Monitoring and evaluation of vegetation indices based on Fuzzy Logic using MODIS satellite (Case study: Bamou National park-Shiraz)

Desertification means land degradation in arid, semi-arid and dry sub-humid in result of climate variability and human-activity. Desertification is the third major challenge for international community in twenty-first century after the twin challenges of climate change and scarcity of fresh water.In fact, desertification, ecological and environmental issues worldwide is an effective way to treat it is monitoring the situation and highly variable factors affecting this phenomenon. This phenomenon has been raised as one of the most striking aspect of environmental degradation and destruction of natural resources in the world.Desertificationeffecting on vegetation cover, water and soil is a serious factor threatening national parks in arid and semi-arid regions of Iran.Applicable process related to desertification control must be based on knowledge of the current state of desertification and it`s intensity.The aim of this study was to evaluate and monitor desertification by using vegetation indices (NDVI and EVI) extracted from MODIS satellite images and classification of desertification by using fuzzy logic.
Material and The study area covers an area with about 47,244 hectares, which has been named as a National Park Bamou.The height distribution of Bamou National Park shows that most of the area is locatedbetween 1700 and 1900 meters altitude and a maximum height of the study area is 2700 meters above sea level.The average annual rainfall in the main station area represents the Shiraz station, the392.9 mm and a mean annual temperature of 17.9 °C.Based on Domarten developed method, Bamou National Park has a semi-arid climate is cold with winter rains. In this researchfor monitoring and evaluating desertification of Shiraz- Bamou national park, the annual changes in vegetation cover were studied during the period of 2000 - 2014. On the other hand this paper tries to monitor desertification changedusing long term-time series analysis of satellite data and vegetation cover indices (EVI & NDVI).Therefore, in this study, profile and map of annual changes were prepared on IDRISI Selva and then analyzed using the MOD13A1product, MODIS sensor, Terra satellite and Aqua system. Finally, using fuzzy logic, profile and desertification intensity map were prepared for 2000-2014.Finally, according to the climatic conditions of the region and based on expert opinion the value of fuzzy classes index changes, the software IDRIDIselva and Arc GIS 10.2 severity of desertification on each indicator based on fuzzy logic was prepared.
Results and Dissociation: Based on the results of EVI & NDVI vegetation destruction of desertification intensity have been more in the north west of the study area.The reason on this destruction and desertification is construction of the new city of Sadra in part of North West and west of this park. It can be said that this degradation is a new form of desertification entitled anthropogenic desertification.So that the construction of Sadra city in the western area of the park, protective of this part is impossible.The results show that EVI is more sensitive than NDVI for monitoring parameters such as canopy cover, leaf area index, canopy structure, phenology and stress plants, since only the NDVI Claro makes obvious elephant in plants. The EVI index due to greater sensitivity to changes in areas with high biomass (vegetation growth season) and mitigate the effects of atmospheric conditions on vegetation index values is more applicable to monitor vegetation changes than NDVI.This paper introduce fuzzy logicas one of the methods for classifying the severity of desertification. Fuzzy logic can be used to determine the boundaries of class and privilege of desertification indicators and explain the process. Fuzzy sets or classes of fuzzy are no sharply defined boundaries and membership or non- membership of a place in a particular.The severity of desertification in the form of fuzzy maps based on each availableindicators provided the values between 0 and 1 as that classes of desertificationon the map.It can be concluded that for better management of desertification it is necessary to prioritize areas affected by desertification according to its severity.As a result, we can say that accurate desertification classification can be helped to manage this phenomenon. In fact it is a set of unpleasant consequences that human environment brings. Hence, monitoring and evaluation of the severity of desertification and mapping always isas one of the most important management and planning tools to achieve sustainable development in the field of natural resources.