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2024 | Book

Developments and Applications of Geomatics

Proceedings of DEVA 2022

Editors: Shashi Mesapam, Anurag Ohri, Venkataramana Sridhar, Nitin Kumar Tripathi

Publisher: Springer Nature Singapore

Book Series : Lecture Notes in Civil Engineering

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About this book

This volume presents the selected papers from the International virtual conference on Developments and Applications of Geomatics. It covers a wide range of topics of GIS applications such as agricultural studies, climate change monitoring and impacts, floods monitoring, natural disasters, environmental impact assessment, ecosystem management and sustainable development, industrial pollution, structural health monitoring, unmanned aerial vehicles, transportation planning, geological mapping, 3D modelling and web GIS applications. This book will be useful for researchers and professionals from various fields whose work includes geographic information system.

Table of Contents

Frontmatter
Analyzing the Potential Application of Low-Cost Digital Image Correlation in Direct Shear Test

Nowadays, Digital Image Correlation (DIC) has become a frequently used optical technique for testing lab materials due to its nature of non-contact method, allowing for full-field displacements and strains to be accurately measured. The purpose of this study is to examine the potential employment of DIC in performing the standard direct shear test by using a modified box to observe and measure the shear properties of a soil sample. Accessible tools (e.g., a consumer grade DSLR camera) and DIC open-source software were employed in this study in order to monitor every portion of the speckled pattern during deformation and tracking the relative displacements. While it is often difficult to separate the relative contributions of individual error sources in any optical technique, we propose the use of two different validation methods for assessing the accuracy of DIC: the noise-floor and the direct comparison with a second trusted source, like transducers. The results of the conducted study demonstrate that the DIC technique implemented on a properly prepared direct shear laboratory setup opens up new possibilities for the effective and accurate analysis of deformations in soil materials under direct shear loading conditions. The calculations of the noise floor of the setup and speckled pattern in terms of the mean and distribution of the displacements showed validated results with STD of 0.001 and 0.0012 mm for the horizontal and vertical planar components, respectively. The displacements measured by DIC showed good agreement with the results of the transducer with an average error of 0.1 mm.

G. Alhakim, C. Nuñez-Temes, J. Ortiz-Sanz, M. Arza-García
Applications of GIS in Estimating the Probable Maximum Earthquake Magnitude for Amaravati Region, Andhra Pradesh, India

An earthquake magnitude and their sizes have a significant impact on damage at a particular site. Hazard analysis provides the insights for vulnerability statistics of the area that is considered under study. Several important parameters including probable maximum earthquake magnitudes (Mmax) are required to quantify the seismic risk. In this study to estimate the Mmax an area of 500 km radial distance has been considered as a seismic study area keeping a center latitude of 16° 52′N and longitude of 80° 51′E. An earthquake catalogue prepared for the period of 221 years, the earthquake data collected from 1801 to 2022, and the historical earthquake data has been collected from several data sources in order to investigate the seismicity of the area. The declustering techniques are used to remove the dependent events from earthquake data. All different earthquake magnitudes are converted into a moment magnitude (Mw) using empirical relations. To estimate the seismic hazard parameters the catalogue completeness analysis was carried out; for this entire catalogue grouped into six different magnitude ranges with a constant bin width of 0.5 Mw. The whole extended study region has been separated into four source zones and designated with zone 1, 2, 3, and 4 based on estimated hazard parameters. The Mmax was estimated considering the data from each zone using Gupta and Kijko-Sellevoll-Bayes (KSB) methods. It has been observed that the obtained Mmax is varying from 6.1 to 6.9 Mw according to Gupta’s method whereas as per the KSB method the estimated Mmax varies from 6.0 to 7.7 Mw. The subzone-2 is contributing the highest value of Mmax compared to other zones. The estimated Mmax can be used further to quantify the seismic hazard risk of the Amaravati region.

M. Madhusudhan Reddy, R. Siddhardha, G. Kalyan Kumar, R. Suresh
Assessing the Effect of Land Use Land Cover Change on the Water Quality Index of a River Basin Using GIS and Remote Sensing Techniques

Water pollution is a major issue faced in both developed and developing countries. Land use land cover changes in urbanization, industrialization, and agricultural processes tend to have negative impacts on water quality at all scales. The water quality index serves as a commonly employed instrument for addressing data organization issues and assessing the effectiveness of management approaches aimed at enhancing water quality. The objectives of this study are estimation of water quality index (WQI) from water quality parameters for the study site using various methods and in determining the influence of land use land cover (LULC) change in water quality for the site. Using WQI, the classification of water quality can be done. GIS and remote sensing technology is used for estimating the LULC change for two time periods. The water quality parameters for calculating the WQI are collected from the Kerala State Pollution Control Board. Estimating WQI and identifying the relationship between LULC and water quality is important for effective and sustainable surface water quality management especially in reducing the pollutant concentration in water body.

W. S. Adhima, J. S. Gouri, Pooja N. Raj, P. S. Riya, Lini R. Chandran
Assessment of Fluctuations in Pre-monsoon and Post-monsoon Ground Water Levels in Kurukshetra, Haryana

Analyzing the trajectory of hydrological indicators is crucial due to significant reduction in water supplies, as well as the rise in demand. The aim of the current study is to evaluate the status of ground water levels in Kurukshetra district at all the seven Blocks viz. Thanesar, Shahbad, Pipli, Babain, Ladwa, Pehowa, Ismailabad for past one decade i.e., from 2010 to 2020. The current study examines ground water variation and trend analysis during the Pre-Monsoon and Post-Monsoon seasons. Also, Inversed Distance Weight (IDW) interpolation approach was used for creating ground water contour maps by using the Arc-GIS 10.8. Results depict that in the Pre-Monsoon study Ismailabad block reflected maximum fluctuation and Pehowa Block reflected minimum fluctuation. In the Post-monsoon study Pehowa Block reflected maximum fluctuation and Ladwa block reflected minimum fluctuation. For Pre-Monsoon, the rate of Groundwater depletion for one decade at seven blocks of Kurukshetra viz. Thanesar 38.88%, Shahbad 27.34%, Pipli 31.86%, Pehowa 6.44%, Ladwa 25.67%, Ismailabad 29.55%, Babain 29.52%. For the Post-Monsoon the rate of Groundwater depletion for one decade for seven blocks of Kurukshetra viz. Thanesar 46.97%, Shahbad 30.32%, Pipli 28.47%, Pehowa 51.58%, Ladwa 25.57%, Ismailabad 36.14%, Babain 27.97%. Average rate of Groundwater Depletion during Pre-Monsoon and during Post-Monsoon seasons for one decade in Kurukshetra district is 27.03%.and 35.28% respectively. As a result, regional entities must design a framework for sensible use of ground resources, with effort made to increase groundwater recharge in order to ensure enough groundwater in the future.

