基于NPP/VIIRS夜间灯光数据的湘鄂赣省际交界区县域经济空间格局及影响因素

doi:10.13249/j.cnki.sgs.2020.06.005

摘要/Abstract

摘要：

采用NPP/VIIRS夜间灯光数据表征经济发展水平，结合空间自相关分析方法对湘、鄂、赣省际交界区县域经济空间格局进行可视化分析，利用地理加权回归模型（GWR）分析相关影响因素的空间异质性。结果表明：湘鄂赣交界区县域经济存在明显的“金字塔”型等级特征，且低水平县（市）相对其他地区更靠近省界，边界效应特征表现突出；空间集聚性层次较低，具有“连片贫困”特征；热点地区大都位于湘、鄂、赣交界区外围地区，冷点地区位于广大的内部腹部地区，“内冷外热”两极分化的不平衡格局仍未能有效化解；劳动、资本、政府作用均具有积极作用，其中劳动投入与资本投入回归系数高值易集中于热点地区，低值则集中于冷点地区。政府作用影响效应一方面随着地区到中心城区距离的增加而依次递减，另一方面表现为省份间影响差异。交通水平与教育发展水平对经济发展差异影响呈现出正负两极分化特征。

关键词: 夜间灯光数据, 省际交界区, 空间格局, 地理加权回归

Abstract:

Compared with the mainstream indicators of GDP economic development level, the night lighting data has the advantages of high objectivity, time series stability and comprehensiveness. So, we use the NPP/VIIRS nighttime light data to characterize the economic development level, the spatial pattern of the county economy in Hunan-Hubei-Jiangxi border regions is visualized by the ESDA method, and the spatial heterogeneity of the factors affecting the economic development is studied by using the GWR model. The results show that: There is insufficient imbalance in the county economy in the Hunan-Hubei-Jiangxi border regions. With the decline of economic development level, the number of counties (cities) has increased significantly, and there is a clear ‘Pyramid’ type of hierarchical characteristics, and the low level county (city) is closer to the provincial border line than other regions, and the border effect shows obvious shielding characteristics; Spatial agglomeration is still at a low level, and the economic links among the counties need to be strengthened urgently. Moreover, this agglomeration is due to the low level similarity and shows the characteristics of ‘continuous poverty’; most of the hot spots are located in the periphery of the border area, the cold point area is located in the vast inner abdomen area. The imbalance between internal cooling and external heat has not been effectively resolved. From the results of spatial heterogeneity of economic effects of related factors, the labor, capital and government function all have positive effects. The high value of the return coefficient of labor input and capital input is in the hot area, and the low value is concentrated in the cold point area. On the one hand, the effect of government action decreases with the increase of distance from the region to the central city, on the other hand, it shows the difference between provinces. The impact of transportation level and education development level on economic development difference will show positive and negative polarization characteristics. From the perspective of spatial pattern analysis, it is necessary to deepen regional cooperation and fully improve the mechanism of coordinated development. From the analysis of influencing factors, it is necessary to improve the efficiency of labor transfer and the quality of labor employment; activate the potential of capital factors; enhance the educational supply capacity and education level; consolidate the construction of transportation infrastructure and actively enlarge the capacity of external traffic corridors in the Hunan-Hubei-Jiangxi border regions; and actively play the role of government guidance to mobilize the enthusiasm of local governments for economic development.

Key words: nighttime light data, border region, spatial pattern, geographically weighted regression

中图分类号:

F061

曾冰. 基于NPP/VIIRS夜间灯光数据的湘鄂赣省际交界区县域经济空间格局及影响因素[J]. 地理科学, 2020, 40(6): 900-907.

Zeng Bing. Spatial Pattern Evolution and Influencing Factors of County-level Economy of Border Regions in Hunan-Hubei-Jiangxi Based on Nighttime Light Data[J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(6): 900-907.

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数据类型	指标	2012年	2015年	2018年
平均夜间灯光	Moran’s I指数	0.156	0.169	0.185
值	Z值	47.008	54.126	62.931

模型参数	2012年		2015年		2018年
模型参数	OLS	GWR	OLS	GWR	OLS	GWR
AIC值	77.864	73.542	109.340	102.671	168.436	167.827
决定系数	0.614	0.787	0.669	0.842	0.672	0.836
校正决定系数	0.538	0.715	0.624	0.732	0.596	0.734