Spatial Variations of Vegetation Index from Remote Sensing Linked to Soil Colloidal Status

Marco Bascietto, Enrico Santangelo and Claudio Beni
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Marco Bascietto: Consiglio per la Ricerca in Agricoltura e L’analisi dell’Economia Agraria (CREA)-Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, CREA-IT, via della Pascolare 16, 00015 Monterotondo, Italy
Enrico Santangelo: Consiglio per la Ricerca in Agricoltura e L’analisi dell’Economia Agraria (CREA)-Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, CREA-IT, via della Pascolare 16, 00015 Monterotondo, Italy
Claudio Beni: Consiglio per la Ricerca in Agricoltura e L’analisi dell’Economia Agraria (CREA)-Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, CREA-IT, via della Pascolare 16, 00015 Monterotondo, Italy

Land, 2021, vol. 10, issue 1, 1-15

Abstract: Recent decades have seen a progressive degradation of soils owing to an intensification of farming practices (weeding and high trafficking), increasing use of pesticides and fertilizers, mainly nitrogen, resulting in a steady decline in soil organic matter, a key component to maintain soil fertility. The work has coupled the normalized difference vegetation index (NDVI) of wheat cultivation in Central Italy to soil properties where the wheat was grown to identify the properties linked to within-field variability in productivity. NDVI was assessed through Copernicus Sentinel-2 (S-2) data during the wheat anthesis phase. The main outcome showed a significant correlation of NDVI variability to soil colloidal status and to the relative quantity in the exchange complex of the Ca 2 + ions. No relationship emerged between NDVI and soil macronutrients (nitrogen, phosphorus, and potassium) concentration. The work suggested that such elements (nitrogen, especially) should not be provided solely considering the vegetation index spatial variations. Rational and sustainable management of soil fertility requires the integration of the NDVI data with the whole complex of soil physical/chemical status. In this way, the identification of the real key factors of fertility will avoid the negative impact of overfertilization. As an example, a fertilization plan was simulated for the sunflower–wheat sequence. The results showed that in the study area additional supplies of N and K would be unnecessary.

Keywords: remote sensing; soil degradation; vegetation index; colloid index; fertilization; nitrogen; phosphorus; potassium; calcium (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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