Journal of Spatial Analysis

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Land cover changes as a basic factor in environmental change act and has become a global threat. In this research, changes in land cover in rural tourism areas by neural networks, Markov chains in software ArcGIS, ENVI, Terrset using the TM and OLI satellite imagery, Landsat Satellite was surveyed for a period of 30 years for three periods of 1985, 2000, and 2015. The findings of the first stage show that land cover changes at the period 1985-2015, were classified in five class residential spaces, Commercial, Green, Empty and mountainous spaces and communication networks. In this study, the area of mountainous and empty spaces (13.25%) has decreased and in contrast, has decreased the amount of green spaces (6.221%), Residential (5.258%), commercial (1.264%) and communication networks (0.529%). Changing land cover as one of the most important environmental risks has been directly influenced by the Commodification phenomenon. Also, the findings of the prediction using the Markov-CA chain showed that with the continuation of the current and excessive loading on the ground, on the horizon of 2030, green cover (Agriculture, gardens and grassland, garden and residential)  and  wild land  and mountain cover have been reduced and to cover residential and commercial villas will be added. Based on research findings concluded that land cover changes in rural tourism areas in order to achieve more profits has become incompatible applications. This change in land cover, in addition to the economic, social impacts, has led to the formation of environmental hazards in the Bharang area. Developing tourism in the study area by removing agricultural land from the production cycle has led to an increase in urban activities and the formation of new activities (service, Residential Garden, residential villa) instead of traditional activities(agriculture and livestock) that are economical. And by loading too much ecological power tolerable land, while posing environmental hazards, causing incompatible activities next to each other, they do not match. Therefore, tourism, which gradually formed over the years and now it has become a part of rural texture, Spatial Conflict and heterogeneity two strains has created for them. Spatial Conflict created, due to changes in land cover and acceptance of incompatible activities that derive from human-nature relationships. This means that the rapid and unpredictable trend of tourism development, the rural landscape has encountered a problem and with changes in land cover, has led to inconsistencies between different activities and eventually has shaped the Spatial Conflict.
 

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The effect of Urban Development on Watershed Hydrological Properties (case study: Tajrish Watershed)
Throughout the human history, societies and rivers have been closely linked, so that the human civilization began from the riverside (Stevaux et al. 2009 (. The quantitative and qualitative characteristic of river is vulnerable to land-use changes (Kang et al. 2010). Natural and urban watersheds are influenced by the rapid land use change due to urban development (Furusho et al. 2013). Hence the importance of land use as an environmental variable have made its changes as a major issue in environmental changes and sustainable development) Verburg et al. 2009).
The development of urbanization and industrialization of cities and communities have undesirable effects on the hydrological response of watersheds. It increases the magnitude of runoff and contamination, reduces the base flow and the groundwater recharge. Hence, urban authorities are urged to pay more attention to the environmental damaging effects of the urbanization process and the increase of construction. In this regard, attention should be paid to the effect of type of land cover and land use on urban runoff and hydrological changes in surface flow. Tehran as the largest metropolis in Iran has ascending trend of land cover and land use changes due to the growing population.
In this research, the effect of urban development on the hydrological characteristics of the Tajrish sub-watershed (in Darband watershed) located north of Tehran has been investigated. Results of this study indicated that the river Darband is exposed to hydrological hazard due to human need for space and land use and land cover changes. The studied area is affected by decreasing pervious area, increase of runoff coefficient, and change in water quality parameters.
Darband River watershed consists of two streams of Darband and Golabdareh which are considered as the major rivers of the Tehran-Karaj Basin. This river originates from the mountains of the Tochal located in northern Tehran. The catchment area of Darband River in the studied area is 39.88 square kilometers.
In this study, aerial photos of years 1345, 1358 and also   and IkONOS images in year 2011 were used to detect the changes in land cover and land use in the Tajrish watershed. Pas-Ghale sub-watershed in upstream of Tajrish was selected as benchmark since its land use doesn't affected by human interventions. SCS-CN method developed by the United States Department of Agriculture (USDA) was used to estimate the quantitative changes in surface storage and runoff volume. Man-Kendall test was used for temporal trend detection of discharge and chemical parameters of surface water and also. The change of water type was identified annually using the Piper diagram in the aqQA software. Frequency analysis was carried out for peak discharge data using the weibull’s empirical method.
During three considered periods, the curve numbers (CN) and runoff coefficient (C) in Tajrish watershed significantly increased. Significant trend was also observed for the chemical parameters of surface flow in Tajrish. While the surface storage and initial abstraction ratio (λ) indicate decreasing trend.  Relationships of CN and λ with rainfall depth (P) were also computed for both studied watersheds. According to the Piper diagram, the distribution of ions in the cation diagrams at both Maghsudbeik and Pasghaleh stations is generally more directed toward sodium. In the triangles of anions, both of the stations studied tend to show more calcium biocarbon content. Presence of sodium ion in the surface water is due to igneous formations in the watershed. The surface water in Pasghale station, indicate a neutral type of water. Whereas, saline water type is detected in the Maghsudbeik station. The increase of urban utilization over the past three decades could be the main cause of changes in the hydro chemical characteristics and water type along the Darband River.
Investigation of land use changes in the Darband watershed indicate that the impervious surface has increased during years of 1996 to 2011. Results also indicate that the CN and λ values in Pas-ghale watershed are more correlated to Pin compared with ones observed in Tajrish. The results also reveal that hydrological modeling in watersheds undergoes land use changes and urbanization will result in imprecision results.
 Many chemical parameters of the water quality of Darband River have been increasing at the Maghsudbeik station such as Chlorine, sulfate, sodium, electric conductivity and TDS and in the coming years, it can be considered inappropriate in terms of agriculture in the water class.
 
