Soil Microtopography Device |
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Concept image of the SMAP satellite, launched by NASA on January 31, 2015
SMAP
SMAP (Soil Moisture Active Passive) is a satellite that was launched by NASA in early 2015 for the purpose of acquiring information about soil moisture levels around the globe. Better information about soil moisture levels results in improved weather forecasting accuracy, flood prediction, and understanding of the water cycle in general.
A key issue with SMAP is the resolution of the imaging that it receives. The "Active" portion of SMAP is currently not functional, so the only information that is being received is from passive imaging. This means that the satellite gets roughly one reading per 500 square miles. In places like Iowa, where soil texture varies widely from area to area, one reading per effective county size is not sufficient to capture the true state of the soil. Information about the roughness of the soil is needed to make an accurate assessment of its moisture levels.
More information about SMAP: http://smap.jpl.nasa.gov/
A key issue with SMAP is the resolution of the imaging that it receives. The "Active" portion of SMAP is currently not functional, so the only information that is being received is from passive imaging. This means that the satellite gets roughly one reading per 500 square miles. In places like Iowa, where soil texture varies widely from area to area, one reading per effective county size is not sufficient to capture the true state of the soil. Information about the roughness of the soil is needed to make an accurate assessment of its moisture levels.
More information about SMAP: http://smap.jpl.nasa.gov/
Our Task
The challenge given to our group is to create a device or system to measure the roughness of soil. The device should be able to take images of one square meter and map the topography of the sample. It needs to be able to do this quickly, accurately, and with minimal preparation time. Our measurement system currently consists of an XBOX Kinect and a Windows 10 machine. Using a Visual Basic program, we use the Kinect to take a snapshot of the ground, and the program returns a two-dimensional array of data as an Excel file. This data is then processed by MATLAB which returns a three-dimensional graph of the sample data so the user can determine the roughness of the sample.