ArcGIS Tools Research Articles

Object‐based image analysis (OBIA)‐based gully erosion dynamics, sediment loading rate and sediment yield study in Lake Hawassa Sub‐basin, Ethiopia

AbstractGully erosion is a serious environmental issue in Lake Hawassa Sub‐basin. It has affected a large portion of the catchment, and a large amount of sediment has been transported into the lake. This condition needs to be addressed. However, before conservation techniques are implemented, the gully systems should be mapped, their extent and changes over time need to be measured, and their capacity to produce sediment from their catchments should be determined. The objective of this study were, therefore, to map and analyse the change in gully erosion and quantify the sediment loading rate and sediment yield from the active and connected gullies in Lake Hawassa Sub‐basin using object‐based image analysis (OBIA) with high‐resolution SPOT 5 satellite image of the years 2011 and 2020. This method was integrated with field observation for mapping gully features of the study area, in comparison with automatic digitization carried out with the help of eCogenition Developer Version 9.1 and ArcGIS tools. Overall accuracy and Kappa coefficient were determined and were found to be 85.2% and 0.81, respectively, for the image of year 2020 and 81.1% and 0.76, respectively, for the image of year 2011. Based on the OBIA method, the extent of gullies (in area) were found to be 63.5 km2 in 2011 and 79.9 km2 showing a rapid increase between 2011 and 2020 (an increase of 16.4 km2 (24.4%) in the 10 years considered). The later result shows that 5.53% of the area of the Lake Hawassa Sub‐basin is affected by gully erosion. The maximum gully density in the study area was found to be 589 km/km2 in 2011 and this increased to 884 km/km2 in 2020. The sediment loading rate from the Lake's catchment was found to be in the range of 12.62 to 38.59 ton per hectare per year. The sediment yield from the Lake's catchment was 8.83 to 27.02 t/ha/year. The total annual volume‐based sediment yield at the Lake generated from the gully was 2.39 million cubic meter considering sediment delivery ratio of 70% for fully connected gullies. This result shows that 0.21% of the storage capacity of the Lake was being lost due to sedimentation from the gully system every year. From the result by dividing the total volume of the sediment by the surface area of the lake, one can see that a silt thickness of 2.51 cm was being deposited in the Lake every year.

GIS-Based Landslide Susceptibility Mapping Using Frequency Ratio and Shannon Entropy Models in Dejen District, Northwestern Ethiopia

A GIS-based study has been carried out to map areas landslide susceptibility using both frequency ratio (FR) and Shannon entropy (SE) bivariate statistical models. A total of 270 landslides were identified and classified randomly into training landslides datasets (70%) and the remaining (30%) of landslides datasets were used for validation purpose. The 11 landslides conditioning factors like slope, elevation, aspect, curvature, topographic wetness index, normalized difference vegetation index, distance from road, distance from river, distance from faults, land use, and rainfall were integrated with training landslides to determine the weights of each landslide conditioning factor and factor classes using both frequency ratio and Shannon entropy models. The landslide susceptibility maps were produced by overlay the weights of all the landslide conditioning factors using raster calculator of the spatial analyst tool in ArcGIS 10.4. The final landslide susceptibility maps were reclassified as very low, low, moderate, high, and very high susceptibility classes both FR and SE models. This susceptibility maps were validated using landslide area under the curve (AUC). The results of AUC accuracy models showed that the success rates of the FR and SE models were 0.761 and 0.822, while the prediction rates were 0.753 and 0.826, respectively.

The Risk of Orofacial Cleft Lip/Palate Due to Maternal Ambient Air Pollution Exposure: A Call for Further Research in South Africa.

