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E. García-Cuesta, I. M. Galván, and A. J. de Castro, “Multilayer perceptron as inverse model in a ground- based remote sensing temperature retrieval problem,” Engineering Applications of Artificial Intelligence, Vol. 21, pp. 26–34, 2008.

has been cited by the following article:

• TITLE: Soil Moisture Retrieval Quantitatively with Remotely Sensed Data and Its Crucial Factors Analysis

  AUTHORS: Ji JIAN, Peifen PAN, Yuanyuan CHEN, Wunian YANG

  KEYWORDS: Soil Moisture, Quantitative Remote Sensing, NDVI

  JOURNAL NAME: Journal of Water Resource and Protection, Vol.1 No.6, December 23, 2009

  ABSTRACT: The Ts/NDVI method was adopted to retrieve soil moisture with multi-temporal and multi-sensor remotely sensed data f ETM+ and ASTER in study area. The retrieved soil moisture maps were consistent with the soil type and vegetation, which were also the two main factors determining the distribution of soil moisture.