基于小波的浙江省NDVI与自然—人文因子多尺度空间关联分析

doi:10.11821/dlyj201503014

摘要/Abstract

摘要：

对地表植被的空间分布格局及其与自然、人文因子间的关系开展综合的、多尺度的定量分析,这是全球气候变化背景下土地利用与覆被研究中的一项重要内容。以地处亚热带湿润季风区的浙江省为研究区,设置了东西向(样线A)和北南向(样线B)两条样线,并应用小波分析方法对研究区NDVI、高程、坡度和土地利用强度等因子的尺度特征以及这些因子间的多尺度相关关系进行了分析。结果表明：①研究区内,NDVI、高程、坡度及土地利用强度的空间分布格局存在四个尺度域;②上述因子在样线A及样线B上的空间分布分别存在两个主要特征尺度,其中东西向(样线A)上的特征尺度为40 km和80 km,北南向(样线B)上主要的特征尺度为30 km和50 km;③在较大尺度域(8 km以上),土地利用强度是影响NDVI空间分布的最主要因素,而在小尺度域(0~8 km),坡度和高程因子成为影响NDVI分布的主要因子。研究还认为,小波分析方法为识别地理要素空间分布的特征尺度、量测要素间任意尺度、任意位置上的相干关系,提供了方便的工具。

关键词: 陆地植被, 环境因子, 尺度特征, 多尺度相关, 小波分析

Abstract:

Terrestrial vegetation ecosystem plays an important role in maintaining the sustainable development of global ecosystem, providing strong supports in exchanging energy and substances between pedosphere and atmosphere. With the rise of global change researches, vegetation research becomes an important content of land use and cover change research, which is one of the branches of studies on global changes. And it is a key step to understand the complex relationships between the vegetation distribution and its physical and artificial processes by using synthetical, quantitative and multi-scale means. In this research, Normalized Differentiation Vegetation Index (NDVI) was calculated as an indicator of vegetation, and three environmental variables were selected as the influencing factors including two topographic variables (elevation and slope) and one human variable (land use intensity, LUI). Continuous wavelet based methods were used to investigate the hierarchical structures and scale-location correlations between NDVI and other environmental factors. And two transects were selected along the east-west orientation (transect A) and the north-south orientation (transect B) in subtropical mountainous and hilly region, Zhejiang, China. The results showed that: (1) Four scales about the spatial distribution of NDVI and its driving factors were identified from the wavelet variance curves, with stronger variance values at larger scales; (2) The characteristic scales along the east-west transect were around 40 km and 80 km, whereas the characteristic scales along the north-south transect were around 30 km and 50 km. In these scales, the distributions of vegetation cover, landform and human activities exhibited richer structure information; (3) Topographic and humanity factors affected the distribution of NDVI at different scales, which was concluded from the wavelet coherence figures. It was proved that the humanity was the major influencing factor in larger scales (>8 km), while the terrain factors had more important effects in relative smaller scales (0-8 km). Generally, wavelet based approach provides an effective tool to analyze the multi-scale structure of ecosystem and to understand the scale-location specific relationships between environmental factors.

Key words: terrestrial vegetation, environmental factors, scale variation, multi-scale correlation, wavelet analysis.

徐芝英, 胡云锋, 甄霖, 庄大方. 基于小波的浙江省NDVI与自然—人文因子多尺度空间关联分析[J]. 地理研究, 2015, 34(3): 567-577.

Zhiying XU, Yunfeng HU, Lin ZHEN, Dafang ZHUANG. Wavelet-based multi-scale analysis of NDVI and background factors in Zhejiang province[J]. GEOGRAPHICAL RESEARCH, 2015, 34(3): 567-577.

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	0~8 km		8~25 km		25~60 km		>60 km
	相干性	通过率/%	相干性	通过率/%	相干性	通过率/%	相干性	通过率/%
NDVI-DEM	0.3264	5.70	0.4061	12.16	0.5766	28.51	0.6223	52.42
NDVI-SLOPE	0.3530	8.54	0.4392	20.29	0.7383	70.35	0.8654	100
NDVI-LUI	0.2914	11.51	0.5209	26.89	0.7613	71.26	0.9397	100

	0~8 km		8~20 km		20~70 km		>70 km
	相干性	通过率/%	相干性	通过率/%	相干性	通过率/%	相干性	通过率/%
NDVI-DEM	0.3277	5.66	0.3704	10.61	0.6516	30.72	0.7945	50.41
NDVI-SLOPE	0.3602	8.80	0.4934	23.66	0.7706	68.08	0.9501	100
NDVI-LUI	0.2758	7.85	0.5513	38.39	0.8400	80.11	0.9420	100