Elham Mehrabi Gohari; Roghaye Shahriyaripour; Ahmad Tajabadipoor; Seyed Roohollah Mousavi
Abstract
This study aims to evaluate and compare the efficiency of Artificial Neural Network (ANN), Regression Tree (RT) and Neuro-Fuzzy (ANFIS) models using a digital soil mapping framework to predict soil texture in a part of Sirjan province. Sampling was carried out at 84 observation points with a regular ...
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This study aims to evaluate and compare the efficiency of Artificial Neural Network (ANN), Regression Tree (RT) and Neuro-Fuzzy (ANFIS) models using a digital soil mapping framework to predict soil texture in a part of Sirjan province. Sampling was carried out at 84 observation points with a regular grid of 2x2 km, and soil texture components were determined from the soil surface depth of 0 to 30 cm. Auxiliary variables included primary and secondary derivatives of the digital elevation model (DEM), a geomorphological map and remote sensing (RS) spectral indices. The appropriate variables selected using the Principal Component Analysis (PCA) feature selection method. Based on PCA, eight topographic variables and six vegetation indices and spectra from RS selected to predict soil texture components (sand, silt and clay). The efficiency of the models was evaluated using coefficient of determination (R2), mean error (ME), root mean square error (RMSE) and normalised root mean square error (nRMSE). The RMSE values in the neuro-fuzzy model compared with the regression tree model. The results of the neuro-fuzzy model were 1.43% for clay, 1.98% for sand and 2.1% for silt, which were 4.32%, 5% and 4.54% lower respectively compared to the regression tree model. The results of this study showed that the ANFIS model was more accurate in predicting clay, silt and sand compared to ANN and RT. Also, the geomorphology map, topographic wetness index, multi-resolution valley bottumn flatness index and Landsat 8 bands 5 and 6 had the highest relative importance in predicting soil texture components.
Asghar Rahmani; Fereydoon Sarmadian; Sayed Roholla Mousavi; Seyyed Erfan Khamoshi
Abstract
Conventional soil mapping is related to High density sampling, affected by scale and expert knowledge So using of new data mining methods in digital soil properties mapping was the main aim of this study for resolving conventional soil survey problems. In this research, 62 surface soil samples based ...
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Conventional soil mapping is related to High density sampling, affected by scale and expert knowledge So using of new data mining methods in digital soil properties mapping was the main aim of this study for resolving conventional soil survey problems. In this research, 62 surface soil samples based on regular grid and expert knowledge opinion were selected after that soil organic carbon(SOC), clay content and CaCO3 were determined in some part of Dryland Kuhin region with area of 372 ha. Data sets were divided to two 80%(calibration) and 20%(validation), respectively. From digital elevation model with 10-meter spatial resolution were derived 19 geomorphometric attribute in SAGA GIS software. Three geomorphometric covariate included TPI, TRI, DEM and landform map unit were chosen PCA and expert knowledge. RStudio and SoLIM Solution software were used for random forest (RF) and fuzzy logic modelling, respectively. The RF modelling results show that for SOC, clay and CaCO3 based on determination coefficient (R2) had 0.63,0.75,0.63 and RMSE 0.17,7.5,5.77 percentage and for SoLIM method revealed that R2 0.47,0.42,0.42 and RMSE 0.2,8.08,4.68 percentage, respectively. Generally, the RF model with creating nonlinear relationship among soil properties and environmental covariate can predicted digital map with appropriate precision for management and sustainable land utilization
khaled Hajimaleki; rouhollah mousavi; Manochehr Gorji; Fereidon Sarmadian
Abstract
Nowadays, the importance of soil conservation in agriculture and natural resources, with the goal of preventing its deterioration and degradation are necessary. Soil and land degradation as a direct cause of the threat to the global environment and human welfare is evident. In this study soil degradation ...
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Nowadays, the importance of soil conservation in agriculture and natural resources, with the goal of preventing its deterioration and degradation are necessary. Soil and land degradation as a direct cause of the threat to the global environment and human welfare is evident. In this study soil degradation mapping was carried out in East Qazvin. Soil map using geopedological method by integration of information layer of lithology, geomorphic and pedogenic was prepared in ArcGIS9.3 software. Data from soil maps with field studies was used as input in GLASOD model and the soil degradation map was prepared. In this study soil map units was used as basis of soil degradation status investigating in the region. Results showed that less than 25% of the study area has a low degree of degradation and in the present circumstances do not require specific management actions, but in other parts of the region, with various degrees of soil degradation was observed. Soil chemical properties degradation include decrease of soil organic matter, loss of soil nutrients and soil salinity are the most important aspects affecting on soil degradation of region. At total of 16,630 hectares of land, about 4028 ,5987, 5128 and 866 respectively low, middle, high and very high soil degradation class are located. Thus according to the results to prevent the spread of this process in this area, management actions is recommended.
Zohreh Alijani; Fereydoun Sarmadian; Seyed Rouhollah Mousavi
Abstract
Today, extensive improvements in fields of soil mapping have increased the purity and accuracy ofsoil maps. Usual mapping methods moreover depend on skills and experience of surveyor inidentifying and delineating the boundaries, also need the high cost and time consuming that face thesoil mapping with ...
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Today, extensive improvements in fields of soil mapping have increased the purity and accuracy ofsoil maps. Usual mapping methods moreover depend on skills and experience of surveyor inidentifying and delineating the boundaries, also need the high cost and time consuming that face thesoil mapping with restrictions. In this study, aerial photographs with 1/40000 scale were used in orderto preparation of the initial interpretive map and determination of sample region. Then, the numbers of24 profiles were described in determined units. After sampling and necessary physicochemical tests,soil map of Kouhin (Qazvin) was prepared and accuracy of map was calculated in two methods in alllevels of taxonomy. The first method was formation of error matrix and calculation of kappa index andsecond was comparison the geopedological map with described profiles and evaluation the results ofeach. Then a part of a geopedological map that had overlapping with map prepared by usual methodwas compared with this map. Results showed the overall accuracy of 67.5, 90.5 and 98.5 percent inlevels of family- subgroup and great group- suborder and order of soil for geopedological methodrespectively.
