Research Conclusion/Discussion

Conclusions

The soil development of Thiaumont platform may not necessarily be what is expected under the Runge model and Catena concept. This is mostly due to soil texture and the relatively short time span the soil has had to develop. For the Catena concept to show heterogeneous soil development, the soil texture must allow the potential energy caused by water traveling through the profile. Soil development is accelerated by a permeable soil texture which was not seen throughout my study area. Since the top soil consisted primarily of clay, there was little water traveling through the soil profile therefore many saturated crater bottoms were seen. Clay rich soil textures impede the leaching of water into the water table. This likely explains the little variation seen in the soils water content and temperature at each recorded position within the crater.

Another major factor in soil development is time. Having been only 100 years since the initial disturbance, it is expected that at least one inch of top soil has been created. However this estimate may likely be less than what is observed as a result of the accumulation of organic litter settling within the crater bottoms.

Although the results were not as I expected, the artillery disturbance of the landscape has undoubtedly caused a different process of evolution. Future studies may in fact provide more empirical evidence supporting my hypothesis. Certain limitations within my data collection process may be overcome by different techniques of analysis.

Further Research

Further research throughout the Verdun battlefield is necessary to conclude that the landscape is developing differently than in the pre-war environment. Perhaps a highly permeable study area will yield the results expected under Runge's energy model and the Catena concept.

Future researchers may find it beneficial to get ONF clearance to dig soil pits and examine the horizonation of the soil profiles. Since the soil profiles were essentially reset to day zero by the pedoturbation caused by explosive munitions, this method could clearly show how much the soils have developed since the initial disturbance. Another helpful piece of information would be knowing the location of the water table. The use of ground penetrating radar may provide valuable information in distinguishing whether or not saturated craters are at or near the water table or if soil texture is causing the retention of water.

The soils seen within the crater bottoms are also likely to be more acidic than at other locations due to the amount of tree litter. Recording the pH of each location may prove beneficial in determining how much this variable is impacting soil development.

Shortcomings

Throughout my research I ran into a number of difficulties. This brings me to the importance of thoroughly constructing a methodology report prior to conducting field research. This process helps with any contingencies that arise so they may be overcome by a deliberate course of action. Unfortunately, not all contingencies may be preemptively recognized and the integrity of the data will perhaps depend upon a quick, formulated decision.

A major shortcoming I ran into during the data collection and processing phase of my research was the difficulty in quantifying my data. I initially had the expectations of using various statistics in my data, however, when I attempted this process I learned that the elevation data from the Nomad GPS unit is too imprecise. In retrospect, my data would have been much more compelling had I taken soil recordings where each point of our micro-elevation data was collected.

Link to website:
http://geographyofthewesternfront.weebly.com/

Story Map

An easy way to show spatial information highlighting a trip is to create an online story map. ESRI provides the online resources needed to do just that. In this blog post, I will walk you through the steps of creating an informative story map.

To begin you need to create an ESRI ArcGIS.com login account. ESRI offers a free 30 day trial on their website. To access the login page, visit this link: https://www.arcgis.com/home/signin.html
If a longer account is needed, consult your schools geospatial facilitator.

Once your account has been created, you can begin accessing the software to create a story map. ESRI offers a number of intuitive layout designs that you can choose depending on your applications. For my story map I used the basic map tour layout seen below.

Runoff Characteristics of Thiaumont Platform

Introduction:

Often times the tools within a GIS are not autonomous. Such is the case when deriving runoff characteristics. In this post, I will provide my workflow in determining which locations within the cratered landscape receive the most surface runoff. This runoff model compliments Runge's energy model in explaining the relationship between the amount of moisture available for leaching and soil development.

Methods:

The process of developing a surface runoff and accumulation model consists of multiple steps. A clear and organized workflow model provides the most efficient means of communicating the process (model 1). Below the model is an explanation of each step. All tools used throughout this project may be found in the spatial analyst toolbox under hydrology and surface.



