This review has identified research gaps that need filling. In Iran, coherent national scale DSM with consistent methodology is needed to update legacy soil maps, and to apply DSM in forestlands, hillslopes, deserts, and mountainous regions which have largely been ignored in recent DSM studies.
The results of the study of soil quality changes can be used in land evaluation, environmental studies and integrated planning and management in order to properly and reasonably utilize natural resources and reduce future soil degradation.
The results of the study of soil quality changes can be used in land evaluation, environmental studies and integrated planning and management in order to properly and reasonably utilize natural resources and reduce future soil degradation.
Most common machine learning algorithms usually work well on balanced training sets, that is, datasets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as a class imbalance problem in machine learning and datasets that do not meet this criterion are referred to as imbalanced data.
Most common machine learning algorithms usually work well on balanced training sets, that is, datasets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as a class imbalance problem in machine learning and datasets that do not meet this criterion are referred to as imbalanced data.
This study shows that ML algorithms can be successfully used for mapping SOC and their uncertainty at a large scale in western Iran where there is a wide range in climate, land use and terrain attributes. The procedural structure permits enhancement of the DSM process without loss of performance, selecting only the most important variables and the best model.
This study shows that ML algorithms can be successfully used for mapping SOC and their uncertainty at a large scale in western Iran where there is a wide range in climate, land use and terrain attributes. The procedural structure permits enhancement of the DSM process without loss of performance, selecting only the most important variables and the best model.
The trend of salinity changes in the study region increases from the east to west, which is consistent with the trends of changes in the most important auxiliary variables identified. These changes are probably due to more sediment in the western areas. Also, the convex shape of the study area can help to move the groundwater eastward to the west.
The trend of salinity changes in the study region increases from the east to west, which is consistent with the trends of changes in the most important auxiliary variables identified. These changes are probably due to more sediment in the western areas. Also, the convex shape of the study area can help to move the groundwater eastward to the west.
Soil salinization is an important threat for agriculture and environment in the eastern coast of Urmia hyper saline Lake. Predicting soil salinization requires rapid and low-cost measurement tools of soil salinity. It is hypothesized that remote sensing and visible near-infrared spectroscopy may offer a feasible method for that purpose.