LAUSR

Although field surveys represent an essential method for determining soil productivity, the use of remote sensing techniques has become a popular option over recent years due to its economic and practical applications. The fundamental basis of this approach is the estimation of soil productivity by using the vegetation indices as an indicator, with reference to the yield. In this study, it is aimed to estimate the productivity potential of the agriculture areas from biomass density in case of limited pedological and parcel-based data. For this purpose, relationships between the FAO Soil Productivity Rating (SPR) and different vegetation indices were investigated. The indices NDVI, RE-OSAVI, and REMCARI were used with Sentinel-2A images. Wheat was selected as an indicator plant to estimate the yield because it is the most occupied (27.47%) cultigen in the field. The study was conducted at the Karacabey State Farm with an area of 87 km2 and is located in Bursa province, Turkey. The research showed a positive relationship between SPR and 2018 yield values (r2 = 0.616). During the tillering period, the r2 for RE-OSAVI was 0.629. In the heading stage, the r2 for NDVI was 0.577. The index REMCARI provided yield estimations with low accuracy coefficient (0.216 ≤ r2 ≤ 0.258) during all vegetation periods. These findings can be interpreted as the monitoring of the land quality with multispectral satellite images via NDVI and RE-OSAVI. In this way, we could decide the time to re-definition of soil properties with land surveys for determination of soil productivity when the detection of a decrease using the indices during some vegetation periods. However, further investigations are needed in controlled trial patterns with differential reference plants, although the findings obtained from the study are promising for the use of spectral vegetation indices to prediction and/or monitoring of soil productivity. Thus, the possibilities of using spectral indices in different ecologies and different plant species can be evaluated from a broad perspective. It was also suggested that Sentinel-2A images may be used for similar studies due to their spectral capabilities with the ESA-SNAP tool.