 

1) The model begins with adding a digital elevation model (DEM) to the project. My elevation model contained microtopographic relief ranging from 401 meters to 406 meters of the Thiaumont Platform, Verdun, France (figure 1).

Figure 1: Digital Elevation Model of Thiaumont Platform. The DEM provides all of the necessary elevation data for the entire process.

 

2) The flow direction tool is used with the DEM entity to determine the direction the water will travel across the surface (figure 2). This tool is essentially calculating the aspect, the maximum angle of downslope direction (ESRI).


Figure 2: Flow direction shows the downslope angle with the steepest gradient

3a) Once the flow direction has been determined a tool may be used to locate any sinks within the watershed and fill them. Depending on the application of the research, this tool may or may not be used. For example, when observing the watershed of a large area, you may want to exclude depressions that collect surface flow. For my application, each sink (crater) was the target of my study so this step was excluded.

3b) The flow accumulation tool is used to calculate areas with the highest rate of movement depending upon the flow direction layer (figure 3). This shows where surface runoff is most likely to occur and where it will accumulate.

Figure 3: Flow accumulation uses the flow direction to determine where water is most likely to flow across the surface.

4) After flow accumulation has been determined, the point pour tool is used to delineate the location of drainage basins (ESRI). The locations calculated in step 3b are used to determine where each microwatershed begins and ends (figure 4).


Figure 4: Pour Point uses the flow accumulation previously calculated to show drainage basins. A hillshade was applied to beter visualize the relationship between elevation and water accumulation.

Results:

The results of this activity provides spatial analysis of water movement and accumulation across a topographic surface. These tools effectively aid in the understanding of fluvial geography by providing spatial representations of where runoff is likely to occur and the location of the resulting drainage basins. Figure 5 shows a three dimensional representation of my study site including hydrologic characteristics that will help in my understanding of soil development under the Runge Energy Model and the Catena concept. According to this model (figure 5), soil development should be accelerated in locations labled as dark blue considering they are unsaturated (Runge).

 

Figure 5: This three dimensional model provides a great spatial representation of the runoff characteristics of the Thiaumont Platform. The microrelief of the landscape adds to the variability in soil development in the area.


 Conclusion:

This exercise provided invaluable information for my studies on landscape evolution of Verdun. Using functions in hydrology allows me to better understand the processes at work forming the landscape. Next week I will explore the recovery of vegetation using the soil knowledge I gained during the past few weeks.



Catena Concept and how it relates to Verdun Craters

Catena Concept
There exists a relationship between soils on one part of the landscape and soils nearby. The Catena concept provides an excellent way of illustrating this geographic relationship using slope dynamics. The main components of a contena are (1) fluxes of water and matter, and (2) the location of the water table (Schaetzl, 2005). On a sloped surface, water infiltration rates depend upon the permeability of the soils and the gradient of the slope. If the slope gradient is high enough, sediments will be transported, and deposited in the form of alluvium and slopewash. The location of the water table determines how well these sediments are deposited, thus contributing to the development of the soils.

According to the Runge Energy Model, the two most important variables for soil development are climate, and relief.  The relief of the landscape determines how the catena concept applies, and the water introduced into the system is dependant upon the climate. In artillery craters of Verdun, France both the Runge Model and the Catena Concept are used to explain soil formation in a way that promotes and/or inhibits the recovery of healthy vegetation.

Much of the Verdun landscape is littered with craters caused by artillery fire during World War I. As a result, soil development changed in process following this initial disturbance. Soil profiles within cratered landscapes can be explained using the Runge model and the catena concept of soil development.

Similar to the Jenny model, Runge's energy model explains soil development as a function of relief, climate, organic constituents, and time (Schaetzl, 2005). Climate and relief, being the most important factors, determine the amount of water accessible to the system and the potential energy of that water moving through the soil profile. Locations where water accumulates and permeates through the soil profile, will have better developed soils (Schaetzl, 2005). The use of Runge's energy model to explain soil development is limited by the permeability of the soil and the location of the water table. Locations with a low water table and soil textures that encourage leaching will have the most developed soil. Alongside water available for leaching is the important variable of relief. This concept is best explained using the Catena concept.