Vikas Singh, A. K. Prabhakar
Assessment of Land Use—Land Cover Changes in District Dehradun (1991–2021)

The region of district Dehradun in Uttarakhand, India has shown a rapid growth in population and urbanization in the last few decades. An attempt was made to assess the land use-land cover (LULC) changes in the entire district in the last 30 years from 1991 to 2021. Satellite imagery from the Landsat—5, 8 with a spatial resolution of 30 m was used as the remotely sensed data and the open-source software QGIS was used to process the data and produce the LULC maps and other important statistics using the maximum likelihood algorithm. The study has shown that during 1991–2021, dense forest, active cropland and sparse vegetation areas have decreased by 17.52%, 62.11% and 7.50% respectively whereas built-up and bare soil areas have increased by 112.23% and 44.32% respectively. No definite conclusions regarding change in areas could be reached for water and dry river bed but in general, the total stream flow area was observed to be decreasing. The average overall accuracy of the classifications was found to be 85.01% with a kappa coefficient of 0.794.

Madhusudan Thapliyal, A. K. Prabhakar
Comparison of Streamflow Simulations for Different DEMs

Hydrological modeling of the rainfall-runoff process is crucial not only for understanding the characteristics of a basin but also for sustainable planning and management of water resources. Most of the hydrologic models require digital elevation model (DEM) as the prime input, from which the basin and its stream network are delineated by using GIS tools. DEMs from various satellite imageries like Cartosat, SRTM, ASTER, IKONOS, and others have been widely used for such purposes. However, the primary challenge is the selection of an appropriate source of DEM, since the accuracy produced from satellite imageries varies. This study aims to compare the streamflow simulations in the Chaliyar basin using a HECHMS model developed from two different DEMs. The Cartosat-DEM and ASTER-DEM are considered for comparison. Results of the study show that Cartosat-DEM gives a clear watershed boundary and area of 2912 km2 which is very close to the India-WRIS data, whereas the ASTER-DEM gives slightly better results in simulating the streamflow based on performance measures of the model.

Nagireddy Venkata Jayasimha Reddy, R. Arunkumar
Comprehensive Analysis of Impact of COVID-19 Lockdown on Air Quality in Andhra Pradesh, India

The Novel Corona Virus Disease (COVID-19) initially observed in Wuhan city of China in 2019 induced a severe risk globally. In a drastic response to the COVID-19 pandemic, the entire country was under social and travel lockdown from 25/03/2020 to 14/04/2020 (21 days), which was extended until May 3, 2020. This lockdown had a significant influence on both the local and global economies, and it will take some time for things to return to normal. However, one major advantage of this lockdown has emerged an increase in the air quality of cities around the world. Therefore, regarding the current situation, in our study, we have analyzed the impact of lockdown on air quality in the state of Andhra Pradesh (Amravati, Rajamahendravaram, Tirupati and Vizag) and also source identification to above mentioned areas during lockdown period. The study results emphasized a statistically significant decline in pollutant concentration. Average Air Quality Index of Vizag declined more by ~34% (96.67–63.52) when compared with Amaravati by ~26% (66–48.78), Tirupati by ~31% (83.8–52.75), Rajamahendravaram by ~4% (60.95–56.59). Future this study identified the potential sources during lockdown towards study areas with the application of HYSPLIT Back Trajectory Analysis (BTA) found that majorly from Bay of Bengal, within the state and partially from surrounding regions Odisha, Tamilnadu, Chhattisgarh, and Telangana.

Donthi Rama Bhupal Reddy, Ramannagari Bhavani
Development of Mobile Application for Assessing Urban Heat Island (UHI) Using Geospatial Techniques a Case Study of Chennai City

Urban Heat Island (UHI) is the phenomenon where urbanization results in an increase in surface temperature among different locations within the city. UHI hotspots not only lead to poor air quality and make people’s health at higher risk, but they also tend to magnify the heat stress and level of thermal discomfort experienced by the people. This study aims to find the UHI spots using thermal remote sensing based on satellites, for the estimation of surface temperature, over a continuous spatial and temporal scale and to develop a mobile application indicating the spatial pattern of UHI and heat stress. Wet Bulb Globe Temperature (WBGT) data collected at various locations across Chennai city was evaluated to obtain the indices reflecting risk levels of heat stress in each area. This was subsequently analyzed in a GIS environment, along with the disaggregated Land Surface Temperature (LST) data, to arrive at valuable information that was used to delineate the hotspots of high heat stress and UHI intensity in the city. Finally, this data was exported to a mobile platform (Android) and an application indicating the spatial pattern of UHI and heat stress was developed, which shows the heat risk zones, mitigation measures, etc. This study confirmed the existence of UHI effect in Chennai city during summer. Temperature difference was found to be even as high as 6–7 °C in many parts of the city. The intensity of UHI was established to be strongly dependent on urban factors such as the density of built-up areas, vegetation cover and presence of water bodies. It was shown that such adverse heat conditions deteriorated the urban environment causing health problems. The results of this study indicate that the highest thermal stress is found in the South-Western and Northern part of the city, which is predominantly crowded, constructed (built-up), industrial and commercial areas.

S. Jayalakshmi
Drones as an Alternate Communication System During Calamities

In this age of rapidly advancing technology, numerous concepts have captured the attention of researchers, and drone technology is no exception. Researchers are significantly captivated by the myriad uses of drones, encompassing civil applications such as the scrutiny of power infrastructure, surveillance of wildlife, transportation of medical supplies to remote locales, identification of forest fire outbreaks, and assessment of landslides. Additionally, they are intrigued by the military potentials, including real-time monitoring, surveillance operations, patrolling activities, and demining efforts. Despite the wide range of applications already explored, some countries still have untapped drone potential. One such area is the utilization of drones as communication relays during natural disasters when conventional communication lines are disrupted. This approach could prove highly beneficial in rescuing affected individuals, as the aerial node created by drones would enable people to communicate with rescue teams using mobile phones or ordinary landline telephones, even when devastating natural calamities like tsunamis, earthquakes, or floods have destroyed traditional communication towers.

