In this article, we are proposing a method using Landsat-8 Operational Land Imager and Thermal Infrared Sensor data for agricultural plastic cover detection. Four normalized difference indices were combined in the rocedure described to achieve onsistent results: the green Normalized Difference Vegetation Index and three ad hoc spectral indices purposely created for this study (rescaled brightness temperature, Plastic 10 Surface Index and Normalized Difference Sandy Index). The sampling time related to the preliminary collection of spectral information on plastic surfaces was reduced using information gathered through the Quality Assessment and Cloud Quality bands. The overall accuracies observed were on average higher than 80%,and the low cost of the open data set used, lacking ancillary data, demonstrated the reliability of the 15 proposed method, proving its suitability for environmental and agricultural monitoring over large areas.
Combining ad hoc spectral indices based on LANDSAT-8 OLI/TIRS sensor data for the detection of plastic cover vineyard / Novelli, Antonio; Tarantino, Eufemia. - In: REMOTE SENSING LETTERS. - ISSN 2150-704X. - STAMPA. - 6:12(2015), pp. 933-941. [10.1080/2150704X.2015.1093186]
Combining ad hoc spectral indices based on LANDSAT-8 OLI/TIRS sensor data for the detection of plastic cover vineyard
NOVELLI, Antonio
;TARANTINO, Eufemia
2015-01-01
Abstract
In this article, we are proposing a method using Landsat-8 Operational Land Imager and Thermal Infrared Sensor data for agricultural plastic cover detection. Four normalized difference indices were combined in the rocedure described to achieve onsistent results: the green Normalized Difference Vegetation Index and three ad hoc spectral indices purposely created for this study (rescaled brightness temperature, Plastic 10 Surface Index and Normalized Difference Sandy Index). The sampling time related to the preliminary collection of spectral information on plastic surfaces was reduced using information gathered through the Quality Assessment and Cloud Quality bands. The overall accuracies observed were on average higher than 80%,and the low cost of the open data set used, lacking ancillary data, demonstrated the reliability of the 15 proposed method, proving its suitability for environmental and agricultural monitoring over large areas.File | Dimensione | Formato | |
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