Figure 1: Pour Point analysis uses elevation data to model where water is likely to accumulate. Areas shown in light blue depict low elevations where soil moisture is highest. Using this data and the Catena concept, areas in light blue are likely to have more developed soil profiles and pronounced horizination.

Under the catena concept, soil development in areas with heavy relief depends upon the location of the water table and fluxes of water and matter within the soil profile (Schaetzl, 2005). In fully saturated crater bottoms (perched water table), soil development is slower than crater bottom well above the water table. Leached material through the soil profiles exacerbates horizonation and soil development (figure 2). As water is introduced into the soil profile, sediments are transported by colluviation and slopewash and deposited within crater bottoms (Schaetzl, 2005).  As a result, soils located within crater bottoms become more developed (Hupy, Schaetzl, 2008).



Figure 2: The catena concept explains soil development as a function of surface topography. On slope surfaces, soil development is not uniform. The movement of water through the soil profile allows for the transportation and deposition of sediments.

Microtopography, often overlooked, is a significant factor influencing soil development. Small changes in relief create pit-and-mound topography that affects variables contributing to soil development such as soil temperature, organic litter accumulation, and water infiltration/movement Schaetzl, 2005). A horizons within crater bottoms are expected to thicken as a result of the decomposition and weathering of organic materials. However, tree litter may impede the growth of vegetation as will erosive activity on crater sides.


Soil Genesis (Annotated References)

Pedology Context (Thiaumont)
    Clay Dominated
            Poorly Drained (low permeability)
    Formation
            Formed over shale and colluvial parent material
            Shallow bedrock
                     perched water tables
            
Soil Development Accelerant

Runge's energy model:  S = f(o,w.t)
Soil (S)
Intensity factor (w) (Water available for infiltration)
      Climate
           Duration and intensity of rainfall
      Relief
           Run-on/Runoff
                 Soil Permeability
           Organizing soil profiles (gravitational forces)
Organic Matter Production (o)
       Source of humus in soil (prevents weathering (melanization))
       Offsets w factor
Time (t)

Applicable to unconsolidated topsoil i.e. loess or till. Less applicable to coniferous forest

The Verdun landscape has a wide range of relief as a result of explosive munitions. This model will be helpful in explaining soil development within the cratered landscape.  Vegetative litter found at the bottom of the craters adds to the organic matter found within the soil (humus).  However, the dominant soil seen at Thiaumont Platform was clay rich, slowing the effectiveness of Runge's model. To be an effective accelerant of soil development, the environment must meet certain criteria. (1) The preexisting soils need to be permeable for a higher rate of water infiltration leading to horizonation (Schaetzl, Anderson, 2005)

Catena Concept
Soil transect running from the base to the top of a hill.
Provides informationon hillslope hydrology and shape, and stratigraphy.
Anthrosols (modified soils due to human activity)

Using ESRI Map Applications to Present Spatial Data

During this week, I explored the various ESRI Online map application templates trying to find the best one to present the data I collected in Verdun, France. Throughout the process I encountered a number of shortcomings that kept leading me back to the basic template design and, unfortunately for ESRI, sometimes Google Tour Builder.

The first map application template I used was the Elevations Profile. I figured this would be a creative way of presenting the landscape context of my data. Before using this template I had these expectations of its particular uses. I imagined being able to use my own DEM layer for my elevation data, and having scroll over effects to present various study sites. Once I began experimenting with the template, I realized it did not nearly meet my expectations. The interface provided is just terrible which I may extend to the ESRI story mapping creation process in general. Very simple tasks quickly become daunting, such as editing your map in general. Unlike the simple story map template, there doesn't seem to be any "builder mode" to edit and add features to the map. The only editing options I was able to find are located at the menu before actually opening the app. Once you get into this editing page, the purpose drop down menu located under Properties must be set to configurable (Figure 1).

Figure 1: To be able to edit an elevation profile template you have to select configurable under the application properties. Note the selection for an application programming interface. To utilize this web mapping application to its fullest extent, some background knowledge of JavaScript, Silverlight, or other API is needed.

