ipaast-czo case study OptRX data: Montalcino (SI, Italy)

Perna, C., Campana, S., Sarri, D., Vieri, M., Baldwin, E. and Opitz, R. (2023) ipaast-czo case study OptRX data: Montalcino (SI, Italy). [Data Collection]

Datacite DOI: 10.5281/zenodo.7867101

Collection description

These data were collected as part of a case study for the ipaast project. The aim of the survey was to produce datasets interoperable for applications in archaeology and precision agriculture.

The OptRx® Crop Sensors (AgLeader Technology, Ames, IO, USA) measure the reflectance in the 630–685 nm (red), 695–750 nm (RE red edge) and 760–850 nm (NIR—Near InfraRed) wavebands. Using those wavebands, NDVI and NDRE indexes are calculated. NDVI and NDRE are vegetative indexes obtained from the red, red-edge and NIR wavebands with formulas 1 and 2:

NDVI = NIR−REDNIR+RED ; NDRE= NIR−RENIR+RE

The two index values range from -1 (bare ground or water) to 1 (highly vigorous vegetation).

To collect data, the sensor was mounted on a ground vehicle, a Kubota B2420 tractor. The sensor was paired with a GNNS receiver, GPS 6500 from AgLeader Technology (Ames, IO, USA). The instrumentation was coupled with the hardware and the rough book (Panasonic ToughPad FG-Z1, Panasonic Core. It was possible to install the sensor facing the ground using a metal bracket positioned on the front of the tractor. The sensor was positioned 1.15 m from the ground, emitting a rectangular footprint of 1.14 m in length and 20cm in width. The data were collected every 30 cm in alternate rows. 12 rows in total were analysed, covering a surface of 1.07 ha.

Data were processed on QGIS. First, the data was interpolated with the Inverse Distance Weighting (IDW) function. The function was set up with a distance coefficient P of 4, with 40 rows and 98 columns. A Gaussian filter with a standard deviation value of 2 and a range of research of 3 was subsequently applied to create a representative raster.

College / School: College of Arts & Humanities > School of Humanities > Archaeology
Date Deposited: 04 Jul 2023 12:19
URI: https://researchdata.gla.ac.uk/id/eprint/1464

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Perna, C., Campana, S., Sarri, D., Vieri, M., Baldwin, E. and Opitz, R. (2023); ipaast-czo case study OptRX data: Montalcino (SI, Italy)

Zenodo

DOI: 10.5281/zenodo.7867101

Retrieved: 2024-06-23