No abstract

Industrial areas play a critical role in urban and regional planning, especially for developing countries where reliable strategies for these areas can promote economic and environmental efficiency. The present study provides an integration of hybrid multi-criteria decision-making (MCDM) theories and Geographical Information System (GIS) processes in order to assess the suitability of an industrial location. Unlike traditional models, an efficient decision analysis demands handling uncertainties and considering dependencies between criteria. The proposed MCDM framework uses fuzzy theory because of the vagueness of experts' judgements. Moreover, Decision-Making Trial and Evaluation Laboratory (DEMATEL) is employed to investigate interrelationships among the criteria. In the proposed empirical solution, analytic network process (ANP) principles are used to deal with systematic interactions. We considered several factors such as accessibility, topography, proximity, and socioeconomic characteristics in the decision-making procedure for a sustainable industrial park. The system is applied to Hamadan province, Iran to determine appropriate locations that are the results of the aggregation of criteria maps in a GIS environment. The results demonstrate that accessibility and economic indicators are essential for choosing an industrial park's location. Additionally, the proposed method can be applied for an efficiency evaluation of available industrial parks.KEY WORDS industrial park establishment; fuzzy theory; analytic network process; land suitability analysis; urban and regional planning

Seasonal snow-covered surface has a critical role in global water resource supplement especially providing fresh water for humankind and flora's consumptions as well as local underground water storages. The in situ measurements of seasonal snow-covered variability are extensively prodigal and costly particularly in existence of severe climate conditions such as high latitude regions and polar areas. It is therefore necessary to apply remote sensing techniques and observations to estimate accurately the snowpack melting and accumulation for different seasons. In this paper, we estimate snow-covered surface variability for four different seasons of year in Mount Odin, Canada using aerial photos. In order to do this, firstly Digital Elevation Model (DEM) with respect to Earth Gravitational Model 1996 (EGM96) for each flight mission of A, B, C and D from these aerial photos by applying Bundle Adjustment (BA) triangulation is being generated precisely. Moreover, the displacement of each two DEMs is computing in order to determine snow-covered surface variability between each two flight missions. The results demonstrate that flight mission C has the highest elevation topographically compare to the missions A, B and D while mission C was planned in February 2011 in existence of vast snow throughout Mount Odin area as well as mission C's DEM which has higher elevation values than the others. The proposed methodology and problem solution and the case study information with the details of each flight mission are discussed in expatiation.

Abstract. Text-based games are environments in which defining the world, the representation of the world to the player (hereafter, agent) and agent interactions with the environment are all through text. Text-based games expose abstract, executable representations of indoor spaces through verbally referenced concepts. Yet, the ability of text-based games to represent indoor environments of real-world complexity is currently limited due to insufficient support for complex space decomposition and space interaction concepts. This paper suggests a procedure to automate the mapping of real-world geometric floorplan information into text-based game environment concepts, using the Microsoft TextWorld game platform as a case. To capture the complexities of indoor spaces, we enrich existing TextWorld concepts supported by theoretical navigation concepts.We first decompose indoor spaces using skeletonization, and then identify formal space concepts and their relationships. We further enhance the spectrum of supported agent interactions with an extended grammar, including egocentric navigation instructions. We demonstrate and discuss these new capabilities in an evacuation scenario. Our implementation extends the capabilities of TextWorld to provide a research testbed for spatial research, including symbolic spatial modelling, interaction with indoor spaces, and agent-based machine learning and language processing tasks.

The random error is following the features of normal distribution function (NDF) which those random errors deviated from the NDF's characteristics can be considered as outliers. In fact, the outliers exist inevitably in any observed parameter that is an undesirable part of the measurement's procedure due to its negative influence on the sensitivity analysis. It is therefore necessary to investigate more efficient methodologies especially for current remote sensing data processing and assimilations. In this paper, the comparisons of Baarda method as the conventional statistical methodology with the Fuzzy approach are presented to detect the outliers at the edges of two data groups: 1. The point cloud of ground-based laser scanner field experiment from one side of a wall, and 2. A group of randomly simulated distributed 3D point cloud. The results show that the Baarda method eliminates the outliers as soon as they are being found while the Fuzzy approach works critically based on the outputs of the statistical tests. Thus, the Fuzzy approach deals mostly with the residuals and those observed errors in the adjustment computational procedures. The obtained results about the successfulness rate of outlier detection for each method are separately presented in both graphical and statistical overview. Also, the capabilities of Fuzzy approach to detect the outliers in different point cloud's size and numbers of existing outliers at the edges of point cloud are investigated and discussed in details.