Only after this is done can you actually begin creating a Elevation profile. This feature is cool and all, but is there an intuitive process that allows you to add your own data? The short answer is no, unless you have knowledge of JavaScript, Flex, Silverlight or another application programming interface. I have yet to figure out how to do even the basic task of saving the elevation profile to be viewed during later use.

I ran into the same problem when attempting to create a mapping application that incorporates a functioning slider. I figured this application would provide an interactive way of comparing my digital elevation model of the region, with aerial imagery. However, similar to the elevation profile template, some knowledge of an API is needed.

As a last resort I reverted back to the original story map template. Although this template doesn't provide the most functional method of presenting spatial data, the interface is very user friendly. To streamline the photo hosting and geocoding process, a .csv file was created with the server addresses to all of my images (Figure 2).

Figure 2: .CSV file with the photo addresses hosted by our GIS server.

 During this process, additional problems were encountered. To be recognized by ArcGIS Online, the format must exactly match their provided template. Null values, fields lacking any input, defeat the purpose of creating a .csv and all of the fields must include relavant information. It is important to note that Internet Explorer is not a recognized browser of the .csv file, for this reason Google Chrome was used

Collecting Data and Interpolating the battlefield

Introduction

While studying the Verdun battlefield in France, we collected large amounts of data that will be useful in analyzing and interpreting the battlefield. Evidence supporting a particular geographic research question is heavily dependent upon this data collection process. To provide empirical evidence to answer my research question, whether warfare may be considered a significant agent promoting ecological and pedological change, volumetric water content, soil temperature, and micro elevation data were collected on the Thiaumont ridge. This information will supplement the research conducted by Joseph Hupy and Thomas Koehler in explaining the change in vegetation and soil evolution. 

Methods

Volumetric water content, and temperatures were recorded on the cratered and non-cratered landscape. Moisture and temperature readings were collected in crater bottoms, crater sides, and crater tops (figure 1). Some areas of the landscape were so disturbed that crater tops were difficult to distinguish since they were often enveloped within one another. Coordinates of each record along with notes were organized using a Trimble Nomad global positioning system (Table 1). To minimize the amount of error involved with our equipment, volumetric water content was recorded five times for each crater position and the results were averaged together. The temperature probe was inserted 15 cm into the soil and left until the temperature stopped moving.

Figure 1: Collecting volumetric water content and temperature of the soil. Readings were taken on the crater bottoms, crater sides, and crater tops. A GPS was used to record the coordinates and characteristics of each site location.



Table 1: Each soil measurement was added to a table that is easily be imported into a GIS. The notes field consisted of various qualitative observations at that site location.


Along with soil moisture and temperature, information on the landscapes surface was also collected. Using a Total Station, we recorded accurate and precise micro elevation data to produce a three dimensional model of the surface. Elevation data was imported into an excel spreadsheet to include each points X,Y, and Z coordinates (Figure 2).
Figure 2: Using a Total Station, elevation data was recorded and compiled into an Excel file to be imported into a GIS. Each point represents the location where surface data was collected and contains an elevation (Z) field.

Once these fields were established, ArcMap was used to interpolate the surrounding elevations using complex algorithms to estimate values not physically recorded. The two methods of interpolation used were Kriging and Spline. Kriging uses a weighted algorithm dependent upon the distance between two points and their elevation values (Figure 3). Spline interpolation uses an algorithm that minimizes surface curvature and creates a model that passes exactly through each of the input values (ESRI) (Figure 4). Both interpolation methods provide a smooth and continuous representation of the area within each input point
Figure 3: A Kriging interpolation algorithm was used to estimate the elevation values between each recorded input. Kriging uses a weighted distance function to determine how output values are dependent upon the distance of multiple input values.

Figure 4: Spline interpolation estimates output values by altering the shape of a plane to pass exactly through each of the input points.
  

