synechococcus strain did not produce any detectable toxins. To validate our Normalized Difference Vegetation Index (NDVI) results, we utilized limnological data, including algal cell counts, and quantified MCs in freeze-dried Microcystis bloom samples collected from the reservoir. Our study revealed patterns and trends in cyanobacterial proliferation in the reservoir over 30 years and presented a historical map of the area of cyanobacterial infestation using the NDVI method. The study found that MC-LR accumulates near the water surface due to the buoyancy of Microcystis. The maximum concentration of MC-LR in the reservoir water was 160 µg L−1. In contrast, 4 km downstream of the reservoir, the concentration decreased by a factor of 5.39 to 29.63 µgL−1, indicating a decrease in MC-LR concentration with increasing distance from the bloom source. Similarly, the MC-YR concentration decreased by a factor of 2.98 for the same distance. Interestingly, the MC distribution varied with depth, with MC-LR dominating at the water surface and MC-YR at the reservoir outlet at a water depth of 10 m. Our findings highlight the impact of nutrient concentrations, environmental factors, and transfer processes on bloom dynamics and MC distribution. We emphasize the need for effective management strategies to minimize toxin transfer and ensure public health and safety.

Temporally transferable crop mapping with temporal encoding and deep learning augmentations

Detailed maps on the spatial and temporal distribution of crops are key for a better understanding of agricultural practices and for food security management. Multi-temporal remote sensing data and deep learning (DL) have been extensively studied for deriving accurate crop maps. However, strategies to solve the problem of transferring crop classification models over time, e.g., training the model with data for a recent year and mapping back to the past, have not been fully explored. This is due to the lack of a generalized method for aggregating optical data with regard to the irregularity in annual clear sky observations and the scarcity of multi-annual crop reference data to support a more generalized DL model. In this study, we tackled these challenges by introducing a method namely Temporal Encoding (TE) to capture the irregular phenological information. Subsequently, we adapted and integrated two methods, i.e., Random Observations Selection (ROS) and Random Day Shifting (RDS) to simulate the variability of temporal sparsity as well as the shifts of crop phenology over different years. We tested this approach with a 1-dimensional Convolutional Neural Network (1D-CNN) and a Transformer Network models. Our results for both classifiers showed that models trained with crop reference data from 2018 and a dense time series of Landsat 7/8 and Sentinel-2 A/B data can be transferred with little decreases in accuracy to map 12 consecutive years from 2010 to 2021. The Transformer Network was slightly more accurate, while the 1D-CNN was much three times faster. Furthermore, the proposed models could achieve similar performances in the same years with and without fully available satellite information. The TE with ROS and RDS appears well suited for improving temporal transferability to support long term historic crop mapping.

Subnational Projections of Lymphatic Filariasis Elimination Targets in Ethiopia to Support National Level Policy.

Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030. Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level. Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets. The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.

Drivers of socio-spatial change in Istanbul: Historical and longitudinal analysis of 5 cases from Bakırköy

This article aims to reveal the social and spatial change in Bakırköy through time and to identify the drivers behind this transformation. Bakırköy has been chosen as it hosted the Roman, Byzantine, and Ottoman Empires, leading to its multicultural and layered structure. It has been influenced by the dominant features of each era, shaping socio-economic changes, spatial transformations, and urban planning practices over the historical process. The interaction of these socio-spatial elements within Bakırköy encompasses broad themes such as social differentiation, economic change, and urban governance, thereby presenting case studies to examine the dynamics of urban areas in Istanbul. The research has been conducted at two levels. First, spatial changes were examined through relevant documents, literature, and historical maps. The periods were determined as the state-led development period (1923-1950), liberalization period (1950-1980), neoliberal transformation period (1980-2000), and globalization period (post-2000), with the pre-1923 period being considered separately. Subsequently, five case studies were selected to represent different functional land use at the local level. The first case study involves an area known as the İskender Çelebi Farm in the 17th century, which was chosen to represent the transformation from a food production area to industrial production in the 18th century and has become a mass housing area in the 20th century, now known as the Ataköy districts. The second and third case studies represent the transformation from industrial production areas in the 19th and early 20th centuries to residential, tourism, and shopping areas. The fourth case study focuses on the coastal strip, which was used as a public space for ‘sea baths’ in the 19th century and today exists as luxury housing projects under private ownership. The fifth case study involves an area that served as an airport in the early 20th century and is currently planned for a hospital and green spaces, although it remains a public service.Through these cases, which demonstrate the shift from the productional use of space to consumption, the study seeks to answer the following questions: First, how do demographic and economic changes play a significant role in the differentiation of urban space, and in a related context, what is the local-scale impact of changing policies on the functional change of the selected cases? The findings reveal that industrial investments, supported by transportation investments, choose their locations in the changing/transforming economic order. The decentralization of industry and the privatization or transformation of public investments into consumption-focused urban areas through public-private partnerships have also been observed. The study aims to prove that this change in space lays the groundwork for social differentiation.

