Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information o...
Local climate zones (LCZ) have become a generic criterion for climate analysis among global cities, as they can describe not only the urban climate but also the morphology inside the city. LCZ mapping based on the remote sensing classification method...
The distribution of data plays a key role in the designing of a machine learning model. Therefore, this paper proposes a novel auto encoder network based on the distribution of polarimetric synthetic aperture radar (PolSAR) data matrix. Designed spec...
Motion object detection (MOD) with freely moving cameras is a challenging task in computer vision. To extract moving objects, most studies have focused on the difference in motion features between foreground and background, which works well for dynam...
This paper develops a novel classification optimization approach integrating class adaptive Markov Random Field (MRF) and fuzzy local information (CAMRF-FLI) for high spatial resolution multispectral imagery (HSRMI). Firstly, the raw classification r...
Quantifying the information content of remote sensing images is considered to be a fundamental task in quantitative remote sensing. Traditionally, the grayscale entropy designed by Shannon’s information theory cannot capture the spatial structu...
Hyperspectral band selection (BS) is an important technique to reduce data dimensionality for the classification applications of hyperspectral remote sensing images (HSIs). Recently, searching-based BS methods have received increasing attention for t...
Recent advancements in digital signal processing and lightweight neural architectures have opened new possibilities for developing efficient and interference-resilient indoor localization systems suitable for next-generation wireless networks. This p...
Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been...
Currently, small object detection in complex remote sensing environments faces significant challenges. The detectors designed for this scenario have limitations, such as insufficient extraction of spatial local information, inflexible feature fusion,...
The purpose of this paper is to analyze the media visibility of investments implemented in Wrocław, with a particular focus on the democratization of urban processes through the Wrocław Participatory Budget (WPB) and to study the public per...
Hyperspectral imaging technology with sufficiently discriminative spectral and spatial information brings new opportunities for robust facial image recognition. However, hyperspectral imaging poses several challenges including a low signal-to-noise r...
The goal of cross-view image based geo-localization is to determine the location of a given street-view image by matching it with a collection of geo-tagged aerial images, which has important applications in the fields of remote sensing information u...
Learning the spatial location associated with visual cues in the environment is crucial for survival. This ability is supported by a distributed interactive network. However, it is not fully understood how the most important task-related brain areas...
Across the United States, there has been a growing interest in local food production, which provides an alternative way to increase self-sufficiency and support greater well-being and food security at the community level. This study focused on the No...
In this paper, a high-accuracy localization problem under a complex non-line-of-sight (NLOS) condition is addressed by a new method that utilizes multiple NLOS paths to improve localization accuracy, as opposed to the traditional method of suppressin...
Local climate zones (LCZs) provide a robust framework for understanding Urban Heat Island dynamics and for supporting climate-sensitive urban planning. Although widely adopted since their introduction in 2012, LCZ mapping remains constrained by urban...
A technology to search for victims in disaster areas by localizing human-related sound sources, such as voices and emergency whistles, using a drone-embedded microphone array was researched. One of the challenges is the development of sound source lo...
Accessibility of urban residents to different services and amenities is a growing concern for policy makers. Urban green spaces (UGS) provide services and benefits that are particularly important for people having less mobility, such as children, the...
The asymmetries between rural and urban areas have continued to increase over the last decades, contributing to an imbalance of economic, social, and territorial dimensions between regions. Urban stores specialized in the commercialization of rural p...
Participatory mapping is a valuable approach for documenting the influence of human activities on species, ecosystems, and ecosystem services, as well as the variability of human activities over space and time. This method is particularly valuable in...
Fingerprinting-based positioning exploiting in two dimensions the spatial side information on fingerprints from adjacent positions relative to a target position is studied. The positioning is performed at the positioning device, utilizing as fingerpr...
This paper proposes a physics-informed identification framework for the spatial and dynamic responses of dual-element pyroelectric infrared (PIR) sensors using variable circular-aperture excitation. The dynamic half is carried through to experimental...
Facing the challenge of the degradation of global water quality, it is urgent to realize the Sustainable Development Goal 6.3.2 (SDG 6.3.2), which focuses on improving global water quality. Currently, remote sensing technology is widely used for wate...
The combination of encryption and digital watermarking technologies is an increasingly popular approach to achieve full lifecycle data protection. Recently, reversible data hiding in the encrypted domain (RDHED) has greatly aroused the interest of ma...
