Characterization and prediction of soil organic matter content in reclaimed mine soil using visible and near-infrared diffuse spectroscopy. Issue 3 (3rd July 2021)
- Record Type:
- Journal Article
- Title:
- Characterization and prediction of soil organic matter content in reclaimed mine soil using visible and near-infrared diffuse spectroscopy. Issue 3 (3rd July 2021)
- Main Title:
- Characterization and prediction of soil organic matter content in reclaimed mine soil using visible and near-infrared diffuse spectroscopy
- Authors:
- Bao, Nisha
Liu, Shanjun
Yang, Tianhong
Cao, Yue - Abstract:
- Abstract: An accurate determination of the soil organic matter (SOM) levels present in reclaimed mine soil is necessary to evaluate the success of the ecological reclamation of mines. Visible and near-infrared diffuse spectroscopy is a fast and efficient method for collecting data for soil management during the reclamation of soil removed from mines. In this work, we used spectroscopy to characterize and estimate the SOM of lands from different reclamation years after coal mining in semi-arid grasslands of North China. Our goals were: (1) to explore the SOM characteristics and the spectra of reclaimed mine soil with different reclamation ages, and (2) to establish a reliable and accurate SOM prediction model by comparing support vector machine (SVM), partial least-squares regression (PLSR), and random forest (RF) modeling methods by determining the optimal preprocessing method and input spectral region. The results showed that spectral characteristics are useful indicators for understanding progressive SOM changes in the topsoil at different reclamation ages. RF is a more appropriate method for assessing the performance of a selected spectral region and provides more accurate results with a root mean square error (RMSE) of 4.34 g·kg −1 between predicted and observed SOM values. This study provides an alternative method that uses spectroscopy to estimate reclaimed soil conditions for the environmental monitoring of mining sites.
- Is Part Of:
- Arid land research and management. Volume 35:Issue 3(2021)
- Journal:
- Arid land research and management
- Issue:
- Volume 35:Issue 3(2021)
- Issue Display:
- Volume 35, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 35
- Issue:
- 3
- Issue Sort Value:
- 2021-0035-0003-0000
- Page Start:
- 276
- Page End:
- 291
- Publication Date:
- 2021-07-03
- Subjects:
- Machine learning algorithm -- mine reclamation -- reclamation years -- reclaimed soil -- VIS-NIR spectra
Arid soils -- Periodicals
Arid regions agriculture -- Periodicals
Desert reclamation -- Periodicals
631.47154 - Journal URLs:
- http://www.tandfonline.com/toc/uasr20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/15324982.2020.1867935 ↗
- Languages:
- English
- ISSNs:
- 1532-4982
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1668.259000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17263.xml