D. S. Vohra, Pradeep Kumar Garg, Sanjay Kumar Ghosh
Drought Analysis of an Area Using Google Earth Engine

Drought is a long period of low rainfall which affects the growth of plants and living organisms. Drought occurs when an area or region suffers below-average rainfall or a water deficit for a prolonged time period. It is one of the most complex environmental disasters across the world. Drought also creates the same impact like floods or cyclones. Drought is categorized as meteorological, hydrological, agricultural and socio-economic. The area which experiences the precipitation deficit subjects to meteorological drought. Reduction in stream flow, ground water, and reservoir and lake levels indicates Hydrological drought. Soil water depletion causes Agricultural drought. The effect caused by the meteorological, hydrological and agricultural drought on people and economic activities is termed as socio-economic drought. This study is focusing on meteorological drought. Standard Precipitation Index (SPI) and Drought Severity Index (DSI) are used to calculate meteorological drought.

Jyothsna Devi Adapa, Keesara Venkatareddy
Effects of Urbanization on Land Use Land Cover of Warangal Region Using RS and GIS

Rapid expansion of urbanization has increased the population and economic growth of towns and cities in various parts of the country. This increase in urbanization has affected the natural resources such as vegetation and water bodies. In the present study, the effects of urbanization on LULC (Land Use Land Cover) changes of Warangal urban and rural areas are studied for the years 2014, 2017 and 2020 for a span of 6 years using the RS and GIS techniques. LANDSAT imagery of 3 years is collected and enhanced and LULC data is extracted for four classes i.e., urbanization (built-up land), agriculture cum forest (vegetation), bear soil (barren land) and water bodies. RS and GIS tools are used to compare and analyze the effect of urbanization. LULC feature extraction is made for urban and rural areas of Warangal region using supervised classification to study the growth of urban areas and its effect on LULC changes. The results indicate a drastic increase in urbanization and barren land, severe decrease in vegetation and a very slight increase in waterbodies. Increase in urbanization and decrease in agriculture cum forest indicates vegetation reduction and built-up area increment which directly affects the climate and environment. Warangal region is being affected due to the rising population and the improper usage of land. The quantitative results obtained explain the effect of urbanization on LULC changes of Warangal rural and urban areas, which helps in the best management and planning of land use for Warangal region.

Ch. Sree Laxmi Pavani, Keesara Venkatareddy, S. Joshmitha
Effect of LULC Changes on Land Surface Temperature

The rapid urbanization of cities has led to significant human-induced alterations to the environment, characterized by the replacement of natural land cover with man-made structures such as concrete, bricks, asphalt, and metal. This transformation disrupts the natural processes of evapotranspiration, resulting in reduced cooling effects and increased heat storage within urban areas. This study involves the Land Surface Temperature (LST) variation over different classes of Land Use Land Cover (LULC) and the effect of change in LULC over the past two decades in and around Hyderabad City, Telangana, India. This is a Tier-1 Indian city experiencing notable LULC changes from the past two decades due to rapid Urbanization. This study examines how urbanization has affected the surface temperatures from the past twenty years, using Landsat 7 and Landsat 8. Spectral indices such a LULC, Radiance, Brightness temperatures and Land Surface Emissivity (LSE) have been generated and utilized for the generation of LST. A substantial change of vegetation increased by 28.92% from 2012 to 2022 period. And also, an urban area increasing by 108.8% but waterbodies have decreasing and increasing patterns in the period of 2012–2022. It is advised to implement efficient urban planning and design solutions to lessen the negative consequences of LST changes caused by LULC. Green space inclusion, vegetation restoration, cool pavement and roofing techniques, and sustainable urban design techniques are among those to be employed in order to reduce the effect of these temperature changes.

Rajashekar Kummari, Pavan Kumar Reddy Allu, Shashi Mesapam, Ayyappa Reddy Allu, Bhargavi Vinakallu, Bhanu Prakash Ankam
Estimation of Aerosol Direct Radiative Forcing in Southern India

The Aerosol Direct Radiative Forcing is a prominent parameter which is used to assess the effect of aerosols on temperature. Previous studies have shown the calculation of ADRF under clear sky conditions and model simulations to know the impact on changes in temperature. In the current study, a novel method is implemented to estimate ADRF under all-sky conditions using Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data. The radiation diagnostics of MERRA-2 provide downward short wave and long wave fluxes under all-sky conditions but not the upwelling fraction of longwave radiation after interacting with the atmosphere. The upwelling fraction is estimated by factored method and difference method in this study and the time series is compared with the available downward flux data. The upwelling longwave flux data from the factored method is found to be appropriate in terms of matching the time series when compared to the data from the difference method. The estimation is carried out for five grid points, each from five climate zones of the study area and the times series plots have shown a better insight on the implemented factored method for the estimation of longwave flux. The ADRF is calculated using the available shortwave fluxes and estimated longwave fluxes at three different levels of atmosphere namely Top of Atmosphere (TOA), Surface and within the atmosphere for the year 2019. The ADRF at TOA and at surface level show that the warm semi-arid and sub-tropical oceanic highland climate regions have experienced higher ADRF when compared to the remaining climate zones. The ADRF in the atmosphere shows that positive ADRF was seen in the same climate regions. This illustrates that the rate of heating is more in the warm semi-arid and sub-tropical oceanic highland climate region in the year 2019.

K. Tharani, Deva Pratap, Keesara Venkatareddy, P. Teja Abhilash
Estimation of Groundwater Potential Zones in Southern Dry Agro-Climatic Area Using Geoinformatics and AHP Technique

The world's demand for groundwater has been severely strained by overuse of groundwater and major climatic change over time. As the global need for drinking water for human consumption, agriculture, and industrial applications grows, so does necessity to assess groundwater. Due to the quick access to data, analysis, and knowledge, they give about resource for further improvement, GIS-based studies have grown in importance in groundwater research in recent years. In order to identify the groundwater potential zone of southern dry agro-climatic area of Mysuru and Mandya District, India, the current study has been carried out. A total of 15 theme layers were established and researched to help define groundwater potential zones. Depending on respective attributes and water potential capabilities, Analytic Hierarchy Process determines weights allocated to each class in all thematic layers. Utilizing data on groundwater prospects in area (CGWB), study's output was cross-validated, and total accuracy of methodology was 80.4%. The resulting groundwater potential zone was divided into three classifications: high, moderate, and low. According to the research, a moderate groundwater potential zone encompasses 65.8% of study area. There are zones with low and high groundwater potential in 6.75% and 27.43% of the area, respectively. The R2 value of 0.8 further demonstrates that estimated groundwater potential index and groundwater level values in recommended AHP model are quite reliable in predicting the outcome. The demarcation of groundwater potential zones has been highlighted as a critical step towards achieving Sustainable Development Goals (SDG 6 and 13), contributing to the implementation of sustainable water and land management.

