Journal of Radar and Optical Remote Sensing
Volume:7 Issue: 2, Spring 2024

 Land surface temperature (LST) is a critical parameter for environmental studies, including climate change analysis, soil moisture monitoring, evapotranspiration estimation, and surface energy balance evaluation. This study aims to validate the accuracy of MODIS LST products (MOD11A1 and MYD11A1) from Terra and Aqua satellites in the Bajestan Desert, Iran, by comparing them with ground-based measurements.

  Ground-based LST measurements were conducted using six thermometers equipped with SMT160 temperature sensors over 15 clear-sky days and nights. MODIS LST products were validated using two approaches: (1) comparison with pixel-level ground-based data and (2) comparison with the average LST values of image windows larger than the pixel size (e.g., 3×3, 5×5). Statistical parameters, including root mean square error (RMSE), coefficient of determination (R²), and standard deviation, were calculated to assess the accuracy of satellite-derived LST.

 The results indicate that MODIS LST products systematically underestimate LST in the barren study area. Nocturnal LST exhibited higher accuracy (RMSE = 1.1) compared to diurnal measurements (RMSE = 3.38). Increasing the size of the window used for averaging resulted in higher standard deviations of pixel temperatures, while RMSE and R² values showed negligible changes, demonstrating the homogeneity of the selected study area.

This study validates the applicability of MODIS LST products in arid environments despite their systematic underestimation. The findings highlight the importance of incorporating homogeneous sampling areas and suggest the need for further improvements in MODIS algorithms for arid regions. The methodologies applied in this study provide a robust framework for LST validation in other arid and semi-arid environments.

 The rapid growth of urbanization and the automotive industry in recent years has significantly increased the demand for transportation in both work and daily life. This rise in transportation demand has led to growing issues such as urban traffic congestion, energy consumption, and environmental pollution. Consequently, the immense social, economic, and environmental pressures have intensified the challenges faced in urban transportation development.

  This study examines the various problems related to urban transportation, including environmental pollution, reduced energy resources, increased material and human losses due to accidents, challenges in managing and supervising urban transportation, and the rising demand during peak hours, particularly in densely populated cities worldwide. The research explores the role of smart cities in addressing these challenges by improving transportation flow and ensuring safe and efficient mobility.

 Urban transportation systems, particularly in peak hours, have become a significant concern for global cities, with rapid growth in demand for efficient transportation services. In response, the development of smart cities provides a framework for overcoming these challenges by facilitating smooth transportation for both people and goods, reducing congestion, and offering real-time data and up-to-date information to transportation users.

Transportation, as a critical link in every aspect of life, is recognized as an essential infrastructure for industrial development and improving social welfare. The concept of smart cities is central to solving urban transportation challenges, offering solutions such as managing traffic congestion, providing real-time information, and promoting environmentally friendly methods of transportation.

 Estimate the large part of the soil surface to calculate its moisture is very important for agriculture since it would improve food security. In current study, four radar images of Sentinel-1 are employed to observe soil moisture in Miyankale Peninsula where is located in Behshahr, Mazandaran province.

  These data are collected since 1394 until 1395 in both VV and VH polarization while imagery mode is Global mode. Soil texture, vegetation disturbs microwaves responses therefore the images are processed to eradicate vegetation effect, then backscatter coefficient calculated.

 These backscatters connect to statistical information gathered by field sampling (hygrometer device) to determine volumetric soil moisture in Miyankale Peninsula. The results show 0.79 for R2 (coefficient of determination) between volumetric moisture and backscatter; 0.62 for R2, between vegetation and backscatter, which confirm the vegetation effect on detecting moisture of soil.

This effect is removed from backscatter. In this study, Global mode in SAR data is appropriate for spares vegetation areas.

 Roads in the forest have several tasks and costly road construction has led the designers to design the best network.

  For this purpose, data layers (slope, direction, forest type, etc.) were prepared and multi-criteria evaluation method of these characteristics was used for preparing suitable plan such that after the classification and valuation of inner layers of maps, Pairwise comparison method in Analytic Hierarchy Process (AHP) was used for weighting the characteristics and a compilation of experts opinions which was designed into questionnaires, entered in the process and using Expert Choice software, the importance coefficient of each layer was obtained.

 Weights of factors, characteristics, and restrictions was imported on multi-criteria evaluation model and the combination of characteristics and overlapping the layers according to their importance factor was performed based on multi-criteria evaluation model.

Option 6 were individuated as the most desirable option because of the minimum amount of multiplying the road length in total distance of skidding and the insignificant difference in soil operation volume.

 The primary challenge in the development of land uses is pinpointing optimal locations that harmonize expansion with the preservation of protected and conservation areas.

  This study develops a precise methodology for determining suitable land uses in the coastal areas of Hormozgan province, Iran, using Geographical Information System (GIS) and Analytic Hierarchy Process (AHP).

 The research focuses on identifying optimal locations for agriculture, industry, and aquaculture, integrating environmental, economic, and social criteria. Key factors like topography, soil characteristics, water availability, and socio-economic aspects were weighted using expert opinions to create a capability map. The results indicate that approximately 687,132.4 hectares are viable for developmental purposes, with industrial development showing the highest potential, followed by agriculture and aquaculture.

This study not only provides critical insights for sustainable land use in Bandar Abbas Coastline but also sets a framework applicable to similar coastal regions worldwide, emphasizing the need for comprehensive, multi-criteria planning in coastal land management. This research innovates by focusing on environmental, economic, and social factors for sustainable development.

 This study explores the role of geomorphology, astronomy, and underground water tables in determining the location and orientation of terraced villages in Iran, focusing on spring routing, underground spring height (MAD), and the sun’s noon alignment with the village center. It also examines ridge line alignment, building orientations toward mountain fronts, and spatial connections within each settlement.

  The research employs a box-counting method and a cubing algorithm to analyze topographical data, enabling the calculation of visible adjacent and non-adjacent zones. Ridge line alignments and building orientations in the four cardinal directions are studied in relation to the central core of each village. Comparative analyses of MAD, TIN, and river flow directions across the case study villages—MASOULEH, ABYANEH, and PALANGAN—provide insights into spatial patterns and proportional relationships.

 The findings indicate a significant correlation between the sun's rotational axis at noon, ridge line orientation, and village centers. The MAD and TIN analysis revealed comparable ratios in river paths across the villages. Specifically, MASOULEH and PALANGAN showed proportional similarities in their lower halves, while ABYANEH exhibited nearly double the values of the other two villages. Additionally, flow river direction patterns varied, with ABYANEH and MASOULEH showing a 3×3 structure, compared to PALANGAN’s 2×2 configuration.

The study emphasizes the smart integration of environmental and astronomical factors in the spatial organization of terraced Iranian villages. The alignment of natural and built elements reflects advanced rural planning, highlighting the role of geomorphology and astronomy in shaping the settlement patterns of Masouleh, Abyaneh, and Palangan.