For urban growth modeling, assessment metrics derived from cell-by-cell comparisons are mainly related to the size of the study area and the urban growth rate. Non-urban areas always occupy an ...important part of the city to which cellular automata (CA) models do not contribute much, so the simulation accuracy is often exaggerated when this part is included. To enable comparing simulation results across models, regions, and time, we developed an improved equivalent area-based assessment (EQASS) method using cell-by-cell comparison metrics. As against existing assessment methods, EQASS is computed by including the same area of urban and suburban areas (i.e., equivalent areas). EQASS was tested in three Chinese coastal cities using a heuristic CA model and two spatial statistical CA models to simulate urban growth. The results show that EQASS can exclude correct rejections that are not attributable to CA models; these correct rejections have a significant impact on the model assessment. The improved assessment can better evaluate the performance of CA models across regions and over time than the conventional assessment method that accounts for the full study area. This study extends the simulation assessment method and provides a good solution for selecting the best CA model from many candidate models.
The positioning accuracy of synthetic aperture radar (SAR) images is affected by factors, such as satellite platform instability, aging of on-board instruments, and environmental changes. Geometric ...calibration is a commonly employed and cost-effective method to enhance the positioning accuracy of SAR images. The classical point-based geometric calibration (PB-GC) model, however, only utilizes the location of ground control points (GCPs) and does not fully exploit the spatial relationships among the GCPs. This study introduces a high-precision geometric calibration method that builds upon the classical model for calibrating SAR imaging systems. This method incorporates the Co-Line-GC and Co-Circle-GC models, where the former uses GCPs distributed on a line while the latter uses GCPs distributed on a circle. The results reveal that, compared to the classical model, our approach enhances the positioning accuracy of Gaofen-3 and Sentinel-1A SAR images by approximately 2 m in eastern China, achieving a mean positioning accuracy of 3.02 m. In terms of calibration performance, a comparison between postcalibrated and precalibrated images indicates that the images are shifted, not distorted, and a better match of the same features between different scenes in the image mosaic is observed after calibration. The improved positioning accuracy of SAR images significantly contributes to global remote sensing mapping, land use change monitoring, and ground target detection applications.
The use of microwave radiation data collected by lunar orbiters to infer the lunar brightness-temperature (TB) distribution is of great importance to lunar scientific exploration. The TB data ...acquired by China's Chang'E-2 passive microwave radiometer (MRM) is one of the basic materials for lunar temperature mapping. Core issues of lunar microwave TB mapping include data fitting at different latitudes, outlier removal, and integrated spatial interpolation considering influencing factors. We applied a third-order Fourier function to fit the lunar TB data, which effectively removes outliers considering the fitting characteristic and three-sigma rule (FCTSR). Because the lunar surface temperature is influenced by a variety of factors such as topography and albedo, we then built a multi-factor co-kriging interpolation method to perform lunar TB mapping accurately. The cross-validation shows that, in terms of the mean-absolute-error and root-mean-square-error, the multi-factor co-kriging interpolation improves the mapping accuracy by 30%–60% compared to inverse distance interpolation and ordinary kriging interpolation. The analysis shows that topography and albedo are the most important factors influencing the lunar TB, and the TB maps at 37 GHz reveal cold spots that can be considered as younger craters. It is concluded that the proposed data fitting, denoising and spatial interpolation methods significantly improve the lunar TB mapping. The results and scientific data can also provide a basic energy map for lunar roving path planning and subsequent lunar exploration.
•TB outliers were effectively removed using the fitting characteristics and three-sigma rule.•A multi-factor co-kriging method was developed to produce accurate lunar TB maps.•The co-kriging improves accuracy by 30%–60% compared to IDW and ordinary kriging.•The TB maps at 37 GHz reveal cold spots that can be identified as younger craters.
Synthetic aperture radar (SAR) image positioning is commonly affected by factors such as platform instability, aging of onboard instruments, and changing observation environments. Thus, geometric ...calibration is needed to improve the accuracy of image positioning before mapping and application. An improved geometric calibration model for SAR images was developed, which does not require long-delayed meteorological data and geometric calibration fields. In this method, the standard atmospheric and Saastamoinen models (SAM-S) are combined for atmospheric delay correction, and this integrated method named SAM-S was used for the first time in SAR image geometric calibration. The method was applied to China's Gaofen-3 satellite and a case study was conducted in the Yangtze River Delta, where the weather is cloudy and rainy. By selecting three images, four images, and five images from eight candidate images with a bandwidth of 60 MHz for calibration experiments, where the geometric positioning accuracy was increasingly stable with more SAR images included in the combination. The root mean square of the calibrated SAR images was about 6 m for different combinations and the maximum error was about 12 m for all images. Two selected areas showed that the geometric calibration has reduced the geometric distortion, showing shapes in the SAR images close to the ground targets. The positioning accuracy improvement of Gaofen-3 images can help improve their application potential in global remote sensing mapping, land-use change monitoring, and ground target detection. The proposed geometric calibration method can also be applied to other SAR missions such as ERS, RADARSAT, and TerraSAR-X.
