Sparse wavelength division multiplex (WDM) enabled distributed satellite cluster networks (DSCNs) have emerged as a promising architecture to accommodate future extensive applications. Networking of the DSCNs will face the challenges of explosively i...
Satellite battery status prediction is crucial for ensuring the healthy operation of future satellite constellations. However, traditional telemetry-based methods, where satellite battery status is transmitted in real time to ground stations for proc...
Low Earth Orbit (LEO) satellite communication networks have become an important means to provide internet access services for areas with limited infrastructure. Compared with the Geostationary Earth Orbit (GEO) satellites, the LEO satellites have lim...
To solve the transmission correlation issue arising from traditional named data networking (NDN) caching during segmenting contents, where users must obtain data blocks related to the requested file blocks to recover the source data, in this paper, w...
The accuracy of Precise Orbit Determination (POD) for Global Navigation Satellite Systems (GNSS) critically depends on optimal tracking station selection. This study proposed and validates a novel framework that integrates a hybrid-weight Technique f...
The satellite-mediated continuous-variable quantum key distribution (CV-QKD) protocol, which relies on off-the-shelf telecommunication components, has the potential for a global quantum communication network with all-day operation. However, the trans...
Research in quantum communications networks (QCNs), where multiple users desire to generate or transmit common quantum-secured information, is still in its beginning stage. To solve for the problems of both discrete variable- and continuous variable-...
This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inferenc...
Geosynchronous satellite maneuver detection is critical for enhancing space situational awareness and inferring satellite intent. However, traditional methods often require high-quality orbital sequence data and heavily rely on hand-crafted features,...
The integration of satellite-borne and ground-based global lightning location networks offers a better perspective to study lightning processes and their evolutionary characteristics within thunderstorm clouds, thereby bolstering the predictive capab...
Backbone satellites in a space information network (SIN) can be used as air base stations or data relay satellites (DRSs) to realize cross-system, cross-network and long-distance relay transmission. In this paper, a traffic load optimization problem...
Studies that use rivers in a last-mile delivery context are scarce. This research considers the first multimodal alternative based on a barge for parcel delivery activities. It proposes two sustainable network designs for a two-echelon distribution....
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoenco...
Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computin...
The traditional on-board centralized-distributed mission negotiation architecture has poor security and reliability. It can easily give rise to the collapse of the whole system when the master node is attacked by malicious nodes. To address this issu...
Geospatial three-dimensional (3D) raster data have been widely used for simple representations and analysis, such as geological models, spatio-temporal satellite data, hyperspectral images, and climate data. With the increasing requirements of resolu...
Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delinea...
Understanding the biases in Deep Neural Networks (DNN) based algorithms is gaining paramount importance due to its increased applications on many real-world problems. A known problem of DNN penalizing the underrepresented population could undermine t...
High-precision rainfall information is of great importance for the improvement of the accuracy of numerical weather prediction and the monitoring of floods and mudslides that affect human life. With the rapid development of satellite constellation ne...
Predicting the shape evolution and movement of remote sensing satellite cloud images is a difficult task requiring the effective monitoring and rapid prediction of thunderstorms, gales, rainstorms, and other disastrous weather conditions. We proposed...
Water depletion is a growing problem in the world’s arid and semi-arid areas, where groundwater is the primary source of fresh water. Accurate climatic data must be obtained to protect municipal water budgets. Unfortunately, the majority of these ari...
Carbon satellites, as the most direct means of observing carbon dioxide globally, offer credible and scientifically robust methods for estimating carbon emissions. To enhance the accuracy and timeliness of urban-scale carbon emission estimates, this...
Vegetation index time-series analysis of multitemporal satellite data is widely used to study vegetation dynamics in the present climate change era. This paper proposes a systematic methodology to predict the Normalized Difference Vegetation Index (N...
The carotid body is a peripheral chemoreceptor that consists of clusters of chemoreceptive type I cells, glia-like type II cells, afferent and efferent nerves, and sinusoidal capillaries and arterioles. Cells and nerves communicate through reciprocal...
This study introduces a global land cover clustering using an unsupervised algorithm, incorporating the novel step of filtering data to retain only temporally stable pixels before applying K-means clustering. Unlike previous approaches that did not a...
Unmanned Aerial Vehicle (UAV) Remote sensing (RS) has unique advantages over traditional satellite RS, including convenience, high resolution, affordability and fast acquisition speed, making it widely used in many fields. To provide an overview of t...
Since the signals of the global navigation satellite system (GNSS) are blocked by buildings, accurate positioning cannot be achieved in an indoor environment. Pseudolite can simulate similar outdoor satellite signals and can be used as a stable and r...
In the arid grasslands of northern China, unreasonable grazing methods can reduce the water content and species numbers of grassland vegetation. This project uses solar-powered GPS collars to obtain track data for sheep grazing. In order to eliminate...
10 December 2021
Many scholars have conducted in-depth research on the theme of land use change and food security, and formed fruitful research results, but there is a lack of quantitative analysis and comprehensive evaluation of research achievements. Therefore, bas...
Information on the harvest date of crops can help with logistics management in the agricultural industry, planning machinery operations and also with yield prediction modelling. In this study, the determination and prediction of harvest dates for dif...
With methods for processing remote sensing data becoming widely available, the ability to quantify changes in spatial data and to evaluate the distribution of diverse landforms across target areas in datasets becomes increasingly important. One way t...
Remote sensing techniques provide crucial insights into ancient settlement patterns in various regions by uncovering previously unknown archaeological sites and clarifying the topological features of known ones. Meanwhile, in the northern part of the...
More than 50% of the world’s population consumes rice. Accurate and up-to-date information on rice field extent is important to help manage food and water security. Currently, field surveys or MODIS satellite data are used to estimate rice growing ar...
Machine learning-based remote-sensing techniques have been widely used for the production of specific land cover maps at a fine scale. P-learning is a collection of machine learning techniques for training the class descriptors on the positive sample...
The ionosphere is one of the largest error sources in GNSS (Global Navigation Satellite Systems) applications and can cause up to several meters of error in positioning. Especially for single-frequency users, who cannot correct the ionospheric delay,...