A. B. Gireesh, M. C. Chandan
Evaluation and Prediction of Land Use and Land Cover Changes in the Kumaradhara Basin, Western Ghats, India

Land use land cover (LULC) is considered as the most significant and obvious indicator of changes in ecosystems. An understanding of current and potential future development opportunities is provided through analysis on the spatiotemporal shifting patterns of LULC and simulation of future scenarios. Kumaradhara river flows in the Western Ghats in southern peninsular, India. It is the major tributary of the Netravathi river, and the catchment has numerous perennial streams and is dominated by dense evergreen forests with high conservation value. In the present study, an integrated approach of remote sensing and geospatial techniques is used to assess LULC changes for the period of 2010–2020, and prediction of future LULC change was carried out by ANN model using MOLUSCE plugin of QGIS for the year 2025. The results have shown that the build-up land has increased considerably, and forest has decreased which is evident from the increase in cultivated land. The predicted LULC showed an increase in built-up land and a significant transformation of barren land. The results of this study indicate significant changes in the LULC pattern.

N. Roopa, N. Namratha, H. Ramesh, K. C. Manjunath
Evaluation of Surface Soil Moisture Using Remote Sensing and Field Studies

Soil moisture (SM) is an important quantity to examine in terms of agriculture, meteorology, and hydrology to understand the evaporation cycle and drought mechanisms. This study aims to estimate surface soil moisture in arid areas using Sentinel-1A SAR data. In order to collect soil samples from sampling grids that are synchronized with Sentinel-1A passes, study area is divided into 80 grids, each measuring 10 m by 10 m. Six SAR images were collected from Copernicus Open Access Hub website. The vegetation index (NDVI) was calculated using a Sentinel-2A image. The SNAP software was used to process the SAR images, and R studio was used to extract NDVI values and backscattered energy of each sample grid. In this study, an empirical equation was developed to model surface soil moisture using the dielectric constant and backscattering coefficients. The performance of the model was assessed using statistical indicators such as the coefficient of correlation, Nash–Sutcliffe efficiency, and root mean square error, which yielded results of 0.85, 1.46, and 0.75, respectively.

T. N. Santhosh Kumar, Abhishek A. Pathak
Evaluation of the Influence of Land Use and Climate Changes in Runoff Simulation Using Semi-Distributed Hydrological Model

Water resources must be managed effectively to meet current and future demands, ensure sustainability, and meet the needs of a growing population. Identification of the characteristics of resources in the basin, such as the land use land cover (LULC), climatic parameters, and runoff, makes it possible to manage water resources for a long time. In this study, using the hydrological model, Soil and Water Assessment Tool (SWAT), a separation strategy, was implemented in the Meenachil River basin in the Kottayam district of Kerala to differentiate the effects of change in climate and LULC on runoff. The calibration and validation of the SWAT model were facilitated by runoff data available at gauging station Kidangoor within the study area from 1987 to 2010 for the calibration (1987–2004) and validation periods (2005–2010), respectively. Four distinct scenarios were examined to determine the relative impact of LULC and climate on runoff. The findings showed that the variation in streamflow over the study area is significantly affected by climate change (84.86%), with land use having a 15.13% influence.

M. S. Saranya, Vinish V. Nair
Flood Damage Assessment of a River Basin Using HEC-GeoRAS

Flood is one of the most catastrophic events among the many different types of natural hazards. It seriously harms people, property and places used for industry and agriculture. A GIS extension called HEC-GeoRAS provides a series of steps, tools and options for preparing river geometry grid data for input into HEC-RAS, which is utilised to create the final inundation map. The DEM and a Basin Landuse Map must be provided as input data for the preparation of river geometry using HEC-GeoRAS model. The flood hydrograph is derived from the synthetic unit hydrograph and probable maximum precipitation, and the PMP value obtained was about 157.3 cm. The total area of the basin was found to be 787 km2 in which the inundated area was 274.279 km2, which is about 35.851% of the total area.

K. C. Amal Vishnu, Vinish V. Nair
Flood Hazard Mapping for Amaravati Region Using Geospatial Techniques

Floods pose a significant natural hazard that can cause extensive damage to infrastructure, property, and human life. The use of geospatial techniques, such as remote sensing, Global Positioning Systems (GPS), and Geographic Information System (GIS), has become increasingly important for flood hazard mapping. The research paper aims to develop flood hazard maps for the Amaravati region, the new capital city of Andhra Pradesh, India, using geospatial techniques, including an Analytic Hierarchy Process (AHP). The region is susceptible to floods due to its location and topography, which includes low-lying areas and water bodies. In the present study, remote sensing techniques were employed to extract information on land use, land cover, topography, and drainage patterns, and GIS to integrate this information with other relevant data, such as rainfall and river flow data, to develop flood hazard maps. Additionally, the study utilized the AHP process, a multi-criteria decision-making method, to weigh and rank various factors involved in the development of the d hazard maps. The AHP process provided a structured and systematic approach to prioritize the importance of different variables and factors in the flood hazard mapping process. The developed maps provide valuable information for decision-makers, urban planners, and emergency management agencies to plan for and mitigate the impact of potential flood events in the region. The AHP process, in combination with geospatial techniques, contributed to the accuracy and reliability of the flood hazard maps. By utilizing geospatial techniques and the AHP, this research paper contributes to the existing knowledge on flood hazard mapping. The findings provide valuable insights that can be applied in flood risk management and disaster preparedness in the Amaravati region.

Sampath Kumar, Talari Reshma, Savitha Chirasmayee, Kasa Priyanka, Kokku Priyanka, Gokla Ram
GIS and RS-Based Soil Erosion and Sediment Yield Modelling in Manikpur, Chhattisgarh, India

The Manikpur coalfield is 300 km2 and is in the Korba district of the Indian state of Chhattisgarh. In India, one of the most severe issues is soil erosion. Calculating exact soil erosion over a specific time is extremely difficult. Huge quantities of mining waste are typically released as over burden dump (OBD) materials by opencast mines. They impact agriculture since they are prone to soil erosion, sedimentation, and poor water quality. An empirical equation of the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Delivery Distributed Model (SEDD) were employed to quantify soil erosion and sediment yield. The findings of these equations were contrasted to those of direct field measurements obtained around the opencast region utilizing an appropriate suspended sediment sampler. The maximum soil erosion value obtained is 79.2 tons/ha/year, and the maximum sediment yield is 57.92 tons/ha/year, according to the findings of this study. The sediment load values from these two models follow the same trend. These models were evaluated for performance and found to be effective, with values of simulated and observed sediment yields R2 = 0.81 and RRMSE = 0.66. The observations revealed that most of the area has a low slope gradient. The opencast mine and overburden dump area have a slight erosion potential due to the higher slope inclination. According to the study, GIS is an effective tool for modelling soil erosion potential and sediment output.

