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首页> 外文期刊>Permafrost and Periglacial Processes >Statistical Analysis of Topographic and Climatic Controls and Multispectral Signatures of Rock Glaciers in the Dry Andes, Chile (27°-33°S)
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Statistical Analysis of Topographic and Climatic Controls and Multispectral Signatures of Rock Glaciers in the Dry Andes, Chile (27°-33°S)

机译:智利干燥安第斯山脉(27°-33°S)的岩石冰川的地形,气候控制和多光谱特征的统计分析

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The dual nature of rock glaciers as ice-rich mountain permafrost and sediment storage systems results in a combination of geomorphic processes and energy balance components controlling their distribution. We use the generalised additive model (GAM), a semi-parametric nonlinear method, to empirically analyse environmental controls and spectral characteristics of rock glaciers in the dry Andes of Chile based on presence/absence data at random point locations and predictor variables derived from digital elevation models and Landsat data. A combination of nonlinearly transformed local and catchment-related terrain attributes (especially local and catchment slope and potential incoming solar radiation, PTSR) characterises the geomorphic and climatic niche of rock glaciers. The influence of (latitude adjusted) relative PISR varies with mean annual air temperature (MAAT): high-PISR sites are favourable for rock glacier development at lower MAATs and low-PISR sites at higher MAATs. TM/ETM+ band 6 (thermal infrared) is an additional nonlinear predictor. The combination of topographic, climatic and multispectral data in a GAM achieves an excellent general discrimination (area under the ROC curve 0.87 on the model domain and 0.94 overall). In automatic rock glacier detection at a sensitivity of 70 per cent, this model achieves a false-positive rate (FPR) of 6.0 per cent overall and 12.8 per cent on the model domain (bootstrap estimates: 7.9% and 16.8%). Dropping the multispectral data significantly increases the bootstrapped FPR by 36 per cent. Thus, the fusion of multisource data using modern nonlinear classification techniques is a promising step towards automatic rock glacier detection.
机译:岩石冰川的双重性质是富含冰的山区多年冻土和沉积物存储系统,导致地貌过程和控制其分布的能量平衡成分相结合。我们使用半参数非线性方法广义加性模型(GAM),基于随机点位置的存在/不存在数据以及从数字数据中得出的预测变量,对智利干燥的安第斯山脉的岩石冰川的环境控制和光谱特征进行经验分析高程模型和Landsat数据。非线性变换的局部和与流域相关的地形属性(尤其是局部和流域的坡度以及潜在的入射太阳辐射,PTSR)的组合表征了岩石冰川的地貌和气候生态位。 (经纬度调整)相对PISR的影响随年平均气温(MAAT)的变化而变化:高PISR站点有利于较低MAAT的岩石冰川发育,而低PISR站点则适用于较高MAAT的岩石冰川发育。 TM / ETM +频段6(热红外)是附加的非线性预测器。 GAM中的地形,气候和多光谱数据相结合可实现出色的一般判别(模型域上ROC曲线下的面积为0.87,总体上为0.94)。在以70%的灵敏度进行自动岩石冰川检测时,该模型的假阳性率(FPR)总体为6.0%,在模型域中为12.8%(引导估计:7.9%和16.8%)。丢弃多光谱数据将使自举FPR大幅提高36%。因此,使用现代非线性分类技术融合多源数据是朝着自动岩石冰川检测迈出的有希望的一步。

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