کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8893574 | 1629189 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Photography measured-value magnification improves local correlation maximization-complementary superiority method of hyperspectral analysis of soil total nitrogen
ترجمه فارسی عنوان
عکاسی بزرگنمایی اندازه گیری می کند روش برتری به حداکثر سازی همبستگی محلی را افزایش می دهد از روش تجزیه و تحلیل بیش از حد نیتروژن
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کلمات کلیدی
طیف بازتابی، عکاسی اندازه گیری بزرگنمایی، حداکثر سازی همبستگی محلی - برتر بودن مکمل، نیتروژن کل خاک،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فرآیندهای سطح زمین
چکیده انگلیسی
Accurate remote retrieval of soil total nitrogen (TN) content is a challenging task due to many factors including soil color. The objective of this study was to investigate whether the photography measured-value magnification (PMM) method improves estimation accuracy by reducing the influence of soil color, when combined with the local correlation maximization-complementary superiority (LCMCS) method. Soil samples were collected from three areas of subsided land in Renqiu, Changzhou, and Fengfeng District, all located in Hebei Province, China. Soil spectral reflectance was measured using an ASD FieldSpec 3 spectrometer in a laboratory environment and the TN content was determined by the Kjeldahl method. After PMM analysis, the LCMCS method was used to build models for TN estimation. The results indicate that the LCMCS model of the PMM group produced lower prediction errors (Coefficient of determination [R2]â¯=â¯0.893, root mean square error of validation [RMSEV]â¯=â¯0.090, mean relative error of validation [MREV]â¯=â¯5.721%) when compared with the local correlation maximization-partial least squares regression (LCM-PLSR) model of the PMM group and the models of the conventional group. Overall, the PMM method combined with LCMCS has great potential to improve the estimation accuracy of TN content and enriches the choice of observation method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CATENA - Volume 165, June 2018, Pages 106-114
Journal: CATENA - Volume 165, June 2018, Pages 106-114
نویسندگان
Lixin Lin, Fengchang Xue, Yunjia Wang, Keqiang Liu,