The Yutu‐2 rover onboard China's Chang’E‐4 was the first to land in the Von Kármán crater on the lunar farside, where structural and dielectric properties may provide previously unknown clues to ...lunar formation and evolution. Based on the Lunar Penetrating Radar (LPR) with 500 MHz onboard the Yutu‐2 rover, we proposed a band‐limited impedance (BLIMP) inversion method to generate continuous dielectric 2‐D profiles with the help of dielectric constants retrieved from point reflectors (e.g., buried rocks), which provide low‐frequency information that may be lost or distorted in the LPR data pre‐processing. The dielectric constants retrieved from point reflectors were transformed from dielectric constant fitting curves, where these discrete dielectric constants were calculated using the hyperbolic fitting method. We estimated that the top fine‐grained regolith thickness along the rover path varies from ∼5.3 to ∼15.0 m in the first 27 lunar days of operation. The thickness variation could most likely be attributed to changes in ancient surface topography buried underground and ejecta from nearby craters. Compared to methods based on a singular dielectric constant, the estimated 2‐D dielectric profile in this study can reduce the uncertainties in lunar regolith thickness estimation, especially in the shallow layers. The BLIMP method and the estimated regolith thickness can improve our understanding of lunar subsurface structure and formation.
Plain Language Summary
The lunar regolith thickness is an important stratigraphic feature for scientific exploration such as temperature inversion and mineral content estimation on the Moon. The Lunar Penetrating Radar (LPR) onboard the Yutu‐2 rover (Chang’E‐4) provides a unique opportunity to probe the dielectric properties of lunar regolith and thereby estimate the regolith thickness on the farside of the Moon. We analyzed the variations in the dielectric constants of the Yutu‐2 LPR data using the band‐limited impedance (BLIMP) method. The analysis reveals a two‐layer subsurface structure with the top layer of fine‐grained ranging from ∼5.3 to ∼15.0 m. Analysis suggests that the variations in the regolith thickness were most likely attributed to changes in ancient surface topography buried underground and nearby craters. Compared to methods based on a singular dielectric constant, the estimated 2‐D dielectric profile in this study can reduce the uncertainties in lunar regolith thickness estimation, especially in the shallow layers.
Key Points
We integrated BLIMP and hyperbolic fitting to inverse continuous 2‐D dielectric profiles
We estimated that the top fine‐grained regolith thickness along the moving path varies from ∼5.3 to ∼15.0 m in the first 27 lunar days
The thickness variation could be attributed to the ejecta from nearby small craters, hence impacting the calculation of dielectric property
Large-scale short-term monitoring and prediction of surface deformation are of great significance for the prevention and control of geohazards in rapidly urbanizing developing cities. Most studies ...focus on individual cities, but it would be more meaningful to address large urban agglomerations and consider the relevance of the regions within them. In addition, the commonly used linear fitting prediction methods cannot accurately capture the dynamic mechanisms of deformation. In this study, we proposed an automatic PS extraction method (named PS-SBAS-InSAR) that improves SBAS-InSAR to extract surface deformation and an Informer-based short-term surface deformation prediction method for case studies in 16 typical cities of the Yangtze River Delta (YRD). The results show that PS-SBAS-InSAR successfully extracted accurate surface deformation sequences of the YRD. During the period from January 2019 to January 2021, the YRD experienced a slight deformation with an average deformation rate within −4, 4 mm/year. Geographically neighboring cities may have associated deformation distributions and similar deformation trends, as indicated by average deformation rate maps and landscape metrics. Both types of deformation (i.e., subsidence/uplift) tend to occur simultaneously, with specific areas of subsidence/uplift occurring in close proximity to areas of concentrated deformation. The Informer model effectively captured the time-series variation in surface deformation, suggesting a slowdown of deformation over the next two months (February 2021–March 2021). Our work contributes to a better understanding of changes and trends in large-scale surface deformation and provides useful methods for monitoring and predicting surface deformation in coastal areas.
