Rapid urbanization has intensified artificial light at night (ALAN) and reduced access to natural dark sky environments. Dark sky parks provide a potential spatial approach for nighttime environmental protection, ecological conservation, and astronom...
Land surface reflectance (LSR) data form the basis of quantitatively remotely sensed applications. For accurate LSR retrieval, atmospheric correction has been investigated by many researchers and implemented in typical processing systems, including c...
The condition of mechanical equipment during machining is closely related to the accuracy and roughness of the workpiece. In an intelligent sensing environment, a large amount of multi-source data reflecting status information are generated during pr...
Understanding the risks posed by potentially toxic metals (PTMs) in large regions is important for environmental management. However, regional risk assessment that relies on traditional field sampling or administrative statistical data is labor-inten...
To date, little attention has been given to remote sensing-based algorithms for inferring urban surface evapotranspiration. A multi-source parallel model based on ASTER data was one of the first examples, but its accuracy can be improved. We therefor...
Short-term load forecasting is an important task for the planning and reliable operation of power grids. High-accuracy forecasting for individual customers helps to make arrangements for generation and reduce electricity costs. Artificial intelligent...
Comprehensive, standardised, multi-temporal inventories of rainfall-induced landslides linked to soil moisture remain scarce, especially in tropical regions. Addressing this gap, we present a multi-source urban inventory for Brazil’s Baixada Sa...
Ocean energy holds out great potential for supplying remote maritime areas with their energy requirements, where the grid size is often small and unconnected to a continental grid. Thanks to their high maturity and competitive price, solar and wind e...
We conducted a detailed study using multi-source data to date the mare activity and lobate scarp formation within the Jules Verne crater on the Moon. In previous studies, the Jules Verne crater has been classified as a pre-Nectarian impact crater. Ou...
Urban industrial land (UIL), which is classified for industrial purposes, is an indispensable component of urban land. Obtaining up-to-date and timely UIL details from the industrial development perspective has practical significance for UIL planning...
Regional power grid load has strong periodicity and randomness, and its load characteristics are affected by many factors. Traditional short-term power load-forecasting methods have certain limitations in accuracy and stability, especially when deali...
Mobile crowdsensing (MCS) is attracting considerable attention in the past few years as a new paradigm for large-scale information sensing. Unmanned aerial vehicles (UAVs) have played a significant role in MCS tasks and served as crucial nodes in the...
Remote sensing of ice phenology for small lakes is hindered by a lack of satellite observations with both high temporal and spatial resolutions. By merging multi-source satellite data over individual lakes, we present a new algorithm that successfull...
In this paper, a lightweight, high-definition mapping method is proposed for autonomous driving to address the drawbacks of traditional mapping methods, such as high cost, low efficiency, and slow update frequency. The proposed method is based on mul...
The home monitoring of patients affected by chronic heart failure (CHF) is of key importance in preventing acute episodes. Nevertheless, no wearable technological solution exists to date. A possibility could be offered by Cardiac Time Intervals extra...
The Abuduo Fault is a Holocene left-lateral strike-slip fault located on the eastern margin of the Tibetan Plateau, potentially connecting eastward with the Garzê–Yushu Fault. Due to its high-altitude setting, this fault remains poorly st...
Remote sensing technology provides a feasible option for early prediction for wheat Fusarium head blight (FHB). This study presents a methodology for the dynamic prediction of this classic meteorological crop disease. Host and habitat conditions were...
Management zoning underpins precision agriculture, but conventional approaches relying on single-date imagery fail to capture inter-annual crop environment variations. Under increasing extreme climate events, single-year zoning exhibits limited adapt...
Rice is one of the world’s most important food crops, feeding over half of the global population and being crucial for food security. Accurate, timely mapping of rice fields is essential for precision agriculture, yet conventional methods relyi...
Sweet taste plays a pivotal role in human dietary behavior and metabolic regulation. With the increasing incidence of metabolic disorders linked to excessive sugar intake, the development and accurate evaluation of new sweeteners have become critical...
Studying population prediction under micro-spatiotemporal granularity is of great significance for modern and refined urban traffic management and emergency response to disasters. Existing population studies are mostly based on census and statistical...
Low-altitude aviation requires spatially resolved turbulence information, but routine observing networks do not directly measure dense three-dimensional eddy dissipation rate (EDR) fields. We formulate EDR retrieval as physics-constrained probabilist...
The mud area in the northern offshore of the Shandong Peninsula constitutes a dynamic source–sink system in China’s continental shelf and is a hotspot for research. However, the provenance of the sediments remains controversial, and the d...
Sentinel-1A and Landsat 8 images have been combined in this study to map rice fields in urban Shanghai, southeast China, during the 2015 growing season. Rice grown in paddies in this area is characterized by wide inter-field variability in addition t...
As one of the most principal meteorological factors to affect global climate change and human sustainable development, temperature plays an important role in biogeochemical and hydrosphere cycle. To date, there are a wide range of temperature data so...
