A Model-Assisted Combined Machine Learning Method for Ionospheric TEC PredictionWeng, Jiaxuan;Liu, Yiran;Wang, Jian
doi: 10.3390/rs15122953pmid: N/A
In order to improve the prediction accuracy of ionospheric total electron content (TEC), a combined intelligent prediction model (MMAdapGA-BP-NN) based on a multi-mutation, multi-cross adaptive genetic algorithm (MMAdapGA) and a back propagation neural network (BP-NN) was proposed. The model combines the international reference ionosphere (IRI), statistical machine learning (SML), BP-NN, and MMAdapGA. Compared with the IRI, SML-based, and other neural network models, MMAdapGA-BP-NN has higher accuracy and a more stable prediction effect. Taking the Athens station in Greece as an example, the root mean square errors (RMSEs) of MMAdapGA-BP-NN in 2015 and 2020 are 2.84TECU and 0.85TECU, respectively, 52.27% and 72.13% lower than the IRI model. Compared with the single neural network model, the MMAdapGA-BP-NN model reduced RMSE by 28.82% and 24.11% in 2015 and 2020, respectively. Furthermore, compared with the neural network optimized by a single mutation genetic algorithm, MMAdapGA-BP-NN has fewer iterations ranging from 10 to 30. The results show that the prediction effect and stability of the proposed model have obvious advantages. As a result, the model could be extended to an alternative prediction scheme for more ionospheric parameters.
Remote Sensing and Data Analyses on Planetary TopographyKim, Jungrack;Lin, Shih-Yuan;Xiao, Haifeng
doi: 10.3390/rs15122954pmid: N/A
Planetary mapping product established by topographic remote sensing is one of the most significant achievements of contemporary technology. Modern planetary remote sensing technology now measures the topography of familiar solid planets/satellites such as Mars and the Moon with sub-meter precision, and its applications extend to the Kuiper Belt of the Solar System. However, due to a lack of fundamental knowledge of planetary remote sensing technology, the general public and even the scientific community often misunderstand these astounding accomplishments. Because of this technical gap, the information that reaches the public is sometimes misleading and makes it difficult for the scientific community to effectively respond to and address this misinformation. Furthermore, the potential for incorrect interpretation of the scientific analysis might increase as planetary research itself increasingly relies on publicly accessible tools and data without a sufficient understanding of the underlying technology. This review intends to provide the research community and personnel involved in planetary geologic and geomorphic studies with the technical foundation of planetary topographic remote sensing. To achieve this, we reviewed the scientific results established over centuries for the topography of each planet/satellite in the Solar System and concisely presented their technical bases. To bridge the interdisciplinary gap in planetary science research, a special emphasis was placed on providing photogrammetric techniques, a key component of remote sensing of planetary topographic remote sensing.
A Comprehensive Evaluation of Three Global Surface Longwave Radiation ProductsZeng, Qi;Cheng, Jie;Guo, Mengfei
doi: 10.3390/rs15122955pmid: N/A
Surface longwave radiation is sensitive to climate change on Earth. This study first comprehensively evaluates the accuracies of surface longwave upward radiation (SLUR) and surface longwave downward radiation (SLDR) among the mainstream surface longwave (LW) radiation products (GLASS, CERES SYN and ERA5); then, the global annual mean values of surface LW radiation as well as its temporal variations from 2003 to 2020 are quantified. The ERA5 SLUR and SLDR show the best accuracies by direct validation, with biases/Stds/RMSEs of −1.05/18.34/18.37 W/m2 and −9.41/24.15/25.92 W/m2, respectively. The GLASS SLUR has the best accuracy under clear-sky conditions with a bias/Std/RMSE of −6.73/14.21/15.72 W/m2. The accuracy of the GLASS SLDR is comparable to CERES SYN. The merit of the GLASS LW radiation is that it can provide rich spatial details due to its high spatial resolution. The global annual mean SLUR is 399.77/398.92/398.19 W/m2, and that of the SLDR is 342.64/347.98/340.47 W/m2 for GLASS, CERES SYN and ERA5, respectively. The interannual variation trends for the three products produce substantially growing long-term trends for the global mean SLUR and SDLR over the globe and land, while there are almost no trends over the ocean. The long-term trends of the seasonal mean SLUR and SDLR in the Northern and Southern Hemispheres are asymmetrical. Our comprehensive evaluation and trend analysis of the mainstream surface LW radiation products can aid in understanding the global energy balance and climate change.