Keywords: Darband River, land cover and land use, Piper diagram, SCS-CN.
 
 

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This study investigates the spatio-temporal dynamics of evapotranspiration (ET) and its modulation by biophysical variables and land use/land cover (LULC) changes in the Karun River Basin, southwestern Iran, from 2000 to 2023. The basin, spanning 67,257 km² and characterized by diverse topography, experiences significant annual water loss (72% of 413 billion m³ national precipitation) due to ET, leading to salt and sediment accumulation. Data from MODIS products (MCD12Q1, MOD13A1, MCD43A3, MOD11A2, MOD16A3, CHIRPS) provided land cover, NDVI, albedo, LST, precipitation, and ET at 500-meter resolution, supplemented by Landsat imagery (30-meter resolution) for validation. Multiple regression and Geographically Weighted Regression (GWR) analyses revealed a 39.5% ET increase (31.48 to 43.92 mm/year), a 32.78% NDVI rise (0.18 to 0.239), and a 16.35% LST decrease (33.52°C to 28.05°C), correlated with a 6.90% agricultural decline (6,939,225 to 6,460,335 ha), a 6.94% rangeland increase (3,840,375 to 4,106,780 ha), and a 42.76% forest expansion (156,000 to 222,700 ha). GWR (AdjR² > 0.97, peak 0.9887 in 2010) identified spatial non-stationarity, with overprediction in mountainous northeast regions and underprediction in agricultural southwest plains, reflecting LULC influences. Landsat-derived false color composites and classifications (overall accuracy 85–90%, Kappa 0.85–0.90) validated a 2,477 km² forest loss to high-ET rangelands/agriculture, driving warm-season ET elevation. Results emphasize the need for integrated hydrological models incorporating irrigation data and high-resolution analyses to enhance sustainable water management in this water-stressed region.

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Revealing surface reflection forcings of land cover in Lorestan province using MODIS sensor products

Introduction
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.   
                                                                                                                  
materials and Method                                                                                                                
 In this study, to reveal the relationship between land cover levels and different land use classes, cross-information matrix analysis was used in the ARC-GIS software platform. Since one of the main objectives of the study was to investigate and reveal the albedo inductions of land cover classes in Lorestan province, so the relationship between these two factors was investigated by cross-matrix analysis technique. In this regard, two sets of data were used. The first set of data was related to land cover classes of MODIS sensor composite product with a spatial resolution of 1 km and hierarchical data format (MCD      
   12(Q2 (MCD product) which was obtained from the database of this sensor

Conclusion
 Land cover classes or perhaps it can be said that land use is one of the most important shapers and determinants of climate near the earth. In this study, it was observed that in general, 5 major land cover classes in the province are separable, among which rangeland and forest lands account for 85% of the total land cover of the province. On the other hand, it was seen in this study that the average spatial albedo of the province in spring, autumn and winter is about 0.2, which is very close to the global value of this component, but in winter the average value of this index in the province reaches 0.3, which can be increased Shows attention. The five land cover classes in the province had their own unique albido induction in winter, which was separable and distinct from each other, but in spring, summer and autumn, no significant distinction of albido induction of these land cover was revealed.                                                                                                                                       

Keywords: Land cover changes, Land surface temperature, Cross-information analysis matrix, Lorestan province