Extra-wide-lane real-time kinematic (ERTK) is a technique that makes full use of extra-wide-lane (EWL) observations to realize instantaneous precise positioning. Beyond the previous study by using triple-frequency signals, the hexa- and penta-frequency signals, referred to as hyper-frequency signals in this study, are currently available for Beidou-3 and Galileo systems, respectively, which will be definitely beneficial to ERTK. In this study, the advantages and performance of hyper-frequency ERTK (HERTK) are profoundly addressed. The mathematical model of generalized HERTK is deduced with canonical formulae to show how model parameters profit from additional signals and high-precision EWL/WL observations. Specifically, the optimal linear combinations of hyper-frequency signals are determined in terms of ionosphere-weighted and ionosphere-float models. The precision gains of both position and ambiguity parameters are numerically demonstrated for single- and multi-epoch, accompanied by a comprehensible explanation of the hyper-frequency enhancement mechanism. The performance of HERTK is evaluated with three long baselines from 248.4 to 511.0 km. The results show that the HERTK achieves instantaneous decimeter-level solutions without the need for complicated narrow-lane (NL) ambiguity resolution (AR). Furthermore, centimeter HERTK can be realized by only accumulating NL phase data over approximately 20 epochs, which essentially leverages the more precise between-epoch information to smooth the noisy solutions. Besides the smoothed positions, the precision of NL ambiguity is also significantly improved, thus enabling rapid and reliable NL AR for long baselines. Higher accuracy of 1–2 cm solutions is achieved within 10–30 epochs.
The modification of the Turia River's course in the 1960s marked a pivotal transformation in Valencia's urban landscape, evolving from a flood protection measure into a hallmark of sustainable urban development. However, recent rainfalls and flooding events produced directly by the phenomenon known as DANA ((Isolated Depression at High Levels) in October 2024 have exposed vulnerabilities in the infrastructure, particularly in the rapidly urbanized southern areas, raising questions about the effectiveness of past solutions in the context of climate change and urban expansion. As a result of this fragility, more than 200 deaths have occurred, along with material losses in 87 municipalities, whose industrial infrastructure accounts for nearly one-third of the economic activity in the Province of Valencia, valued at 479.6 million euros. This paper presents, for the first time, a historical-document-based approach to evaluate the successes and shortcomings of Valencia's flood management strategies through policy and spatial planning analysis. Also, this paper remarks the ongoing challenges and potential strategies for enhancing Valencia's urban resilience, emphasizing the need for innovative water management systems, improved drainage infrastructure, and the renaturalization of flood-prone areas. The lessons learned from Valencia's experience in 1957 and 2024 can inform future urban planning efforts in similar contexts facing the dual pressures of environmental change and urbanization.
Hyperspectral remote sensing crop classification is crucial in precision agriculture management. However, existing studies are usually difficult to adequately model the complex nonlinear feature distributions in hyperspectral data, which often limits the classification performance and affects the recognition accuracy. In order to enhance the model’s ability to represent and discriminate complex nonlinear boundaries in hyperspectral images without introducing an attentional mechanism, an improved HybridSN (Hybrid-KANet) model based on the Kolmogorov-Arnold network (KAN) is proposed in this study. The model introduces a 3D fast kernel-activated convolutional layer, replaces the traditional linear activation function with a radial basis function (RBF), and realizes the nonlinear feature representation by spline paths and basis function paths. To enhance the model’s ability to model high-dimensional nonlinear features, a KANLinear layer is integrated into the classifier in place of the traditional fully connected structure. By employing fitting using learnable B-spline basis functions, the model can adaptively adjust to local features and achieve fine-grained approximation of complex decision boundaries in the input space. Experiments are conducted on Indian Pines and WHU-Hi-LongKou hyperspectral remote sensing datasets. The results show that the model achieves overall classification accuracies of 99.22% and 99.87% on the two datasets, which are 1.71% and 0.11% better than HybridSN; the mean intersection and merger ratio (mIoU) is improved by 4.77% and 0.53%, and the Kappa coefficient is improved by 1.96% and 0.15%, respectively. The ablation experiments demonstrate the advantages of RBF kernel function in modeling complex nonlinear relationships by systematically comparing the differences in classification performance and boundary modeling ability of different kernel functions, which improves the classification accuracy and spatial consistency. In conclusion, the Hybrid-KANet model proposed in this study provides theoretical innovation for precision agriculture management and a new solution for hyperspectral remote sensing crop classification.
Ao preparar este trabalho, não nos moveu, em absoluto, a pretensão de abordar assunto inédito ou de criar uma metodologia nova para solucionar problema antigo. Nossa intenção é, simplesmente, tentar eliminar dúvidas e controvérsias quanto à aplicabilidade do método aerofotogramétrico na preparação da base cartográfica indispensável ao projeto de obras de irrigação.
