Next Article in Journal
Using Landsat and Sentinel-2 Data for the Generation of Continuously Updated Forest Type Information Layers in a Cross-Border Region
Previous Article in Journal
Variability of Major Aerosol Types in China Classified Using AERONET Measurements
Previous Article in Special Issue
Prediction of Soil Organic Carbon based on Landsat 8 Monthly NDVI Data for the Jianghan Plain in Hubei Province, China
Open AccessArticle

Visible and Near-Infrared Reflectance Spectroscopy Analysis of a Coastal Soil Chronosequence

1
School of Geographic Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
2
Meteorology and Climate Centre, School of Mathematics and Statistics, University College Dublin, Belfield, Dublin 4, Ireland
3
Department of Infrastructure Engineering, University of Melbourne, Parkville 3010, Australia
4
Institute of Soil Science, Chinese Academy of Science, Nanjing 210008, China
5
School of Systems Science, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2336; https://doi.org/10.3390/rs11202336
Received: 4 September 2019 / Revised: 4 October 2019 / Accepted: 7 October 2019 / Published: 9 October 2019
The soil chronosequence is a useful method for investigating pedological theories. Soil chemical, physical and mineralogical properties in chronosequences change over time and exhibit systematic and time-dependent trends, which can be used to analyze the rates and directions of pedogenic changes. The potential of soil spectroscopy as an emerging, rapid and cost-effective technique for predicting soil properties has been widely accepted and has motivated the application of spectroscopic techniques to the analysis of soil chronosequence. We present a soil chronosequence derived from 1000-year-old calcareous marine sediments and examine changes in six soil properties over this period. We evaluated the utility of a soil spectroscopic method to detect soil property changes and to predict the pedogenic properties and soil ages of the chronosequence. The results show that some soil pedogenic processes, such as soil organic matter accumulation, CaCO3 leaching and clay migration, can be identified in the millennium chronosequence. Power chronofunctions are formulated for soil organic matter (SOM) and Logarithmic chronofunctions are fitted for clay, CaCO3 and pH. These pedogenic processes are identified in the reflectance intensity and absorption features of soil spectroscopy, and pedogenic properties can be calibrated via soil reflectance spectroscopy. Profile ages can also be predicted via pseudo multi-depth spectra of soil profiles, and soil spectral curves for 0–30 cm generated the best prediction results (RPD = 1.85). We conclude that soil properties, changing due to weathering and soil formation, act as a bridge linking spectroscopy and weathering levels/pedogenic processes. The results imply that applying spectroscopy techniques to chronosequence study and mapping the degree of soil development in certain areas should be possible. View Full-Text
Keywords: soil chronosequence; spectroscopy; pedogenic property; soil age; partial least squares regression soil chronosequence; spectroscopy; pedogenic property; soil age; partial least squares regression
Show Figures

Graphical abstract

MDPI and ACS Style

Zheng, G.; Ryu, D.; Jiao, C.; Xie, X.; Cui, X.; Shang, G. Visible and Near-Infrared Reflectance Spectroscopy Analysis of a Coastal Soil Chronosequence. Remote Sens. 2019, 11, 2336.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop