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Study on Surface Temperature Characteristics of Chengdu Based on Multi-temporal Landsat Data

机译：基于多时间覆盖数据的成都表面温度特性研究

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摘要

By studying the multi-year surface temperature (LST) phenomenon in the center area of Chengdu, the characteristics of surface temperature in the context of population (POP), gross domestic product (GDP), and building index (NDBI) reflecting the state of urban economic development are analyzed. The relationship between ground temperature and various factors, and the possible causes of the formation of geothermal phenomena. The exploratory regression, Ordinary Least Square model (OLS), Geographic Weighted Regression model (GWR), and frequency ratio method were used to evaluate the correlation and differentiation characteristics of the ground temperature and each factor after using the atmospheric correction method to obtain the ground temperature data. It is determined that there is a significant correlation between the variables and the LST, and the factors are dependability; The LST overall level showed a decreasing trend, The area of the high temperature area shows a growing trend, There are slow cooling zones in the study area; Different economic intensity ranges contribute to the slow temperature drop zone. The index of the "FR" that is quoted is quantified to give the degree of a slow cooling zone, which makes it more intuitive in the text. At the same time, GWR model supplemented the local masking of OLS model in correlation analysis and the model performs better.
机译：通过研究成都市中心地区的多年表面温度（LST）现象，人口（POP）背景下的表面温度特征（POP），国内生产总值（GDP）和建筑指数（NDBI）反映了分析了城市经济发展。地下温度与各种因素之间的关系，以及地热现象形成的可能原因。探索性回归，普通最小二乘模型（OLS），地理加权回归模型（GWR）和频率比方法用于评估地温度和使用大气校正方法获得地面后的各个因素的相关性和分化特性温度数据。确定变量与LST之间存在显着的相关性，而且因素是可靠性; LST整体水平表现出降低趋势，高温面积的面积显示出不断增长的趋势，研究区有缓慢的冷却区;不同的经济强度范围有助于缓慢温度下降区。被引用的“FR”的索引量化以提供缓慢冷却区的程度，这使得文中更直观。同时，GWR模型补充了OLS模型在相关分析中的局部掩蔽，并且该模型更好地执行。

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