Kwestia kształtowania przestrzeni publicznych, choć jest tematem licznych analiz, rzadko odnosi się bezpośrednio do obszarów wiejskich. Tymczasem coraz częściej pojawia się potrzeba tworzenia i modernizacji wspólnych przestrzeni na terenach wiejskich. Celem pracy była ocena znaczenia rewitalizacji i potencjału turystycznego przestrzeni publicznej w opinii osób decydujących o zagospodarowaniu przestrzennym gmin powiatu tarnowskiego. W badaniach zastosowano kwestionariusz ankiety on-line przesłany do urzędów 16 gmin wiejskich i miejsko-wiejskich powiatu tarnowskiego oraz wywiady z przedstawicielami urzędów odpowiedzialnych za planowanie przestrzenne i promocję gminy. Wykazano, że gminy powiatu tarnowskiego są atrakcyjne pod względem turystycznym i zarówno mieszkańcy, jak i turyści chętnie korzystają z dostępnych elementów przestrzeni publicznej. Włodarze gmin doceniają znaczenie przestrzeni publicznej w życiu mieszkańców oraz w promocji gminy i w planach zagospodarowania często ujmują rewitalizację oraz tworzenie nowych miejsc wspólnych.
All ophiolite associations mark epochs of active tectonic movements, which lead to significant petrological processes and modification of the relief of the Earth's crust. Here we present a geological-petrographical characterization of one ophiolitic associations composed of: a) serpentinites; b) amphibolites-metamorphosed volcanic rocks and tuffs; c) metagabbros and metagabbrodiabases, placed among the Proterozoic metamorphic complex in the Rhodope Massif of Bulgaria on the Balkan Peninsula, South-Eastern Europе. The goal is to clarify the paleogeographical and geological setting during its creation. The methods of lithostratigraphic profiling and correlations on the database of geological field mapping were used, supplemented by microscopic, geochemical and isotopic studies of numerous rock samples. The summarized results confirm a certain stratigraphic level of the Ophiolite Association among the metamorphic complex and a complicated and protracted heterogenetic development, which is typical for the ophiolite associations created in eras of closing oceans, opposite movement of tectonic plates, subduction-obduction environment with appearance of autochthonous Neoproterozoic magmatism. Obducted fragments of serpentinites mark an old erosional continental surface, subsequently covered by transgressively deposited pelitic-carbonate sediments. The general conclusion of our study confirms the concept that the metamorphic complex of the Rhodope Massif represents a unified stratigraphic system consisting of two petrographic groups of different ages, with which we oppose the idea of a trust construction, launched by a group of geologists.
The hydroclimatological monitoring network in Haiti was inadequate before 2010 due to a lack of meteorological stations and inconsistent data recording. In the aftermath of the January 2010 earthquake, the monitoring network was reconstructed. In light of the prevailing circumstances and the mounting necessity for hydroclimatological data for water resource management at the national level, it is of paramount importance to leverage and optimize the limited available data to the greatest extent possible. The objective of this research is to develop regional equations that facilitate the transfer of climatic data from climatological stations to locations with limited or absent data. Physiographic and climatological characteristics are used to construct the hydrologic information transfer equations for sites with limited or no data. The validity of the regionalization techniques was assessed using cross-validation. The results enable estimation of hydrological events through the specific patterns of behavior of each region of the country, identified in cartography of homogeneous zones.
At present, states and entire regions that possess significant reserves of sought-after minerals have great potential to maintain and even improve their socio-economic position in the foreseeable future. Since the beginning of 2000, the increase in mining volumes of minerals has been more than 50%; however, more than half of all extracted raw materials fall to only five leading countries: China, the USA, the Russian Federation, Australia, and India. This article presents the results of the analysis of the global structure of mineral production by type and geographic region. The article provides an in-depth analysis of the world’s leading mining companies, identifying the key players in the industry. A comprehensive overview of each company’s performance, including key financial indicators and production statistics, is presented. The main environmental risks as a result of the continued increase in the global scale of mining have been identified. The prospects for the development of the mining sector are shown. The results of the study can be used by the scientific community as an information source.
Soner Uereyen, Igor Klein, Christina Eisfelder
et al.
With temperatures in Central Asia (CA) increasing more than the global average, this region is one of the global hotspots affected by climate change. CA is mostly characterized by arid climate, which is why available water resources are of paramount importance for the societies, economies, and the environment. In this regard, quantifying changes on the land surface and controlling factors that influence land surface dynamics are of great interest to improve our understanding of climate change impacts in this region. Hence, this study analyzes multivariate time series covering climatic, hydrological and Earth observation (EO)-based land surface variables. The used EO time series characterize the land surface and include data on the normalized difference vegetation index (NDVI), surface water area (SWA), and snow cover area (SCA) between December 2002 to November 2021. To analyze these time series, we employ trend analyses and a causal discovery algorithm. Both analyses were carried out at multiple spatial and temporal scales. The results show that NDVI trends were mostly significantly negative in the Northwest and positive in the Northeast of CA in summer. In summer and autumn, the percentage of significant negative NDVI trends outweighed the positive trends. For SWA, the detected trends were mostly significant negative throughout all scales. Significant negative trends were retrieved for SCA across all seasons, except for autumn regionally. Particularly the Tian Shan and Pamir mountains show significant declines of SCA in winter and spring. The causal analyses revealed that the NDVI is mostly controlled by water availability in summer. In spring and autumn, temperature is the leading driver on the NDVI. Likewise, temperature is found to largely control SWA in spring and autumn. SCA is mostly negatively coupled to temperature during spring and autumn. A positive coupling between SCA and precipitation is identified in winter.
