The NIR Community from ASD Inc., a Malvern PANalytical company

Join us for our next free webinar - Analyzing and Groundtruthing Soil Characteristics

August 23, 2016

Our 2016 webinar series focuses on one ASD spectroscopy application each month.

If you haven't watched each of our previous webinars, visit our webinar recordings page to see what you missed. Some of our past topics include: NIR, Metamorphic Petrology, and Remote Sensing, On-orbit Sensor Absolute Radiometric Calibration for Earth Remote Sensing, and Adventures in Albedo.

This September, our webinar focuses on the application of soil characteristics. 

In this webinar you will learn:

  • How (and why) water alters the spectral reflectance of soil
  • The importance of the location of water in the soil
  • Nutrient and organic matter analysis of soil
  • UAS sensor calibration using an ASD instrument
  • Groundtruthing a UAS sensor using an ASD instrument

It's Textbook: FieldSpec Spectroradiometer Referenced in Advances in Spectroscopic Methods for Quantifying Soil Carbon

September 25, 2012
In the recently published textbook, Managing Agricultural Greenhouse Gases: Coordinated Agricultural Research Through Gracenet to Address Our Changing Climate, ASD’s FieldSpec portable spectroradiometer was mentioned as preferred instrumentation.

While discussing “Advances in Spectroscopic Methods for Quantifying Soil Carbon,” in the subsection covering Instrumentation, authors included ASD’s FieldSpec spectroradiometer as a valuable tool in NIR research.  

Important for academic and industry research, ASD’s FieldSpec portable spectroradiometer can provide rapid results for those using it in the field.
Advancements to the FieldSpec line including fiber optic accessories and ruggedized portable designs have gained the spectroradiometer notoriety in many verticals.

For more information on the FieldSpec line, ASD reps are available to answer application questions.

Contact ASD Today!


Reflectance Spectroscopy for Soils and Crops Research – See it at the ASD booth at ICPA!

July 09, 2012

Reflectance spectroscopy offers a versatile and precise way to extract important information from soils and crops. ASD’s FieldSpec 4 and HandHeld 2 instruments are valuable tools to researchers in the field of precision agriculture.

Researchers already use this method to assess soil fertility and crop nutrients analysis. They are attracted to the portability, non-destructive measurement, and immediate lab-quality results that our spectroradiometers provide.

Add sophisticated calibration modeling by our SummitCAL experts to create a full crop and soils analysis solution.

Soil applications include total carbon levels and carbonate levels. Crop applications include nitrogen status, soil fertility and water status.

Examples of constituents ASD instrumentation can measure:  
- Moisture
- Total carbon/Inorganic carbon
- Total nitrogen/Mineralized nitrogen
- Clay/Silt/Sand
- Soil organic matter
- Cation-Exchange Capacity (CEC)
- pH

Check out our spectroradiometers and related crops and soils applications at the ICPA Conference in Indianapolis, July 15 – 18. ASD’s booth number is 12.

For more information about the conference, visit the ASD events page.

Accurately Measuring Soil Carbon Using a LabSpec Spectrometer

October 06, 2011

Growing concerns over carbon emissions are driving research focused on the measurement of carbon soil flux. Carbon dioxide may be emitted due to oxidation of organic carbon or may be sequestered in either organic or mineralized forms. Organic carbon and carbonate can be measured using the ASD LabSpec® 2500 portable spectrometer to help monitor carbon flux in soils. Measurement of soil carbon with ASD LabSpec can help agronomists and farm managers optimally change their management practices to promote sequestration of atmospheric carbon dioxide into farm soils.

April Update: Soils Analysis using ASD Spectrometers

April 06, 2011

By Brian Curtiss

Review of Selective Events in the Field of Remote Sensing and Reflectance Spectroscopy During 2010

January 24, 2011

The following are a few highlights of events in the field of remote sensing in 2010 from the perspective of ASD.

Spectral Reflectance of Wetted Soils

November 29, 2010

Soil gets darker when it gets wet, but the color doesn’t change much. It seems simple until you look at the difference in spectra created by water absorption. My first thought was, "how hard can this be?" -- Has anyone else said that but then regretted it later?

Soil reflectance spectra are responsive to a number of soil characteristics, including water content, mineral content, the presence or absence of organic material and the roughness or coarseness of the soil. The early results weren’t great; measured data did not match the visible. We know that wet soil produces strong glint, which could be due to salts in the soil that dissolve in water. However, this effect doesn't change the spectra much. Though we over-predicted reflectance in visible, we still observed some interactions in water and soil.

