Ahstract-A 5 MWp PV solar power station will be installed in a remote area of China. This new system may contribute to addressing the area's serious electricity shortage, while also minimizing damage to the environment. The PV station consists of photovoltaic generation system and battery energy storage system, which combine with the existing small-hydro facility to form an autonomous hybrid generation system. In this system, the small-hydro works in V/f control mode, the PV and battery storage systems work in P/Q control mode to make full use of solar energy and reduce the amount of water and diesel used. In this paper we analyze and evaluate the stability of the hybrid system using a PSCAD simulation. Reasonable measures and recommendations are proposed based on these results.

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As an effective statistical learning tool, AdaBoosting has been widely used in the field of pattern recognition. In this paper, a new method is proposed to improve the classification performance of hyperspectral images by combining the minimum noise fraction (MNF) and AdaBoosting. Because the hyperspectral imagery has many bands which have strong correlation and high redundancy, the hyperspectral data are pre-processed by the minimum noise fraction to reduce the data's dimensionality, whilst to remove noise bands simultaneously. Then, we use an AdaBoost algorithm to conduct the classification of hyperspectral remotely sensed image. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well.

Support Vector Machine (SVM) is used to classify hyperspectral remote sensing image in this paper. Radial Basis Function (RBF), which is most widely used, is chosen as the kernel function of SVM. Selection of kernel function parameter is a pivotal factor which influences the performance of SVM. For this reason, Particle Swarm Optimization (PSO) is provided to get a better result. In order to improve the optimization efficiency of kernel function parameter, firstly larger steps of grid search method is used to find the appropriate rang of parameter. Since the PSO tends to be trapped into local optimal solutions, a weight and mutation particle swam optimization algorithm was proposed, in which the weight dynamically changes with a liner rule and the global best particle mutates per iteration to optimize the parameters of RBF-SVM. At last, a 220-bands hyperspectral remote sensing image of AVIRIS is taken as an experiment, which demonstrates that the method this paper proposed is an effective way to search the SVM parameters and is available in improving the performance of SVM classifiers.

Abstract. With China’s first stereo imaging satellite ZY-3’s successful launch and two satellites networking operation, space remote sensing becomes an important means of data acquisition for survey and mapping, and geographic information updating in China.The updating period of 4D products in China is shortened by one third, the geographic information updating capability was improved more than 2 times.After more than eight years of stable and continued earth observation, ZY-3 statellites data coverage has gradually achieved more than half of the earth land which enables the overseas service for global geospatial application. Focusing on the Chinese domestic mapping applications and services, the data of ZY-3 and other domestic land observation satellites can be real-time pushed and distributed across China through the satellite cloud service platform, and worldwide for facilitating the "Belt and Road" initiative, which is promoted through the GEOSS as well for global application.This paper presents the overseas geometric accuracy evaluation and validation of ZY-3 satellites images, which was carried out systematically for the first time abroad and complements with China’s mapping evaluation practices to provide a comprehensive technical guidelines for global mapping application. The direct location accuracy of ZY-3 satellites sensor corrected image products were further evaluated and verified cooperating with the University of Vienna, Austria. The location deviations in mountain area and in flat area were analyzed and compared to check the deviation pattern and validate their consistency with the results in China.Utilizing China’s ZY-3 satellites images ranging from 2012–2018, the DSM was generated automatically based on a semiglobal optimization method (Yue et al. 2016) using self-developed software SDP without ground control points but using SRTM data as elevation reference to improve the geometric accuracy. The result shows the elevation accuracy of DSM is 3.19 m (RMSE), satisfying the local requirement for 10m interval contour mapping.The planar accuracy of DOM generated without ground control points utilizing ZY-3 satellites images within 2012–2015 is 2.46 m (RMSE). With 128 orthorectified aerial photo slots provided by NGD of Laos as reference, the planar accuracy of the DOM generated utilizing ZY-3 satellites images from 2016–2018 is 1.65 m (RMSE), which can satisfy the local 1:25000 planar accuracy requirement and overlay with the local 1:2000 transportation data exactly. The overseas geometric accuracy evaluation and validation of ZY-3 satellites images provides a systematic and practical guidance for future global applications by complementing with china’s experience, which would be beneficial to overseas users in acknowledging the usage of ZY-3 satellites data and help to promote it’s global applications.