Despite being underreported, orofacial cleft lip/palate (CLP) remains in the top five of South Africa's most common congenital disorders. Maternal air pollution exposure has been associated with CLP in neonates. South Africa has high air pollution levels due to domestic burning practices, coal-fired power plants, mining, industry, and traffic pollution, among other sources. We investigated air pollutant levels in geographic locations of CLP cases. In a retrospective case series study (2006-2020) from a combined dataset by a Gauteng surgeon and South African Operation Smile, the maternal address at pregnancy was obtained for 2,515 CLP cases. Data from the South African Air Quality Information System was used to calculate annual averages of particulate matter (PM) concentrations of particles < 10 µm (PM10) and < 2.5 µm (PM2.5). Correlation analysis determined the relationship between average PM2.5/PM10 concentrations and CLP birth prevalence. Hotspot analysis was done using the Average Nearest Neighbor tool in ArcGIS. Correlation analysis showed an increasing trend of CLP birth prevalence to PM10 (CC = 0.61, 95% CI = 0.38-0.77, p < 0.001) and PM2.5 (CC = 0.63, 95% CI = 0.42-0.77, p < 0.001). Hot spot analysis revealed that areas with higher concentrations of PM10 and PM2.5 had a higher proclivity for maternal residence (z-score = -68.2, p < 0.001). CLP birth prevalence hotspot clusters were identified in district municipalities in the provinces of Gauteng, Limpopo, North-West, Mpumalanga, and Free State. KwaZulu-Natal and Eastern Cape had lower PM10 and PM2.5 concentrations and were cold spot clusters. Maternal exposure to air pollution is known to impact the fetal environment and increase CLP risk. We discovered enough evidence of an effect to warrant further investigation. We advocate for a concerted effort by the government, physicians, researchers, non-government organizations working with CLP patients, and others to collect quality data on all maternal information and pollutant levels in all provinces of South Africa. Collaboration and data sharing for additional research will help us better understand the impact of air pollution on CLP in South Africa.

Coastline change rate estimation on the southern coastal districts of Tamil Nadu, India using the multi temporal Google Earth images and GIS based statistical approach

&lt;p&gt;Coastal erosion is the process of wearing away material from the coastal profile due to an imbalance in the supply and export of material from a particular section of the coast which cause property damage, and the loss of land. This study investigates the rate of erosion and accretion along the southern coast of Tamil Nadu which was exposed to a lot of tourism and development activities. The shorelines were delineated for the years 2000,2005,2010,2015 and 2020 on the high-resolution multi-temporal satellite images in the Google Earth Pro software by visual interpretation. The long-term and short-term changes were studied by three statistical parameters functionalized in DSAS v 5.0 tool in ArcGIS 10.6 software such as endpoint rate, net shoreline movement and linear regression rate (Cenci et al., 2018). The positions of the shoreline in 2030 and 2040 are forecasted using the Kalman filter-based forecast tool in DSAS and the changes were analysed. During the study period, the average rate of changes in Kanyakumari is -1.26 m/year, Tirunelveli is -1.01 m/year and Tuticorin is -1.09 m/year. the transects showed significant erosion along 19.54% of Kanyakumari, 3.79% of Tirunelveli, and 17.81% of Tuticorin coasts, and significant accretion is observed in 1.31% of Kanyakumari, 1.07% of Tirunelveli and 3.02% of Tuticorin coasts. The outcome of shows that erosion is prevailing on the Kanyakumari coast and erosion is prevailing in Tuticorin.&lt;/p&gt;&#x0D;

Spatial inequality in Bangladesh: A geospatial analysis

Spatial inequality of development is an important issue in Bangladesh. In this study a set of sectors-education, infrastructure, health, and economy-and sectoral components/indicators were selected aiming at investigating the spatial inequality scenario of Bangladesh. All components/indicators of each sector were weighted overlaid using ArcGIS tool. Finally, the overall spatial inequality of development was generated overlaying all the sectoral inequality maps. The spatial inequalities were revealed categorically from the highest overlaid cell value as the most lagged area to the lowest value as the most advance area. A serious centralized character towards the capital Dhaka was identified almost in all the sectors in spatial inequality maps of Bangladesh. The overall spatial inequality map identified a total of 16 districts in the comparatively ‘lagged area’ category; and 44 districts in the category of the ‘moderate area’. Only one district (the capital Dhaka) was identified in the category of ‘most advance area’, while three districts (Chittagong, Gazipur, Narayanganj) found in the ‘advance area’ category. Most of the lagged districts were identified in the north-west and north-east parts of Bangladesh. Besides, the districts of Chittagong Hill Tracts (Bandarban, Khagrachari, Rangamati) were also found most lagged..

