Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Effect of Thiobacillus, sulfur, and vermicompost on the water-soluble phosphorus of hard rock phosphate.

Sulfur, organic matter, and inoculation with sulfur-oxidizing bacteria are considered as amendments to increase the availability of phosphorus from rock phosphate. The present study was conducted to evaluate the best combination of sulfur, vermicompost, and Thiobacillus thiooxidans inoculation with rock phosphate from Yazd province for direct application to agricultural lands in Iran. For such study, an experiment was carried out in a completely randomized design with factorial arrangement: Elemental sulfur originated from Sarakhs mine at three rates, 0% (S1), 10% (S2), 20% (S3), vermicompost at two rates, 0% (V1), 15% (V2), and inoculation without (B1) and with (B2) T. thiooxidans, in three replications. The results showed that water-soluble phosphorus (WSP) content was significantly higher in inoculated treatments compared to non-inoculated treatments. Sulfur had a significant effect on WSP. The highest solubility rate of rock phosphate was obtained in 20% of sulfur (S3) treatments and it was 2.4 times more than S1 treatments. Vermicompost also had a significant and positive effect on WSP of rock phosphate dissolution. The results also revealed that the highest concentration of WSP, sulfate and the lowest pH were obtained in treatments with 20% sulfur, 15% vermicompost inoculated with T. thiooxidans (B2S3V2).