‘Everything In Its Right Place’—Selective Depositions in Bronze Age Southwest Sweden

Hoards have played a significant role in our narratives of the European Bronze Age, but their purpose and meaning have been the source of much debate. These debates have been positively impacted by studies that investigate the ways in which hoards are connected to specific landscape contexts. In this paper, we discuss the outcome of one such in-depth field study of 62 Bronze Age metalwork deposition locations from the Swedish province of Halland. By systematically analysing digital sources such as museum archives, church records and historical maps, we were able to establish the locations of a number of previously unlocated finds, which were then visited in the field. Through this combined archival work and fieldwork, we distinguished several patterns that allude to a connection between metalwork deposits, object types and specific places in the landscape. These patterns shed light on the landscape context of hoards in this region and illuminate how deposition patterns changed over time; we consider some factors that may help to explain these changes. The results emphasize the importance of landscape studies for understanding the role of selective deposition in European Bronze Age societies, and more broadly, the social implications of hoards in their context.

Spatial constraints in cellular automata-based urban growth models: A systematic comparison of classifiers and input urban maps

Spatial constraints are fundamental to integrating the spatial suitability to urbanization into Cellular Automata-based (CA) urban growth models, but there is a lack of consensus on the optimal methods for this purpose. This study compared the performance of three probabilistic classifiers to generate suitability surfaces for CA-based urban growth models: Logistic Regression using Generalized Linear Model (LR-GLM), Logistic Regression using Generalized Additive Model (LR-GAM), and Random Forest (RF). The study also evaluated the sensitivity of these classifiers to the input urban map adopted as a dependent variable. For this analysis, seven maps were tested: the historical urban map containing the entire extent of the urban footprint, and six additional maps containing only the recently urbanized areas over timeframes ranging from one year up to two decades. The comparison evaluated the goodness of fit of the suitability surfaces and the spatial accuracy of the urban growth simulations, using five large Brazilian cities as case study areas. The results revealed that the RF classifier significantly outperformed the LR-based classifiers. However, this overperformance was more prominent when incorporating the new urban cells over the last one to two decades of growth as input urban maps. In addition, the sensitivity analysis of the input urban maps emphasized the benefits of calibrating the classifier using the recently urbanized cells rather than the historical urban extent. We consistently observed these results concerning classifiers and input urban maps across all five case study areas. Thus, the RF classifier combined with a training dataset containing the newly urbanized areas over at least the last 10 years systematically resulted in the suitability surfaces with the highest predictability among all tested scenarios.

Blending Indigenous and western science: Quantifying cultural burning impacts in Karuk Aboriginal Territory.

The combined effects of Indigenous fire stewardship and lightning ignitions shaped historical fire regimes, landscape patterns, and available resources in many ecosystems globally. The resulting fire regimes created complex fire-vegetation dynamics that were further influenced by biophysical setting, disturbance history, and climate. While there is increasing recognition of Indigenous fire stewardship among western scientists and managers, the extent and purpose of cultural burning is generally absent from the landscape-fire modeling literature and our understanding of ecosystem processes and development. In collaboration with the Karuk Tribe Department of Natural Resources, we developed a transdisciplinary Monte Carlo simulation model of cultural ignition location, frequency, and timing to simulate spatially explicit cultural ignitions across a 264,399-ha landscape within Karuk Aboriginal Territory in northern California. Estimates of cultural ignition parameters were developed with Tribal members and knowledge holders using existing interviews, historical maps, ethnographies, recent ecological studies, contemporary maps, and generational knowledge. Spatial and temporal attributes of cultural burning were explicitly tied to the ecology of specific cultural resources, fuel receptivity, seasonal movement patterns, and spiritual practices. Prior to colonization, cultural burning practices were extensive across the study landscape with an estimated 6972 annual ignitions, averaging approximately 6.5 ignitions per Indigenous fire steward per year. The ignition characteristics we document align closely with data on historical fire regimes and vegetation but differ substantially from the location and timing of contemporary ignitions. This work demonstrates the importance of cultural burning for developing and maintaining the ecosystems present at the time of colonization and underscores the need to work collaboratively with Indigenous communities to restore ecocultural processes in these systems.

Mapmaking Process Reading from Local Distortions in Historical Maps: A Geographically Weighted Bidimensional Regression Analysis of a Japanese Castle Map

Shoho Castle Maps are maps of castle towns throughout Japan drawn by Kano School painters on the order of the shogun in 1644. The Shoho Castle Map of Takada, Joetsu City, Niigata Prefecture was used to visualize local distortions in historical maps and to scrutinize the mapmaking process. A novel method, geographically weighted bidimensional regression, was developed and applied to visualize the local distortions of the map. Exaggerated expressions by mapmakers that have not been identified in previous studies were revealed. That is, in addition to the castle being drawn enlarged, the town where the merchants and artisans lived was drawn larger than the castle. Therefore, the Takada Shoho Castle Map reflects mapmakers’ intentions, besides enlarging military facilities, which appear to have emphasized the pictorial composition of the map by placing the main gate to the castle at the center and drawing the map area evenly from the center in a well-balanced layout.