Energy efficient route prediction for solar powered vehicles

Solar powered vehicles are currently being developed towards entirely self-sustaining vehicles that harness their energy directly from the sun. For such vehicles, it is important to optimise their solar exposure while driving, thereby reducing their energy consumption through fossil fuels. Research has emerged to estimate optimised routes for solar vehicles, and this paper builds on this work to expand on the parameters used to calculate the route, thereby improving the energy-harnessing quality of the route together with its overall utility for the driver. The ArcGIS tool and the open weather API are used to predict the solar potential of a vehicle by taking into account shade based on surrounding topography, vehicle type, weather, distance and time of day. The model was implemented as a user mobile application ‘Drive Solar’ that calculates the optimal route for the user based on their preferences for time and energy efficiency. The effectiveness of the prediction model was tested using a solar irradiance sensor in Dublin city. The results show that the model predicts the route with the most energy absorbed with a 51.65% accuracy and chooses the route with the most energy consumed with a 86.65% accuracy. We conclude that Drive Solar can aid in the transition to widespread use of self-sustaining solar vehicles.

Estimation of Spatial Groundwater Recharge and Surface Runoff in the Gaza Coastal Aquifer Using GIS-Based WetSpass Model

Assessment of the spatial distribution of water recharge and surface runoff is essential for water resource management and planning. This research evaluates spatial distributions of groundwater recharge, surface water flow, and evapo-transpiration for the Gaza coastal aquifer, Palestine in 2020 using the WetSpass model integrated with GIS. The ArcGIS tool is implemented to create grid maps of the WetSpass model data, such as temperature, rainfall, wind velocity, potential evapo-transpiration, soil map, land use, topography, gradient, and water depth. The model generates computerized maps of yearly groundwater recharge, surface water flow, and evapo-transpiration. The WetSpass model's calibration procedures were implemented by manually altering or changing the model parameters already included in the WetSpass model within a predetermined range of values. The simulated results revealed that the average yearly groundwater recharge was 42 mm/year, surface runoff was 38 mm/year and actual evapotranspiration was 268 mm/year. The research findings would help local stakeholders and decision-makers manage groundwater resources in a sustainable and effective manner.

An Assessment of Ongoing Developments in Water Resources Management Incorporating SWAT Model: Overview and Perspectives

Land and water are the most necessary natural resources because the entire life system depends on them. It requires proper management to achieve maximum utilization. When used in conjunction with Arc GIS, the Soil and Water Assessment Tool (SWAT) is a promising model for simulating the agricultural watershed since it can forecast runoff, sediment and nutrient transport, and erosion under various management scenarios. Furthermore, the model is better at evaluating both the spatial and non-spatial variation of hydrological methods under a very large watershed. This study uses the methodology employed by the SWAT model for the estimation of surface runoff and sediment yield and discusses in detail the setup of the model computer file needed by the model sensitivity analysis parameter and validation area unit. SWAT is a well-known hydrological modeling method used in many hydrologic and environmental simulations. Over 17 years (2005-2021), 212 studies were found from various peer-reviewed scientific publications listed on the SWAT online database (CARD). Applicability studies were divided into five categories: water resources, streamflow, erosion, land-use planning and agricultural settings, climate change scenarios, and model parameterization. Hydrologic phenomena and adaptations in various river basins have been investigated. They mostly examined environmental impacts and preventive techniques to ensure an understanding of effective environmental regulation. Streamflow susceptibility to climatic changes was shown in climate change studies. Modeling streamflow parameters, model modifications, and basin-scale calibrations were investigated. Future simulation aspects such as data sharing and the opportunity for improved future analysis are also discussed. A multimodal approach to future simulations, as well as more efforts to make local data available, are both very good ideas.

Evaluation of Site Resilience Based on Social Capital Theory: A Case Study of Dongsi district

Along with the outbreak of COVID-19 in China, numerous of small and medium-sized enterprises are losing their customers, confronted with the risk of bankruptcy, and communication among the public also witnesses a drop attributed to epidemic prevention policy, which can both be describe as the decrease of social capital. Although the research on resilience city theory is mounting in recent years, there are only a few papers focus on resilience city based on social capital. This paper will build a method analyzing the resilience of Dongsi district from three different perspectives, including enterprises perspective, enterprises and individuals’ perspective and individuals’ perspective. In this process, data of enterprises and public space’s location will be collected, utilizing kernel density tool in Arcgis and Daily average population heat diagram to evaluate the resilience of enterprises and community of Dongsi district respectively. The result shows that the resilience of Dongsi district is low. Enterprises far from streets are devoid of social capital because of the location of some enterprises are disperse and customers flow are low. Additionally, the public spaces, which can promote the communication between local residents, like squares and parks in the site are in small quantity and public show less interest in four attractions inside Dongsi area, indicating that Dongsi is more vulnerable faced to disasters due to the low cohesion among the community.

