Through the combination of the geographic information systems (GIS) and the integrated information model, the stability of regional bank slope was comprehensively evaluated. First, a regional bank slope stability evaluation index system was established through studying seven selected factors (slope grade, slope direction, mountain shadow, elevation, stratigraphic lithology, geological structure and river action) that have an impact on the stability of the slope. Then, each factor was rasterized by GIS. According to the integrated information model, the evaluation index distribution map based on rasterized factors was obtained to evaluate the stability of the regional bank slope. Through the analysis of an actual project, it was concluded that the geological structure and stratigraphic lithology have a significant impact on the evaluation results. Most of the research areas were in the relatively low stable areas. The low and the relatively low stable areas accounted for 15.2% and 51.5% of the total study area respectively. The accuracy of slope evaluation results in the study area reached 95.41%.

Fire, a phenomenon occurs in most parts of the world and causes severe financial losses, even, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management. Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, remote sensing and the reviewed papers that predicted the fire risk in the field of remote sensing and geographic information system were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy analytic hierarchy process (AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices. Discussion and Conclusion: The findings indicate that RS and GIS are effective tools in the study of fire risk prediction.

To achieve sustainable development, detailed planning, control and management of land cover changes that occur naturally or by human caused artificial factors, are essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods, 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55% and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used after assessing the accuracy, and the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. Then web GIS application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website CSS, HTML and JavaScript languages were used. HTML is  responsible for creating the foundation and overall structure of webpage but beautifying and layout design on CSS. 

Proper understanding of LULC changes is considered an indispensable element for modeling. It is also central for planning and management activities as well as understanding the earth as a system. This study examined LULC changes in the region of the proposed Pwalugu hydropower project using remote sensing (RS) and geographic information systems (GIS) techniques. Data from the United States Geological Survey's Landsat satellite, specifically the Landsat Thematic Mapper (TM), the Enhanced Thematic Mapper (ETM), and the Operational Land Imager (OLI), were used. The Landsat 5 thematic mapper (TM) sensor data was processed for the year 1990; the Landsat 7 SLC data was processed for the year 2000; and the 2020 data was collected from Operation Land Image (OLI). Landsat images were extracted based on the years 1990, 2000, and 2020, which were used to develop three land cover maps. The region of the proposed Pwalugu hydropower project was divided into the following five primary LULC classes: settlements and barren lands; croplands; water bodies; grassland; and other areas. Within the three periods (1990–2000, 2000–2020, and 1990–2020), grassland has increased from 9%, 20%, and 40%, respectively. On the other hand, the change in the remaining four (4) classes varied. The findings suggest that population growth, changes in climate, and deforestation during this thirty-year period have been responsible for the variations in the LULC classes. The variations in the LULC changes could have a significant influence on the hydrological processes in the form of evapotranspiration, interception, and infiltration. This study will therefore assist in establishing patterns and will enable Ghana's resource managers to forecast realistic change scenarios that would be helpful for the management of the proposed Pwalugu hydropower project.

The rapid development of cities and urbanization in China has forced the growth of new channels for buying agricultural products. The purpose of this research is to examine how Internet of Things (IoT’s) technologies can digitize a traditional fresh food supply chain. Comparative and descriptive analysis methods are used to highlight the major pain points in the traditional supply chains and assess how digital transformation could help. We delve into every part of digital transformation, which includes establishing an information platform based on IoT and developing smart storage options. Our findings revealed that through end-to-end digital integration, supply chain efficiency is improved with shorter lead times and leaner inventories that yield reduced costs as well as fewer losses while ensuring product quality and traceability. In sum, such an approach would enhance sustainability within the fresh food value chain. As such, our article highlights key aspects of transitioning towards a digital environment in this sector for those planning similar ventures.

The study focused on investigating the effects of varying levels of HA (HA₁ = 0, HA₂ = 25, HA₃ = 50, HA₄ = 75, and HA₅ = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm², a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.