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Displaying 36 - 40 of 661GIS-based forest fire susceptibility mapping in Iran: a comparison between evidential belief function and binary logistic regression models
The aim of this research was to produce forest fire susceptibility maps (FFSM) based on evidential belief function (EBF) and binary logistic regression (BLR) models in the Minudasht Forests, Golestan Province, Iran. At first, 151 forest fire locations were identified from Moderate-Resolution Imaging Spectero Radiometer data, extensive field surveys, and some reports (collected in year 2010). Out of these locations, 106 (70%) were randomly selected as training data and the remaining 45 (30%) cases were used for the validation goals.
Assessment of SAR speckle filters in the context of object-based image analysis
The initial step in most object-based classification methodologies is the application of a segmentation algorithm to define objects. In the context of synthetic aperture radar (SAR) image analysis, the presence of speckle noise might hamper the segmentation quality. The aim of this study is to assess the segmentation performance of SAR images when no filter or different filters are applied before segmentation.
Predicting ESP and SAR by artificial neural network and regression models using soil pH and EC data (Miankangi Region, Sistan and Baluchestan Province, Iran)
Monitoring exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR) variability in soils is both time-consuming and expensive. However, in order to estimate the amounts of amendments and land management, it is essential to know ESP and SAR variations and values in sodic or saline and sodic soils. Thus, presenting a method which uses easily obtained indices to estimate ESP and SAR indirectly is more optimal and economical. Input data of the current research were 189 soil samples collected based on a regular networking approach from Miankangi region, Sistan plain, Iran.
Development of a land suitability model for saffron (Crocus sativus L.) cultivation in Khost Province of Afghanistan using GIS and AHP techniques
In this study, we have attempted to develop a land suitability model for saffron, an agronomic crop, which is economically viable, environmentally bearable and socially equitable at Khost Province of Afghanistan. The objective was to determine different land suitability classes for saffron cultivation using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). A decision tree was developed encompassing the physical, economic and social criteria.
Agroecology territories: places for sustainable agricultural and food systems and biodiversity conservation
The development of sustainable agricultural and food systems is of significant importance considering the still-growing world population. For this, it is imperative to consider not only quantitative production issues, but also environmental issues such as water pollution, biodiversity loss, and land degradation as well as social and economic issues such as organization of supply chains and communication and coordination among stakeholders.