Geospatial Technology for Landscape and Environmental Management

Channel planform reflects the quasi-natural equilibrium in response to energy distribution and carrying capacity of the river. If the river is unable to carry its sediment load, then accretion on the river bed and the formation of several channel bars are inevitable consequences for alluvial rivers. The Ichamati River is a distributary channel of the Mathabhanga River, disconnected from its parent source at Majdia in Nadia district of West Bengal and hardly received any water from the Mathabhanga River except monsoon season. The downstream part of the river is chiefly maintained by groundwater and tidal activity. However, the shortage of water supply from the upstream and unwise downstream human activities has been decreasing the flow velocity and transportation capacity of the river and causing excessive siltation on the river bed. This abundant source of clay-rich fine sediment and perennial source of river water boost the rapid growth of brick kilns along the riverbank over the years. The incursion of sediment-rich tidal water by adjacent brick kilns of the Ichamati River has altered the sediment–water budget of the river. Most of the brick kilns were established within 200 m peripheries of the riverbank violating the guidelines of the Pollution Control Act of 1986 which have directly or indirectly affected different aspects of the channel planform like channel width, depth, meander geometry, cut-off formation process and natural mobility of the river. To study this spatio-temporal planimetric variability of the river, the US Army Toposheet of 1922 and multi-temporal Landsat images of 1976, 1996 and 2016 were used in this study. Besides, the cross-sectional survey of the river was conducted with the help of an echo-sounder and a GPS during 2013–2018. A questionnaire survey was also performed to acquire information regarding the expansion of brick kilns, annual rate of brick production, sediment extraction rate and land-use activities of brick kilns. This study revealed that the natural shifting and meander mobility of the river have been gradually decreasing with the expansion of brick kilns in the last few decades. The channel width was drastically reduced, and the temporal change rate of the channel width was also decreasing due to the control movement of bank lines during 1976–2016. The excessive siltation within the channel causes upliftment of the river bed as measured 9 cm year⁻¹ during 2013–2018. This river is slowly decaying with time and may disappear in future if the proper restoration planning will not implement to revive the river.

The aim of this study is to prepare an integrated water resource action plan for conjunctive use of available water resource in a sub-humid tropical watershed of East India. This paper describes the quantification and delineation of potential zones of groundwater of a micro-watershed Ghumuda of Odisha along with an integrated plan for sustainable development of water resource. Applying simplistic water balance approach with groundwater controlling parameters estimation of annual dynamic groundwater resource is done. Delineation of potential zones is done by developing various thematic maps using satellite imagery and associated databases. Overlaying the thematic maps and keeping in view the available groundwater resource, an integrated water resource plan is prepared in Arc-GIS software. From the study, the net annual groundwater availability is found to be 80.989 ha m, while the annual draft is 10.18 ha m. After superimposing thematic layers like slope, hydro-geomorphology, line magnets, and land use in the GIS environment, four groundwater potential zones are identified such as poor, moderate, good to moderate, very good. More than 50% area of the watershed falls in a moderate prospect zone. The final action plan map is developed with an aim to utilize the maximum potential of groundwater as well as surface water for sustainable development of agriculture and local residents of the watershed. Different water conservation structures like Nala bunds, percolation tanks, and check dams are recommended along with a proposed groundwater utilization point map for recharge and sustainable discharge of groundwater at convenient sites. The results and the action plan obtained from this study can be helpful for future agricultural growth with sustainable groundwater development. The action plan can be applied to similar hydrologic characteristic areas for overall water resource augmentation.

Flood, a constant phenomenon especially in the semi-arid areas and flood plain regions, can be seen as one of the most destructive natural hazards jeopardizing the life of a population, their property, and their physical and economic environment. This paper focus on hydrologic modeling using the HEC-RAS model in combination with Watershed Modeling System (WMS) tools compares to the Flood Hazard Index (FHI) method using GIS in the Seyad basin situated in the southwestern region of Morocco with an area of 1512.85 km². The goal sought in this study is to evaluate flood risk in the Seyad basin that covers the cities of Taghjijt, Aday, Amtoudi, Tagriante, and Timoulayn’Ouamalougt that are areas with important agricultural lands. The HEC-RAS approach combines the surface hydrologic model and the digital terrain model data. This combination allows the mapping of the flood zones by using the WMS tools. This approach predicts flood occurrence probability for different times and determines the intensity of the flood (depth and velocity of floodwater) by using the existing hydrological data. On the other hand, The Flood Hazard Index method presents a multi-criteria index to assess flood risk areas, using six physical parameters namely: Permeability, slope, distance from the drainage network, land use, drainage network, and flow accumulation. A weight is calculated from the analytic hierarchy process method and applies to each parameter. HEC-RAS method allows the mapping of a flood with a flood water surface profile that shows the depth of flood for Annual Exceedance Probability (AEP) while FHI permits establishing flood risk level without indicating the depth of water. In both approaches, six types of simulations were performed with the return periods of 10, 20, 50, 100, 200, and 500 years and the simulation revealed that the most susceptible areas to flooding are the area along the Seyad River.