After interpolating the surrounding elevation values, the surface models were imported into ArcScene to be spatially examined in three dimensions. Both raster images were added to the program and processed to float on a custom surface as described in the previous post. This created a three dimensional model of the Thiaumont study area (Figures 5-6).

Figure 5: Kriging interpolation of Thiaumont ridge rendered in 3D.

Figure 6: Spline interpolation rendered in 3D. This method has a more pronounced representation of the surface because the model passes directly through each input value.

Figure 6: Spline interpolation rendered in 3D. This method has a more pronounced representation of the surface because the model passes directly through each input value.

Discussion

To fully examine the soils data, various processing tools will be used to determine the significance the cratered landscape has on the developing vegetation and soil. Soil moisture content and temperature will be compared to the surface data to determine if the artillery bombardment of the Verdun battlefield has significantly altered the landscape in a way that the recovered environment is set on a different pathway compared to the undisturbed environment. Hydrology tools will be used to examine how surface flow has been altered in heavily cratered areas.

Conclusion

The modeling of our study area using highly accurate and precise elevation data is important to be included with my soil measurements. To understand why this environment is behaving differently from its prewar environment, the data must be examined spatially. Within upcoming blog posts, I will begin quantitative analysis to provide evidence of this divergent pathway.

Collecting and Viewing DEM data in ArcScene

Introduction:

During the continuing government shutdown, a problem began to arise within the Geographic community. Reliance upon the United States Geological Survey (USGS) for gathering spatial information has begun to put a toll on GIS users within academia and the private sector alike. Creative methods of data collection have to be pursued to overcome such a dilemma. In this blog post I will cover the use of ASTER DEM data provided by Japan, to create a three dimensional model of the World War I Verdun battlefield.

Background Information

As mentioned above, relying on a single source for spatial data is considered poor practice within the geographic community. This reliance not only causes a dilemma in the wake of a government shutdown, but also exclude other valuable resources that should be considered.  Our search for different distributors of spatial data brought us to a collaborative project by the Ministry of Economy, Trade, and Industry of Japan (METI), and the United States National Aeronautics and Space Administration (NASA). METI and NASA are jointly developing a publicly accessible digital elevation model using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite.  ASTER provides land coverage between 83°N and 83°S with a resolution of 1 arc-second (30 meter) at a 95% confidence level (Group on Earth Observations).  This data offers a suitable alternative to the USGS in providing accurate and precise elevation data.

Methods

To begin collecting data I will direct you to the website where you will create a login account used to access the tiles of your study area. http://gdem.ersdac.jspacesystems.or.jp/login.jsp.  Once your account has been set up, navigate to the homepage by clicking ASTER GDEM at the top of the page. The tiles are accessed by selecting "Search" located on the side tab of the homepage. This should bring up an interactive map sectioned off by square tiles (Figure 1).

Figure 1: Interactive map used during the tile selection process. The four selection methods are listed at the top of the webpage under the search header. To select a method, use the tabs located above the map. 

 Use the map to zoom to your area of interest (AOI). For the purposes of my class our study area is a single tile located in Eastern France at roughly 5°W and 49°N. The interactive map has four methods of tile selection depending on the size of your study area. You can select the tiles of your AOI directly, select the tiles of your AOI by creating a polygon around it, use an existing shapefile containing the extents of your study area, or if you know the coordinates you can select the tile at that location. I used the select tiles directly method while paying attention to the coordinates of the cursor in the lower left hand corner of the map. 

Once you found the tile(s) within your AOI, click start located above the map to begin the selection process.  After selecting your tiles, click next below the map to bring up your selection queue and click next again.  If you are not already logged in, you will be prompted to do so otherwise you will be directed to the ASTER GDEM terms of use and policy agreement. It is very important that you select disaster as your purpose for the download as disaster relief/mitigation is the primary intended use of the data.  After selecting agree you can begin the downloading process. Navigate to your download and extract the files to your desired directory. This ends the data collection process for obtaining ASTER elevation data.

