It is of great significance to research the spatial pattern of the urban system of the Yangtze River economic belt to analyze the characteristics and laws of the spatial structure of the Yangtze River economic belt and to promote the optimal development of the urban system of the Yangtze River economic zone. In this paper, the time data of the Yangtze River economic zone are corrected using Landsat satellite data and the clustering analysis method. The threshold of the urban built area is obtained by comparing the auxiliary data with other auxiliary data. Based on this threshold, a total of eight typical landscape pattern indicators—including the total area of the landscape, the total patch number, and the aggregation index—are used, and then FRAG-STATS 4.2 software is used to analyze the spatial pattern of urban development in the Yangtze River economic zone from 1992 to 2013. The results show the following: (1) During the period from 1992 to 2013, the urbanization of the Yangtze River economic zone expanded rapidly; the area of urban built-up area increased by a factor of 9.68, the number of patches increased by a factor of 2.39, and the patch density increased greatly, indicating that the Yangtze River economic zone, with an increasing number of towns and urban areas, continues to expand. (2) The complexity of the landscape patch shape gradually increased, the small and medium-sized cities continued to grow, more small towns emerged, and the total length of the border and the average density had average annual growth rates of 21.56% and 21.58%; the degree of aggregation and the mutual influence are increasing. (3) The maximum plaque index and the aggregation index show an overall declining trend. However, there are some fluctuations and disorder in the process of evolution, such as the total area of the landscape, the total patch number and the total patch density, which reflects that the Yangtze River economic zone is in the process of urbanization and has irregular and disordered characteristics.

To grasp the evolutionary characteristics and regularity of urban land expansion patterns in the Poyang Lake Ecological Economic Zone, this study, based on nighttime lighting data, uses the Landsat series satellite simultaneous data and cluster analysis to correct the Defense Meteorological Satellite Program–Operational Linescan System (DMSP-OLS) nighttime lighting data and then uses the auxiliary data-based comparison method to determine the threshold for extracting the urban built-up area. Based on this threshold, a total of eight typical landscape pattern indicators, including landscape total area, total patches number, patches density, maximum patches index, and agglomeration index, etc., are selected. Next, the landscape spatial pattern analysis method and standard deviation ellipse method are used. The results show the following: (1) In 1992–2013, urbanization in the Poyang Lake Ecological Economic Zone expanded rapidly. The urban built-up area increased by 8.13 times, the number of plaques increased by 1.5 times, and the shape complexity of landscape plaques gradually increased. There is a large correlation between the changes in the total boundary length, and the average boundary density, the average annual growth rate of the two is 21.33% and 17.45%. (2) The two indicators of maximum plaque index and aggregation index show a downward trend year by year. However, there are some fluctuations and irregularities in the evolution of the total landscape area, total plaque number and plaque density. (3) The long axis and the short axis of the standard deviation ellipse of the Poyang Lake Ecological Economic Zone show small variation during the inspection period and generally have an elliptical shape. The movement of the center of gravity is mainly from the southwest to the northeast, but the migration of the center of gravity is relatively small. Based on this, this paper proposes three countermeasures and suggestions as a guide to promote the optimization and development of the spatial expansion pattern of the Poyang Lake eco-economic zone.

Accurate estimation of direct horizontal irradiance (DHI) is a prerequisite for the design and location of concentrated solar power thermal systems. Previous studies have shown that DHI observation stations are too sparsely distributed to meet requirements, as a result of the high construction and maintenance costs of observation platforms. Satellite retrieval and reanalysis have been widely used for estimating DHI, but their accuracy needs to be further improved. In addition, numerous modelling techniques have been used for this purpose worldwide. In this study, we apply five machine learning methods: back propagation neural networks (BP), general regression neural networks (GRNN), genetic algorithm (Genetic), M5 model tree (M5Tree), multivariate adaptive regression splines (MARS); and a physically based model, Yang’s hybrid model (YHM). Daily meteorological variables, including air temperature (T), relative humidity (RH), surface pressure (SP), and sunshine duration (SD) were obtained from 839 China Meteorological Administration (CMA) stations in different climatic zones across China and were used as data inputs for the six models. DHI observations at 16 CMA radiation stations were used to validate their accuracy. The results indicate that the capability of M5Tree was superior to BP, GRNN, Genetic, MARS and YHM, with the lowest values of daily root mean square (RMSE) of 1.989 MJ m⁻²day⁻¹, and the highest correlation coefficient (R = 0.956), respectively. Then, monthly and annual mean DHI during 1960–2016 were calculated to reveal the spatiotemporal variation of DHI across China, using daily meteorological data based on the M5tree model. The results indicated a significantly decreasing trend with a rate of −0.019 MJ m⁻²during 1960–2016, and the monthly and annual DHI values of the Tibetan Plateau are the highest, while whereas the lowest values occur in the southeastern part of the Yunnan−Guizhou Plateau, the Sichuan Basin and most of the southern Yangtze River Basin. The possible causes for spatiotemporal variation of DHI across China were investigated by discussing cloud and aerosol loading.