The present study is geospatial modeling in the assessment of environmental resources for sustainable water resource management in a Gondia District, India, using geographical information system (GIS) and remote sensing (RS) techniques. The monsoon rains in Gondia District are concentrated in the four months from June to September and receive 90.81% rainfall, post-monsoon 1.86%, pre-monsoon 4.83%, and winter 2.48%. The distribution of annual rainfall in Gondia is very uneven. The major river is Wainganga tributaries are Bagh, Pangoli, Gadhvi, Chor, Chandan, and Bawanthadi. Out of the total area received in the district, reserved forest area is 56.4%, protected forest area is 26.3%, and unclassified forest area is 17.3%. There are 192 small irrigated ponds below 100 ha, and its projected irrigation capacity is 10,897 ha. There are also 294 Kolhapuri type dams with a projected irrigation capacity of 10,075 ha and 1559 storage dams with a projected irrigation capacity of 14,817 ha. The water is neutral to alkaline in nature with pH ranging from 6.6 to 8.92 with high TDS range from 140 to 2184 ppm. The aim of this present study was to evaluate environmental resource units that have been delineated based on the geospatial modeling of environment parameters with appropriate weights in GIS and RS techniques. The data can be used for area management, utilized in restoration and conservation of natural resources studies in the future.

The intrusion of saltwater into a freshwater aquifer is of particular concern to the coastal community. Removal of excess groundwater from the shallow aquifers is known to be the primary cause of contamination by saltwater. In this study, groundwater samples were obtained in the 2016 and 2017 pre-monsoon and post-monsoon seasons at 105 locations from dug wells and bore wells along the coast of Andhra Pradesh in the Krishna and Godavari deltas. Groundwater samples are tested for large ions to determine the infiltration of saltwater and to classify the salinity sources in the delta zone. The various hydrogeochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDSs), Ca²⁺, Mg²⁺, K⁺, Na⁺, CO₃, HCO₃⁻, Cl⁻, and SO₄²⁻ are evaluated for the delineation of the intrusion of saltwater in terms of Ca²⁺/Mg²⁺, Cl⁻/(CO₃ + HCO₃⁻), Na⁺/Cl⁻ ratios. It is reported that the availability of fresh groundwater is 14% and 62%, respectively, during the pre-monsoon and post-monsoon seasons. The percentage levels of contamination in groundwater for slight, moderate, injuriously, highly, and severely categories are 43%, 22%, 12%, 8%, and 1%, respectively, for pre-monsoon season. However, during the post-monsoon season, the levels of contaminations in the above-mentioned categories are 22%, 9%, 4%, 1%, and 3%. The extent of contamination during the post-monsoon season is observed to be lower than during the pre-monsoon. The groundwater ratio of Na⁺ − Cl⁻ during pre-monsoon and post-monsoon seasons is 71% and 60%, respectively. The saltwater mixing index (SMI) is also measured, and extremely high is found.

“Village” is the microlevel or the baselevel where the development starts. It may be social, economic, political, or environmental. Proper planning, monitoring, and managing natural resources are always a challenging task for decision-makers and experts. In the present scenario, the use of remote sensing (RS), geographical information system (GIS), global positioning system (GPS), and other information technology has the potential to manage the natural resources for sustainable livelihood. Implementation of these technologies in microlevel planning through the micro watershed approach is always encouraging and for these, we need a storehouse of the different geospatial database. In the present study, an attempt has been made to use the geospatial technology in the land and water resources management of a village enclosed within a micro watershed. The geospatial database has been generated at the cadastral level or plot level, i.e., at 1:4000 scale. The resource inventory includes land use/land cover, digital elevation model (DEM), slope, geomorphology, ground water prospect, soil, and land capability maps. The site suitability analysis technique is used to develop the land and water resources management action plan. In the land resource management plan, seven types of alternative land use practices are suggested for the study area. On the other hand, the water resource management action plan suggests suitable sites for the construction of bore well and dug well. Further, the action plan suggests the site for the construction of different farm ponds, check dam, nala bund, water harvesting structure, etc. The integration of the action plan map on the DEM gives a 3D perspective which will be an add-on in terms of visualization to the administrators and decision-makers.