SPATIAL AND TEMPORAL DISTRIBUTION CHARACTERISTICS OF CULTURAL RELICS PROTECTION UNITS AND DISASTER RISK ANALYSIS IN BEIJING

Abstract. As the ancient capital of the Six Dynasties and the current capital, Beijing has a rich historical and cultural heritage. As a carrier of culture, cultural preservation units have significant historical, artistic, and scientific value in their own right. In this paper, we use the mean nearest neighbor, kernel density analysis, and standard deviation ellipse tools in ArcGIS 10.2 software to analyze the spatial and temporal distribution characteristics of different types and periods of cultural heritage units in Beijing and their potential seismic and meteorological hazard risks, to provide strong data support for the conservation and use of cultural heritage units in Beijing. The results show that the different types of cultural preservation units in Beijing are unevenly distributed, with the two categories of modern important historical sites and representative buildings and ancient buildings being more numerous and concentrated in Dongcheng District, Xicheng District, and Haidian District in central Beijing, and the three categories of ancient tombs, ancient ruins, cave temples, and stone carvings being less numerous and concentrated in the outer administrative districts of Beijing. In recent years, the relative humidity in Beijing has shown a decreasing trend, while the average temperature has shown an increasing trend, and this dry and hot environment is not conducive to the conservation of cultural preservation units. This dry and hot environment is not conducive to the protection of cultural preservation units and is prone to damage such as cracking, collapse, deformation, and discoloration of bamboo, wood, rocks, and other cultural heritage elements. It is concluded that in terms of specific regions, the number of cultural heritage units in central Beijing is high, the period is late and the risk of seismic hazards is high, while the number of cultural heritage units in the outer administrative regions of Beijing is low, the period is early and the risk of seismic hazards is low. In conclusion, to enhance the conservation and use of cultural heritage units in Beijing, the relevant authorities should strengthen the daily management of the three high-density and high-risk areas of cultural heritage units in Dongcheng District, Xicheng District, and Haidian District, while at the same time not relaxing the emergency disaster prevention and mitigation of the smaller number and earlier period of cultural heritage units in the peripheral administrative districts.

Geospatial measurement of urban sprawl using multi-temporal datasets from 1991 to 2021: case studies of four Indian medium-sized cities

In recent decades, medium-sized Indian cities have experienced accelerated urban growth due to the saturation of large cities. Such rapid urban growth combined with inadequate urban planning has triggered urban sprawl in medium-sized Indian cities. In this context, the present study focuses on the geospatial measurement of urban sprawl in four rapidly expanding Indian medium-sized cities located in diverse physiographic regions, such as Lucknow urban agglomeration (UA), Bhubaneswar UA, Raipur UA, and Dehradun UA. Multi-temporal Landsat imageries from 1991 to 2021 were downloaded for land cover classification through the maximum likelihood classification tool in ArcGIS 10.3. Thereafter, spatiotemporal land cover change detection was performed based on the classified land cover maps. The presence of urban sprawl was detected using the relative entropy index while the urban expansion index quantified the urban sprawl typologies such as edge expansion, leapfrog development, and ribbon development. The results exhibited a rapid rise in built-up land cover from 1991 to 2021. The prevalence of urban sprawl was detected in all four cities as per the relative entropy index. Edge expansion typology of urban sprawl was dominant compared to leapfrog development and ribbon development. Such urban growth phenomenon creates a hindrance in promoting sustainable urban development in medium-sized Indian cities. The results obtained from this paper would assist urban planners and policymakers in developing strategies to encourage planned urban growth. This paper exhibits the potential of geoinformatics to monitor and analyze urban sprawl.

