Agro-ecological evaluation of sustainable area for citrus crop production in Ramsar District, Iran

Citrus growing is regarded as an important cash crop in Ramsar, Iran. Ramsar District has a temperate climate zone, while citrus is a sub-tropical fruit. Few studies on citrus crop in terms of negative environmental factors have been carried out by researchers around the world. This study aims to integrate Geographical Information System (GIS) and Analytical Network Process (ANP) model for determination of citrus suitability zones. This study evaluates the agro-ecological suitability, determine potentials and constraints of the region based on effective criteria using ANP model. ANP model was used to determine suitable, moderate and unsuitable areas based on (i) socio-economic, morphometry and hydro-climate factors using 15 layers based on experts’ opinion; (ii) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite image of the year 2003 with 98.45% overall accuracy, and (iii) developed Multiple Linear Regression (MLR) model for citrus prediction. Thereby, weighted overlay of 15 factors was obtained using GIS. In this study, the citrus orchards map of 2003 and the new map of the citrus areas of 2014 namely Citrus State Development Program (CSDP) of the study area were compared. The results of this study demonstrated: (i) suitable areas (free risk areas) based on negative environmental factors and areas which are susceptible to citrus plantation; (ii) high-risk areas which are unsuitable for citrus plantation, and (iii) the high weights derived by ANP model were assigned to altitude, frost and minimum temperature. The MLR model was successfully developed to predict citrus yield in Ramsar District by 10% error. The MLR model would propose optimum citrus crop production areas. As conclusion, the main outcome of this study could help growers and decision makers to enhance the current citrus management activities for current and future citrus planning

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Comparison of two classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classificatio

Comparison of the Effect of Teaching Methods of Flipped Class and TBL in Enhancing Psychological Empowerment

Introduction: Today, it is felt as necessary to promote the psychological empowerment of individuals, especially at thepostgraduate level using an appropriate educational approach. Therefore, the aim of the current study was to investigate the effect of flipped class (FC) and team-based learning (TBL) in enhancing psychological empowerment.Methods: This semi-experimental study (pretest-posttest model) was conducted on postgraduate students in the Facultyof Medicine. Ninety students were included in the study using census method. After applying the inclusion and exclusioncriteria, forty students were divided into two groups of 20 in a non-random way according to their gender and educational level. The workshop teacher randomly selected one of the groups as a TBL and the other as an FC. A two-day workshop was held for each group (12 hours of training in total). The educational method was TBL in one group and FC in another. Spritzer’s Psychological Empowerment questionnaire was used for data collection in preand post-test (one month apart). This questionnaire includes 12 questions (based on a five-point Likert scale) to assess the 4 aspects of job meaningfulness, feeling to be qualified, feeling to be effective, and feeling to have the freedom of choice. The minimum and maximum scores are 12 and 60, respectively. The experts of the field have confirmed its reliability. Its Cronbach-Alpha values were reported in previous studies at 0.86 and 0.89, respectively. Data were analyzed using statistical tests in SPSS16 and Wilcoxon and Mann-Whitney non-parametric tests.Results: The Mann-Whitney U-test indicated no significant difference between the total mean of the two groups (FC: 35.20±1.73, TBL: 34.30±1.26) in the pre-test (P=0.157). However, there was a significant difference between the psychological empowerment scores of the two groups in the post-test (P0.001).Conclusion: Due to the influence of the TBL technique on psychological empowerment at the postgraduate level, it seems that TBL is more useful and practical for enhancing psychological empowerment

Saffron Response to the Rate of Two Kinds of Potassium Fertilizers

In order to investigate the response of saffron to rate and time of application and two kinds of potassium (K) fertilizers, a factorial experiment was conducted with three factors, including the amount of potassium (0, 20.75, 41.5, 65.25, 83 and 103.75 kg K.ha-1); time of application (annual application of K, and application of cumulative potassium needed for 4 years in the first year; these plots received 415, 332, 249, 166, 83, 0 Kg K.ha-1,respectively in the first year and at other three years not received any K fertilizer); and sources of potassium (K2SO4 and KCl) with three replications in a randomized complete block design in Gonabad agriculture and natural resource research station for 4 years. Results of the first year were not analyzed, because these results not related to fertilizer treatments.Results showed that effect of potassium rate on saffron dry stigma was significant (

Application of artificial neural network in prediction of municipal solid waste generation (case study: Saqqez City in Kurdistan province)

