The Journal "Agriculture and Forestry"
Časopis "Poljoprivreda i šumarstvo"
- Since 1955 -
Year 2022, Volume 68 Issue 2 (30.06.2022)
| Year : | 2022 |
| Volume : | 68 |
| Issue : | 2 (30.06.2022) |
| Authors : | Mihai Valentin HERBEI, Radu BERTICI , Florin SALA |
| Title : | THE USE OF REMOTE SENSING IMAGES IN ORDER TO CHARACTERIZE THE SOIL AGROCHEMICAL INDEXES IN RELATION TO THE AGRICULTURAL CROPS |
| Abstract : | The present study evaluated the interdependence relationship between agrochemical soil indexes, agricultural crops, NDVI and SAVI indices, respectively Red Edge band, based on RapidEye remote sensing images. The NDVI, SAVI, and Red Edge were used to characterize the crops. Agrochemical indices of pH, humus (H), saturation in bases (V), nitrogen index (NI), phosphorus (P) and potassium (K) content, were used for the soil characterization. Kendall's correlation analysis revealed a very strong correlation between P and Red Edge (r = -0.905), moderate correlations between P and NDVI respectively SAVI (r = 0.619), and weak correlations between K and Red Edge (r = -0.524). The regression analysis facilitated the achievement of 2nd degree polynomial equations for the P prediction based on NDVI under the conditions of R2= 0.724, p <0.01, the P prediction based on SAVI under conditions of R2= 0.718, p <0.01, respectively P prediction based on Red Edge, under conditions of R2= 0.985, p <<0.001. Prediction of K was possible based on NDVI, under the conditions of R2= 0.774, based on SAVI under the conditions of R2= 0.768, and respectively based on Red Edge under condition of R2= 0.889. For the other agrochemical indices, the predictive relations in condition of low statistical safety were obtained (e.g. for pH based on Red Edge, R2= 0.696; for H based on Red Edge, R2= 0.538). For all agrochemicals, the safety predictions achieved through regression analysis were higher based on the Red Edge band compared to NDVI or SAVI indices. |
| For citation : | Herbei, M.V., Bertici R., Sala F. (2022). The use of remote sensing images in order to characterize the soil agrochemical indexes in relation to the agricultural crops. Agriculture and Forestry, 68 (2): 23-33. doi:10.17707/AgricultForest.68.2.02 |
| Keywords : | agrochemical indices, NDVI, prediction model, Red Edge, SAVI, soil |
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