Evolution of innovation networks in industrial clusters and multidimensional proximity: A case of Chinese cultural clusters

The innovation and optimization of cultural industry clusters is important to the promotion of economic structural transformation and high-quality development. Taking 31 provinces (municipalities directly under the Central Government and autonomous regions in China) as the research object, the cross-sectional data included the number of joint patent applications for culture and related industries among provinces (regions) in 2014, 2016, 2018 and 2020. Then, the cluster innovation network was constructed using social network analysis (SNA) based on scientific identification of cultural industry clusters. This new cluster innovation network structure and its spatial evolution characteristics are accessible with the help of UCINet and ArcGIS tools. Finally, the multiple regression-quadratic assignment procedure (MR-QAP) method is used to determine the influence of geographical proximity, technological proximity, and social proximity on the evolution pattern of the cultural industry cluster innovation network. The results of the study are important for improving the efficiency of national cultural industry innovation and promoting regional synergistic development.

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

Transportation is regarded as one of the most important issues currently being researched; this issue needs the search for approaches or processes that might lessen many contemporary traffic concerns. Congestion, pollution, and accidents have escalated lately, negatively impacting urban environments, economic development, and citizens’ lifestyles. The rise of illnesses and epidemics throughout the world, such as COVID-19, has created an urgent need to find the best way to save people’s lives. The vehicle routing problem (VRP) is a well-known moniker for improving transportation systems and is regarded as one of the ancient and contemporary difficulties in route planning applications. One of the main tasks of VRP is serving many customers by determining the optimal route from an initial point to a destination on a real-time road map. The best route is not necessarily the shortest-distance route, but, in emergency cases, it is the route that takes the least fitness cost (time) and the fastest way to arrive. This paper aims to provide an adaptive genetic algorithm (GA) to determine the optimal time route, taking into account the factors that influence the vehicle arrival time and cause delays. In addition, the Network Analyst tool in ArcGIS is used to determine the optimal route using real-time map based on the user’s preferences and suggest the best one. Experimental results indicate that the performance of GA is mainly determined by an efficient representation, evaluation of fitness function, and other factors such as population size and selection method.

Assessment of suitable land for surface irrigation using spatial information systems: Case of Bilate River Basin in the Rift Valley Lakes Basin, Ethiopia

Identifying the limited available resource, use of improved irrigation technology and better water resources management have been suggested as mechanisms for increased production. To optimize the agricultural production, knowing the available land for irrigation is mandatory. This study aimed to assess the suitable land for surface irrigation using different spatial parameters (normalized difference vegetation index, soil, slope, proximity, rainfall deficit, and land use). Land suitability was assessed by considering the individual parameters and then by overlaying. The overlay suitability analysis was performed by using weighted overlay tool within spatial analyst tool in ArcGIS. After excluding the irrigation constraints suitable land for surface irrigation was identified. Based on the individual parameters analysis the normalized difference vegetation index gives the largest land size which is 95 % of the total land as suitable. While the slope factor gives the lowest figure which is 57 % of the total land is suitable for irrigation. The weighted overlay analysis, gives only 28.46 % of the total land in the basin was suitable for surface irrigation. More than 93 % of this suitable land is grouped in to small scale while only about 7 % is used for medium to large scale irrigation.

A comprehensive spatially-explicit analysis of agricultural landscape multifunctionality using a New Zealand hill country farm case study

CONTEXTMultifunctionality can refer to the capacity of a landscape to provide a wide range of ecosystem services (ES). Maintaining or restoring multifunctionality in agricultural landscapes is considered an efficient solution to achieve sustainable agricultural production because multiple ES provided by a landscape can support both environmental protection and socio-economic benefits. Quantifying the provision of ES provides fundamental information to measure landscape multifunctionality and inform sustainable land management strategies. Although a large number of studies have been carried out to measure landscape multifunctionality and associated ES, comprehensive spatially explicit assessments at the farm scale are limited. OBJECTIVEThis research applies a wide range of spatial models, tools, and methods to spatially quantify the provision of multiple ES as well as the pattern of landscape multifunctionality in farmed landscapes. METHODSTo quantify the provision of multiple ES provided by the landscape, the bio-physical models provided by InVEST (e.g., Nutrient Delivery Ratio and Sediment Delivery Ratio models) and land use land cover-based assessments using spatial analysis tools in ArcGIS were employed. The Analytic Hierarchy Process was applied to calculate the landscape multifunctionality index which is an integration of multiple ES supply. Hot spot analysis using Getis Ord Gi* statistics was utilised to examine the spatial distribution of multiple ecosystem services. A hill country farm in New Zealand is chosen as a case study because it is a good example of a diverse landscape that is facing significant environmental issues due to intensive agricultural production. RESULTS AND CONCLUSIONSOur study reveals that the provision of ES and the pattern of landscape multifunctionality is highly variable across the farm. Both positive and negative relationships among ES are found and the interactions between them are mainly reflected in three ES bundles: the agricultural land, the indigenous forest and wetlands, and the mixed land uses. Furthermore, our study demonstrates that the quality of landscape is significantly dependent on the landscape management goals and preferences of the farmer so involving them into the process of ES and landscape multifunctionality assessment at a farm scale is essential step to obtain more comprehensive results. SIGNIFICANCEResults from this study enable important questions to be answered regarding the spatial variation of ES provision and how land use and land management goals relate to the value and quality of landscape multifunctionality. This can provide valuable information to design future multifunctional landscapes and inform decision making in relation to sustainable land use management.

