Showing 4 results for Entropy
Sahar Darabi Shahmari, Amir Saffari,
Volume 6, Issue 2 (9-2019)
Abstract
Landslide susceptibility mapping is essential for land use planning and decision-making especially in the mountainous areas. The main objective of this study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran using two statistical models such as an index of entropy and Logistic Regression and to compare the obtained results. At the first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and lithology were extracted from the spatial database. Using these factors, landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use planning in the Dalahoo basin, Iran.
Dr Abdolmajid Ahmadi, ,
Volume 10, Issue 1 (5-2023)
Abstract
Extended abstract
Landslide risk zoning is one of the basic measures to deal with and reduce the effects of landslides. Vernesara watershed is one of the areas where many landslides have been observed in different parts of it. In this research, in order to zone the risk of landslides using the entropy index, first the ranges of landslides were determined, then the effective factors in the occurrence of range movements were prepared in the ArcGIS software environment, and a landslide susceptibility map of the studied area was prepared. . The prioritization of effective factors using Shannon's entropy index showed that the slope layers, land use, surface curvature, topographic humidity index and topographic position index had the greatest effect on the occurrence of landslides in the region. Also, zoning landslide sensitivity with the mentioned model and evaluating its accuracy using the ROC curve shows the very good accuracy of the model (79.6 percent) with a standard deviation of 0.0228 for the studied area. The zoning map shows that the low-risk areas cover only 13% of the area and more than 56% of the area is in the area with high risk of landslides, which indicates the high potential of the area in the occurrence of landslides. . Construction at a distance from fault lines, waterways and the steep Asmari Formation and safety of communication routes are the most important measures to reduce the amount of damage caused by landslides in Vernesara watershed.
Key words: natural hazards, landslide, entropy, folded Zagros.
Nazanin Salimi , Marzban Faramarzi, Dr Mohsen Tavakoli, Dr Hasan Fathizad,
Volume 10, Issue 3 (9-2023)
Abstract
In recent years, groundwater discharge is more than recharge, resulting in a drop-down in groundwater levels. Rangeland and forest are considered the main recharge areas of groundwater, while the most uses of these resources are done in agricultural areas. The main goal of this research is to use machine learning algorithms including random forest and Shannon's entropy function to model groundwater resources in a semi-arid rangeland in western Iran. Therefore, the layers of slope degree, slope aspect, elevation, distance from the fault, the shape of the slope, distance from the waterway, distance from the road, rainfall, lithology, and land use were prepared. After determining the weight of the parameters using Shannon's entropy function and then determining their classes, the final map of the areas with the potential of groundwater resources was modeled from the combination of the weight of the parameters and their classes. In addition, R 3.5.1 software and the randomForest package were used to run the random forest (RF) model. In this research, k-fold cross-validation was used to validate the models. Moreover, the statistical indices of MAE, RMSE, and R2 were used to evaluate the efficiency of the RF model and Shannon's entropy for finding the potential of underground water resources. The results showed that the RF model with accuracy (RMSE: 3.41, MAE: 2.85, R² = 0.825) has higher accuracy than Shannon's entropy model with accuracy (R² = 0.727, RMSE: 4.36, MAE: 3.34). The findings of the random forest model showed that most of the studied area has medium potential (26954.2 ha) and a very small area (205.61 ha) has no groundwater potential. On the other hand, the results of Shannon's entropy model showed that most of the studied area has medium potential (24633.05 ha) and a very small area (1502.1 ha) has no groundwater potential.
Shamsollah Asgari, Kourosh Shirani,
Volume 11, Issue 2 (8-2024)
Abstract
Gully erosion is one of the advanced forms of soil erosion, which needs to be analyzed and identified in order to protect the soil. In this research, according to the complex system of factors influencing the creation of ditch erosion, 23 factors were analyzed in the two famous Dempster-Schiffer models and the entropy model, and using Google Earth images and field visits, 331 ditch points were identified, recorded, and a ditch distribution map was prepared. Spatial data of gully erosion distribution were divided into two random training (70%) and experimental (30%) groups. In this research, two indicators of tolerance coefficient and variance inflation factor were used to check the collinearity test, and as a result, two indicators of waterway density and relative humidity index were removed and 21 factors were used in the modeling process. The output results of the layers, weighting and classification and integration in two Dempster-Schiffer and entropy models are the extraction of the zoning map of the gully's erodibility sensitivity. and 30% of the calibration and validation of the models, the area under the ROC system performance characteristic curve and the area under the AUC diagram of the Dempster-Schiffer model with an explanation factor of 0.934 and the maximum entropy model with an explanation factor of 0.936, both models have an acceptable percentage of the area under the curve were that this issue shows the high performance of both models in the region. Among other results of statistical analysis, the prioritization of the impact of 21 factors in causing ditch erosion in the region was determined. The scientific results of the research can be promoted and taught, and from the practical point of view, the relevant executive body to control ditch erosion can take the necessary measures using the results of this research.
