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Variogram Analysis for Assessing Landscape Spatial Heterogeneity in NDVI: an Example Applied to Agriculture in the Jiansanjiang Reclamation area, Northeast China

机译:基于NDVI的景观空间异质性评估的方差分析:以中国建三江垦区农业为例

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摘要

It is necessary to characterize and monitor the spatial heterogeneity of agricultural landscapes, to assist the spatial understanding of some related agricultural processes and to predict food production patterns. In the study, variogram models fitted to empirical variograms are proposed to retrieve spatial heterogeneity characteristics, and they are applied to NDVI data generated from Landsat TM imagery at a 30 m pixel scale. Four representative study sites with distinct landscape patterns, located in the Honghe farm of Jiansanjiang Reclamation Area, Northeast China, were selected for spatial heterogeneity testing and analyzing. The results provided quantitative agricultural landscape knowledge: (1) the agricultural landscape heterogeneity at different directions within the study area could be effectively quantified with the variogram model and then interpreted; (2) the spatial heterogeneity of the dry land matrix was normally larger than that of the paddy field matrix; and (3) the agricultural spatial heterogeneity was affected by two factors: the land use type and the distribution pattern of land use types. As remote sensing techniques can now provide various types of surface monitoring data, we argue that quantitative variogram analysis of the data for spatial heterogeneity can help identify explain related ecological phenomena. It could also be used to improve quantitative agricultural remote sensing monitoring in a spatial heterogeneity area as well.
机译:有必要刻画和监测农业景观的空间异质性,以协助对一些相关农业过程的空间理解,并预测粮食生产方式。在研究中,提出了适合经验变异图的变异图模型以检索空间异质性特征,并将其应用于从Landsat TM影像生成的30 m像素尺度的NDVI数据。选择了位于中国东北剑三江垦区红河农场的四个具有代表性的具有不同景观格局的研究地点进行空间异质性测试和分析。研究结果提供了定量的农业景观知识:(1)利用变异函数模型可以有效地量化研究区域内不同方向的农业景观异质性,然后对其进行解释; (2)旱地基质的空间异质性通常大于水田基质的异质性; (3)农业空间异质性受土地利用类型和土地利用类型分布格局两个因素的影响。由于遥感技术现在可以提供各种类型的地面监测数据,因此我们认为,对数据进行空间变异性的定量变异函数分析可以帮助识别相关的生态现象。它还可以用于改善空间异质性地区中的定量农业遥感监测。

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