We over-predicted water absorption bands because we didn’t realize water absorption was inhibited by something. We cleaned field samples, but the dried soil was not sterilized. We hypothesized water was bonding with soil and changing the molecular vibration amplitude. Using a Gaussian curve correction factor in each water band, we observed seven spectral functions including water, soil, CDOM and Gaussians. We matched results to 4 different soil measurements. The corrected model did fairly well, but errors remain in some soils, so we see the method needs more work. Using Gaussian fits, we may be able to hypothesize about the vibrational modes to test on different soil mineralogy.

Of course, just because it fits doesn't mean you should believe it! There may be alternative explanations for the darkening effect (see Anstrom 1925, Twomey, Bohren, Morgenthaler 1986). Anstrom's work was the first spectral measurement of water and soil in 1925. Twomey, Bohren and Morgenthaler explored an index of refection and scattering effects.

ASD equipment is so much better than what was available previously. With it, we were able to conclude that the darkening effect is spectrally bland, shows significant absorption in IR and the absorption spectrum is modified by soil.

An Innovative Approach to Normalize Soil Reflectance Spectra

November 03, 2010

When Alex [Goetz] asked me to speak at this symposium, I knew I wanted to present something special instead of doing an overview. I decided to look at variation between spectrometers to assess stability and variability of soil reflectance measurements with different ASD instruments under different conditions in the lab. [Information on different types of portable ASD Fieldspec spectrometers is at: http://www.asdi.com/products/instrumentation/portable]

Soil spectroscopy is well studied and used in many applications. Dozens of soil attributes can be estimated from NIR and reflectance data, but people use different kinds of data and methods making this process less robust. In order to reduce variability, we need a single spectrometer to create and validate the model.

Every measurement needs an internal standard, especially those used in the field of scientific study. There are many soil spectra libraries. The World Spectral Group database, as an example, contains 7000 samples, five attributes, 60 instruments, 80 users and 40 protocols.  To add validity to soil spectroscopy, we must standardize the process and be able to take reference material into the field so we can reduce variability.

There are a few problems associated with this, though: Water is hard to control, and soil moisture can affect the spectra markedly. Different instruments in source and destination labs can also cause variations in the soil spectra. Other causes of variability include type of device, sample preparation, measurement protocol, humidity, optics and more. We must assume that operator error affects the standard, too. Protocol calls for reference measurement at the beginning and end of each sampling run to account for this.

Standards need testing. We were very careful with the lab equipment, including testing chambers and stabilization. The objectives for this study are to compare three ASD spectrometers under controlled conditions and to analyze instrument protocols and conditions for each.

We measured various soils with several ASD devices. In the first experiment, we used all three ASD devices in the same lab at same time. This produced generally low variation despite the fact that our aggregated soil samples contained various grain sizes.

In a second experiment, we sent the ASD instruments to three different labs in Israel to re-measure the samples. Each lab’s humidity level differed, making for higher variation than in the first experiment. The handheld probe was an especially large source of variation.

Protocol for this experiment was an 11-step method. We found some variations in the second experiment, even in the average environment. The largest of these variations occurred in the least humid lab, because the soil samples tended to dry over the course of the experiment. Good protocol minimizes the need to correct light sources and geometry, but variation is still a factor.

So, how do we correct for variation? Analytical chemistry uses certified internal standards. We can borrow that model to correct the spectra. The solution must be inexpensive, available around the world, spectrally stable, materially inert, stable chemically and similar in particle size to soil. Industry standards include formica, ground glass and bleached sand. Even with these correction factors in place, we found some variation in the instruments.

We set out to design a correction via a normalized additive factor. We found bleached sand to be the most favorable standard. We then tested effects of using different standards on false alarms for classification of soils. Formica was the worst of these standards. The effects of these additives were not visible in correlations of soil indices, but we found sand to work best in our calculations for finding soil content.

Though variation sources are numerous, including instrument, operator and protocol, we found that measurement protocol and external conditions dominate variation in this environment. The instrument accounts for less variation (up to 10% variation across spectrometers). As variation is not an issue of ratio indices, but is an issue of partial least squares, internal reference standards help validate the model.

We propose that this method enables the variable spectra of a given soil sample to be translated into a common denominator. Thus, it should facilitate the exchange of spectral information among scientists worldwide and allow creation of a robust soil database for diverse applications.

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