Reconstructing of historical land cover based on contemporary cartographical materials

Historical land use reconstructions help to assess climate change, interactions between ecosystems and human and strengthen the knowledge about these interactions. They are conducted on the basis of historical maps that only cover certain areas. Hence, there is a need to seek other maps enabling historical land use to be reconstructed. The aim of study is to assess the suitability of contemporary maps for reconstructing a historical non-forest area range in the Western Carpathians. The content of contemporary maps was compared with that of historical maps, including the number of glades, their area and the length of their boundaries. Over 60% of glades were reconstructed, which is 90% of the glade area inventoried based on historical maps. Over 50% glades with an area of less than 1ha were not reconstructed. However, the area they occupy does not account for 2% of the total glade area. Thus, it has no significant impact on the total area of the reconstructed glades. As much as 90% of the boundaries' length was reconstructed. The study shows that contemporary maps may be useful in reconstructing the forest and glades range and may be an additional source of information to verify the content of historical maps.

Centennial loss of lake wetlands in the Yangtze Plain, China: Impacts of land use changes accompanied by hydrological connectivity loss

Humans have played a fundamental role in altering lake wetland ecosystems, necessitating the use of diverse data types to accurately quantify long-term changes, identify potential drivers, and establish a baseline status. We complied high-resolution historical topographic maps and Landsat imagery to assess the dynamics of the lake wetlands in the Yangtze Plain over the past century, with special attention to land use and hydrological connectivity changes. Results showed an overall loss of 45.6 % (∼11,859.5 km2) of the lake wetlands over the past century. The number of lakes larger than 10 km2 decreased from 149 to 100 due to lake dispersion, vanishing, and shrinkage. The extent of lake wetland loss was 3.8 times larger during the 1930s–1970s than that in the 1970s–1990s. Thereafter, the lake wetland area remained relatively stable, and a net increase was observed during the 2010s–2020s in the Yangtze Plain. The significant loss of lake wetland was predominately driven by agricultural activities and urban land expansion, accounting for 81.1 % and 4.9 % of the total losses, respectively. In addition, the changes in longitudinal and lateral hydrological connectivity further exacerbated the lake wetland changes across the Yangtze Plain through isolation between lakes and the Yangtze River and within the lakes. A total of 130 lakes have been isolated from the Yangtze River due to the construction of sluices and dykes throughout the Yangtze Plain, resulting in the decrease in the proportion of floodplain marsh from 28.3 % in the 1930s to 8.0 % in the 2020s. Furthermore, over 260 sub-lakes larger than 1 km2 (with a total area of 1276.4 km2) are experiencing a loss of connectivity with their parent lakes currently. This study could provide an improved historical baseline of lake wetland changes to guide the conservation planning to wetland protection and prioritization area in the Yangtze Plain.

A ‘sea monster’ depicted in the 1585 map of Iceland may exemplify spy-hopping behaviour in cetaceans

While there is a long history of misidentifying whales as sea monsters, historical maps and anecdotes can provide early depictions and descriptions of cetacean biology. For example, the map of ‘Islandia’ [Iceland] reproduced by Abraham Ortelius (1527–1598) in numerous printings of his atlas Theatrum orbis terrarum has an array of sea monsters, including the ‘Staukul’, that was said to stand upright out of the water for extended periods. This may be the earliest portrayal of spy-hopping, a common behaviour in which whales elevate themselves above the water to observe their surroundings.

Economic Development Drives Massive Global Estuarine Loss in the Anthropocene

AbstractEstuaries have great ecological and economic value and sustain both population and economic growth. Global‐scale analyses suggest that human activities drive estuarine area change but these projections neglect direct human‐estuary interactions and socio‐economic feedbacks. Here, we quantified area changes of 2,396 estuaries in response to recent human impacts (e.g., land reclamation, estuarine dam construction) and economic development between 1984 and 2019, and find that estuarine area shrank by 5,372 km2 whereas upland submergence created 5,015 km2 of estuarine area elsewhere. Approximately 44% (n = 1,046) of today's estuaries have been directly altered through land reclamation, estuarine dam construction, or a combination of both, and ∼250,000 acres (1,027 km2) of estuarine area have been directly converted to urban or agricultural fields. Nearly 90% (923 km2) of land reclamation occurred in Asia linked to recent advances in economic development during the middle‐income stage. Additional historical mapping and 5‐year interval analyses revealed that while human alterations were insignificant during the low‐income stages, estuaries were predominantly altered during their middle‐income stages, where estuarine degradation is a common consequence of economic growth. However, this trend stabilizes in high‐income countries with the adaption of conservation laws and policies. Together, our results indicate that large‐scale estuarine loss can be avoided by preserving estuaries in low‐ and mid‐income countries in the early stages of economic development.

