DESERT ECOSYSTEM ENGINEERING JOURNAL
Year:2018 | Volume:6 | Issue:17 |Papers Count:6

Introduction Vegetation cover is an important indicator in the arid and semi-arid areas and plays an important role in balancing the ecosystems. Monitoring vegetation cover changes is of great importance because of vegetation effects on the environment. This monitoring provides detailed quantitative and qualitative information. It is therefore important to monitor dynamic changes in vegetation and to investigate the factors that are driving these changes in order to guide regional environmental management. Changes in vegetation could be tracked by satellite time-series data and trend analysis. Analysis of vegetation time series improves considerably our understanding of vegetation annual changes. Touran Biosphere Reserve accommodates three areas of Wildlife Refuge, National Park, and Protected Area. This reserve is the second largest biosphere reserve in the world. In terms of international categories, Touran is a special habitat of steppe grasslands in Central Asia and Desert-Saharas peculiar to West Asia. The aim of this research is to evaluate vegetation trend in Touran Protected Area using MODIS vegetation time series data from 2001 to 2015. . . .

Introduction Assessment of land use spatiotemporal changes provide valuable data for managers to elaborate plans. Land use change modeling is one of the methods used by planers to manage land use changes. Detection of such changes may help decision makers and planners to understand the factors in land use and land cover changes in order to take effective and useful measures. Remote sensing (RS) and geographic information system (GIS) techniques are among the effective tools to detect and assess land use changes. Land cover mapping and change detection have increasingly been recognized as one of the most effective tools for environmental resource management. The latter is recently one of the most widely used techniques to predict land use through the variation of this model. The Markov prediction methods can serve to analyze the dynamic behavior of land use in a time-space pattern to provide forecasts of future changes that can help in making decisions. The present study aims to predict land use changes using Markov chain model in Samal watershed in Bushehr province. . . .

Introduction Today, a significant portion of the water consumption in Iran, especially in the drinking sector, is provided by water resources. Exploitation of groundwater resources requires knowledge of the quantitative and qualitative status of aquifers. By determining the chemical quality of groundwater, an estimate of the health status of these water resources can be obtained and, depending on its state, the type of use is determined. In this regard, direct and indirect methods can be used to understand the qualitative characteristics of water. Direct methods, despite their high precision, require a high size of observational data, involves substantial time and cost. Hence, numerous indirect methods have been developed for simulating natural systems and estimating their parameters using a computer based on complex calculations. The main advantage of these methods is the ability to learn time series and prediction. One of these methods is modeling or hydrological simulation. The modeling of groundwater quality is an important tool for planning and decision-making in the management of water resources. The goal of this research is to identify the ability of intelligent model of Support Vector Machines (SVM), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) for modeling groundwater quality variables (EC, SAR, TDS, and TH) in Gero plain and zoning these variables. Therefore, it can provide an appropriate management tool for controlling quality parameters for drinking and farming. . . .

Introduction Water erosion is one of the most important factors in land degradation in large parts of Iran as it destroys fertile soils and agricultural lands. The impact of soil erosion and related sediments decreases significantly to water quality and reservoir capacity. In semiarid areas like the Menderjan watershed in the west Isfahan province, sheet and rill erosion contributes to the sediment dynamics in a significant way. Particularly, sheet and rill erosion processes and related morphologies and features are very common in this region. Hence, this study is aimed at identifying and quantifying the major erosion process dynamics. Therefore, we applied an integrated approach combining the USPED and RUSLE models with data mining, remote sensing, and GIS methods. . . .

Introduction The attraction model algorithm spatially depends on the neighborhoods of the central pixels that are attracting surrounding sub-pixels. Another possibility is the hypothesis of subpixel interaction as introduced by Mertens et al. (2003) and Atkinson (2005). In order to reach a pixel state with the maximum number of sub-pixels of identical classes neighboring, there are several methods such as genetic algorithms (Mertens et al., 2003) and pixel swapping (Atkinson, 2005) that the techniques use the initial pixel fraction values as a constraint. . . .

Introduction Background and objectives Gully erosion is one of the destructive forms of soil erosions that may lead to a considerable volume of soil loss. This erosion type in addition to on-site and off-site effects has an important role in land degradation and forming in some watersheds. In this regard, due to gully erosion in some provinces of Iran such as Hormozgan, Bushehr, Fars, Khorasan, Semnan, and Zanjan vast agricultural areas are under threat of gully erosion. There are biological and mechanical methods that are available for controlling this type of erosion. One of the most important issues before designing any biological or mechanical practices is knowledge about morphological characteristics of gullies and process of their development. Therefore, this study was planned to assess morphological changes and development of gullies during 1955-2016 years in Idelo watershed in Zanjan Province, Iran. . . .