GSA2015

Last week students from the lab were at the Geological Society of America meeting in Baltimore, where they presented research done in the lab. Here are some photos.

Article on recent field work

Here is an article recently published on our August 2015 field trip.

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Amanda Henck Schmidt
Assistant Professor
Geology Department
Oberlin College

http://www.oberlin.edu/faculty/aschmidt

In Which an Exciting New Land Use Dataset Makes Itself Known to the Group

Hello,  Joe here.  With the carto-freak David, we make up the GIS side of the research group’s “Spatial Command”.  We don’t like to get our fingers dirty and so are instead lucky enough to spend hours on end in a windowless computer lab making minute adjustments to processes that we know will inexplicably fail anyway.  Not that I’m bitter about the work I do or anything…

Anyway, Spatial Command is currently looking at a series of watersheds along the Mekong river, tying isotope data (specifically 210Pb and 137Cs) from soil samples to other parameters, like relief, rainfall, and land use.  The isotopes get counted in Harbin, our reliable germanium detector.  Data like relief, we can calculate from elevation models, and in fact, we used the wonderful GDEM dataset from NASA to that effect.  Rainfall was a bit harder to do in-house, so we turned to the quite useful APHRODITE dataset from the Research Institute for Humanity and Nature (RIHN) and the Meteorological Research Institute of Japan Meteorological Agency (MRI/JMA).  That leaves us with land use data, the source of some exciting new developments for Spatial Command, and the subject of this blog post.

Harbin, showing enormous patience with one the bozos from the lab, this is something Harbin has to put up with on a daily basis, as everyone who works in this lab is quite a joker.

Previously, we had been using the GlobCover dataset from the European Space Agency for our larger scale analysis and an in-house supervised classification of Landsat 8 data trained by yours truly for a smaller scale study of three basins.  Spatial Command was all set to use GlobCover for our larger project, when word came in that a newer, more precise dataset existed, GlobeLand30, a global dataset with a spatial resolution of 30 meters.  Needless to say, our cartographic natures were excited by this possibility.  But we were still cautious.  Where had this dataset come from?  Sure it was more precise, but was it more accurate?  We decided to take one step beyond guessing, and put it to the test!

GlobeLand30 is a product from the National Geomatics Center of China, and was released in 2014.  The image data used to create GlobeLand30 were primarily 30 meter Landsat TM and ETM+ images from within a year of 2010.  They undertook an extensive accuracy assessment, and reported an accuracy of 83.51%, but we decided it would be prudent to assess the accuracy of our study area specifically.

When comparing the GLOBCOVER and GlobeLand30 against accuracy assessment regions defined by me from Landsat 8 data, certain issues presented themselves.  Namely, that each dataset was divided into different land use classes.  The GlobCover dataset was divided into 23 different classes, GlobeLand30 had 10, and because we were primarily interested in quantifying agriculture, we had only 4 classes.  Both the accuracy assessment and eventual application necessitated some amount of class combination.

Eventually, all data was combined into four classes:  Agriculture, Forest (comprising all natural vegetation), artificial surfaces, and water.  Some classes that were irrelevant to the areas used for accuracy assessment, like “tundra”, were ignored.  Then it was smooth sailing to the goods; we plugged the data into ENVI, generated some confusion matrices, and then we were Good To Go!

The overall accuracy of GlobCover for our area was 72.22%, and the overall accuracy of GlobeLand30 was 76.76%.  The accuracy for each individual class was also good, although classes that were not widely represented in the data used for accuracy assessment tended to have lower calculated accuracy.

As you can see from the maps comparing the GlobCover and GlobeLand30 datasets, the precision afforded by the GlobeLand30 means that the boundaries between classes are much more accurate.  However there are also still areas of disagreement between GlobeLand30 and the hand-classified dataset used for accuracy assessment.  The classification I did by hand was primarily from Landsat 8 satellite images, between that and my unfamiliarity with the region, it is certainly possible that I have misclassified things that the GlobeLand30 classification system classified correctly because they used a wider range of data sources that may have helped distinguish between things that were visually similar in the satellite data, like cropland and grassland.

Still, it seems clear that GlobeLand30 is the better choice, and we at Spatial Command are excited to get a chance to work with it.  The next time you hear about it from us will be when we have some preliminary results about how land-use correlates with our isotope counts.

Soil Pits Winter Term 2015

Soil Pits Site Descriptions & Analyses

CH-014 (Basin 35)

 

•   CH-014 was collected from a riverbank. The O/A horizon is an organic-rich silt loam about 15cm deep. The B¹ horizon (15-35cm) is very clayey, possesses a weak structure, and is between 30-40% gravel. The B² horizon is 50-60% gravel. The flatland approaching the bank appears to be a grassy field with a few scattered small trees. The field slopes sharply towards the bank. The levels of ¹³⁷Cs and ²¹⁰Pb_ex exhibit fairly typical exponential-type decay with depth. The amount of ²¹⁰Pb_ex decreases more quickly than the amount of ¹³⁷Cs.

