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Reducing the lag in the accuracy assessment of multi-temporal land-cover products has been a hot research topic. By identifying the changed strata, the annual accuracy in multi-temporal products can be quickly evaluated. However, there are still two limitations in the accuracy assessment of multi-temporal products. Firstly, the setting of the parameters (e.g., the total sample size, allocation of samples in the changed strata, etc.) in the fundamental sampling design is not based on specific setting criteria. Therefore, this evaluation method is not always applicable when the product or research area changes. Secondly, the accuracy evaluation of multi-temporal products does not consider the influence of misclassification. This can lead to an overestimation of the accuracy of changed strata in single-year evaluations. In this paper, we describe how the total sample and the assignment of samples in every stratum can be adjusted according to the characteristics of the land-cover product, which improves the applicability of the evaluation. The samples in the changed strata that propagate misclassification are essentially pixels that have not undergone any land-cover change. Therefore, in order to eliminate the propagation of this inter-annual classification error, the misclassified samples are reclassified as unchanged strata. This method was used in the multi-temporal ESA CCI land-cover product. The experimental results indicate that the single-year accuracy, considering classification error, is closer to the traditional evaluation accuracy of single-temporal data. For the categories with a small ratio of unchanged strata samples to changed strata samples, the accuracy improvement, after eliminating the classification errors, is more obvious. For the urban class, in particular, the misclassification affects its estimated accuracy by 9.72%. [ABSTRACT FROM AUTHOR]

Solar irradiance received at the lunar surface is crucial for interpreting brightness temperatures detected by orbiters and for understanding the thermal, physical, and dielectric properties of the lunar regolith. We developed a real‐time effect solar irradiance (ESI) model that accounts for the influence of surface relief and terrain shading. This model was integrated with a standard thermal model to examine ESI fluctuations and their impacts on the diurnal physical temperature variations. To assess the effects of spatial resolution, we selected four locations with significant ESI disparities for simulation, then compared lunar surface temperatures at various spatial scales, ranging from 20 m to 25 km. Utilizing brightness temperature data obtained from the Chang'E‐2 (CE‐2) microwave radiometer (MRM), we integrated the shallow physical temperature profiles with the radiative transfer equation to simulate brightness temperatures and determine dielectric loss at different frequencies. In the Von Kármán crater, the received ESI exhibits a cyclical pattern of approximately 18 years and areas with rugged topography may exhibit larger ESI variations (∼7%). We found that the spatial resolution of ESI has a minimal effect on the physical and brightness temperatures at resolutions of 10 km or coarser. At the shallow layer, the average dielectric loss values are 0.0128–0.0170, 0.0083–0.0110, 0.0055–0.0073, and 0.0061–0.0081 for the CE‐2 frequencies of 3, 7.8, 19.35, and 37 GHz, respectively. The integration of real‐time ESI modeling, thermal dynamics, radiative transfer equations, and observational data enhances our comprehension of the physical temperature profile and thermal characteristics of shallow regolith. Plain Language Summary: The combination of solar irradiance and temperature data sets detected by orbiters can help to explain the temperature variation and thermophysical properties of shallow lunar surface. This study develops a real‐time effect solar irradiance (ESI) model that takes into account the influence of lunar topography and integrates it with a thermal model to simulate physical temperature variations within the Von Kármán crater. We compared lunar surface physical temperature profiles at spatial resolutions of 20, 240, 500 m, 1, 5, 10, 15, and 25 km, each exhibiting distinct ESI characteristics, to assess the impact of spatial resolution. We then simulated the temperature data in the four frequencies consistent with Chang'E‐2 (CE‐2) microwave radiometer and obtained the average ranges of dielectric loss. At 3, 7.8, 19.35, and 37 GHz, the average dielectric loss ranges were determined to be 0.0128–0.0170, 0.0083–0.0110, 0.0055–0.0073, and 0.0061–0.0081, respectively. These findings provide valuable insights for analyzing lunar surface temperature and observed brightness temperature, as well as for inverting physical and dielectric properties of the shallow regolith (e.g., dielectric loss). Key Points: Analyzing lunar shallow temperature variation with real‐time effect solar irradiance (ESI) model considering terrain influenceAssessing the real‐time ESI impact on physical and brightness temperature curves at diverse spatial resolutionsEstimating the dielectric loss of shallow regolith by coupling simulated brightness temperature data with observations [ABSTRACT FROM AUTHOR]

The simplification of lines plays a crucial role in map generalization and multiscale representation; however, addressing inconsistent sidedness relationships between the simplified lines and their neighboring features poses a persistent challenge. In order to preserve correct and consistent sidedness relationships following simplification, this study introduces a novel line simplification method. This method incorporates topological constraints pertaining to left–right sidedness relationships, formulated as an optimization procedure based on the proposed partial total least squares method with constraints. The primary objective is to minimize the positional difference between the line features before and after simplification, with the sidedness relationship represented as an inequality constraint. Moreover, an optimization algorithm is derived to address the simplification problem effectively while adhering to the specified constraints. The proposed method is then applied to simplify the lines within three distinct datasets. Experimental results validate the efficacy of the proposed method in maintaining sidedness consistency across all tested datasets. In comparison to the Douglas–Peucker (DP) method, the proposed method exhibits minimal vertical displacement variance in the line feature points post‐simplification. Additionally, it achieves a smaller overall positional difference between the simplified and original lines compared to the DP method. These findings underscore the superior performance of the proposed method in maintaining sidedness relationships and minimizing positional differences during the line simplification process. [ABSTRACT FROM AUTHOR]

A weighted and partial total least squares method for the errors-in-variables (EIV) model with linear equality and inequality constraints is presented. A collected observation vector is formed by the independent variables both in the observation vector and the design matrix. The proposed model is solved based on the Lagrange method and by transforming the problem into a linear complementary problem. The performance of the proposed method is studied by two numerical experiments. The results show that, the proposed method is capable of solving the linearly constrained EIV model efficiently. [ABSTRACT FROM AUTHOR]

Urban light rail transit systems have a significant potential to alter future urban development. We developed a new cellular automata model (CACG) based on conjugate gradients, and applied it to 1) simulate historical urban development at Jinhua of China, and 2) project future development scenarios incorporating the effect of future light rail transit stations (LRTS). The model produced a realistic urban pattern for 2018 with overall accuracy exceeding 95%, Kappa coefficient exceeding 70% and figure-of-merit exceeding 32%, indicating the model's ability to accurately capture urban dynamics. We predicted three different scenarios: a benchmark scenario of business as usual (BAU), a scenario focusing on LRTS, and an individual-factor-based scenario (ILRTS). The results show that the annual urban development intensity has the strongest correlation with LRT stations for LRTS-scenario, followed by ILRTS-scenario and BAU-scenario. The model can be readily applied elsewhere to assess the impact of urban infrastructure on future development. [ABSTRACT FROM AUTHOR]