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The evaluation of irrigation suitability plays a crucial role for the socio-economic development of the society, especially in the region of Sundarban. For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop yield. The entropy information theory, several irrigational indices, multivariate statistics, GIS, and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region. In total, 33 groundwater samples were collected in 2018 (April and May), and they were evaluated for major cations, anions, as well as other parameters like electrical conductivity (EC), soluble sodium percentage (SSP), potential salinity (PS), total dissolved solids (TDS), Kelly ratio (KR), sodium absorption ratio (SAR), permeability index (PI), residual sodium carbonate (RSC), magnesium hazard (MH), and residual sodium bicarbonate (RSBC). The overall trend of the principal cations and anions is in the sequence of Na+ ≥ Mg2+ ≥ Ca2+ ≥ K2+ and HCO3− ≥ Cl− ≥ NO3− ≥ SO42− ≥ F−, respectively, whereas the spatial variation of %Na, SAR, RSBC, and MH demonstrate very poor irrigation water quality, and spatial variation of KR, RSC, SSP, PI, and PS signifies that the irrigation water quality is excellent to good. In order to identify the specific association and potential source of the dissolved chemical in the groundwater, statistical techniques like correlation and principal component analysis were also employed. The hydrochemical facies indicates that mixed type makes up the bulk (51.51%) of the water samples. Following the Wilcox plot, more than 75% of the water samples are good to doubtful; however, by the US salinity hazard map, roughly 60.60% of the samples had high salinity (C3-S1 zone). The EWQII reports that no samples fall into the very good (no restriction) category, whereas 30.30%, 30.30%, and 39.40% of the sample wells record good (low restriction), average (moderate restriction), and poor (severe restriction) irrigation water quality, respectively. Based on this study, the bulk of the groundwater samples taken from the study area are unsuitable for cultivation. The findings of this study will also help decision-makers develop adequate future plans for irrigation and groundwater resource management. [ABSTRACT FROM AUTHOR]

The Republic of Trinidad and Tobago is an archipelagic Small Island Developing State (SIDS), situated on the southern end of the chain of Caribbean islands. Several factors such as climate, topography, and hydrological characteristics increase its susceptibility and vulnerability to flooding which results in adverse socio-economic impacts. Many Caribbean islands, including Trinidad and Tobago lack a flood risk assessment tool which is essential for a proactive mitigation approach to floods, specifically in the Caribbean due to the incommensurate flooding events that occur because of the inherent characteristics of SIDS. This research focuses on the problem of flooding using susceptibility analysis, vulnerability analysis and risk assessment for the island of Trinidad, whilst also presenting a repeatable and appropriate methodology to assess these risks in regions that have similar characteristics to Trinidad. This is especially useful in Caribbean countries because of a lack of internal human capacity to support such efforts. Flood hazard indexes (FHI) and vulnerability indexes (VI) were generated for this study using subjective and objective weighting technique models to identify regions that are affected by flooding. These models were Analytical Hierarchy Process (AHP), Frequency Ratio (FR) and Shannon's Entropy (SE). Comparative analyses of the three models were conducted to assess the efficacy and accuracy of each to determine which is most suitable. These were used to conduct a risk assessment to identify risks associated with each Regional Corporation of Trinidad. Results indicate that FR is the most accurate weighting technique model to assess flood susceptibility and risk assessment in Trinidad, with an Area Under the Curve (AUC) of 0.76 and 0.64 respectively. This study provides an understanding of the most appropriate weighting techniques that can be used in regions where there are challenges in accessing comprehensive data sets and limitations as it relates to access to advanced technology and technical expertise. The results also provide reasonably accurate outcomes that can assist in identifying priority areas where further quantitative assessments may be required and where mitigation and management efforts should be focused. This is critical for SIDS where vulnerability to flooding is high while access to financial and human resources is limited. [ABSTRACT FROM AUTHOR]