The lakes are important ecological units in urban ecosystem which preserve local climate, groundwater, and biodiversity. The unplanned continuous population growth in urban area causing severe destruction to the urban ecosystem across the world. The lake in urban areas provides many functional advantages, they play a vital role in flood management, and are related to the underground water quantity and quality, they preserve the biodiversity and habitat of surrounding area, and they are huge areas of urban heat sinks within incessant built-up area. Delhi the capital of India is around 97% urbanised and home for around 26 million people, which is situated over the Yamuna watershed. To make this city sustainably resilient it is important to study about the hydrological sustainability of the city, which is deteriorating with every passing year. Encroachment, pollution, rapid urban growth, dispersal of solid waste, pumping for drinking water is some of the anthropogenic activities which intensifies the reduction of these hydrological units. Between 1970–2009 around 108 lakes were lost, in between 2009–2013 around 230 lakes have been lost and cannot be revived. Those which still exists are in terrible condition, all the lakes are dying silently which results in serious depletion of groundwater and impacting the ecology. Taking into the consideration of all above facts the present study is an attempt to create an inventory for current status of the lakes and wetlands using remote sensing and GIS techniques and their ecohydrological consequences on the surrounding environment. For the study Six lakes have been identified from different part of Delhi, which are on verge to devastating if not provided with immediate attention. Time series satellite images from LISS-III and Survey of India maps of 1:50,000 were used for the study.

Groundwater potential zones perform a crucial function in hard rock terrain. With this view, the study has been carried out to identify the groundwater prolific zones using remote sensing (RS) and geographical information system (GIS) in Kamina sub-watershed of Bhima River Basin, Shirur Taluka of Pune District, Maharashtra, India. The thematic maps such as geology, geomorphology, DEM, slope (%), rainfall, soil, drainage density, dug well density, borewell density, land use/land cover mapswere generated to identify the potential zones. Saaty’s Analytical Hierarchy Process (AHP) is an efficient tool for the delineation of groundwater potential zones. The AHP proposes a weight for each evaluation criteria according to the decision maker’s pairwise comparisons of the criteria. The hierarchy is built depending on the degree of influence made by each factor on groundwater potentiality. Finally, the AHP combines the criteria weight and the option scores. The ground water potential zone map so generated is divided into four classes (very low, low, moderate and high) depending on the possibility of groundwater potential. The resultant map depicts that 15.91, 23.3, 23.96, and 36.83% of the area represents ‘‘poor,’’ ‘‘moderate,’’ ‘‘high,’’ and ‘‘very high’’ groundwater favorable zones, respectively. The highest potential area is located toward eastern and southern region because of flood plains facilitating high infiltration, drainage of Ghodriver and thick soil cover. The areas having low potential is toward the basin boundary and northern parts of the study area due to highly dissected plateau, poor soil depth, steep slopes and low infiltration rate. The findings of the studycan helpin the formulation of an efficient management plan for sustainable development of the area.

Morphometric analysis is a mathematical examination of the shape and dimension of the earth's surface that illustrates the interrelationship between hydraulic parameters and geomorphologic characteristics of a drainage basin. The present study indicates the effectiveness of remote sensing (RS) and geographic information system (GIS)-based morphometric analysis of a sub-watershed of Damodar River basin in Ramgarh district, Jharkhand, India. The sub-watershed and drainage texture of the study area is extracted by ASTER DEM and topographical map in the GIS environment. Morphometric parameters such as stream order, stream length, bifurcation ratio, drainage density, stream frequency, form factor, and circulatory ratio are calculated. The sub-watershed’s total drainage area is 46.71 km² and shows a dendritic drainage pattern that designates homogeneous lithology, gentle regional slope, and lack of structural control. The study area is designated as the fifth-order basin with a drainage density (D_d) value ranges 9.91 km/km². An extensive field survey supports the results. Results of the study have immense significance for engineers, managers, and planners for management of soil, water and provide watershed prioritizing management activities in the area.