Assessment and Projections of Marine Heatwaves in the Northwest Pacific Based on CMIP6 ModelsXue, Jingyuan;Shan, Haixia;Liang, Jun-Hong;Dong, Changming
doi: 10.3390/rs15122957pmid: N/A
To assess the abilities of global climate models (GCMs) on simulating the spatiotemporal distribution of marine heatwaves (MHWs), GCMs from the Coupled Model Intercomparison Program in Phase 6 (CMIP6) were evaluated from a historical period between 1985 and 2014 in the Northwest Pacific Ocean using a dataset that synthesizes remote sensing data. MHW simulation capabilities were assessed using Rank Score (RS) and Comprehensive Rating (MR) metrics that include both spatial and temporal scoring metrics. It was found that most CMIP6 models overestimate cumulative intensity, while mean and maximum intensities, in addition to the duration, were underestimated in the historical period. Possible future changes in MHWs were also examined based on the rank-based weighting ensembles under four shared socioeconomic pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). MHWs were identified using both a fixed 30-year baseline and a 30-year sliding baseline. In all scenarios, all MHWs metrics except frequency will have an increasing trend for the fixed baseline method. The frequency of MHWs will decrease after the 2050s. Days will first increase and then stabilize under various scenarios. MHWs will take place for more than 300 days by the end of the 21st century for the SSP5-8.5 scenario. The cumulative intensity in the SSP5-8.5 scenario is roughly six times higher than that in the SSP1-2.6 scenario by the end of the 21st century. A fixed baseline will result in near-permanent MHWs at the end of the 21st century. There will be no permanent MHWs at the end of the 21st century. Using the 30-year shifting baseline to define the MHWs can improve future MHW projections by capturing the spatiotemporal variability features of the MHWs.
Performance Assessment of Multi-GNSS PPP Ambiguity Resolution with LEO-AugmentationLi, Qin;Yao, Wanqiang;Tu, Rui;Du, Yanjun;Liu, Mingyue
doi: 10.3390/rs15122958pmid: N/A
The fast motion of low Earth orbit (LEO) satellites provides rapid geometric changes in a short time, which can accelerate the initialization of precise point positioning (PPP). The rapid convergence of ambiguity parameters is conducive to the rapid success of ambiguity fixing. This paper presents the performance of single- and four-system combined PPP Ambiguity Resolution (AR), enhanced with an ambiguity-float solution LEO. Two LEO constellations were designed: L was a typical polar orbit constellation, with a higher number of visible satellites at high latitudes than at low and middle latitudes; and M was designed to compensate for the lack of visible satellites at low and middle latitudes. The ground observation data of the LEO satellites at the MGEX stations were simulated. Because the global navigation satellite systems (GNSSs) were fully operational, the GNSS data were real observation data from the MGEX stations. Based on the daily observation datasets collected at 258 stations in the global MGEX observation network over three days (from 1 January to 3 January 2022), in addition to the LEO simulation data, we evaluated the positioning performance of LEO ambiguity-float solution-enhanced PPP ambiguity resolution and compared it with LEO-enhanced PPP. The L+M mixed constellation was able to reduce the time to first fix (TTFF) of the four-system combined PPP-AR to 5 min, and four LEO satellites were sufficient to achieve this. L+M mixed constellation was able to reduce the convergence time of the four-system combined PPP to 2 min. Unlike PPP-AR, PPP required more LEO satellites for augmentation to saturate.
Traffic Sign Detection and Recognition Using Multi-Frame Embedding of Video-Log ImagesXu, Jian;Huang, Yuchun;Ying, Dakan
doi: 10.3390/rs15122959pmid: N/A
The detection and recognition of traffic signs is an essential component of intelligent vehicle perception systems, which use on-board cameras to sense traffic sign information. Unfortunately, issues such as long-tailed distribution, occlusion, and deformation greatly decrease the detector’s performance. In this research, YOLOv5 is used as a single classification detector for traffic sign localization. Afterwards, we propose a hierarchical classification model (HCM) for the specific classification, which significantly reduces the degree of imbalance between classes without changing the sample size. To cope with the shortcomings of a single image, a training-free multi-frame information integration module (MIM) was constructed, which can extract the detection sequence of traffic signs based on the embedding generated by the HCM. The extracted temporal detection information is used for the redefinition of categories and confidence. At last, this research performed detection and recognition of the full class on two publicly available datasets, TT100K and ONCE. Experimental results show that the HCM-improved YOLOv5 has a mAP of 79.0 in full classes, which exceeds that of state-of-the-art methods, and achieves an inference speed of 22.7 FPS. In addition, MIM further improves model performance by integrating multi-frame information while only slightly increasing computational resource consumption.
