Spatial Upscaling of Sparse Soil Moisture Observations Based on Ridge Regression
نویسندگان
چکیده
منابع مشابه
Spatial Upscaling of Sparse Soil Moisture Observations Based on Ridge Regression
Available ground-based observation networks for the validation of soil moisture remote sensing products are commonly sparse; thus, ground truth determinations are difficult at the validated remote sensing pixel scale. Based on the consistency of temporal trends between ground truth and in situ measurements, it is feasible to estimate ground truth by building a linear relationship between tempor...
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[1] The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the ground resolution (typically >10 km) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from current and upcoming soil moisture satellite missions. Given typical levels of observed spatial variability in soil moisture fields, t...
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Soil moisture state and variability control many hydrological and ecological processes as well as exchanges of energy and water between the land surface and the atmosphere. However, its state and variability are poorly understood at spatial scales larger than the fields (i.e. 1 km2) as well as the ability to extrapolate field scale to larger spatial scales. This study investigates soil moisture...
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Based on the feature map principle, Sparse Kernel Ridge Regression (SKRR) model is proposed. SKRR obtains the sparseness by backward deletion feature selection procedure that recursively removes the feature with the smallest leave-one-out score until the stop criterion is satisfied. Besides good generalization performance, the most compelling property of SKRR is rather sparse, and moreover, the...
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Soil moisture content (SMC) is one of the most significant variables in drought assessment and climate change. Near-real time and accurate monitoring of this quantity by means of remote sensing (RS) is a useful strategy at regional scales. So far, various methods for the SMC estimation using a RS data have been developed. The use of spectral information based on a small range of electromagnetic...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2018
ISSN: 2072-4292
DOI: 10.3390/rs10020192