In order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.

A Detailed geophysical investigation was conducted on Knossos territory of Crete Island. Main scope was the detection of underground archaeological settlements. Geophysical prospecting applied by an experienced geophysical team. According to area dimensions in relation to geological and structural conditions, the team designed specific geophysical techniques, by adopted non-catastrophic methods. Three different types of geophysical techniques performed gradually. Geophysical investigation consisted of the application of geoelectric mapping and geomagnetic prospecting. Electric mapping focusses on recording soil resistance distribution. Geomagnetic survey was performed by using two different types of magnetometers. Firstly, recorded distribution of geomagnetic intensity and secondly alteration of vertical gradient. Measured stations laid along the south-north axis with intervals equal to one meter. Both magnetometers were adjusted on a quiet magnetic station. Values were stored in files readable by geophysical interpretation software in XYZ format. Oasis Montaj was adopted for interpretation of measured physical properties distribution. Interpretation results were illustrated as color scale maps. Further processing applied on magnetic measurements. Results are confirmed by overlaying results from three different techniques. Geoelectric mapping contributed to detection of a few archaeological targets. Most of them were recorded by geomagnetic technique. Total intensity aimed to report the existence of magnetized bodies. Vertical gradient detected subsurface targets with clearly geometrical characteristics.

Land suitability analysis using geographic information systems (GIS) is one of the most widely used method today. In this type of studies, GIS and geo-spatial statistical tools are used to evaluate land units and present the results in suitability maps. The present work aims to characterize the suitability of soils in the province of Catamarca for pecan nut production according to the variables: rockiness, salinity, risk of water-logging, depth, texture and drainage described in the Soil Map of Argentina at a scale of 1:500,000 published by the National Institute of Agricultural Technology. A classification of the suitability of the soil cartographic units was made according to crop requirements, applying the methodology proposed by FAO. The standardization of variables made by omega score and the calculation of the spatial classification score were carried out as a result of the synthesis of the spatial distribution of soil suitability. The applied methodology allowed obtaining the soil suitability map resulting in a total of 60,662 km² suitable for pecan nut production, which accounts for 59.8% of the total area of the province.

Forest fire, as a discontinuous ecological factor of forest, causes the changes of carbon storage and carbon distribution in forest ecosystem, and affects the process of forest succession and national carbon capacity. Taking the burned land with different forest fire interference intensity as the research object, using the comparison method of adjacent sample plots, and taking the combination of field investigation sampling and indoor test analysis as the main means, this paper studies the influence of different forest fire interference intensity on the carbon pool of forest ecosystem and the change and spatial distribution pattern of ecosystem carbon density, and discusses the influence mechanism of forest fire interference on ecosystem carbon density and distribution pattern. The results showed that forest fire disturbance reduced the carbon density of vegetation (P < 0.05). The carbon density of vegetation in the light, moderate and high forest fire disturbance sample plots were 67.88, 35.68 and 15.50 t∙hm^-2, which decreased by 15.86%, 55.78% and 80.79% respectively compared with the control group. In the light, moderate and high forest fire disturbance sample plots, the carbon density of litter was 1.43, 0.94 and 0.81 t∙hm^-2, which decreased by 28.14%, 52.76% and 59.30% respectively compared with the control group. The soil organic carbon density of the sample plots with different forest fire disturbance intensity is lower than that of the control group, and the reduction degree gradually decreases with the increase of soil profile depth. The soil organic carbon density of the sample plots with light, moderate and high forest fire disturbance is 103.30, 84.33 and 70.04 t∙hm^-2 respectively, which is 11.670%, 27.899% and 40.11% lower than that of the control group respectively; the carbon density of forest ecosystem was 172.61, 120.95 and 86.35 t∙hm^-2 after light, moderate and high forest fire disturbance, which decreased by 13.53%, 39.41% and 56.74% respectively compared with the control group; forest fire disturbance reduced the carbon density of eucalyptus forest, which showed a law of carbon density decreasing with the increase of forest fire disturbance intensity. Compared with the control group, the effect of light forest fire disturbance intensity on the carbon density of eucalyptus forest was not significant (P > 0.05), while the effect of moderate and high forest fire disturbance intensity on the carbon density of eucalyptus forest was significant (P < 0.05).

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.