Healthcare accessibility and site suitability analysis is an elongated and complex task that requires evaluation of different decision factors. The main objective of the present study was to develop a hybrid decision-making approach with geographic information systems to integrate spatial and non-spatial data to form a weighted result. This study involved three-tier analyses for assessing accessibility and selecting suitable sites for healthcare facilities, and analysing shortest-path network. The first tier of analysis stressed the spatial distance, density and proximity from existing healthcare to find more deprived and inaccessible areas in term of healthcare facilities. The result revealed that spatial discrepancy exists in the study area in term of access to healthcare facilities and for achieving equal healthcare access, it is essential to propose new plans. Thus, require finding suitable sites for put forward new healthcare service, which was highlighted in the second tier of analysis based on land use land cover, distancing to road and rail, proximity to residential areas, and weighted overlay of accessibility as decision factors. Finally, in the third tier of analysis, the most suitable site among the proposed healthcare was identified using the technique for order of preference by similarity to ideal solution. The road network analysis was also performed in this study to determine the shortest and fastest route from these healthcare facilities to connect with district medical hospital. The present study found some suitable sites throughout the district on inaccessible zones where people are deprived from better healthcare facilities. This attempt will highly helpful for preparing a spatial decision support system which assists the health authorities regarding the healthcare services in inaccessible, underprivileged, and rural areas.Electronic supplementary materialThe online version of this article (10.1007/s41324-020-00330-0) contains supplementary material, which is available to authorized users.

The structural performance of any transport network may be mainly evaluated using connectivity, accessibility, hierarchy and morphology. The evaluation of accessibility is one of the most important aspect in defining the performance of a road network structure. The present study is concerned with proposing a methodology for the city—level opportunity (or) urban services and distance based accessibility evaluation. The various opportunities (or) urban services like schools, colleges, ATM’s, banks, hospitals, police stations, petrol bunks, bus stops, parks and theatres up to a specified distance of 0–5 km radius were considered for the analysis. The weights were assigned to different opportunities and were analyzed using Weighted Scoring Model. The Mean Weighted Accessibility Index has been determined for each location to identify the level of accessibility in a particular location. The study attempts to define the level of road network accessibility at different locations in the study area. In the later stage, this study tried to establish the relationship between the number of opportunities and trip attraction rates and the results were discussed. The present work was also intended to prove the efficiency of Geographical Information Systems in opportunity based accessibility assessment.

Spectral numerical wave models are unable to predict extreme sea conditions accurately, and the probability of occurrence of a given wave parameter for fixed return periods (RPs) remains unexplored by such an approach. In this study, the significant wave height (SWH) parameter that plays a major role in ocean engineering and marine and naval activities was estimated spatially for the entire Bay of Bengal (BOB) region for the given RPs. Spatially gridded 44 years of SWH data at a spatial resolution of 1° × 1° were considered, and return value maps were generated for the BOB for 10-, 15-, 25-, 50-, and 100-year RPs. The peak over threshold (POT) model was chosen over a generalized Pareto distribution for data fitting and calculating the return values. As there is no existing method to determine the threshold value for use in the POT model, in this study, for the first time, an algorithm was designed to calculate the threshold value, which determined the accuracy of the estimation. Along with the conventional time-series analysis of the SWH data using POT, the novelty of the study lies in the spatial return period maps generated for the entire BOB region leading to the basin scale estimation.

The growth of an urban city is determined by the efficiency of its transport network structure. Existing road networks in many of the urban cities in India are unable to meet the increasing travel demand. The demand can be met only through the effective utilization of existing road networks, for which proper connectivity, high accessibility, and effective network morphology are necessary. In many metropolitan cities, the transport network is rapidly expanding at the center while the peripheral growth of the city is ignored. A structural-parameter-based evaluation of the transport network is necessary for acquiring a clear understanding of the existing road network of a city. While the evaluation of the structural parameters of the transport network is a challenging task, understanding the interrelationship among the parameters is no less challenging. Each parameter should be examined by considering the relationship with the other parameters to devise effective strategies for improving the efficiency of an existing transportation system. This study analyzed the relationship between connectivity, accessibility, spatial pattern, and development for the existing transport network of Hyderabad city, India. The results show a strong correlation between these parameters. The use of GIS in this study simplified the analysis. The obtained results would be useful to the concerned urban transportation planning authorities for effective decision-making and policy implementations.

Agriculture is one of the deciding factors of Indian economy, contributing almost 17% of the total GDP. Every year, crops are lost due to natural disasters. This academic research may provide a solution for a long-standing problem in the industry. Crop insurance is one of the most effective ways to not only compensate loss, but also to increase poor farmers’ resilience. Remote sensing has huge potential in the crop insurance market; it can be exploited for vulnerability mapping, damage assessment, risk mapping, and various other aspects. The purpose of this study was to present a method for evaluating crop vulnerability over an area using remote sensing and Geographic Information System (GIS), followed by an assessment of crops damaged due to flood. For application purposes, a crop risk map was prepared from a GIS model for the determination of crop insurance parameters. The study area selected (i.e., the Morigaon and Nagaon districts of Assam) is very much flood-prone. The districts have almost 50% agricultural land of the total land cover, thus making the crops very vulnerable to recurrent flooding. For this study, assessment of damage to crops due to flood was performed for a full year, followed by crop risk map generation from the GIS model. The results revealed that 345 km2 of land was inundated by flood in August 2016. Due to the flooding, 1435.08 km2 of agricultural land bearing crops was damaged at different levels. The crop risk map depicts 103.33 km2 of cropland at high risk due to flood.