Over the years, the management of municipal solid waste (MSW) has been improved to some extent through installation of various schemes, development of new treatment technologies and implementation of economic instruments. Despite such progress, solid waste problems still impose an increasing pressure on cities and remain one of the major challenges in urban environmental management. Although approximating of waste generation in its management is important, the prediction of its production is a difficult job due to the effect of various factors on it. Artificial intelligence is an exciting and relatively new application of computers. It provides new opportunities for harnessing the scarce and often scattered pieces of valuable knowledge and experience in solid waste management which at present is in the possession of the privileged few. While conventional algorithmic programming replaced much of the sophisticated and repetitive analytical work of the solid waste practitioner, artificial intelligence is poised to take over the no-less important tasks of the ill-structured and lessdeterministic parts of the planning, design and management processes. In this research with application of feed forward artificial neural network, we proposed an appropriate model to predict weight of waste generation in Saqqez city of Iran. For this purpose, we used time series of generated waste of Saqqez which have been arranged weekly, from 2004 to 2007. After performing of the mentioned model, determination coefficient (R ) and mean absolute relative error (MARE) in neural network for test have been achieved to be 2 equal to 0.648 and 2.17% respectively

A GIS-based fuzzy-analytic hierarchy process (F-AHP) for ecotourism suitability decision making: A case study of Babol in Iran

© 2020 Elsevier Ltd Managing ecotourism through appropriate zoning is critical for land use planning. This study is the first to integrate a geographic information system (GIS) with a Fuzzy-Analytic Hierarchy Process (F-AHP) to evaluate the relative importance of physical, natural, environmental, and socio-economic factors for determining the suitability of ecotourism sites. Eleven factors were selected through questionnaire-based surveying of 35 ecotourism and land management experts. F-AHP was applied to weight these factors in order to index and map the suitability of an Iranian case study area for ecotourism using GIS data. A reliable model for the identification of zone suitability was developed which revealed that landform and distance to stream, followed by temperature and elevation were the most important factors for calculating the suitability index. This paper provides useful insights into this novel application of a GIS-based F-AHP for ecotourism planning relevant for policy-makers, planners and practitioners

A GIS-based fuzzy-analytic hierarchy process (F-AHP) for ecotourism suitability decision making: A case study of Babol in Iran

© 2020 Elsevier Ltd Managing ecotourism through appropriate zoning is critical for land use planning. This study is the first to integrate a geographic information system (GIS) with a Fuzzy-Analytic Hierarchy Process (F-AHP) to evaluate the relative importance of physical, natural, environmental, and socio-economic factors for determining the suitability of ecotourism sites. Eleven factors were selected through questionnaire-based surveying of 35 ecotourism and land management experts. F-AHP was applied to weight these factors in order to index and map the suitability of an Iranian case study area for ecotourism using GIS data. A reliable model for the identification of zone suitability was developed which revealed that landform and distance to stream, followed by temperature and elevation were the most important factors for calculating the suitability index. This paper provides useful insights into this novel application of a GIS-based F-AHP for ecotourism planning relevant for policy-makers, planners and practitioners

A GIS-based fuzzy-analytic hierarchy process (F-AHP) for ecotourism suitability decision making: A case study of Babol in Iran

Managing ecotourism through appropriate zoning is critical for land use planning. This study is the first to integrate a geographic information system (GIS) with a Fuzzy-Analytic Hierarchy Process (F-AHP) to evaluate the relative importance of physical, natural, environmental, and socio-economic factors for determining the suitability of ecotourism sites. Eleven factors were selected through questionnaire-based surveying of 35 ecotourism and land management experts. F-AHP was applied to weight these factors in order to index and map the suitability of an Iranian case study area for ecotourism using GIS data. A reliable model for the identification of zone suitability was developed which revealed that landform and distance to stream, followed by temperature and elevation were the most important factors for calculating the suitability index. This paper provides useful insights into this novel application of a GIS-based F-AHP for ecotourism planning relevant for policy-makers, planners and practitioners

Facies analysis and sequence stratigraphy of the Asmari Formation in the northern area of Dezful Embayment, south-west Iran

This paper concerns the sequence stratigraphy of the Oligocene (Rupelian–Chattian)–Early Miocene (Burdigalian) Asmari Formation based on microfacies analysis of the sediments in the Ghale Nar Oilfield, central area of Zagros fold-thrust belt. Fourteen facies types typical for upward shallowing trend from open marine (MF 1–3), to shoal (MF 4-5), semi-restricted and restricted lagoon (MF 6–12) and finally to near-shore lagoon (MF 13-14) depositional environments were identified. Based on the environmental interpretations, we reconstructed a homoclinal ramp mainly represented by its inner and middle sectors. Facies types MF 4–14 are characterized by the occurrence of large and small porcelaneous benthic foraminifera representing a shallow-water setting of an inner ramp influenced by wave and tide processes. MF1 (Pabdeh Formation), and 2 -3 with planktonic, large and small hyaline benthic foraminifera represent between FWWB and SWB. Four third-order depositional sequences were recognized. In this study, in order to better correlate the identified sequences with pre-defined sequences of the Asmari Formation in the Dezful Embayment and the Izeh zone that are chronologically well-defined, we use their number instead of their name. Sequence 2 mainly consists of an open marine environment in the base, followed by semi-restricted to restricted lagoonal facies. Sequences 36 are characterized by semi-restricted to restricted lagoonal facies. Moreover, the regional relative sea-level change curves correlate well with the global sea-level change curves