A Correction Method of Positioning for Deep-Sea Camera Data

The deep-sea camera is the most intuitive and effective detection tool for seabed investigation, and the accuracy of camera positioning can ensure its data value. A bundled ultra-short baseline (USBL) positioning system is generally employed to realize the spatial positioning of an underwater camera. The influence of the underwater acoustic environment and other factors cause USBL positioning data to become unstable, leading to abnormalities, or missing data, which creates difficulties for camera positioning. In order to solve the problem, this paper selects the seabed camera data of the “XunMei” mineralization area acquired from the China south Atlantic voyage. Moreover, the USBL positioning data, combined with high-precision terrain, bathymetry, and ship-borne GPS positioning data, were analyzed and mined comprehensively. In order to eliminate the abnormal data, a four-dimensional anomaly culling model of USBL positioning data is established based on the time and space scales through the ArcGIS tool. Then, modeling, simulation, and interpolation prediction are performed for the positioning data after anomaly elimination to achieve the geographic location correction of the hydrothermal sulfide near-bottom camera and its data. This method has achieved good results in practical applications. The corrected water depth profile of the camera survey line is compatible with the high-precision terrain detected at different times in the same area. The characteristics of the corrected video images are compatible with the sample characteristics of the TV grab sampling position. A set of high-quality positioning data (sampling test 5000 points) not participating in the correction model is compared with the corrected USBL data at the same position. The following results are obtained: in the case of a confidence interval of 95%, the correlation coefficient is 1, the significance is 0, there is no significant difference between the corrected data after the simulation and its original positioning data (not participating in the model), and the correction error is below 5 m. This shows that the problem of locating a submarine camera and its data can be solved using the proposed four-dimensional anomaly elimination model established based on the USBL positioning data, high precision terrain, bathymetry and GPS data, and the corresponding cubic polynomial least-squares correction model.

DISTRIBUTION PATTERNS AND SETTLEMENT DENSITY USING NEAREST NEIGHBOR ANALYSIS AND KERNEL DENSITY ANALYSIS IN DIY COASTAL AREAS

DIY's coastal area is one of DIY's development priorities by establishing the site as an economic corridor that impacts physical development, such as settlements in the coastal area of DIY. This study aims to analyze the distribution and density of settlements. The method used in research is a quantitative descriptive and Geography Information System approach. The analysis used in this study is Nearest Neighbour Analysis (NNA) and Kernel Density Analysis with an analysis tool in ArcGIS 10.5. The results of the NNA show that the three districts located on the coast of DIY have the same distribution pattern characteristics, namely, the clustered pattern, which means the NNA index value is &lt;1 or the T value ranges from 0-0.80. The results of the kernel density analysis show that the most significant density is found in Kulon Progo Regency, precisely in Wates District, and Bantul Regency, precisely in Srandakan District. At the same time, for Gunung Kidul Regency, it is less significant, and the density is only centered on one density point. Several factors cause settlement density, including physical factors (topography, slope, soil type, and clean water sources), accessibility (proximity to transportation routes and proximity to the city center), availability of facilities and infrastructure (electricity network, educational facilities, and health), and environmental factors (natural and human resources).Keywords: Settlements, Coastal, NNA, Kernel Density

Peri-urban area delineation and urban sprawl quantification in Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using geoinformatics