B. Himajwala, A. D. Prasad
Groundwater Level Trends Over Southern India

Groundwater is essential for obtaining freshwater and plays a crucial role in promoting sustainable development in agriculture, industry, and the socioeconomic status of an area. However, due to the extensive use of groundwater, many areas in India are facing a decline in their groundwater levels. Groundwater level time series analysis aids in detecting trends, analyzing behavior, and determining the causes of water level decline. We considered four seasons for identifying the trends in groundwater levels i.e. Post-Monsoon Rabi, Monsoon, Pre-Monsoon and Post-Monsoon Kharif seasons. Using Mann–Kendall test, analysis of trends for Southern India which consists of 8 states was performed. Data on the piezometric level of 181 observation wells from 1996 to 2018 has been taken into consideration. The significant declining trend was observed in 47 observation wells in monsoon season, 61 wells in post-monsoon Rabi, 27 wells in post-monsoon Kharif and 45 wells in pre-monsoon from the results. Out of all wells only one well exhibited increasing trend over 8 states. The outcomes of the study are going to help the groundwater development authorities in the respective states for resource management, water supply planning, groundwater recharge management, environmental protection and policy formulation and regulation.

Kotapati Narayana Loukika, Keesara Venkatareddy, Eswar Sai Buri
Impact of Climate Change on Streamflow Over Nagavali Basin, India

Natural disasters such as cyclones pose a serious threat to the Indian coast. The Nagavali basin is an interstate east-flowing river that supports agricultural and domestic water demands in Koraput, Kalahandi, and Rayagada districts in Odisha, as well as Vizianagaram and Srikakulam in Andhra Pradesh. Furthermore, this basin is especially prone to cyclones generated by low-pressure depressions in the Bay of Bengal. The present research aims to simulate the streamflow of the Nagavali basin using the SWAT model and to provide historical information as well as future changes within streamflow in response to climate change. Calibration (1991–2005) and validation (2006–2014) of the SWAT model showed a satisfactory for monthly streamflow. The downscaled bias-corrected geographically separated the NASA NEX-GDDP dataset was employed for simulating the future streamflow under two RCP scenarios, 4.5 and 8.5. The analysis periods were divided into 27-year blocks that included a historical period (1980–2005) as well as three future periods, namely near term (2022–2047), the middle future (2048–2073), and the far future (2074–2099). Under both scenarios, the CNRM-CM5 model predicted a rising trend in precipitation and streamflow. Under RCP 4.5, the CNRM-CM5 model showed the greatest percentage change of 22.06% in the far future, with a corresponding streamflow change of 36.26%. Under RCP 8.5, the BNU-ESM, CNRM-CM5, and IPSL-CM5A-MR models represent percentage change in precipitation ranging from 22.09 to 26.28% and corresponding streamflow ranging from 33.81 to 45.11%, respectively, in the far future. Peak discharges are estimated at various return periods with Log Pearson Type III probability distribution. The estimated peak discharge (5626 m3/s) of the 100-year return period was observed in 2006. This study findings are useful to water resource managers.

Nageswara Reddy Nagireddy, Keesara Venkatareddy
Impervious Surface Area Prediction Using Landsat Satellite Imagery and Open Source GIS Plugin

In India, population growth is rapidly increasing and the rural people are moving to urban areas for improving their socio-economic activity of life. For sustaining the human needs, most of the land use land cover features are migrating to impervious surfaces, which may lead to decreasing the infiltration capacity of the soil and increasing the flood frequency. Land Use Land Cover (LULC) maps are helpful to monitor and predict the impervious surface area using the Remote Sensing techniques. The proposed work aims to simulate the impervious surface area of Jagtial, Telangana, India, in the year 2050. This is accomplished by using Landsat satellite images from the years 2000, 2005, 2010, 2015, and 2020, and applying the Random Forest classification algorithm to generate LULC maps. The maximum tree depth is set at 30, the maximum number of trees is 250, and the maximum number of samples per class is 1000. A land use simulation model, based on Cellular Automata and Markov Chains, is employed to calibrate and optimize the LULC images. The model predicts the LULC map for the years 2020 and 2050, which are validated using existing classified LULC images. The imperviousness index of the LULC classes is used to estimate the impervious surface area of the location. The analysis of the multi-temporal LULC images shows that biophysical and socioeconomic factors have a significant impact on the increase in built-up areas and the decline in water bodies by the year 2050.

Ayyappa Reddy Allu, Shashi Mesapam
Influence on Water Characteristics Away from Various Sources of NIT Kurukshetra Using ArcGIS

In this paper we assess the characteristics of various water sources of the NIT Kurukshetra campus using ArcMap 10.8 Software. Water Quality Index (WQI) is used to evaluate the drinking water quality from different sources on the NIT Kurukshetra Campus using the Weighted Arithmetic Method. A way of rating water quality is the Water Quality Index. It was done to determine the area’s overall groundwater quality significance. It is a useful instrument for determining the quality of groundwater. Electroconductivity, color, odor, taste, pH, Chlorides (Cl), total dissolved solids (TDS), total alkalinity (TA), and total hardness (TH) are used in this study to calculate the quality of water at NIT Kurukshetra Campus. Water quality measurements were gathered at five distinct places on the NIT Kurukshetra Campus. The results revealed that all of the stations have Excellent water quality, according to the values of the WQI although the readings of most of the sources measured are above acceptable and occasionally permissible limits also but the water quality still comes out as excellent. The data from the evaluation was then processed using ArcGIS’ spatial analysis function in which the Kriging technique of Interpolation is used from which various spatial distribution maps for various water source locations were constructed after selecting the appropriate interpolation strategy. Using Image Overlapping, the variation of physicochemical characteristics of some parameters with length is also determined.

