中文摘要：

以中国295个地级行政单元为研究对象，基于NPP—VIIRS夜间灯光数据、土地覆被数据和国家基础地理信息数据，构建“鬼城”指数模型，并采用空间统计分析方法，揭示中国地级行政单元“鬼城”现象的空间分异格局。结果表明：经济发展较快的一些东部沿海城市和地区“鬼城”现象较为鲜见，资源枯竭型城市、地处山区的一些城市以及经济发展较为落后的地区和城市则是“鬼城”现象的典型代表；从全国范围看，“鬼城”指数呈现出中部〉西部〉东部，北方〉中部〉南方的趋势；“鬼城”指数较高的地级单元集聚性个体差异较小，“鬼城”指数较低的单元集聚性个体差异则较大；“鬼城”的热点区域形成“丁”字格局，冷点分布则比较破碎；随着城市等级的降低，“鬼城”指数呈现出逐渐上升的态势，且指数的分布区间由离散态向集中态逼近。

英文摘要：

NPP-VIIRS nighttime lights data, land cover data and national fundamental geographic information data were used to build ＂ghost towns＂ index model to reveal spatial difference pattern of ＂ghost towns＂ phenomenon in China at prefecture level by taking both 295 prefecture level units and spatial statistics analysis methods into consideration. The results showed that the ＂ghost towns＂ of eastern coastal cities and regions with rapid development of economy were rarely appear. Resource-exhausted cities, hilly cities and lagging economic development cities and regions were typical representative of ＂ghost towns＂. The ＂ghost towns＂ index showing a trend of the central China〉the western China〉the eastern China, and the North〉the Central 〉the South from all over the country. Individual difference of prefecture units cluster with higher ＂ghost towns＂ index were small, the lower prefecture units cluster were large. Hot spots formed a pattern of ＂ding＂ word, the distribution of cold spots were more fragmentation. As the city level lowering, the ＂ghost towns＂ index showing a rising trend, and the distribution interval of index from discrete to concentrate.