Extracting Typical Samples Based on Image Environmental Factors to Obtain an Accurate and High-Resolution Soil Type Map

Soil surveying and mapping provide important support for environmental science research on soil and other resources. Due to the rapid change in land use and the long update cycle of soil maps, historical conventional soil maps (CSMs) may be outdated and have low accuracy. Therefore, there is an urgent need for accurate and up-to-date soil maps. Soil has a high correlation with its corresponding environmental factors in space, and typical samples contain an appropriate soil–environment relationship of soil types. Understanding how to extract typical samples according to environmental factors and determine the implied soil–environment relationship is the key to updating soil maps. In this study, a hierarchical typical sample extraction method based on land use type and environmental factors was designed. According to the corresponding relationship between the soil type and the land use type (ST-LU), the outdate soil map patches caused by changes in land use were excluded, follow by typical samples being extracted according to the peak intervals of the soil–environmental factor histograms. Additionally, feature selection was performed through variance analysis and mutual information, and four machine learning models were used to predict soil types. In addition, the influence of environmental factors on soil prediction was discussed, in terms of variable importance analysis. Using an overall common validation set, the results show that the prediction accuracy using typical samples for learning in the modeling set is above 0.8, while the prediction accuracy when using random samples is only about 0.4. Compared with the original soil map, the accuracy and resolution of the predicted soil maps based on typical samples are greatly improved. In general, typical samples can effectively explore the actual soil–environment knowledge implied in the soil type map. By extracting typical samples from historical soil type map and combining them with high-resolution remote sensing data, we can generate new soil type maps with high accuracy and short update cycle. This can provide some references for typical sampling design and soil type prediction.

Structural Control at Monte Somma and Vesuvio during the Last 5600 Years through Time and Space Distribution of Volcanic Vents

Vesuvio is likely the most if not one of the most dangerous volcanoes in the world. It is an active volcano, quiescent since 1944. The activity of the Monte Somma and Vesuvio volcanic complex is commonly referred to as two central volcanic edifices, namely Monte Somma and Vesuvio. Nevertheless, the opening of numerous eruptive fissures and related vents have characterized Monte Somma and Vesuvio throughout their lives. Spatter cones, spatter ramparts, and related eruptive fissures are disseminated downslope of Vesuvio’s main cone and on the southern slopes of the volcano. Similarly, cinder cones, spatter cones, and welded spatters are distributed in the sequence cropping out on the Monte Somma cliff and on the northern slopes of Monte Somma. In this work, a total of 168 eruptive vents have been identified and characterized in a GIS environment in which field data have been merged with relevant information from historical maps and documents. These vents have been arranged into units bounded by unconformities (Unconformity Bounded Stratigraphic Units) defining the eruptive history of the volcano. Alignments of vents and eruptive fissures within each unit have been compared with regional tectonic elements and the volcano-tectonic features affecting Monte Somma and Vesuvio during the last 5600 years, thus inferring that different structural trends were active in the different stratigraphic units. In particular, we show that the N300°–320° regional, Apennine, left-lateral, strike-slip fault system, the N040°–055° Torre del Greco direct fault system, the N70° and the EW fault system, and the generally NS oriented group of local brittle elements, all analyzed here, were differently active during the investigated time span. These tectonic trends might control the position of the eruptive fissures and vents in case of future unrest of the volcano.

Development Of Historical Map Using Padlet To Improve Students' Chronological Thinking Skills

Development Of Historical Map Using Padlet To Improve Students' Chronological Thinking Skills

High-Resolution Temperature Evolution Maps of Bangladesh via Data-Driven Learning

As a developing country with an agricultural economy as a pillar, Bangladesh is highly vulnerable to adverse effects of climate change, so the generation of high-resolution temperature maps is of great value for Bangladesh to achieve agricultural sustainable development. However, Bangladesh’s weak economy and sparse meteorological stations make it difficult to obtain such maps. In this study, by mining internal features and links inside observed data, we developed an efficient data-driven downscaling technique to generate high spatial-resolution temperature distribution maps of Bangladesh directly from observed temperature data at 34 meteorological stations with irregular distribution. Based on these high-resolution historical temperature maps, we further explored a data-driven forecast technique to generate high-resolution temperature maps of Bangladesh for the period 2025–2035. Since the proposed techniques are very low-cost and fully mine internal links inside irregular-distributed observations, they can support relevant departments of Bangladesh to formulate policies to mitigate and adapt to climate change in a timely manner.