Efficient building damage assessment after disasters is vital for emergency response and loss evaluation, but the task is complicated by diverse building structures and complex environments. Traditional methods using Convolutional Neural Networks (CNNs) struggle to capture global contextual features, limiting damage categorization accuracy. To address this, we introduce the High-Resolution Transformer Architecture for Building Damage Assessment (HRTBDA), which enhances multi-scale feature extraction. A Cross-Attention-Based Spatial Fusion (CSF) module is proposed to utilize the attention mechanism, improving the model’s ability to identify detailed associations in damaged buildings. Additionally, we propose a deep convolution network matching optimization strategy that integrates a multilayer perceptron and expands the receptive field, enhancing global feature perception. HRTBDA’s performance was evaluated on two public datasets and compared with five recent frameworks. The model achieved an F1-score of 86.0% in building localization and 78.4% in damage assessment, with a 4.8% improvement in detecting minor damages. These results demonstrate HRTBDA’s potential for improving building damage assessment and highlight its significant advancements over existing methods.
Mathematics as an area of study occupies an important place in higher education. Due in part to its utility in other disciplines as well as its role in student learning, institutions of higher education (IHEs) often have large numbers of mathematics faculty with different balances of teaching and research in different ranks and appointment structures. Most flagship IHEs, especially state land-grant institutions, have large undergraduate populations taking mathematics courses in many cases built around the widespread use of calculus and the connections between mathematics and science, technology, and engineering. These connections have made mathematics departments essential to universities\cite{olson2012engage} and emphasized the critical role math plays in supporting student success \cites{reinholz2020time,calcscience} in all areas of post-secondary education. We tend to take that essential nature of mathematics at the undergraduate level, and for research universities at the graduate level, as a given, but that characterization no longer holds for some IHEs.
Modeling-Simulation-Optimization workflows play a fundamental role in applied mathematics. The Mathematical Research Data Initiative, MaRDI, responded to this by developing a FAIR and machine-interpretable template for a comprehensive documentation of such workflows. MaRDMO, a Plugin for the Research Data Management Organiser, enables scientists from diverse fields to document and publish their workflows on the MaRDI Portal seamlessly using the MaRDI template. Central to these workflows are mathematical models. MaRDI addresses them with the MathModDB ontology, offering a structured formal model description. Here, we showcase the interaction between MaRDMO and the MathModDB Knowledge Graph through an algebraic modeling workflow from the Digital Humanities. This demonstration underscores the versatility of both services beyond their original numerical domain.
We define a mathematical notion of complex adaptive system by following the original intuition of G.K. Zipf about the principle of least effort, an intuitive idea which is nowadays informally widespread in complex systems modeling. We call generalized evolution principle this mathematical notion of interaction spaces theory. Formalizing and generalizing Mandelbrot's ideas, we also prove that a large class of these systems satisfy a power law. We finally illustrate the notion of complex adaptive system with theorems describing a Von Thünen-like model. The latter can be easily generalized to other complex systems and describes the appearance of emergent patterns. Every notion is introduced both using an intuitive description with lots of examples, and using a modern mathematical language.
ABSTRACT Buttenfield (1988) pioneered research on multiple representations in the dawn of GIScience. Her efforts evoked inquiries into fundamental issues arising from the selective abstractions of infinite geographic complexity in spatial databases, cartography, and application needs for varied geographic details. These fundamental issues posed ontological challenges (e.g. entity classification) and implementational complications (e.g. duplication and inconsistency) in geographic information systems (GIS). Expanding upon Buttenfield’s line of research over the last three decades, this study reviewed multiple representations in spatial databases, spatial cognition, and deep learning. Initially perceived as a hindrance to GIS, multiple representations were found to offer new perspectives to encode and decipher geographic complexity. This paper commenced by acknowledging Buttenfield’s pivotal contributions to multiple representations in GIScience. Subsequent discussions synthesized the literature to outline cognitive representations of space in the brain’s hippocampal formation and feature representations in deep learning. By cross-referencing related concepts of multiple representations in GIScience, the brain’s spatial cells, and machine learning algorithms, this review concluded that multiple representations facilitate learning geography for both humans and machines.
We re-examine the old question to what extent mathematics may be compared with a game. Mainly inspired by Hilbert and Wittgenstein, our answer is that mathematics is something like a rhododendron of language games, where the rules are inferential. The pure side of mathematics is essentially formalist, where we propose that truth is not carried by theorems corresponding to whatever independent reality and arrived at through proof, but is defined by correctness of rule-following (and as such is objective given these rules). Goedel's theorems, which are often seen as a threat to formalist philosophies of mathematics, actually strengthen our concept of truth. The applied side of mathematics arises from two practices: first, the dual nature of axiomatization as taking from heuristic practices like physics and informal mathematics whilst giving proofs and logical analysis; and second, the ability of using the inferential role of theorems to make surrogative inferences about natural phenomena. Our framework is pluralist, combining various (non-referential) philosophies of mathematics.