Quantitative Analysis of Desertification-Driving Mechanisms in the Shiyang River Basin: Examining Interactive Effects of Key Factors through the Geographic Detector ModelNgabire, Maurice;Wang, Tao;Liao, Jie;Sahbeni, Ghada
doi: 10.3390/rs15122960pmid: N/A
Desertification is a global eco-environmental hazard exacerbated by environmental and anthropogenic factors. However, comprehensive quantification of each driving factor’s relative impact poses significant challenges and remains poorly understood. The present research applied a GIS-based and geographic detector model to quantitatively analyze interactive effects between environmental and anthropogenic factors on desertification in the Shiyang River Basin. A MODIS-based aridity index was used as a dependent variable, while elevation, near-surface air temperature, precipitation, wind velocity, land cover change, soil salinity, road buffers, waterway buffers, and soil types were independent variables for the GeoDetector model. A trend analysis revealed increased aridity in the central parts of the middle reach and most parts of the Minqin oasis and a significant decrease in some regions where ecological rehabilitation projects are underway. The GeoDetector model yielded a power determinant (q) ranging from 0.004 to 0.270, revealing elevation and soil types as the region’s highest contributing factors to desertification. Precipitation, soil salinity, waterway buffer, and wind velocity contributed moderately, while near-surface air temperature, road buffer, and land cover dynamics exhibited a lower impact. In addition, the interaction between driving factors often resulted in mutual or non-linear enhancements, thus aggravating desertification impacts. The prominent linear and mutual enhancement occurred between elevation and soil salinity and between elevation and precipitation. On the other hand, the results exhibited a non-linear enhancement among diverse variables, namely, near-surface air temperature and elevation, soil types and precipitation, and land cover dynamics and soil types, as well as between wind velocity and land cover dynamics. These findings suggest that environmental factors are the primary drivers of desertification and highlight the region’s need for sustainable policy interventions.
Rice False Smut Monitoring Based on Band Selection of UAV Hyperspectral DataWang, Yanxiang;Xing, Minfeng;Zhang, Hongguo;He, Binbin;Zhang, Yi
doi: 10.3390/rs15122961pmid: N/A
Rice false smut (RFS) is a late-onset fungal disease that primarily affects rice panicle in recent years. Severe RFS can decrease the yield by 20–30% and severely affect rice quality. This research used hyperspectral remote sensing data from unmanned aerial vehicles (UAV). On the basis of genetic algorithm combined with partial least squares to select the feature bands, this paper creates a new method to use the Pearson correlation coefficient method and Instability Index between Classes (ISIC) method to further select characteristic bands, which further eliminated 27.78% of the feature bands when the model monitoring accuracy was improved overall. The prediction accuracy of the Gradient Boosting Decision Tree model and Random Forest model was the best, which were 85.62% and 84.10%, respectively, and the monitoring accuracy was improved by 2.22% and 2.4% compared with that before optimization. Then, based on the UAV hyperspectral data and the combination of characteristic bands selected by the three band optimization methods, the sensitive band ranges of rice false smut monitoring were determined, which were 698–800 nm and 974–997 nm. This paper provides an effective method of selecting characteristic bands of hyperspectral data and a method of monitoring crop diseases’ using unmanned aerial vehicles.
Analysis of the Characteristics and Ideas of Ancient Urban Land-Use Based on GIS and an Algorithm: A Case Study of Chang’an City in the Sui and Tang DynastiesChen, Siliang;Dong, Yue;Chen, Xiangyu;Xu, Xinyue;Gong, Jiangbo
doi: 10.3390/rs15122962pmid: N/A
As ancient cities are spaces that represent the development of civilization, it is worth exploring and studying their characteristics and conceptions of land use. In this regard, the focus has turned to the issue of how to achieve the efficient mining of massive urban remote sensing data through human–computer collaboration. In this paper, a new intelligent method of analyzing urban land use characteristics and their cultural significance is proposed; it is feasible, effective, accurate, manageable, and portable. The method is based on a geographic information system (GIS) and a specific algorithm. The city plan was calibrated with the help of satellite remote sensing images and sites. By constructing the “urban element area acquisition and analysis model”, various operations for areas in the city plan were realized, including an area value calculation, land use structure calculation, area modulus analysis, area ratio analysis between areas, and determination of the cultural significance of numbers and ratios. Taking the Sui and Tang dynasties capital city of Chang’an as an example, we found the existence of a set of urban planning techniques through area modulus (standard area units) for the first time; it took the market area as the modulus A and the area of Daxing Palace as the expanded modulus 2A, made the area of important areas in the city an integer multiplied by the modulus value (for example, the overall scope of the city is 100A, the rectangular urban area is 90A, and the small city area is 10A), and made the key values and numerical ratios have a cultural significance (such as 4.5, 5.5, 10, 25, 30, 100, 12:10, 1.618:1, 9:5, 45:1, 2:1), reflecting the planning and design concept of the capital city, into which the ancient Chinese deliberately integrated “number, shape and meaning”. In addition, we carried out supplementary verification with the Roman city of Timgad and the Japanese city of Heijo-kyo, discovering that they also have design methods for area planning. We believe that land use planning can better meet the practical needs of urban resource distribution. Compared with urban form design, it might have chronological precedence. By setting the area modulus and the modulus value of each area, the grid-shaped city achieves the rational distribution of land and the establishment of order in an efficient way, and this thought and operation method greatly contributed to the advancement of ancient civilizations.