Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India

Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms

Editorial

Urbanization and Geo-Informatic

Assessment of network traffic congestion through Traffic Congestability Value (TCV): a new index

Traffic congestion is a major and growing problem in urban areas across the globe. It reduces the effective spatial interaction between different locations. To mitigate traffic congestion, not only the actual status of different routes needs to be known but also it is imperative to determine network congestion in different spatial zones associated with distinct land use classes. In the present paper, a new formula is proposed to quantify traffic congestion in the different spatial zones of a study area characterized by distinct land use classes. The proposed formula is termed the Traffic Congestability Value (TCV). The formula considers three major influencing factors: congestion index value, pedestrian movement and road surface conditions; since these parameters are significantly related to land use in a region. The different traffic congestion parameters, i.e. travel time, average speed and the proportion of time stopped, were collected in real time. Lower values of TCV correspond to a higher degree of congestion in the respective spatial zones and vice-versa and the results were validated in the field. TCV differs from the previous approaches to quantifying traffic congestion since it focuses on the causes of network congestion while in previous works the focus was generally on link flow congestion

Vulnerability zoning of urban areas against earthquake (case study: Urmia city)

The danger of earthquake always overshadows human societies and causes irreparable damage to these societies; therefore, preparedness to deal with this crisis by identifying vulnerability points and removing them is effective in reducing the damages caused by earthquake. Due to the location of Iran on one of the two world’s earthquake belts and the existence of many faults, the occurrence of earthquakes on the plateau of Iran is a natural phenomenon. Iran is one of the ten earthquake-prone countries in the world. Consequently, the city of Urmia is no exception to this rule due to its location in the hillsides of the Zagros Mountains and witnesses a large number of earthquakes with different intensities every year. Therefore, to deal with the above problem, we need more detailed studies in the fields of construction and safety. In this study, in order to evaluate the severity of earthquake vulnerability, effective parameters were identified and weighted using fuzzy hierarchical analysis process. Vulnerability maps were prepared by index overlap method and fuzzy logic, for statistical blocks of Urmia city and were presented visually in spatial information system. The results showed that about 50% of the city is vulnerable to earthquakes; to be more precise, about 151574 square meters, i.e. 0.005% has a very high degree of vulnerability and 11538359 square meters, with a percentage of 0.40%, has a high degree of vulnerability to earthquakes

LAND SURFACE TEMPERATURE ANOMALIES IN RESPONSE TO CHANGES IN FOREST COVER

Land cover/use changes specially the forest cover changes affect the local surface temperature (LST) of the earth. In this study, a combination of remote sensing and GIS techniques was used to scrutinize the interactions between LST anomalies and deforestation in Sardasht County, NW Iran. The land cover/use change layers of the study area were extracted from Landsat satellite imagery based on Binary Encoding classification and change detection technique. The radiometric correction analysis were done for each Landsat image to derive LST map layers. According to the results, a descending trend in forest cover with a total 2560 ha decline in area and an ascending trend of about 4 degrees rise in surface temperature values on both forest and non-forest areas were detected in the study area from 1984 to 2017. The temporal and spatial analysis yielded high rates of reverse temporal correlation (-0.81) between forest areas and LST anomalies while the correlation value of 0.76 was found for non-forest areas and LST. The regression analysis of the values confirmed the correlation results to be trustable at 99 percent. It was also found that the deforested areas of the study area correlate with the LST rise spatially with a very high correlation (0.98) from which a tangible interaction of the parameters can be inferred

LAND SURFACE TEMPERATURE ANOMALIES IN RESPONSE TO CHANGES IN FOREST COVER

Land cover/use changes specially the forest cover changes affect the local surface temperature (LST) of the earth. In this study, a combination of remote sensing and GIS techniques was used to scrutinize the interactions between LST anomalies and deforestation in Sardasht County, NW Iran. The land cover/use change layers of the study area were extracted from Landsat satellite imagery based on Binary Encoding classification and change detection technique. The radiometric correction analysis were done for each Landsat image to derive LST map layers. According to the results, a descending trend in forest cover with a total 2560 ha decline in area and an ascending trend of about 4 degrees rise in surface temperature values on both forest and non-forest areas were detected in the study area from 1984 to 2017. The temporal and spatial analysis yielded high rates of reverse temporal correlation (-0.81) between forest areas and LST anomalies while the correlation value of 0.76 was found for non-forest areas and LST. The regression analysis of the values confirmed the correlation results to be trustable at 99 percent. It was also found that the deforested areas of the study area correlate with the LST rise spatially with a very high correlation (0.98) from which a tangible interaction of the parameters can be inferred

A novel approach of mapping landscape aesthetic value and its validation with rural tourism data

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Forest Fire Risk Zone Mapping of Eravikulam National Park in India: A Comparison Between Frequency Ratio and Analytic Hierarchy Process Methods

Forest fire is one of the most common natural hazards occurring in the Western Ghats region of Kerala and is one of the reasons for forest degradation. This natural disaster causes considerable damage to the biodiversity of this region during the dry fire season. The area selected for the present study, Eravikulam National Park, which is predominantly of grassland vegetation, is also prone to forest fires. This study aims to delineate the forest fire risk zones in Eravikulam National Park using remote sensing (RS) data and geographic information system (GIS) techniques. In the present study, methods such as Analytic Hierarchy Process (AHP) and Frequency Ratio (FR) were used to derive the weights, and the results were compared. We have used seven factors, i.e. land cover types, normalized difference vegetation index, normalized difference water index, slope angle, slope aspect, distance from the settlement, and distance from the road to prepare the fire risk zone map. The area of the prepared risk zone maps is divided into three zones, namely low, moderate, and high. From the study, it was found that the fire occurring in this area is due to natural as well as anthropogenic factors. The prepared forest fire risk zone maps are validated using the fire incidence data for the period from January 2003 to June 2019 collected from the records of the Forest Survey of India. The investigation revealed that 72% and 24% of the fire incidences occurred in the high risk zone of the maps prepared using the AHP and FR methods, respectively, which ascertained the superiority of the AHP method over the FR method for forest fire risk zone mapping. The receiver operating characteristic (ROC) curve analysis gives an area under the ROC curve (AUC) value of 0.767 and 0.567 for the AHP and FR methods, respectively. The risk zone maps will be useful for staff of the forest department, planners, and officials of the disaster management department to take effective preventive and mitigation measures