STUDY ON SPECTRAL FEATURES OF SOIL ORGANIC
MATTER
HE Ting WANGJing LIN Zongjian CHENG Ye
KEY WORDS: Soil Organic Matter (SOM); Spectral Features, Stepwise Regression Analysis
ABSTRACT:
The study on soil spectral reflectance features is the physical basis for soil remote sensing. Soil organic matter content influences the
soil spectral reflectance dramatically. This paper studied the spectral curves between 400nm~2500nm of 174 soil samples which
were collected in Hengshan county and Yixing county. Fourteen types of transformation were applied to the soil reflectance R to
remove the noise and linearize the correlation between reflectance (independent variable) and soil organic matter (SOM) content
(dependent variable). Then, methods such as derivative spectrum technology, stepwise regression analysis, were applied to study the
relationship between these soil spectral features and soil organic matter content. It shows that order 1 derivative of the logarithm of
reflectance (OIDLA) is the most sensitive to SOM among the various transform types of reflectance in consideration. The regression
model whose coefficient of determination reaches 0.885 is built. It predicted the soil organic matter content with higher effect.
CLC NUMBER:P237.4; P237.9; P272
1. INTRODUCTION
The research of earth resources and environment by remote
sensing method is directly or indirectly related to soil optical
characters because soil is one kind of the most exposed earth
backgrounds. Therefore, the study on reflective characteristic of
soil spectra is the physical base of soil remote sensing. The
appearance of High Spectral Resolution Imaging Spectrometer
provides a new technique for this study. Researchers can fully
take the advantage of the Imaging Spectrometer, Spectra-Image
conformity, to reconstruct spectra from images and compare
them to spectra data collected on the ground, and then to
perform synthetically analysis. It supports not only on band
selection and design of sensors, but also on interpretation and
analysis of remote sensing image data. Soil organic matter is an
ingredient of soil solid-phase matter and serves as a reserve for
many essential nutrients which called “nutrient bank for plant”,
and its loss is closely linked with the decline of soil productivity.
The content and composition of soil organic matter have strong
effects on soil reflectance. The color of the soil is usually
closely related to its organic matter content, with darker soils
being higher in organic matter, which indicates the relationship
between soil organic matter content and its visible light
reflectance. Although there are a lot of inversion methods used
to get the organic matter content from soil reflectance [l]-[9],
all of these methods subject to certain limitation to some extent,
and display biggish error when applying in different soil
categories. To date, there is no versatile model which is fit for
all over the world and the waveband selection for different
study area is also diverse. This paper intended to analyze the
relationship between soil reflectance data and organic matter
content from 174 soil samples, accordingly extracting organic
matter content information from reflectance data, evaluating the
application potential of hyperspectral remote sensing technique
in monitoring soil organic matter content in the visible and near
infrared spectrum, detecting spectral characteristics sensitive to
organic matter content and establishing corresponding inversion
model for soil organic matter content prediction.
2. DATA AND METHODS
2.1 SAMPLING DESIGN
174 soil samples are collected from topsoil (about 5cm),
including 43 soil samples collected from Yixing sample plot
and 132 soil samples collected from Hengshan sample plot.
There are two typical kinds of geomorphy in Hengshan County:
Loess Plateau and Maowusu Desert, and its main soil types are
loessal soil, sand soil, aeolian sandy soil and so on. Its soil is
relative infertile and contains low content soil organic matter;
Yixing county is located at Tai Lake bank, its soil is
comparative fertile, the main soil types include yellow-brown
soil, limestone soil, brown-red soil, paddy soil and so on,
containing higher content soil organic matter. The selection of
these two areas can make sure that there are comparative large
range of organic matter values (0.124% ~ 4.86% ). The soil
samples were collected from planar areas containing bare soil,
and the selection of sampling areas considered various land-use
types and soil types. 4 or 5 typical survey stations were selected
in each sampling area, and then one soil sample was selected in
each survey station with 5 times spectral measurements before
each soil sampling. Spectral measurements used ASD FieldSpec
FR field spectrometer, and used a fiber optic probe with 3
degree field-of-view to vertically observe objectives. The
wavelength coverage of ASD FieldSpec FR Spectrometer is
from 350 nm-2500 nm, including 3 nm spectral resolution
between 350 nm-1000 nm, 10 nm spectral resolution between
1000 nm-2500 nm[10] 0 During observation, the surveyors
should take the fiber optic probe in their hands and face to light
source (the sun) direction, and the probe must be vertical with
measuring objectives. A 75cm><75cm white reflection plate was
used for obtaining absolute reflectance. While measuring,
radiance but not reflectance was directly detected. Firstly, the
radiance of white plates was measured for 5 times, and then the
radiance of soil objectives was also measured for 5 times. The
illumination conditions between objectives and reference white
plates must be consistent as much as possible, and then the
average values were calculated. The ratio between averaged soil
radiance and radiance of white plates is the soil reflectance.
This kind of measurement method can eliminate the effects of
some random noises compared with direct measurement of soil
reflectance.
2.2 Measurement of soil organic matter content
This study used volumetry assay to measure organic matter
content of soil samples. The method is described as follows:
