International Journal of Sustainable Agricultural Management and Informatics (7 papers in press)
Remote Sensing in Water Balance Modelling for Evapotranspiration at a Rural Watershed in Central Greece
by Nicolas Dalezios, Nicholas Dercas, Anna Blanta, Ioannis Faraslis
Abstract: There is an increasing trend in water balance modelling for remote sensing tools, which provide distributed information of watershed features. The papers objective consists of exploring the remote sensing potential for evapotranspiration estimation in water balance modelling of a small rural watershed with limited data, namely Portaikos rural mountainous watershed of 132 km2 in Thessaly, Greece. Three water balance models with small number of parameters are used, namely Abulohoms, GR2M and Xiong-Guo model, respectively. Two approaches are considered. At first, monthly potential evapotranspiration derived from conventional meteorological data is used as input to the models. Second, air temperature is derived from land surface temperature (LST) of NOAA/AVHRR satellite images for monthly evapotranspiration estimation. Time series of the above parameters for 13 years (1981-1993) are used. The remote sensing potential for evapotranspiration estimation is assessed by comparing the observed and simulated monthly runoff at the output of Portaikos watershed. Four error statistics are used for validation. The results are considered quite satisfactory for the four error statistics. The GR2M shows relatively better performance than the other models for all the error statistics, as well as for the satellite-based approach, which shows slightly better performance than the conventional approach.
Keywords: Remote sensing; water balance models; rural watershed; evapotranspiration; satellites; water resources management.
Residents concerns and attitudes towards policies and strategies of solid waste management facilities
by Stilianos Tampakis, Veronica Andrea, Paraskevi Karanikola, Despina Sidi
Abstract: The current study examines the concerns and attitudes of the residents in the Municipality of Lagadas, Greece and in particular the gateway community of Mavrorachi Sanitary Landfill (MSL) and it offers a general understanding of public perceptions regarding sanitary landfills and waste management issues from the residents point of view. The results of the present study indicate that there is a low acceptance for the MSL and also NIMB phenomena are spotted, while there is a positive view concerning financial issues and employment in a local level. The case study can be used as a valid tool in the planning, design and management of waste management facilities and especially for sanitary landfills, in areas all around the world facing similar challenges such as lack of space and NIMB phenomena.
Keywords: sanitary landfill; acceptability of a solid waste management facility; illegal dumpsites; quality of life; strategies and policies; means of information; NIMB.
A Hybrid Framework for detection of diseases in Apple and Tomato crops with Deep Feed Forward Neural Network
by Praneetha Rajupalepu, Vektatramaphanikumar Sistla, Venkata Krishna Kishore Kolli
Abstract: The traditional farming methods with low productivity and crop damage due to diseases have resulted in low economic growth of the farmer. To overcome this problem, an expert system capable of monitoring the crop growth and early detection of the diseases is highly essential for the farmer to take preventive steps. In this work, image processing and soft computing techniques were used to detect the diseases well in advance. First, a hybrid image enhancement technique was developed by fusion of threshold-based and principle component analysis colour enhancement techniques. Then the enhanced images were divided into three individual color channels (Red, Green, Blue) and then 27 statistical features comprising of texture, color and energy were computed from the individual channels. The same statistical features of the first-level wavelet decomposition were then appended to those 81 features. Finally, the features were classified by the deep feed forward neural network to identify the disease type. Performance evaluation of the method was validated on tomato and apple datasets. The proposed method outperformed the existing methods by yielding 94.06% true positive rate on tomato dataset and achieved 96.78% true positive rate on apple dataset.
Keywords: Precision Agriculture; Principle Component Analysis; Statistical features; Deep feed forward neural network; Wavelets; etc.
