On the Criterion of Proximity to the True Value: Information Approach
Issue:
Volume 7, Issue 1, June 2019
Pages:
1-4
Received:
25 March 2019
Accepted:
28 May 2019
Published:
9 July 2019
Abstract: What is the criterion of proximity to the true value of the measured value: absolute or relative error? The least squares method traditionally operates with absolute values of corrections to measured values, and the equalization is carried out under the condition of the minimum of the sum of squares of absolute corrections. However, as shown in the article, the informational approach leads to the conclusion that the measure of proximity to the true value is a relative measurement error. Therefore, it is advisable to carry out an equalization under the condition of a minimum of the sum of squares of not absolute, but relative corrections. This is equivalent to equalization, in which the weight of the correction depends on the size of the object being measured: the larger the object being measured, the smaller the weight of the corresponding amendment, and its value can be increased during equalization. In this case, the described approach leads to a kind of “method of least relative squares” (MLRS). Another interesting consequence of the information approach is that the relative measurement error modulus has the meaning of the probability of a measurement result deviating from the true value. The article presents the required information approach formulas for the weights of the amendments when using the MLRS. In particular, it is shown that the angular discrepancy distribution in a triangle depends on the lengths of the sides.
Abstract: What is the criterion of proximity to the true value of the measured value: absolute or relative error? The least squares method traditionally operates with absolute values of corrections to measured values, and the equalization is carried out under the condition of the minimum of the sum of squares of absolute corrections. However, as shown in the...
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Spatial Enhancement of DEM Using Interpolation Methods: A Case Study of Kuwait’s Coastal Zones
Nawaf Al-Mutairi,
Mohammad Alsahli,
Mahmoud Ibrahim,
Rasha Abou Samra,
Maie El-Gammal
Issue:
Volume 7, Issue 1, June 2019
Pages:
5-12
Received:
7 August 2019
Accepted:
4 September 2019
Published:
19 September 2019
Abstract: Digital elevation models (DEMs) are essential tools utilized in several branches of science, including environmental, geological, and geospatial studies. Unfortunately, high-accuracy DEM data such as LiDAR are not publicly available, and the coverage is limited. Therefore, the use of alternative methods, such as interpolation techniques (i.e., kriging, inverse distance weighting, radial basis functions), is greatly advantageous for the production of enhanced DEMs. The results of this study show that interpolated DEMs had minimal errors (RMSE = 1.44) with an increase of about 28% from the original DEM. However, the spatial resolution of interpolated DEM data was enhanced significantly by 83%. The deterministic interpolation methods provided more accurate estimations for producing DEMs in the coastal zones of Kuwait than geostatistical interpolation methods. The reference elevation data were collected using GPS and accurate topographic maps (1:25,000), and elevation points from the interpolated DEM were matched significantly (R2 = 0.88; R2 = 94, respectively). Given the lack of accurate DEM data, the interpolated DEM produced in this study are held in high regard and highly recommended for use in the coastal zone of Kuwait.
Abstract: Digital elevation models (DEMs) are essential tools utilized in several branches of science, including environmental, geological, and geospatial studies. Unfortunately, high-accuracy DEM data such as LiDAR are not publicly available, and the coverage is limited. Therefore, the use of alternative methods, such as interpolation techniques (i.e., krig...
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A Microwave Scattering Model for Simulating the C-Band SAR Backscatter of Wheat Canopy
Wenjia Yan,
Yuan Zhang,
Tianpeng Yang,
Xiaohui Liu
Issue:
Volume 7, Issue 1, June 2019
Pages:
13-24
Received:
11 July 2019
Accepted:
31 July 2019
Published:
20 September 2019
Abstract: Accurate simulation of microwave scattering characteristics of wheat canopy can provide valuable insights into the scattering mechanisms of wheat crops. In this study, a wheat canopy scattering model (WCSM) was developed on a basis of first-order microwave radiative transfer equation. Several WCSM inputs, including wheat canopy and soil parameters, were measured in situ at the time (or near the time) of the satellite observation. The backscattering coefficients of wheat fields were then simulated at various incident angles and polarization modes. Four C-band quad-polarized (Radarsat-2 and Gaofen-3) SAR data were used to evaluate the WCSM performance in four key growth stages of winter wheat from stem elongation to ripening in 2017. Results showed that the WCSM simulated backscattering coefficients of wheat fields with error lower than 1.8 dB. This study demonstrates that the proposed WCSM is effective in characterizing the C-band backscatter features of wheat crops for various growth phases. It also indicated that the operational potential of C-band satellite SAR systems such as the Radarsat-2 and the China Gaofen-3 SAR in monitoring wheat growth for food safety in important agricultural regions.
Abstract: Accurate simulation of microwave scattering characteristics of wheat canopy can provide valuable insights into the scattering mechanisms of wheat crops. In this study, a wheat canopy scattering model (WCSM) was developed on a basis of first-order microwave radiative transfer equation. Several WCSM inputs, including wheat canopy and soil parameters,...
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