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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site
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Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site

机译：在Barrax试验场中将MODIS地表温度降尺度为Landsat空间分辨率的分解方法的评估

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摘要

Thermal infrared (TIR) data are usually acquired at a coarser spatial resolution (CR) than visible and near infrared (VNIR). Several disaggregation methods have been recently developed to enhance the TIR spatial resolution using VNIR data. These approaches are based on the retrieval of a relation between TIR and VNIR data at CR, or training of a neural network, to be applied at the fine resolution afterward. In this work, different disaggregation methods are applied to the combination of two different sensors in the experimental test site of Barrax, Spain. The main objective is to test the feasibility of these techniques when applied to satellites provided with no TIR bands. Landsat and moderate imaging spectroradiometer (MODIS) images were used for this work. Land surface temperature (LST) from MODIS images was disaggregated to the Landsat spatial resolution using Landsat VNIR data. Landsat LST was used for the validation and comparison of the different techniques. Best results were obtained by the method based on a linear regression between normalized difference vegetation index (NDVI) and LST. An average was observed between disaggregated and Landsat LST from four different dates in a study area of .
机译：通常以比可见和近红外（VNIR）更高的空间分辨率（CR）来获取热红外（TIR）数据。最近开发了几种分解方法，以使用VNIR数据提高TIR空间分辨率。这些方法基于在CR处TIR和VNIR数据之间的关系的检索或神经网络的训练，此后将以高分辨率使用。在这项工作中，在西班牙Barrax的实验测试地点，将不同的分解方法应用于两种不同传感器的组合。主要目的是测试将这些技术应用于没有TIR频段的卫星时的可行性。 Landsat和中度成像光谱仪（MODIS）图像用于这项工作。使用Landsat VNIR数据将来自MODIS图像的地表温度（LST）分解为Landsat空间分辨率。 Landsat LST用于验证和比较不同技术。通过基于归一化植被指数（NDVI）和LST之间的线性回归的方法，可获得最佳结果。在研究区的四个不同的日期观察到了分解的和Landsat LST之间的平均值。

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