Special Issue on: ICDSST & PROMETHEE DAYS 2018 Sustainable Approaches with MCDA Methods in Agri-Environment Policies
Mapping Soil Erosion Potential Zones with a Geo-Spatial Application of Multi Criteria Evaluation Technique Model in Highlands of Ethiopia
by Afera Halefom, Asirat Teshome, Ermias Sisay, Biruk Shewayirga, Mihret Dananto
Abstract: Soil erosion is considered one of the major problems affecting soil quality and water resources. Erosion and soil degradation increase significantly due to irregular and undulating topography, which is a serious problem of loss of fertile soils each year. Based on GIS with the integration of the MCE analysis, an attempt was made to combine a set of factors such as Slope, Topographic Wetness Index, Aspect, Stream Power Index, Elevation and Curvature to have a fruitful decision to fulfill to the stated objective in Megech Watershed. Out of the total watershed area (525.594 km2): 0.004 km2 (0.001%), 34.210 km2 (6.509%), 353.195 km2 (67.205%), 138.007 km2 (26.260%) and 0.132 km2 (0.025%) areas are very high, High, Medium, Low and Very low prone to soil erosion respectively. Therefore, for minimizing soil erosion problems in Megech watershed, biological and physical measurements of soil and water conservation techniques should be conducted.
Keywords: Erosion; Megech; MCE; GIS; Raster calculator; Susceptibility mapping.
Decision Making under the scope of Forest Policy: Sustainable Agroforestry Systems in Less Favoured Areas
by Stefanos Tsiaras, Jason Papathanasiou
Abstract: The aim of the paper is to apply Multiple Criteria Decision Analysis in order to propose suitable agroforestry systems as a sustainable choice for the forestation of abandoned agricultural land in a mountainous, less favoured area. The promotion of regional development through the increase of wooded land is a strategic target of Forest Policy in the European Union. MCDA was used for the selection of the most suitable agroforestry system taking into consideration all three pillars of sustainability: environment, society and economy. Fourteen agroforestry systems well adapted in the study area were analyzed with the PROMETHEE method under six criteria: cost, expected revenue, working hours, waiting period for the first yield, water demands and fertilizers. According to the results, the most suitable agroforestry system for the study area is the combination of pomegranate with medick. The findings could be useful in Forest Policy planning, contributing to the forestation of less favoured areas in Greece.
Keywords: Multiple Criteria Decision Analysis; Policy Making; Regional Development; Agroforestry; sustainability; PROMETHEE.
Towards a computer-based Decision Support System for aquaculture stakeholders in Greece in the context of climate change
by Orestis Stavrakidis-Zachou, Nikos Papandroulakis, Astrid Sturm, Panagiotis Anastasiadis, Frank Wätzold, Konstadia Lika
Abstract: Climate change constitutes an increasing concern for aquaculture. The uncertainty surrounding the future implications of this phenomenon coupled with the financial importance of the sector necessitate the development of appropriate frameworks and tools that can support management decisions and ensure the sustainability of future aquaculture production. Facilitated by emerging information technologies, Decision Support Systems (DSS) are becoming increasingly popular in sectors of primary production and deal with various aspects of decision-making from the operational to the strategic level. In this paper we present ongoing work, in the frame of the EU-ClimeFish project, towards the development of a computer-based DSS that simulates and visualizes the impacts of different climate change scenarios on Greek aquaculture, including economic impacts. The description contains details on the structure, constituent models, and current status of implementation of the DSS. The applicability of the generated tool in decision-making is discussed and planning for further development is outlined.
Keywords: Climate change; aquaculture; ClimeFish; DSS; European sea bass; DEB model; economic model;.
Building theory of agri-food supply chain resilience using Total Interpretive Structural Modelling and MICMAC analysis
by Guoqing Zhao, Shaofeng Liu, Carmen Lopez, Haiyan Lu, Sebastian Elgueta
Abstract: Agri-food supply chains are inherent with some unique characteristics and that can be easily disrupted compared with other supply chains. Therefore, supply chain resilience factors are relevant and can be taken into consideration. In this paper an attempt has been made to build a theoretical framework of resilience factors in agri-food supply chains with the help of Total Interpretive Structural Modelling and Matrix of Cross Impact Multiplications Applied to Classification analysis. The results of the total interpretive structural modelling demonstrate that leadership plays a vital role in enhancing the resilience of the agri-food supply chain. Furthermore, the matrix of cross impact multiplications applied to classification analysis results indicate that leadership and working team stability along with strong driving power should be given critical focus by agri-food supply chain managers to facilitate the improvement of agri-food supply chain resilience. This paper contributes to the extant theory building in the field of agri-food supply chain resilience, to fill the gap that a few researches have been conducted on agri-food supply chain resilience theory building.
Keywords: Agri-food supply chain resilience; Total Interpretive Structural Modelling; MICMAC analysis.