Polycentric urban structure is the recent trend of new-age sustainable cities in India. Limited research is reported focused on quantitative analysis of polycentric structure at the intracity level. In the present research, a detailed database has been generated using multitemporal satellite imageries. Zone-wise quantitative analysis, supported by the database, exhibits clear evidence of transit-oriented polycentric urban growth around Old Faridabad, NIT and Ballabhgarh. Linear urban expansion close to highways, railways, metro ways and urban extension as Greater Faridabad has led to the vertical expansion of the city. Highly variable urban density has been observed in the southern and south-western zones. Shannon's entropy has identified even distribution of built-up around Old Faridabad, whereas clustering of high urban density around NIT and Ballabhgarh. Getis-Ord Gi* statistics have identified a consistent increase of urban hot spot areas from 21.92% (2007), 26% (2012) to 27.48% (2017). The present study suggests planners and policymakers to improve the connectivity between the upcoming urban centre Greater Faridabad, three existing urban centres and other under-developed districts of Haryana to achieve balanced development. Such a step would contribute to the sustainable solutions for various issues over the hot spot around the current urban centres and achieve inclusive urban growth in Faridabad. Moreover, current findings contribute to building a model framework for analysing urban growth patterns even for other satellite cities of India. [ABSTRACT FROM AUTHOR]

This study is focused on developing an approach for spatial mapping of groundwater by considering four types of factors (geological, topographical, hydrological, and climatic factors), and by using different bivariate statistical models, such as frequency ratio (FR) and Shannon's entropy (SE). The developed approach was applied in a fractured aquifer basin (Ameln Basin, Western Anti-Atlas, Morocco), to map the spatial variation of groundwater potential. Fifteen factors (15) influencing groundwater were considered in this study, including slope degree, slope aspect, elevation, topographic wetness index (TWI), slope length (LS), topographic position index (TPI), plane curvature, profile curvature, drainage density, lineament density, distance to rivers and fault network, normalized difference vegetation index (NDVI), lithology, and land surface temperature (LST). The potential maps produced were then classified into five classes to illustrate the spatial view of each potential class obtained. The predictive capacity of the frequency ratio and Shannon's entropy models was determined using two different methods, the first one based on the use of flow data from 49 boreholes drilled in the study area, to test and statistically calibrate the predictive capacity of each model. The results show that the percentage of positive water points corresponds to the most productive areas (high water flow) (42.86% and 30.61% for the FR and SE models, respectively). On the other hand, the low water flows are consistent with the predicted unfavorable areas for hydrogeological prospecting (4.08% for the FR model and 6.12% for the SE model). Additionally, the second validation method involves the integration of 7200 Hz apparent resistivity data to identify conductive zones that are groundwater circulation zones. The interpretation of the geophysical results shows that the high-potential zones match with low apparent resistivity zones, and therefore promising targets for hydrogeological investigation. The FR and SE models have proved very efficient for hydrogeological mapping at a fractured basement area and suggest that the northern and southern part of the study area, specifically the two major fault zones (Ameln Valley in the north, and the Tighmi-Tifermit Valley in the south) has an adequate availability of groundwater, whereas the central part, covering the localities of Tarçouat, Boutabi, Tililan, and Ighalen, presents a scarcity of groundwater. The trend histogram of the evolution of positive water points according to each potentiality class obtained suggests that the FR model was more accurate than the SE model in predicting the potential groundwater areas. The results suggest that the proposed approach is very important for hydrogeological mapping of fractured aquifers, and the resulting maps can be helpful to managers and planners to generate groundwater development plans and attenuate the consequences of future drought. [ABSTRACT FROM AUTHOR]

Urbanisation induced land use and a land cover change is a proliferating phenomenon worldwide. The impacts of chaotic urban growth are all well documented. To overcome the ill effects of urbanisation, continuous monitoring and sustainable planning are the keys. As the future urban growth in India is predicted to take place in small cities of less than a million populations, it is the crucial time to plan a strategy for sustainable urban growth. Mangaluru, being a small, emerging city has the basic fertility required for urban growth. But the deficiencies of spatial data availability and lack of insight for impending urbanisation scenario would hamper the sustainable management of urban growth in the region. In this context, the current study proposes to map land use and land cover and monitor the spatiotemporal dynamics of urban growth in Mangaluru urban agglomeration, India, during 1972–2018. The present study employs techniques of remote sensing and geographic information system (GIS) and uses Landsat series of imageries. The land use and land cover changes and dynamics of urban growth have been studied using change detection, Shannon entropy, and spatial trend analysis. The study reveals that the rapid increase in the built-up area is largely induced by intense in fill growth in the core range of the city which is further corroborated by the Shannon entropy value, which indicates the compact nature of city growth. It has been found that built-up area has increased from 3.68% in 1972 to 18.79% in 2018. Agricultural land on the other hand decreased from 36.51–11.22% during 1972–2018 period. The spatial trend of change analysis represents the expansion of built-up land along with the transport network, and predominantly following a north–south course. Landsat image classification has also shown that Land use and land cover have largely changed during 1972–2018. [ABSTRACT FROM AUTHOR]