In general, low density airborne LiDAR (Light Detection and Ranging) data are typically used to obtain the average height of forest trees. If the data could be used to obtain the tree height at the single tree level, it would greatly extend the usage...
Global ocean heat content (OHC) is generally estimated using gridded, model and reanalysis data; its change is crucial to understanding climate anomalies and ocean warming phenomena. However, Argo gridded data have short temporal coverage (from 2005...
The rapid development of marine ranching in recent years provides a new way of tackling the global food crisis. However, the uncontrolled expansion of coastal aquaculture has raised a series of environmental problems. The fast and accurate detection...
With the rapid development of global navigation satellite systems (GNSS) and their increasingly wide range of applications in atmospheric science, total electron content (TEC) data are widely used in the theoretical study of layer coupling related to...
Accurate thermospheric mass density (TMD) prediction is critical for applications in solar-terrestrial physics, spacecraft safety, and remote sensing systems. While existing deep learning (DL)-based TMD models are predominantly data-driven, their per...
The classification and extraction of street tree geometry information in road scenes is crucial in urban forest biomass statistics and road safety. To address the problem of 3D fine extraction of street trees in complex road scenes, this paper design...
Accurately and precisely grasping the spatial distribution and changing trends of China’s regional population is of great significance in new urbanization, economic development, public health, disaster assessment, and ecological environmental p...
Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With the technolog...
Geographical object classification and information extraction is an important topic for the construction of 3D virtual reality and digital twin cities in urban areas. However, the majority of current multi-target classification of urban scenes uses o...
30 June 2022
Monitoring the fine spatiotemporal distribution of urban GDP is a critical research topic for assessing the impact of the COVID-19 outbreak on economic and social growth. Based on nighttime light (NTL) images and urban land use data, this study const...
3 April 2022
Rapid economic and social development has caused serious atmospheric environmental problems. The temporal and spatial distribution characteristics of PM2.5 concentrations have become an important research topic for sustainable social development moni...
An accurate estimation of evapotranspiration (ET) from crops is crucial in irrigation management, crop yield assessment, and optimal allocation of water resources, particularly in arid regions. This study explores the estimation of seasonal evapotran...
Tea is an important economic plant, which is widely cultivated in many countries, particularly in China. Accurately mapping tea plantations is crucial in the operations, management, and supervision of the growth and development of the tea industry. W...
The identification and representation of building roof topology are basic, but important, issues for 3D building model reconstruction from point clouds. Always, the roof topology is expressed by the roof topology graph (RTG), which stores the plane–p...
Industrial agglomeration, as a typical aspect of industrial structures, significantly influences policy development, economic growth, and regional employment. Due to the collection limitations of gross domestic product (GDP) data, the traditional ass...
With the rapid development of Unmanned Aerial Vehicle (UAV) technology, more and more UAVs have been used in forest survey. UAV (RGB) images are the most widely used UAV data source in forest resource management. However, there is some uncertainty as...
The intertidal zone, as a dynamic ecosystem at the interface of land and sea, plays a critical role in environmental protection and disaster mitigation. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is equipped with the Advanced Topograph...
The biomass of rice at maturity serves as a vital indicator for assessing overall productivity, and its accurate estimation holds significant importance for ensuring food security and promoting sustainable agriculture. To improve the precision of cur...
Chlorophyll-a (chl-a) is an important parameter of water quality and its concentration can be directly retrieved from satellite observations. The Ocean and Land Color Instrument (OLCI), a new-generation water-color sensor onboard Sentinel-3A and Sent...
Data about the movements of diverse objects, including human beings, animals, and commodities, are collected in growing amounts as location-aware technologies become pervasive. Clustering has become an increasingly important analytical tool for revea...
Chlorophyll-a (Chla) and total suspended solid (TSS) concentrations are important parameters for water quality assessment, and in recent years, machine learning has been shown to have great potential in this field. However, current water quality para...
Surface reflectance (SR) estimation is the most essential preprocessing step for multi-sensor remote sensing inversion of geophysical parameters. Therefore, accurate and stable atmospheric correction is particularly important, which is the premise an...
Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Great...
The coastline plays an important role in indicating the conditions of social-economic development in the coastal zone. In this study, an integrated assessment framework was proposed to address the provincial and county-level spatiotemporal dynamics o...
It is significant to study the vegetation of protected areas in rugged mountains where the vegetation grows naturally with minimal eco-society environmental stress from anthropogenic activities. The shadow-eliminated vegetation index (SEVI) was used...
of 103