Sökresultat - "multi-source data"

Urban vitality is a critical indicator of urban development quality and livability. However, existing studies often rely on single-source data or subjective evaluation methods, making it challenging to comprehensively and objectively capture the spatial-temporal characteristics of urban vitality. Th...

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The grassland in Inner Mongolia was classified using the method of integrating remote sensing data with non-remote sensing data. Based on daily MODIS enhanced vegetation index (EVI), monthly MODIS EVI was calculated, and was analyzed by principal component analysis (PCA) further, whose first three c...

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The design of effective forest management strategies requires the precise characterization of forested areas. Currently, different remote sensing technologies can be used for forest mapping, with optical sensors being the most common. The objective of this study was to evaluate the synergistic use o...

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Assessing energy consumption in existing old residential buildings is key for urban energy conservation and decarbonization. Previous studies on old residential building energy assessment face challenges due to data limitations and inadequate prediction methods. This study develops a novel approach...

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Waterlogging and flood disasters, often induced by persistent heavy precipitation, present additional hurdles to China’s agricultural resilience.. Assessing the impact of waterlogging disasters on crops is an essential basis for guiding agricultural disaster prevention and mitigation, and is of grea...

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Establishing nature reserves is an effective measure to achieve SDG 15.5, but human disturbances have reduced their conservation efficacy, making it essential to closely monitor human activities and their impacts within these areas. The paper proposes a framework to monitor human activities and eval...

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Rice yield prediction is critical for ensuring food security, particularly in major rice-producing countries like China. While Unmanned Aerial Vehicles (UAVs) equipped with hyperspectral imaging are widely used for yield prediction due to its ability to capture detailed spectral information, they ma...

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[Objective] In response to four major challenges faced in the development of urban rail transit O&M (operation and maintenance), Nanning Rail Transit Line 4 is taken as the practice platform to construct an intelligent O&M system for signaling system driven by data and intelligent decision-m...

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Multi-source remote sensing spatiotemporal fusion aims to enhance the temporal continuity of high-spatial, low-temporal-resolution images. In recent years, deep learning-based spatiotemporal fusion methods have achieved significant progress in this field. However, existing methods face three major c...

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Grasslands constitute the largest terrestrial ecosystem, currently sequestering significant amounts of atmospheric carbon and playing a critical role in climate change mitigation and the global carbon cycle. Tajikistan is a key representative of Central Asian, effective and accurate grassland Above-...

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The combination of extreme rainfall and rapid urbanisation significantly escalates flood risks in major cities, underscoring the importance of accurately identifying causative factors and formulating differentiated management strategies to enhance urban resilience. This study focuses on the central...

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To better understand the temperature changes in face slab concrete and address challenges such as delayed curing and outdated methods in complex and variable environments, this study investigates the use of visualization and real-time feedback control in concrete construction. The conducted study sy...

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Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. Current one-class classification (OCC) approaches are mainly designed...

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The sound speed profile (SSP) is an important feature in the field of ocean acoustics. The accurate estimation of SSP is significant for the development of underwater position, communication, and associated fundamental marine research. The Res-SACNN model is proposed for SSP inversion based on the c...

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This paper presents a multi-source data-driven hybrid path planning framework that integrates global A* search with local Deep Q-Network (DQN) optimization to address complex terrestrial routing challenges. By fusing ASTER GDEM terrain data with OpenStreetMap (OSM) road networks, we construct a stan...

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Accurate crop yield prediction is essential for stabilizing food supply chains and reducing the uncertainties in financial risks related to agricultural production. Yet, it is even more essential to understand how crop yield models make predictions depending on their relationship to Earth Observatio...

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This study addresses the suboptimal efficiency of regional science and technology innovation resource allocation by proposing a multi-source data fusion algorithm grounded in set pair analysis. Through a systematic review of theories and methodologies on science and technology innovation resource al...

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High-speed rail (HSR) station areas play a vital role in shaping urban form, stimulating economic activity, and enhancing spatial vitality. Understanding the factors that influence this vitality is key to supporting sustainable urban development and transit-oriented planning. This study investigates...

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As urbanization has accelerated, rail transit has evolved from being a mere means of transportation to a public area that houses the city’s cultural memory and serves as a crucial portal for the public to understand the culture of the city. As an urban public space with huge passenger flow, the metr...

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Amid rapid urbanization and accelerated population aging, spatial inequality in the distribution of healthcare facilities has become a pressing challenge in Shenyang. The dual problem of overconcentration of high-level medical resources in the urban core and insufficient primary care provision in pe...

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