CH-015 (Basin 35)

   

• The soil comprising CH-015 is a uniform, coffee-brown color throughout the column. The O/A horizon is a dark clay loam that is high in organics and is about 35cm thick. The B horizon is gravelly silt clay with 40-50% gravel and weak structure. This soil pit is located in a farm field. The amount of ¹³⁷Cs and ²¹⁰Pb_ex both increase between the 0-5cm section and the 5-10cm section, and drop off dramatically with increased depth. This pattern suggests that this area has experienced a change in erosion rates.

CH-028 (Basin 35)

  

 

• CH-028 was collected on the ridge crest of a young coniferous forest. The first 4cm of soil is a grey silt loam that could be a less-developed forest A-horizon but may also be an erosional layer. The B¹ horizon is a yellowish-brown silty clay soil with a well-developed blocky structure. The B² horizon is a dark brown, sticky clay and has a well developed blocky structure. The soil profile contains low concentrations of ¹³⁷Cs and ²¹⁰Pb_ex and we only observe these isotopes in the upper 10cm of the soil. This suggests that the area has experienced significant erosion.

CH-029 (Basin 35)

  

• CH-029 was collected from a fallow agricultural field that was probably forest at one time. The A horizon extends for about 30cm and is an olive-brown silt loam that contains some roots. The B horizon extends for another 30cm and is a yellowish brown silty clay. The horizons are separated by a whitish carbonate accumulation. The relatively uniform levels of ¹³⁷Cs and ²¹⁰Pb_ex throughout the soil profile indicate that the soil has been mixed by a plow.

CH-030 (Basin 35)

    

• CH-030 was collected at the edge of a young coniferous forest, off the ridge seat. The A horizon extends for 20cm and is a silty loam. The B horizon extends for over 30cm below the A horizon and is a brownish yellow sandy clay. This soil pit looks similar to the others, except that it contains a more weakly developed zone of carbonate accumulation (stage 2 carbonate development). The absence of ¹³⁷Cs and ²¹⁰Pb in the 10-15cm section suggests that the soil currently at the 15-20cm depth used to be at the surface, but new soil has been deposited on top of it.

CH-061 (Basin 49)

     

 

•  CH-061 was collected from a cliff in a fairly vegetated area. The pit is composed of a deep, well developed tropical soil, overlain with a forest soil. The A horizon extends for 5cm and is a light silty sand. The B¹ horizon extends for 25cm and is a sandy clay. The B² horizon is clayey and demonstrates stage II carbonate accumulation. The soil profile exhibits a small amount of ¹³⁷Cs and a comparatively much greater amount of ²¹⁰Pb_ex.

CH-081 (Basin 11)

     

•       CH-081 was collected from a relatively high elevation road cut on a moderate (10-15°) slope in an old forest. The A¹ horizon extends for 37cm and is a deep, organic-rich silt loam of a very dark color. The A² horizon extends for 23cm and is a dark, yellowish brown sandy silt The level of ¹³⁷Cs in the upper 15 cm of the soil remains relatively uniform, but the amount of ²¹⁰Pb_ex decreases in an exponential fashion.  

Additional Resources

• Walling, Colins, and Sichingabula, 2003. “Using Unsupported Lead-210 Measurements to Investigate Soil Erosion and Sediment Delivery in a Small Zambian Catchment.” Geomorphology, 52(2003), pp. 193-213. http://www.sciencedirect.com/science/article/pii/S0169555X02002441

•   The authors provide information on how to estimate erosion rates using FRN observations in areas where ¹³⁷Cs inventories may be low or nonexistent, relying on unsupported ²¹⁰Pb measurements in soil cores to construct sediment budgets that differentiate between several main types of land use in the study area. This relates well to our project, especially since some of the soil pits do not have high concentrations of ¹³⁷Cs.

• Mabit, Benmansour, and Walling, 2008. “Comparative Advantages and Limitations of the Fallout Radionuclides ¹³⁷Cs, ²¹⁰Pb_ex, and ⁷Be for Assessing Soil Erosion and Sedimentation.” Journal of Environmental Radioactivity, 99(2008), pp. 1799-1807. <JER_2008.pdf>.
• This paper provides a great review of the information we can gather from FRN distribution in the soil, and the limitations associated with potential findings. The authors discuss the implications of different concentrations of FRNs in soil columns and detail what type of erosion/deposition could have led to that distribution. This provides a detailed background on soil pits and what they can tell us about past and ongoing conditions.

•   Walling and He, 1999. “Using Fallout Lead-210 Measurements to Estimate Soil Erosion on Cultivated Land.” Soil Science Society of America Journal, 63(1999), pp. 1404-1412.  
• This paper focuses on using ²¹⁰Pb to estimate rates of water-induced soil erosion on cultivated land. Soil cores showing the distribution of ²¹⁰Pb in the soil are the investigative tool used. This relates well to the objectives of our project examining the effects of changes in land use on erosion rates. 

•     Mabit et al, 2014. “Fallout ²¹⁰Pb as a Soil and Sediment Tracer in Catchment Sediment Budget Investigations: A Review.” Earth-Science Reviews, 138(2014), pp. 335-351. http://www.sciencedirect.com/science/article/pii/S001282521400115 
• Mabit et al. provide a full walkthrough of the applications of fallout ²¹⁰Pb as a soil and sediment tracer, focusing on catchment sediment budget investigations. This review encompasses applications of ²¹⁰Pb that are beyond the scope of our investigation, but it would be useful to go through and read the sections on soil pits.