In Southeast Asia, rising population, economic growth, and lack of land supply in the city core have led to the widespread irreversible land cover transformation in peri-urban areas. Such extensive and haphazard urban growth in peri-urban areas raises concern about analyzing and promoting planned urban growth. Therefore, this paper attempts to assess land cover changes from 2001 to 2021 and delineate peri-urban areas of a midsized Indian city, i.e., Thiruvananthapuram Urban Agglomeration (UA) using geoinformatics. The maximum likelihood supervised classification tool in ArcGIS 10.3 was used to prepare land cover maps for 2001, 2007, 2014, and 2021. Further, the presence of urban sprawl in the peri-urban areas was detected through Shannon’s entropy index. The urban sprawl typologies in the peri-urban areas were quantified using the adjacent neighborhood relationships concept. The results revealed rapid growth in built-up land cover and decline in non-built-up land cover within Thiruvananthapuram UA during the study period. Peri-urban areas were delineated based on nine indicators, such as total population, population growth, population density, literacy rate, percentage of the male workforce, percentage of the female workforce, agricultural land cover, distance from urban core, and percentage of cultivators to agricultural workers. A rise in Shannon’s entropy index from 1.59 in 2001 to 2.05 in 2021 exhibited the occurrence of rapid urban sprawl in the peri-urban areas. Dominance of discontinuous low-density development, i.e., scatter development typology of urban sprawl, was observed in peri-urban areas of Thiruvananthapuram UA. Such studies using geoinformatics would assist local governments in scientifically formulating sustainable urban policies and plans.

Diversity of bloom forming harmful algal species in the central Bonny Estuary, Niger delta, Nigeria

This study was carried out from December 2018 to November 2019 to examine the distribution and abundance of harmful algal species (HAS) in the central Bonny estuary. Seven sampling stations were established with ArcGIS tool. Microalgae species were sampled with 20 mm mesh plankton net. Nutrients were analyzed in the laboratory using the APHA 4500 Method, while physicochemical characteristics were determined in situ. Results revealed that environmental gradients were adequate to support life in that part of the estuary except for phosphate (2.90 ± 0.22-9.48 ± 1.06 mg l-1). A total of 31 HASs categorized into 17 genera and three classes were determined: Bacillariophyceae (29 species), Chlorophyceae and Cyanophyceae (one species each). Navicula amphibola had the highest density (4.713 103 cells l-1) while Pinnularia divergens recorded the lowest density (0.00049 103 cells l-1). Total density values decreased across seasons with 9.157 103 cells l-1 in dry season and 8.907 103 cells l-1 in wet season. Checklist of species across stations showed that five species were distributed across the seven stations, while two were found only in Station 2 and 7. Diversity indices revealed Shannon’s index ranged between 3.17 and 3.25 and species evenness ranged between 0.78 and 0.88, while Margalef range value (3.09-3.31) was considered moderately stable. Therefore, there is a need for proper management practices which could help to reduce the level of nutrient discharge into the central Bonny estuary.

A STUDY ON THE SHORELINE CHANGES AND LAND USE/LAND COVER ALONG THE KETA COASTAL ZONE

Abstract. The Keta Municipality has undergone a rapid increase in population due to economic and commercial activities. This led to the municipal’s coastal and shoreline zone being faced with severe environmental challenges throughout the years. The goal of the study was to evaluate Keta’s shoreline changes and the coastal Land Use Land Cover (LULC) using multi-temporal remote sensing datasets. These datasets were subjected to the following image processing techniques such as image enhancement, image classification and, shoreline extraction. The Digital Shoreline Analysis System (DSAS), a plugin tool in ArcGIS was utilized to assess the rate of shoreline changes (i.e., erosion or accretion) from 2000 to 2020. These were achieved based on the following statistical methods used; Linear Regression Rate (LRR), Net Shoreline Movement (NSM), and End Point Rate (EPR). The LULC analysis indicated that built-up areas and water bodies have increased rapidly from 14.71–18.43%, and 47.68–50.46% respectively from 2000 to 2021. In terms of the shoreline changes, LRR showed a mean of −0.95m/year with 68.22% faced with erosion and accretion of 31.78%. The EPR and NSM revealed a mean shoreline change of −1.19m/year and −26.3/period respectively from 2000 to 2021. The EPR and NSM results both revealed that 69.24% experienced erosion and 30.76% accretion, indicating the prevalence of erosion at the shoreline. This research is to contribute to both the development of Keta’s shoreline protection and management measures as well as sustainable land use planning. Also, aids in achieving most of the Sustainable Development Goals in the municipal.