Rahul Deopa, K. K. Singh
Landslide Hazard Zonation Mapping Using Remote Sensing and GIS in Mountainous Terrain

Landslides are a devastating natural phenomenon that can cause significant damage to people, property, and infrastructure. Various physical, geological, climatic, and tectonic factors can contribute to landslides in different parts of the world. In addition to natural causes, improper construction and chaotic development can also lead to landslides and the destruction of property and lives. Landslide hazard zonation (LHZ) is a method of dividing a landmass into homogeneous zones and ranking. Landslides are a pervasive and destructive hazard in the Himalayan regions. While they cannot be completely eliminated, their effects can be minimized. This study focuses on the Garhwal Himalaya region to identify areas prone to landslides. Geographical Information System (GIS) was used to create a database, analyze, and generate output. LISS III images were used to create the land use land cover (LULC) map and Landsat satellite data was used to identify. This research paper aims to integrate various techniques and tools to generate a geospatial database for landslide hazard zone delineation in the study area. LISS III images were used for land use land cover (LULC) mapping and Landsat satellite data for lineaments identification. The Analytical Hierarchy Process (AHP) approach was used to determine the weights of the landslide influence parameters. ERDAS Imagine and ArcGIS software were used to integrate the input layers after assigning them suitable weights. The primary objective of this research paper is to combine the various existing methods and tools to create a Geo-spatial database for delineating landslide hazard zones in the study area. The resulting map's susceptibility to landslides has been divided into five categories, namely very low, low, moderate, high, and very high. This LHZ map can be of great benefit to planners and designers in selecting the most appropriate route paths.

Dolonchapa Prabhakar, Anoop Kumar Shukla, Babar Javed, Satyavati Shukla
Modeling Daily Streamflow from Idamalayar Catchment Using SWAT

SWAT, a semi-distributed, continuous, and process-based hydrologic model, is used for many applications such as streamflow simulations, water quality modeling, sediment yield modeling, etc. It requires spatial as well as temporal data as input. The present study examines the application of SWAT in simulating the daily streamflow from the Idamalayar catchment, Kerala. The model was simulated from 1987 through 2017 using daily meteorological data keeping three years as a warm-up. To calibrate and validate the model, a stand-alone tool, SWAT-CUP, is used. The model's capability to reproduce daily streamflow was assessed by means of the four performance- measures, which are R2, NSE, PBIAS, and RSR. The values of these indicators turned out to be 0.64, 0.61, 22.5, and 0.63, respectively, in calibration, and while validating, these values were found to be 0.75, 0.67, 36.9, and 0.58, respectively. These values show that the model reasonably simulated the streamflow, especially at a daily time scale. Global sensitivity analyses showed that the effective hydraulic conductivity in main channel alluvium is the most sensitive parameter, followed by the SCS runoff curve number.

C. Reshma, R. Arunkumar
Modelling the Low Impact Development Alternatives for Rainfall Runoff Reduction

In order to control storm water overland runoff, which in turn regulates flood volume and flow rate, one of the surface runoff mitigation and treatment approaches is Stormwater Best Management Practice (BMP). Sustainable drainage systems (LID) are widely recommended and used in many parts of the world. In the United States and Canada, LID is called Low Impact Development (LID), which is an approach that encourages the interaction of natural processes with the urban environment to keep and rebuild ecosystems for water management. LID can be used to manage stormwater runoff at the property level. In this study four different elements in LID were studied for their efficiency in reducing runoff that include permeable pavement (PP), infiltration trenches (IT), bioretention cells (BC), and rainwater barrel (RB) storage. Hydrological performance of these LID practises in the storm water network were performed using PCSWMM which is considered one of the most promising hydrological models.

B. Aneesha Satya, M. Shashi, Allu Pavan Kumar Reddy
Performance Evaluation of Support Vector Machine and Random Forest Techniques for Land Use-Land Cover Classification—A Case Study on a Mili Scale Agricultural Watershed, Tadepalligudem, India

Land Use-Land Cover Mapping, obtained at a specific time, plays a crucial role in planning and monitoring both regional and global surfaces of the earth. For monitoring and analysis of small-scale agricultural watersheds with an area of less than 10,000 ha, a Land Use-Land Cover (LULC) classification that is nearly accurate is required. With the availability of Sentinel-2 datasets with spatial and temporal resolutions of 10 m and 5 days, LULC mapping and monitoring can be improved. However, conventional methods of classification are unable to demonstrate real features. In recent years, the introduction of machine learning techniques has made it possible to classify LULC effectively and efficiently, particularly for watersheds on the milli-scale. Therefore, in the present study, LULC maps are obtained for an agricultural watershed in Tadepalligudem, West Godavari district, Andhra Pradesh, using supervised Machine Learning methods. To highlight the importance of machine learning in LULC classification for a milli-scale watershed, Support Vector Machines (SVM) and Random Forests (RF) are compared with conventional Maximum Likelihood Classification methods. LULC was calculated using Sentinel-2 data acquired from the United States Geological Survey for three months in 2020. The field observations detected a total of four classes, and the training datasets were obtained using both visual inspection and field observations. Using Overall Accuracy, Kappa Coefficient, and R-Squared values, the accuracy of the LULC maps relative to the ground truth is determined. The study reveals that the overall accuracy of SVM and RF is 87.5 2.00 and 85.5 2.00, respectively, whereas it is 70.87 1.80 for Maximum Likelihood classification. The mean Kappa coefficient values for SVM and RF are 0.86 and 0.85, respectively, while for maximum likelihood classification, it is 0.67. The observed average R-squared value for the support vector machine is 0.67, whereas it is 0.69 for the RF. In addition, it is observed that SVM performs admirably among the three classification methods.

Chirasmayee Savitha, Talari Reshma
Photogrammetric Survey of an Intertidal Area: A Case Study in NW Spain

For years, bathymetry technique has been employed to obtain georeferenced data of the depths of the water using an echo sounder on board. This led to some problems in shallow water because it requires a shallow draft boat, but thanks to technological advances, in recent years, Unmanned Aerial Vehicles (UAVs) are used for a wide variety of applications, including bathymetry in these context. There are recent works that propose its use through multispectral data or photographic images. These methods allow much more complete and precise work to be carried out, since data collection could not be possible through traditional methodology. In the present work, a combination of the data obtained by photogrammetric survey with UAV is made for the zones that are characterized by a shallower depth and bathymetric survey with a low-cost sounder (fishing sounder) for the deeper zones. From the combination of both methods, the bathymetry of the intertidal zone of the Pontedeume estuary (Spain) is obtained. In this way, Digital Terrain Model (DTM) and bathymetry are performed, which provides complete information of the morphological characteristics created by sea currents.

