Land evaluation is a key factor in land-use spatial planning, affecting both success and sustainability. This study showcases the value of using the multi-criteria evaluation (MCE) and multi-objective land allocation (MOLA) GIS decision-making tools determine the most favorable spatial development of various land-use types, for Qaleh Ganj County in Iran. Weighted linear combination (WLC) and ordered weighted averaging (OWA) were used to assess the potential of seven land uses based on predefined criteria. MOLA was also used for land-use zoning based on suitability. The results derived from these techniques indicate that the rangeland zone with 30.80% and the ecotourism zone with 22.9% have the highest suitability potential, and aquaculture with 0.26% and tourism with 0.24% have the lowest potential in Qaleh Ganj. Considering the 7 land uses and a lot of defined criteria, MCE and MOLA provided an automatic and flexible way of dealing with qualitative multi-dimensional environmental effects, factors, constraints and objectives. The combination of WLC and OWA helped to manage selection factors differently, as their level of risk and trade-off is different. The result can be considered as optimal suitability maps with an environmental preservation goal which can help to protect the natural environment of this area, and will also allow for continued economic development. The approach described in this study can help developing countries and the sensitive area facing environmental challenges due to rapid development. This approach and its application procedures can be applied to similar territorial contexts, where several territorial factors should be considered and taken into account.
This article was conducted to perform a temporal and spatial analysis in order to identify suitable climatic regions for tourism. We investigated tourism climate conditions in Fars province from 2006 to 2016 using tourism climate index (TCI). Also, modified inverse distance weighting (IDW) interpolation is applied to generate the optimal spatial pattern of the TCI distribution. The relationship between the interpolation accuracy and a critical IDW parameter, called power value (β), was evaluated for optimization. The results revealed that during four months of May, April, October, and November, 70–83% of cities in Fars province show excellent and ideal climatic comfort. In the four months of July, December, January, and March, about 45–54% of Fars province provide good and very good conditions for tourism activities. The spatial distribution of TCI also shows that the cities in the northern part generally have the most desirable conditions during the hot season, while the southern cities of Fars province are more suitable for tourism during the cold season. Also, analysis of optimization steps demonstrated that power value (β) affects interpolation accuracy. As our study suggests, using the optimal power values (β) of 1 and 2 can lead to optimal spatial interpolation of the TCI distribution. Overall, we found IDW and TCI as reliable tools for assessing bioclimatic comfort conditions, considering β-value as an influential factor that should be evaluated to achieve optimal interpolation results.
Marshlands in arid and semi-arid areas are considered constantly changing environments due to unsecured water supplies as a result of high evapotranspiration and limited and highly variable rainfall. Classification of marshlands in these regions and mapping of their land cover is not an easy task and maps need to be upgraded frequently. Satellites provide enormous amounts of information and data for the continuous monitoring of changes. The aim of this paper is to introduce an approach using multispectral satellite imagery that was adopted to classify and monitor the Al Hammar Marsh (Iraq) over several years and to suggest a relationship between the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), and the Normalized Difference Water Index (NDWI), using Landsat 8 data with a resolution of 30 m × 30 m, validated with Sentinel-2 datasets at 10 m × 10 m. Six land cover classes were used: (1) open water, (2) dry area, (3) dense vegetation, (4) medium-density vegetation, (5) sparse vegetation, and (6) wet soil. Three indices, NDWI, NDMI, and NDVI, were chosen for the automatic classification of each pixel and the creation of a time series of land cover maps. The proposed method can efficiently classify and monitor marshlands and can be used to study different marshlands by adjusting the thresholds for NDVI, NDMI, and NDWI. Overall, the correlation for all classes (R) between Landsat 8 and Sentinel-2 is about 0.78. Thus, this approach will help to preserve marshes through improved water management.
Soil organic carbon (SOC) is known as a vital ecosystem service, resulting from interactions of ecological processes. It is important for its contributions to food production, mitigation, and adaptation to climate change. In this study, we investigated the relationship between tree density and tree trunk circumference with the soil chemical properties in the small tree line area located in Józsefmajor, Hungary. The interrelation between different chemical soil properties also was measured. For this purpose, samples were taken in 24 plots (6 m×13m) from 0–10 soil depths. Tree density and tree trunk circumference in each plot were measured. The Near-Infrared spectroscopy technique (Wavelength Range: 1300–2600nm MEMS (micro-electromechanical systems) technology) was used to estimate the chemical properties of the soil. Pearson and Spearman correlation analysis was applied to study the interrelationships between two multivariate data sets, tree density and trunk circumference were compared with soil properties. The results showed a significant relationship between some soil chemical parameters, especially between soil organic carbon (SOC) and total N and also the cation exchange capacity (CEC) with SOC and total N. Besides, this study shows that the plots containing more trees and with a higher trunk circumference provide higher SOC and total N concentrations. Trunk circumference has a slightly stronger correlation with these two soil properties compared to those of tree density.
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