Now that you have collected your data, it can be imported into a GIS for manipulation and analysis. For our intended purposes we wanted to create a three dimensional model of the Verdun battlefield showing just how crucial it was for both combative forces to secure the north and south ridgelines east of the Meuse River. Since the tiles downloaded using the process above covered a larger area than necessary, the clip function was used to extract only my AOI. Using a separate raster, I designated the extent of the battlefield to create a new, smaller elevation raster. Figure 2 shows an overlay of my DEM clip on top of the ASTER tile.

Figure 2: A DEM clip (red to green diverging, dark) overlay on top of downloaded ASTER tile. The clip was created using a georeferenced raster of the Verdun battlefield

After creating the DEM clip of our AOI, it was imported into ArcScene to visualize the battlefield in three dimensions. When downloading data from the GDEM website, it comes preset to the WGS84 spatial reference. To ensure spatial integrity, the raster was re-defined and projected using the ETRS 1989 datum in UTM zone 31 North. Once the raster has been projected, it can be set to float on a custom surface within the layer properties, designating each pixel value from the DEM to represent change in elevation (Figure 3).

Figure 3: Setting base heights to float on a custom surface within the layer properties dialog box. This will create the three dimensional surface desired for the model. 

Once the raster has been set to float on a custom surface, it can be viewed in three dimensions. If for any reason your raster is not a three dimensional model, you may have to change the vertical exaggeration located in the general tab of the scene properties (Figure 4). If vertical exaggeration is set at zero, it will show no change in elevation which is obviously not an accurate depiction of Earth's surface. A vertical exaggeration set at "none" will maintain the elevational scale of 1:1; whereas, a vertical exaggeration set at "5" will embellish the changes in elevation five to one.

Figure 4: Setting the vertical exaggeration to emphasize changes in elevation. To view the model in 3D, make sure your models vertical exaggeration is not set to zero.

Results

Additional features within ArcScene may be used to enhance the quality of your model.  Changing the raster surface resolution can help in achieving either a "smoother" or more pronounced image (Figure 5 and Figure 6).

Figure 5: A smooth surface model using large X and Y cell sizes to show smooth changes in elevation

Figure 6: A rough surface model using a majority of the DEM's pixel values to depict changes in elevation.

The color scheme can also be changed to emphasize contrasts in elevation using warm and cool colors. The symbology can be changed from stretched to classified if you want to create color classes within a pre-defined elevation range. This may be useful when determining the suitability for a feature at a certain location (Figure 7 and Figure 8).  

Figure 7: Rendering the raster in a continuous, stretched color scheme to enhance the surface elevations. 

Figure 8: Rendering the raster in a classified color scheme to detect suitable locations of battlefield defensive locations.

Conclusion

Elevation data within a GIS has a number of practical uses. In future blog posts, I will continue to explore the Verdun battlefield by using various tools such as slope, aspect, and viewshed analysis.  Although I initially encountered the dilemma of losing the USGS as a data source, it was easily overcome by a quick search online. This brings me to my second point.

Collecting data from multiple sources should be considered best practice within the geospatial discipline. It offers a wide range of discretion to influence the integrity of your model.  Reliance on a single developer may be hazardous, acting as a limiting agent to your methods. Creditable alternatives exist beyond the conventional hosts such as USGS and the US Census Bureau. A quick google search came up with a number of sites distributing their data at no costs. Within the scope of my studies, these sources will be a valuable asset to my understanding of the Verdun battlefield.

ASTER information

http://www.earthobservations.org/art_200906_aster.shtml

Data sources

http://data.geocomm.com/catalog/index.html

http://gdem.ersdac.jspacesystems.or.jp/index.jsp

http://geodata.grid.unep.ch/

Creating an Online Story Map

An easy way to show spatial information highlighting a trip is to create an online story map. ESRI provides the online resources needed to do just that. In this blog post, I will walk you through the steps of creating an informative story map.

To begin you need to create an ESRI ArcGIS.com login account. ESRI offers a free 30 day trial on their website. To access the login page, visit this link: https://www.arcgis.com/home/signin.html 
If a longer account is needed, consult your schools geospatial facilitator.

Once your account has been created, you can begin accessing the software to create a story map.