NDLI: Regression Kriging-Based Upscaling of Soil Moisture Measurements From a Wireless Sensor Network and Multiresource Remote Sensing Information Over Heterogeneous Cropland

Content Provider	IEEE Xplore Digital Library
Author	Jian Kang Rui Jin Xin Li
Copyright Year	2004
Abstract	The ground truth estimated by in situ measurements is important for accurately evaluating retrieved remote sensing products, particularly over heterogeneous land surfaces. This letter analyzes the role of multisource remote sensing observations on the upscaling of soil moisture observed by a wireless sensor network at the pixel scale via the regression kriging (RK) method. Three types of auxiliary remote sensing information are employed, including Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature Vegetation Dryness Index (TVDI; 90 m), Polarimetric L-band Multiband Radiometer brightness temperature (700 m), and Moderate Resolution Image Spectroradiometer TVDI (1000 m). Moreover, a comparison with the ordinary kriging method is analyzed. The spatial inferences show that the RK method is more accurate and that its spatial pattern is more consistent with the auxiliary data when the trend is successfully removed, particularly when spatial continuity is destroyed by irrigation. The ASTER TVDI has a higher resolution and stronger correlation with soil moisture and yields more accurate interpolation results than the other types of remote sensing information. Although medium-resolution data do not substantially contribute to capture the spatial patterns of soil moisture, such data may still improve the prediction accuracy.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	92
Ending Page	96
Page Count	5
File Size	682659
File Format	PDF
ISSN	1545598X
Volume Number	12
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Soil moisture Remote sensing Irrigation Accuracy Market research Correlation Soil measurements wireless sensor network Regression kriging (RK) remote sensing soil moisture spatial heterogeneity upscaling
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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