Lysine lactylation (Kla) is a recently discovered post-translational modification implicated in energy metabolism, cellular reprogramming, and disease progression. Here, we train the existing ProteinBERT-based predictor PBertKla on an integrated mult...
This paper presents a unique case of the application of remote sensing methods in archaeological survey devoted to ancient pre-Roman Imperial roads in the Southern Levant. The results of our preparatory remote sensing research and subsequent fieldwor...
Recent advances in remote sensing technologies and the cost reduction of surveying, along with the importance of natural resources management, present new opportunities for mapping land cover at a very high resolution over large areas. This paper pro...
Acquiring a large number of in situ water spectral measurements is fundamental for constructing water color remote-sensing retrieval models and validating the accuracy of water color remote-sensing products. However, traditional manual site-based wat...
Land surface temperature plays an essential role in estimating radiation budgets, in heat balance studies, as a control for climate dynamics and for soil–vegetation–atmosphere transfer modeling, and in studying the impact of land use/land...
Against the backdrop of digital transformation in higher education, campus information is often dispersed across independent platforms, creating fragmented access and retrieval barriers. To address these challenges, this study proposes a multimodal a...
Consisting of ten cities in four Chinese provinces, the Huaihai Economic Zone has suffered serious air pollution over the last two decades, particularly of fine particulate matter (PM2.5). In this study, we used multi-source data, namely MAIAC AOD (a...
The European Space Agency (ESA) defines Earth observation (EO) Level 2 information product the stack of: (i) a single-date multi-spectral (MS) image, radiometrically corrected for atmospheric, adjacency and topographic effects, with (ii) its data-der...
Mangroves, as unique coastal wetlands with numerous benefits, are endangered mainly due to the coupled effects of anthropogenic activities and climate change. Therefore, acquiring reliable and up-to-date information about these ecosystems is vital fo...
As agricultural commodities become increasingly financialised, reliable soybean futures forecasts are important for risk management and market monitoring. This study examines the main No. 1 soybean futures contract listed on the Dalian Commodity Exch...
With global warming, ice avalanche hazards have escalated, becoming one of the most severe cryospheric disasters on the Qinghai–Tibet Plateau. To date, research on ice avalanches remains limited, focusing largely on individual glaciers and lack...
Urban park cooling accessibility is often assessed using temporally aggregated thermal performance, which may obscure variation in accessible cooling potential. We combined Landsat-derived park cooling intensity with a fixed network of 77 park destin...
Reliable carbon price forecasts support compliance planning and transition risk management, but multi-source backtests can appear accurate when observations are aligned by calendar date rather than actual availability. We develop a point-in-time fram...
This study investigates whether shareholder value creation, defined as beta-adjusted outperformance relative to a market benchmark, can be effectively predicted in an emerging market using a sequential machine learning framework. While prior research...
Wheat is one of the main crops in China, and crop yield prediction is important for regional trade and national food security. There are increasing concerns with respect to how to integrate multi-source data and employ machine learning techniques to...
As a vital part of the Eurasian temperate grassland, the Chinese temperate grassland is primarily distributed in the Inner Mongolia Plateau. This paper focuses on mapping temperate grassland dynamics from the 1980s to the 2010s in Inner Mongolia, whi...
Spatiotemporal fusion (STF) is considered a feasible and cost-effective way to deal with the trade-off between the spatial and temporal resolution of satellite sensors, and to generate satellite images with high spatial and high temporal resolutions....
Tracing the provenance and understanding the ore-forming processes of coastal zircon–titanium placers are important issues in placer research. The Wenchang area in Hainan Province is one of the important coastal zircon–titanium placer enr...
Land surface temperature (LST) serves as a pivotal component within the surface energy cycle, offering fundamental insights for the investigation of agricultural water environment, urban thermal environment, and land planning. However, LST monitoring...
In the era of big data, advances in relevant technologies are profoundly impacting the field of real estate appraisal. Many scholars regard the integration of big data technology as an inevitable future trend in the real estate appraisal industry. In...
Aboveground dry weight (AGDW) and leaf area index (LAI) are indicators of crop growth status and grain yield as affected by interactions of genotype, environment, and management. Unmanned aerial vehicle (UAV) based remote sensing provides cost-effect...
Honeypots and lightweight honeypoints record scanning, reconnaissance, and exploitation attempts against deliberately exposed services. In operational exports, however, observations from the same source are often split across dates, decoys, alerts, t...
This work presents a multi-objective approach for scheduling energy consumption in data centers considering traditional and green energy data sources. This problem is addressed as a whole by simultaneously scheduling the state of the servers and the...
Wildfires have become more frequent and intense worldwide due to climate change and anthropogenic activities, which is why accurate and timely burned area mapping is essential for estimating damage and effective post-fire recovery planning. Synthetic...
19 October 2022
Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and processing multi-source data to generate risk predictors and consuming significant time and computa...
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