Determination of Optimum Geo-Morphometric Parameters to Digital Soil Map (Case Study: Tehran Province, Iran)

Introduction: Todays, geo-morphometric parameters named as environmental co-variates are used to digital soil maps, so that using these data, the results of soil tests are generalized to similar areas. For this object, finding the suitable environmental variables is of special importance. Since understanding changes in land surface processes requires comprehensive identification of the environmental variables present in it (Bishop et al., 2012), and these changes are mainly due to changes in morphology, structure, composition, passage of time, and human activities (Bishop et al., 2003), and considering the importance of selecting appropriate environmental variables to increase the accuracy in preparing a digital map using a geographic information system, this research seeks to identify and introduce these appropriate environmental variables based on data analysis and reliable statistical tests, so that digital maps with the desired accuracy can be prepared in the geographical area of Tehran province.
Materials and Methods: In addition, other researchers' use of the results of this study and the environmental variables introduced in it will result in the use of the same initial variables in the preparation of different digital maps, and as a result, there will be a better possibility of comparison between different digital maps. The importance of this study is that the study of these factors is important and significant, and research results in this field have not been published before in Tehran province, so they can be used by other researchers to prepare digital maps in future studies. The objective of this study was to determine the appropriate environmental data that can be used to a digital soil map of Tehran province. Data were processed and 49 environmental data were statistically analyzed included Digital Elevation Model, Analytical Hillshading, Landforms, Texture, Flow Accumulation, Protection Index, Clusters, Cross-Sectional Curvature, Longitudinal Curvature, LS Factor, Vertical Distance to Channel Network, Topographic Wetness Index, Channel Network Base Level, Valley Depth, Catchment Slope, Slope, Relative Slope Position, Drainage Basins, Closed Depression, Slope Aspect, Convergence Index, Channel Length, Multi-resolution Valley Bottom Flatness Index, Multi-resolution index of ridge top flatness, Modified Catchment Area, Output, Variance, Sunset, Sunrise, Day Length, Bands Sensor, Salinity Index, Gypsum Index, Brightness Index, Carbonate Index, Clay Index, Normalized Difference Vegetation Index. These environmental covariates were statistically analyzed and the values with the highest R², CV and the lowest RMSE were evaluated as favorable environmental data. Based on these results, bands 2, 3, 4 and 8 were introduced as the best bands of Landsat 8 satellite images to evaluate environmental covariates. The selection of environmental data is of special importance in the preparation of digital maps by co-kriging method, on this basis, in this study, the identification of suitable environmental data for the preparation of digital soil maps in Tehran province was targeted.
Results and Discussion: Based on the results of the present study, out of 49 environmental data reviewed, based on statistical analysis, 14 favorable environmental data were selected. Thus, it is concluded that in preparing a digital soil map, to ensure the accuracy of generalization of laboratory measurement results of soil samples to similar areas, DEM, Slope, CNBL, VDCN, Landforms, Texture, Valley Depth can be used, Convergence Index, MRVBF, MRRTF, TWI, Drainage Basins, Channel and Brightness Index were used as desirable auxiliary data in soil studies in the geographical area of Tehran province. This study showed consistency with previous studies in this field regarding correlation coefficients (Zeinali et al., 2016) and (Darstani Farahani et al., 2016).
Conclusion: In another study, bands 1 to 5 and 7 of the TM sensor were found to be suitable for preparing soil salinity maps, which was consistent with the results of this study (Zeinali et al., 2016).The results of these study use to future soil research.

These environmental covariates were statistically analyzed and the values with the highest R2, CV and the lowest RMSE were evaluated as favorable environmental data. Based on these results, bands 2, 3, 4 and 8 were introduced as the best bands of Landsat 8 satellite images to evaluate environmental covariates. The selection of environmental data is of special importance in the preparation of digital maps by co-kriging method, on this basis, in this study, the identification of suitable environmental data for the preparation of digital soil maps in Tehran province was targeted. Based on the results of the present study, out of 49 environmental data reviewed, based on statistical analysis, 14 favorable environmental data were selected. Thus, it is concluded that in preparing a digital soil map, to ensure the accuracy of generalization of laboratory measurement results of soil samples to similar areas, DEM, Slope, CNBL, VDCN, Landforms, Texture, Valley Depth can be used. , Convergence Index, MRVBF, MRRTF, TWI, Drainage Basins, Channel and Brightness Index were used as desirable auxiliary data in soil studies in the geographical area of Tehran province. This study showed consistency with previous studies in this field regarding correlation coefficients (Zeinali et al. 2016) and (Darstani Farahani et al. 2016). In another study, bands 1 to 5 and 7 of the TM sensor were found to be suitable for preparing soil salinity maps, which was consistent with the results of this study (Zeinali et al. 2016).The results of these study use to future soil research.