Landslides are natural and incidentally man-made phenomena. Developing landslide risk reduction plans in order to preserve the natural and human resources are pivotal. This study sets out to prioritize landslide-controlling factors by using the Shannon’s entropy model and the GIS techniques. A total of 90 landslides were identified using extensive filed surveys and interpreting the Google Earth images. A Landslide inventory map was prepared in the GIS environment together with eleven controlling factors as inputs, namely precipitation, elevation, slope percentage, slope aspect, lithology, land use/land cover, the normalized difference vegetation index (NDVI), and the distance to streams/faults/roads/villages. The results revealed that the land use/land cover, the distance to streams, and the distance to faults were the top-ranked factors of the highest importance in landslide occurrence, while the distance to villages, and the distance to roads were of the least importance. Further, the model validation results attested to the great performance of the adopted model where the area under the receiver operating characteristic curve (AUROC) was 0.879. Considering that about 32% of the watershed is located in the high and very high sensitive area, it is recommended to avoid land use change in landslide-prone areas to reduce relative risk of landslide.

The flash flood is the most dangerous natural disaster to mountainous highways in tropical countries due to its special characteristics. It has occurred quite frequently on mountainous highways and directly threatened road infrastructure, economy, and lives every year. Meanwhile, detailed flash flood spatial prediction maps are rarely available on these highways. Shannon's Entropy model and GIS permit cheaper, more efficient, easy to use, and updated flash flood-prone areas forecasting. Therefore, this study applied Shannon's Entropy model and GIS to generate a detailed flash flood susceptibility map along National Highway-6 of Hoa Binh province of Vietnam. Twelve input factors that influence flash floods within the research area were used and collected from different sources. These mentioned factors corresponded to twelve thematic maps in the GIS environment. In this paper, the ROC curve method was used to evaluate the accuracy of the flash flood forecasting map and given a very good value (81.1%). The flash flood forecasting map can help organizers and decision-makers have safety rescue solutions or give early warning to people who have lived along this highway for better flash flood prevention and management. [ABSTRACT FROM AUTHOR]

Urbanization is considered as a significant driver of land use and land cover change which is closely associated with the growth of population and economy. Geographical Information System and remote sensing technology are efficient tools for detecting patterns and trends of urban growth. In order to avoid unwanted impact of urban growth at the local and regional level, planning for expected future growth is essential. Bengaluru (previously known as Bangalore), in Karnataka, India, is a city of economic success, challenges, opportunities, hopes and above all, a city of dreams for immigrants. The study aims to quantify trends of urban growth in Bengaluru city using Geographical Information System, remote sensing techniques and Shannon's Entropy method. The study reveals an increasing trend in the entropy values for the city signifying urban sprawl or dispersed development of the city. It also indicates spatial shifting of growth centres within the city. Results of demographic and spatial analysis were verified through visual survey of ground truth. The process and the findings have a high utility to comprehend the land use changes and forecast expansion patterns to develop a future scenario, which may be further used to prepare planning and management strategies at regional as well as local levels. [ABSTRACT FROM AUTHOR]

The purpose of current study is to produce groundwater qanat potential map using frequency ratio (FR) and Shannon's entropy (SE) models in the Moghan watershed, Khorasan Razavi Province, Iran. The qanat is basically a horizontal, interconnected series of underground tunnels that accumulate and deliver groundwater from a mountainous source district, along a water- bearing formation (aquifer), and to a settlement. A qanat locations map was prepared for study area in 2013 based on a topographical map at a 1:50,000-scale and extensive field surveys. 53 qanat locations were detected in the field surveys. 70 % (38 locations) of the qanat locations were used for groundwater potential mapping and 30 % (15 locations) were used for validation. Fourteen effective factors were considered in this investigation such as slope degree, slope aspect, altitude, topographic wetness index (TWI), stream power index (SPI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Using the above conditioning factors, groundwater qanat potential map was generated implementing FR and SE models, and the results were plotted in ArcGIS. The predictive capability of frequency ratio and Shannon's entropy models were determined by the area under the relative operating characteristic curve. The area under the curve (AUC) for frequency ratio model was calculated as 0.8848. Also AUC for Shannon's entropy model was 0.9121, which depicts the excellence of this model in qanat occurrence potential estimation in the study area. So the Shannon's entropy model has higher AUC than the frequency ratio model. The produced groundwater qanat potential maps can assist planners and engineers in groundwater development plans and land use planning. [ABSTRACT FROM AUTHOR]