M. Gil-Docampo, S. Peña-Villasenín, S. Peraleda-Vázquez, R. Carballo, N. Gómez-Conde
Potential Zones Identification to Effectively Exploit Solar and Wind Energy in the State of Assam—A MCDA Approach Using GIS and Remote Sensing

With the frequent coal shortages, increased demand and rising global warming comes the need to switch to renewable sources of energy. Assam being rich in terms of Solar and Wind potential, the untapped energy needs to be harnessed in a sustainable manner. In this study the requirements for solar to produce maximum possible output will be understood and using the tools of GIS the best locations for solar and wind system installation will be found using the criterions for efficient harnessing of renewable energy. In order to accomplish this, 10 different criterions for Solar are considered that include Horizontal Irradiance, Average Annual Temperature, Distance from Power Transmission Lines, Distance from Residential Area, Elevation, Slope, Average Annual Cloud Cover, Humidity, Aspect. Similarly, for Wind 7 different criterions are considered which includes Wind Speed, distance from power transmission lines, Distance from Roads, Distance from Residential Area, Slope, Distance from Airports, Bird Sites. By performing weighted overlay analysis using AHP model, the suitable areas are defined and undesirable regions are excluded from suitability map for both Wind and Solar results.

P Taniya Raj, N. S. R. Prasad
Prediction of Soil Organic Carbon in Unscientific Coal Mining Area Using Landsat Auxiliary Data

Unscientific coal mining is affecting soil attributes, deteriorating soil health and crop productivity, and is reflected by the soil organic carbon (SOC) content. The quantification of SOC is challenging with limited resource availability; however, satellite covariance is the alternate source of SOC determination with minimum labour requirement and limited laboratory facilities. An attempt is made to estimate the SOC using Landsat data and a model is developed by evaluating stepwise and enter/removal regression approaches. Fourteen predictor variables were used to build models and evaluate the prediction accuracy. Results showed that the SOC ranges 0.81–2.41% under unscientific coal mine affected sites; NDVI and BSI range 0.16–0.61 and −0.35–0.12 with mean 0.32 and −0.03, respectively. SOC is correlated with RI (r −0.33) and GRVI (r 0.34). The enter (all variables in a block enter in a single step) approach linear regression model (Model 3) using multiple variables can explain only 43% SOC (RMSE 0.66 and R2 0.43). The stepwise linear regression model (Model 2) and Model 3 predicted the SOC as 6.94 and 3.78% higher than the actual SOC data. The model performance is increased by using multiple variables which may subside the less number of soil samples.

Naorem Janaki Singh, Lala I. P. Ray, Sanjay-Swami, A. K. Singh
Rainfall Runoff Modeling Using HEC-HMS for Munneru River Basin, India

The aim of this study was to assess the accuracy and suitability of the Hydrologic Engineering Center (HEC)—Hydrologic Modeling System (HMS) in predicting daily streamflows. In this study, we utilized the models that were integrated with the ArcGIS interface for hydrological research for the Munneru River basin, India comes under Lower Krishna River basin covering the drainage area of 10,390 square kilometers. The main focus of the streamflow analysis was to determine the effectiveness of the model when calibrated and optimized using observed flows in simulating gauged streamflows. To run the model, daily weather gauge station data for the 1993–2017 period were used as inputs, along with Land Use/Land Cover (LU/LC) classes generated from remote sensing satellite imagery, a soil map, and a Digital Elevation Model (DEM). To assess model performance and calibration, daily stream discharge data from the Keesara gauge station maintained by Central Water Commission (CWC) which is an outlet of the basin were utilized.

Eswar Sai Buri, Keesara Venkatareddy, K. N. Loukika
Spatio-Temporal Surface Urban Heat Island Effect Analysis Over Tiruchirappalli City, India, Using GIS Techniques

This study investigates the effects of urbanization on the climatic conditions of a region and the occurrence of urban heat islands (UHIs). The study area was analysed for variations in UHI effects during the summer and winter seasons over a 20-year period, and hot spots (HS) and cold spots (CS) were identified. Results indicate that the Land Surface Temperature (LST) is higher during summer nights than winter nights, and rural areas are cooler than urban areas. The study also found significant differences in LST within the study area, with the Cauvery delta experiencing a dip and the BHEL industrial area showing a significant spike in temperature. HS and CS maps were developed for Tiruchirappalli. The findings of this study can provide valuable insights for policymakers and urban planners to mitigate the UHI effects and improve the climate resilience of urban areas.

K. S. Arunab, Ajay Badugu, Aneesh Mathew, Padala Raja Shekar
Simulation of Streamflow and the Assessment of Nutrient Loadings for the Indravati River Basin of India using SWAT

Indravati River basin, a northern tributary of Godavari River, has a catchment area of 44,153 km2 and is shared by the states of Maharashtra, Chhattisgarh, Telangana, and Odisha of India. It is one of the significant river basins for human and ecological needs and helps people through agriculture. However, due to rising nutrient toxicity from excessive agricultural and industrial runoff, a hydrological and water quality model is essential to assess streamflow and nutrient loadings and provide water management scenarios to reduce nutrient toxicity. The present study is focused on the development of a hydrological and water quality model to simulate streamflow, Nitrates and Ammonium ion loadings for the Indravati watershed for the period 2000–2012 using QGIS interface for SWAT (QSWAT) and for performing the Global Sensitivity analysis using SUFI-2 algorithm on SWAT-CUP for assessing the most sensitive parameters which affect the model’s efficiency. SUFI-2 within SWAT-CUP was used to calibrate and validate the model over a monthly time step, with 8 parameters corresponding to streamflow and 6 parameters corresponding to nitrates and ammonium ion loadings in streamflow chosen based on the literature available. The simulation period 2000–2012 revealed a strong correlation between observed and simulated streamflow, nitrates and ammonium ion loadings. Statistical performance criteria using R2 and Nash–Sutcliffe Efficiency (NSE) were 0.65, 0.70 and 0.67, and 0.64, 0.67 and 0.65 for streamflow, $${\mathbf{N}\mathbf{O}}_{3}^{-}$$ loading and $${\mathbf{N}\mathbf{H}}_{4}^{+}$$ loading, respectively. SWAT-CUP calibration and validation techniques provided the best-fitted values for all 14 parameters, 95PPU plots which show the best estimation curves for streamflow and nutrient loads considered, and global sensitivity analysis using t-Stat and P-value. This study has revealed that CN2, GW_DELAY, CH_N2, ESCO, GW_REVAP, and SOL_K are the most significant parameters affecting the streamflow and N_UPDIS, RCN, SOL_NO3, and CH_ONCO_BSN are the most significant parameters affecting the nutrient loadings of the Indravati River basin. There had not been any study of this type on this Indravati River basin. SWAT is used as it provides a flexible structure that allows finding solutions for different water resources, land management, and water pollution problems. The findings of this study would aid in managing land and water resources sustainably for future purposes.