Predicting future urban land-use scenarios and assessing their encroachment on ecological land is important for sustainability policy formulation. This study develops a new Futureland model using ...cellular automata with user-defined transformation rules, graphical neighborhood configuration and matrixed transformation cost to simulate multiple land-use changes. Compared with existing models, Futureland applies different factors to different land-use types in a single simulation experiment. Futureland was developed using Geospatial Data Abstraction Library and parallel computing, which significantly improve the implementation efficiency. The case study of Shanghai 2010-2020 illustrates an overall accuracy of 86.6% and a Kappa simulation of 0.79. The land-use scenarios for 2020-2035 were projected under greenspace planning constraints using Futureland. The results indicate that Shanghai's urban sprawl will gradually slow down by 2030, and the increased urban areas will be mainly in the urban fringes and suburban regions. Futureland can help decision-makers to manage future land-use and optimize urban planning policies.
In DEM generation using interferometric synthetic aperture radar (InSAR), the ground control points (GCPs) for refinement and reflattening are usually selected by manual selection, field surveying, ...GPS points and existing basemaps, which may not be completely suitable for consequent processes. We proposed a new method (auto-PS-GCP) of GCP selection based on permanent scatterers, which automatically defines the thresholds for the coherence, amplitude, and amplitude dispersion index to select permanent scatterer as the GCPs. The GCP thinning (auto-PS-GCP-Thin) was further conducted considering the point density, distances among points and terrain conditions. We used a three-stage assessment that includes: (1) phase stability and intensity of the GCPs, (2) RMSEs of the elevations between GCPs and homonymous points in the reference DEM, and (3) generated DEM accuracy. Three areas respectively in the plain, hilly and mountainous regions were selected to verify the proposed methods. The assessment using both SRTM DEM andICESat-2 points shows that the DEM accuracy of auto-PS-GCP-Thin was improved by 20%∼30% for different areas compared to the manual, where the best DEM accuracy of 4.71 m was found in the plain area. It is concluded that the proposed methods are effective and reliable in various areas with different terrain conditions.
In this study, we proposed a pixel-level projection method for fine particulate matter (PM 2.5 ) over a long term and across a large area using a combination of Landsat images, PM 2.5 data from ...monitoring stations, and historical gridded PM 2.5 data. We considered the spatial dependence effects of the particulate matter using a spatial lag model to quantify the relationship between PM 2.5 concentration and land coverage indices, where the latter were calculated by the built-up, vegetation, and water indices. The future land coverage indices for the pixel-level projection of PM 2.5 were derived from the future land-use scenario predicted by the Futureland model. We applied the method to analyze the spatial patterns of PM 2.5 in the Yangtze River Delta (YRD), China, from 2000 to 2020, and then projected its pixel-level scenario in 2030. The projected PM 2.5 shows high concentrations in the north and low in the south and temporally decreases compared to 2010. The projection of the fine-grained PM 2.5 scenario can help adjust YRDs environmental and industrial policies, as well as implement its management strategies for sustainable urban development. Our method can be used to predict future patterns not only for long-term and large-scale pixel-level PM 2.5 concentrations but also for other environmental parameters.
The identification of optimal landing sites is a critical first step for successful missions to the Moon and other extraterrestrial bodies, necessitating the integration of various environmental ...factors over large spatial scales. At the lunar south pole, site selection must balance engineering safety with areas of high scientific interest, requiring extensive analysis of potential locations. Although intelligent algorithms have been increasingly investigated for this purpose, the application of deep learning techniques in landing site selection remains unexplored. In this study, we employ one-dimensional convolutional neural networks (1D-CNNs) to quantitatively assess potential landing sites for exploration and lunar base construction, considering both scientific and engineering criteria. We also evaluate the influence of various factors on site selection using Shapley additive explanations (SHAP) values. The 1D-CNN model demonstrates robust performance across training, validation, and testing phases. Potential landing sites identified comprise less than 1% of the total study area, with factors such as visibility, volatile distribution, topography, and geological characteristics playing crucial roles. By applying operational constraints, we delineate sites suitable for direct landings and further refine this subset for base construction based on stringent requirements for resource utilization and energy sustainability. The combined use of CNN and SHAP enables more effective potential site screening and a deeper understanding of the factors influencing selection. Our findings offer a valuable framework for future lunar south pole expeditions, potentially minimizing manual survey efforts and enhancing the precision of landing site selection.