Urban growth is a spatial dynamic phenomenon that indicates population growth, economic expansion, city importance level, and so on. The use of current and historical data in urbanization analysis is necessary in urban spatial studies and future urban planning. This research aims to study, examine, and assess the urban expansion of Tripoli spatially and temporally by using remotely sensed data, geographic information systems (GIS), and the statistical relative Shannon entropy model. Remotely sensed data (four satellite images from 1984, 1996, 2002, and 2010) and GIS were used to determine the extent of urban area and urban growth in Tripoli in five different directions. Shannon's entropy model was implemented to analyze and assess urban expansion trends as a process and pattern in the study area. Results show that the Tripoli metropolitan area has a high level of sprawl along its urban expansion history. The hypothesis employed for Shannon's entropy zone division produces good insights on overall urban growth, urban growth direction, and specific urban growth over time. The obtained results provide good guidance for modeling urban sprawl processes, understanding urbanization causative factors, and predicting future urban patterns. Furthermore, the findings of current paper can be used by decision makers and urban planners to identify past and present urban expansions tendencies to prepare for future urban demands. [ABSTRACT FROM AUTHOR]

Abstract: Although remotely sensed images have been used to study urban growth patterns the world over, very few studies have employed these methods to examine the growth of Iranian cities. Shiraz is perhaps the most important city in the southern part of Iran and, thus, was selected for this study. We used satellite images of the study area from the period between 1976 and 2005, and population censuses of Shiraz. By applying classification methods to the satellite images four main types of land use were extracted: water, built-up, vegetation and bare land. Then, the area coverage for all the land use types at different points in time were measured and coupled with population data. The results demonstrate that, over the entire study period, development in Shiraz cannot be characterized as sprawl. Since 2000, however, one can see evidence of sprawl. These results are also supported by calculations using Shannon’s entropy. A further finding is that vegetation growth did not keep pace with that of population or the built-up area; more recently, vegetation has greatly declined. It is advisable that future plans for the city give serious consideration to the preservation of available vegetation and, when possible, the restoration of vegetation that was destroyed in the past. [Copyright &y& Elsevier]

Flooding is a very common worldwide natural hazard causing large-scale casualties every year; Iran is not immune to this thread as well. Comprehensive flood susceptibility mapping is very important to reduce losses of lives and properties. Thus, the aim of this study is to map susceptibility to flooding by different bivariate statistical methods including Shannon's entropy (SE), statistical index (SI), and weighting factor (Wf). In this regard, model performance evaluation is also carried out in Haraz Watershed, Mazandaran Province, Iran. In the first step, 211 flood locations were identified by the documentary sources and field inventories, of which 70% (151 positions) were used for flood susceptibility modeling and 30% (60 positions) for evaluation and verification of the model. In the second step, ten influential factors in flooding were chosen, namely slope angle, plan curvature, altitude, topographic wetness index (TWI), stream power index (SPI), distance from river, rainfall, geology, land use, and normalized difference vegetation index (NDVI). In the next step, flood susceptibility maps were prepared by these four methods in ArcGIS. As the last step, receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated for quantitative assessment of each model. The results showed that the best model to estimate the susceptibility to flooding in Haraz Watershed was SI model with the prediction and success rates of 99.71 and 98.72%, respectively, followed by Wf and SE models with the AUC values of 98.1 and 96.57% for the success rate, and 97.6 and 92.42% for the prediction rate, respectively. In the SI and Wf models, the highest and lowest important parameters were the distance from river and geology. Flood susceptibility maps are informative for managers and decision makers in Haraz Watershed in order to contemplate measures to reduce human and financial losses. [ABSTRACT FROM AUTHOR]