Ch. Venkateswarlu, R. Manjula, P. Yuvaraja, S. Hemavathi
Spatiotemporal Analysis of Agricultural Drought in Krishna River Basin

Agricultural drought is a period of time with decreasing Soil Moisture (SM) which is the main variable to define and identify agricultural drought. However, the actual water content in the soil is very rarely taken into consideration due to the unavailability of fine-resolution SM both temporally and spatially. Many agricultural drought studies for this reason are performed based on hydro meteorological variables like rainfall, temperature, evapotranspiration, runoff, etc. With the advance in microwave remote sensing, Soil Moisture Active Passive (SMAP) Level 3 data is able to provide daily SM estimates at 9 km resolution globally. This study uses SMAP L3 SM along with soil properties data from Harmonic World Soil Database (HWSD) to derive Soil Water Deficit Index (SWDI) for analyzing spatiotemporal agricultural drought in Krishna River Basin (KRB). Agricultural drought has been analyzed for both long-term (yearly) and short-term (monthly, seasonal) in KRB from 2016 to 2021. Temporal analysis of SWDI shows all the years and seasons from 2016 to 2021 in KRB are dry years with 2020 and 2021 having less drought than other years. Though all the seasons and years of the study period are dry, SWDI is able to capture inter-annual and inter-seasonal variation in the basin. SWDI when compared to the Aridity Index (AI) extracted from World Atlas of Desertification, dry/non dry lands captured by AI are justified by SWDI showing extreme dry/mild dry areas. Moreover, this study shows the potential of Remote Sensing SM in agricultural drought monitoring studies.

Hussain Palagiri, Manali Pal
Towards Imaging-based Quantification of Deterioration Using Colour Space Study

This work presents an approach for imaging-based measurement of structure deterioration for M30 grade concrete. The samples are subjected to a variety of concrete deterioration chemicals including 5% concentrated solutions of H2SO4, HCl, NaCl, and MgSO4 for 3, 7, 14, and 28 days, respectively. Red, Green, and Blue (RGB) colour space is not advisable for colour-based detection or colour analysis because of the mixing of colour and intensity information as well as non-uniform features. Hue, Saturation, and Value (HSV) colour space can quantify the surface colour detection of deterioration by the various chemical agents with respect to the duration of the attack. The surface colour change of the concrete cube specimen can be identified with respect to the duration of the attack and the type of chemical involved; meanwhile, it gives the residual strength of the specimen. This method enables the construction of a visual spectrum-based quantification tool for the degree and duration of deterioration by establishing empirical equations.

V. Guru Prathap Reddy, K. Bhanu, T. Tadepalli, Rathish Kumar Pancharathi
Trend Analysis of Climate Variables and Extremes Over Maner River Basin, India

Long-term trend analysis of meteorological variables is required for implementing any hydrological model or a basin. Spatio-temporal variations in precipitation and temperature of a basin are helpful for meteorologists, agriculturists, and policymakers to make appropriate decisions. It is necessary to understand the changes in rainfall characteristics using gridded precipitation data and robust statistical analysis for making decisions. In this study, the long-term trend of climate variables, i.e., precipitation, temperature over the Maner basin is studied during 1951–2020 at seasonal and annual timesteps. The non-parametric statistical methods of Mann-Kendall (MK) tests was performed using IMD daily gridded (0.25 × 0.25) data for 70 years. The magnitudes in the rainfall, temperature, and their extremes (CDD, CWD, PRCPTOT, R10, R20, R95, RX1DAY, RX5DAY, TNN, TNX, TXN, and TXX) are analyzed using Sen’s slope method. The increase trend was noticed at the upper and lower Maner basins successively during the winter and pre-monsoon seasons. At the upper Maner basin, a decline in monsoon precipitation is visible. In terms of annual precipitation and post-monsoon, no significant trend was found. In the Maner basin, there was an upward trend in both the maximum and minimum annual temperature trends. According to an analysis of extreme indices, the annual total rainfall days (wet days) (R95PTOT) were on the rise across the basin, despite the fact that the consecutive wet days (CWD) and dry days (CDD) showed a decreasing trend. While the extreme indices for minimum and maximum temperatures (TNX and TNN) showed no discernible trend, respectively. The TXX and TXN of maximum temperature indices showed an increasing trend. These increasing trends in wet days and extreme temperatures in the Maner basin may be majorly attributed to changes in urbanization in the city of Karimnagar and land use changes in the basin. These all changes experience changes in precipitation patterns, which could have implications for water availability and management in the region.

Koppuravuri Ramabrahmam, Keesara Venkatareddy
Urban Dynamics and Impact Assessment of Bengaluru–Mysuru Expressway Corridor

The focus on the provision of basic amenities and infrastructure has been a major issue in urban planning because of urban growth and sprawl. It is one of the reasons that adversely contributes to the loss of natural resources and encourages unbalanced and uneven urbanization in developing nations like India. The government and planning authorities are increasingly considering regional development to accommodate the incursion of people into downtown urban areas therefore encouraging comprehensive, sustainable development. By a methodological approach and the use of multi-temporal satellite data, this study aims to explain the urban growth along the Bangalore–Mysuru motorway as influenced by the transportation corridor. The objective of the transport corridor development is to increase the efficiency of the corridor's transportation and logistics systems and to spur regional economic growth by taking advantage of better connectivity and transportation infrastructure. A transport corridor can help the region along the corridor achieve more sustainable and spatially balanced economic growth. To analyse the existing development pattern and provide a framework for predicting how land will be used in the future, land use mapping and related data are developed. Later for the analysis, a cellular automata-based model derives the name from the input layers utilized, namely Slope Land use Excluded Urban Transport Hillshade (SLEUTH) was performed to meticulously examine subdivision-level specifics of the area affected by the corridor. The results of this study will aid policymakers and planners in making choices about upcoming urban trends that support a more secure, healthy, efficient, sustainable, and livable urban ecosystem.

S. Suhas, V. Bhavani, B. M. Vishwanath, Ruthvik Krishna, M. C. Chandan
Metadata
Title
Developments and Applications of Geomatics
Editors
Shashi Mesapam
Anurag Ohri
Venkataramana Sridhar
Nitin Kumar Tripathi
Copyright Year
2024
Publisher
Springer Nature Singapore
Electronic ISBN
978-981-9985-68-5
Print ISBN
978-981-9985-67-8
DOI
https://doi.org/10.1007/978-981-99-8568-5