Developing countries have ineffective and outdated land administration systems (LAS) which make it a challenge to properly register, manage and secure tenure for local communities. Moreover, limited maintenance budgets prevalent in these countries make it difficult for organizations to conduct regular systematic updates of geographic information. For a LAS to remain useful, it must reflect realities on the ground, and this can only be achieved if land information is reported regularly. However, if changes in the land are not captured in properly administered land registers, LAS lose societal relevance and are eventually replaced by informal systems. Volunteered Geographic Information (VGI) can address these challenges by providing a timely, affordable, flexible, inclusive, up-to-date, and fit for purpose land information to support the limited current systems. However, the consideration and integration of such external sources relies on the quality and credibility of contributed datasets by the public. The public whom in most cases are non-geographic experts can contribute datasets of varying quality and detail, resulting in the reluctance of officials to utilize VGI in their databases. Therefore, this study proposes a Kappa statistical measure methodology: a consensus-based measure of agreement to establish ‘proxy’ quality and credibility of VGI. The methodology was successfully implemented in a case study of Botswana to demonstrate its effectiveness in establishing trust and confidence of contributed datasets by the public. The innovative approach to Kappa presented here, minimizes the need for ground truthing of VGI data.

Understanding climate variability under various climate scenarios is essential to predict the adverse impacts of climate change. Climate variability is often assessed by detection and estimation of trends in the observed and future climate variables. The objective of this study is to determine the trends in precipitation (PCP), minimum and maximum temperature (TMAX, TMIN) in Telangana, India which is a semi-arid region. To assess the observed climate trends, gridded rainfall and temperature data obtained from the Indian Meteorological Department (IMD) for 63 years (1951–2013) are used in the present study. The future climate scenarios for Telangana are assessed using the regional climate model data obtained from Coordinated Regional Climate Downscaling Experiment under RCP 4.5 and RCP 8.5 for 31 years (2020–2050). Climate variability is assessed by calculating co-efficient of variation, parametric (linear regression) and non-parametric tests (Mann–Kendall and Sen’s Slope) are employed at each grid point to determine the possible trends in the climate. The results exhibit a significant increasing trend in for both TMAX and TMIN observed data. Whereas, the daily PCP exhibits no specific pattern indicating uncertainty in precipitation. For the future period, RCP 4.5 scenario shows an increasing trend for PCP and TMAX, while decreasing trend is observed for TMIN. RCP 8.5 scenario results show a decreasing trend for PCP and increasing trends for both TMAX and TMIN.

The aim of this paper is to use Kriging (spherical, exponential, and Guassian models) and Inverse distance weighted (IDW) methods to prepare the water quality map. In addition, the relationship between water quality and distance to fault is determined in northeast of Fars province, Iran. Adaptive neuro fuzzy inference system method is also used to predict groundwater quality. The measured Sodium adsorption ratio and electrical conductivity parameters that are obtained from 384 wells in 2005 to 2014 are utilized to determine groundwater quality. The results show that the Kriging method (spherical model) has a higher accuracy with lower RMSE value than IDW method. Thereafter, this model is used to prepare the interpolation maps. Moreover, the results indicate the hybrid model in terms of maximum R2 and the minimum error is suitable enough to predict water quality parameters. In addition, the results depict by increasing the number of fault, the groundwater quality is decreased and vice versa.

Geomorphosites are the geomorphological landforms that have scientific, cultural, aesthetic and socio-economic values due to human perception. Mama Bhagne Pahar is one of the ancient geomorphosites in West Bengal which has specific and unique geomorphic characteristics than its surrounding area. Now a days, Global Positioning System (GPS) has become a standard surveying technique due to its accuracy and effectiveness. In the present study, perimeter and area of Mama Bhagne Pahar has been calculated from the data collected from GPS survey. Here, principle of Pythagorean theorem has been applied to calculate the perimeter of Mama Bhagne Pahar and calculation of area has been done by applying Coordinate method. Finally, vulnerability of the study area has been assessed using both qualitative and quantitative approaches. In this respect, a map showing encroachment of Mama Bhagne Pahar by human settlements has been prepared by using data collected from GPS survey coupled with high resolution Google Earth satellite image with the help of Arc GIS software.

The Chalakudy river, a seventh order tropical drainage system emerging from the Western Ghats is flowing through the Southern Granulite Terrain of Peninsular India. Anomalies in the hierarchical organization of drainage networks reflect the effects of anthropogenic interferences and structural controls in the development of a drainage basin. The anomalies in the drainage composition are determined from bifurcation index, hierarchical parameters and stream gradient index. Computation of drainage indices is carried out with the aid of vectorized data derived from Survey of India (SOI) open series topo maps and Shuttle Radar Topographic Mission (SRTM) data (3Arc resolution) using ArcGIS 10.4 software. Here we discuss the quantitative methodology to determine the hierarchical anomaly index, hierarchical anomaly density and hierarchical anomaly number of drainage basin from geospatial data with an attempt to infer the degree of geomorphic evolution of the sub-basins from the analysis. The sub-basins are in their mature to the late mature stages of geomorphic evolution. It is observed that the tectonically induced diffusive process and anthropogenic interferences in the drainage basin altered the hierarchical organization of drainage network of Chalakudy river basin.