Disaster is a term used for an unusual event that has a negative impact on life, environment, and materials. This event is more unwanted than unusual as most of the time this is caused due to reasons, we remain unaware of. Disasters could be natural or man-made like floods, earthquakes, volcanic eruptions, accidents, gas leakage, forest fire, etc. Since the disaster occurs due to reasons that are unknown and is an untimely phenomenon, we have a lesser scope of avoiding it. The use of emerging technologies, early warnings, immediate incidence response, and post-recovery activities can well be employed to mitigate the losses that the disaster would lead to. One such emerging technology is the Internet of things (IoT). The sensor nodes used in an IoT architecture independently are capable of sensing the environment and gathering data. This data can be further sent to the sink node/base station which has the responsibility of reporting the data ahead of the network, for initiating actuation on the basis of the data gathered and analyzing the data. This can help in monitoring for the purpose of early warning of disasters. The actuations can help provide immediate incidence response. Furthermore, upon the integration of data analytics with IoT, the data generated with the help of sensors can be used for predictive analysis and inference drawing in order to enable early disaster prediction and mitigation of losses that might occur due to the same. Thus, the potential of IoT is to provide rescue, response, mitigation, and preparedness to manage a disaster. This chapter explains the role of IoT in disaster management along with proposing a generic model having distinct layers through well-defined functionality. The chapter also explains the integration of cloud and IoT that could improve the efficiency of IoT applications in disaster management.

The application of information and communication technologies has led the reforms in the governance in Indian cities. It has also read to greater citizen participation in governance. People are important because their participation is the precondition for successfully functioning of the smart city system. The paper tries to develop a framework of systematic analysis to explain e-participation of citizens in India. The paper tries to identify and measure key indicators of e-participation in India. Survey of 200 respondents is analyzed from four smart cities across India. The paper applies regression and concludes that all the indicators have a significant impact on e-participation of citizens in smart cities. The study finds that though the government is investing a huge amount of funds in smart cities development but still a lot is to be done. Also, the concept of participatory approach is currently not a prominent research theme among scholars. Therefore, the current work will address this gap to unravel the conceptual framework of e-participation of citizens in smart cities in India.

The monitoring of land use land cover (LULC) change is essential to estimate the urban sprawl as the rapid growth of urban areas affects the ecology and eminence of city life. LULC forms a reference line of the spatial map for observing, managing, and planning activities for urban development. The LULC change dynamics is self-explanatory using GIS and remote sensing techniques. Thus, the present study uses these techniques to understand the spatial–temporal variability of LULC of Nagpur city, Maharashtra, from 2000 to 2020. The study area is a center for economic, education, and medical activities; therefore, changes should be analyzed to understand urban growth trends. The LULC classification is performed considering four different classes, i.e., barren land, built up, agriculture (include shrubs, urban forest, small plantation, vegetation area), and water bodies. The LULC results show that the built-up area is increased by 26.62% from 2000 (41.24%) to 2020 (67.86%), with a slight increase in water bodies 0.19% is also evident. On the other hand, the area covered with vegetation is decreased by 15.93% from 2000 (30.17%) to 2020 (14.24%), and barren land is reduced by 10.88%. The present study also includes predicting the LULC map using the artificial neural network-based (ANN) cellular automata (CA) model, using seven different driving parameters, like elevation, slope, aspect, distance to major roads, distance to water bodies, central building distance, and population. The prediction model showed an overall accuracy of 81.23% in predicting the 2025 LULC maps with the help of 2015 and 2020 LULC data. The result of the prediction model evidents a maximum growth of 30.88% in the built-up area as compared to year 2020. Therefore, the study results show that the use of LULC and CA-ANN model will be suitable to understand the future trend, and it will help the administration and planner for the development of the sustainable city.

Urbanization is likely to increase the rate of slum growth, as it has in the past. According to the 2011 Indian census, the population of Udhampur urban area is 91,366, with 35,507 people living in the Udhampur municipal area and 48,508 people living in Udhampur's outgrowths. Udhampur city is divided into 21 municipal wards. Out of 21 slums, 11 slums are non-notified, and ten are notified. This research attempts to categorize slums based on living standards, which will help formulate sustainable development techniques for better implementation of slum improvement projects. Data about the socioeconomic and physical condition of the slums have been collected using field surveys. For clustering slums in different categories, a 2 × 2 × 2 matrix is formed. For creating an indicative matrix, essential inputs were identified, and an overall matrix table for all the slums with their scores was prepared. A georeferenced very high-resolution satellite imagery with a ward boundary map was used to create a base map. Different maps were generated showing current slum distribution and also the spatial distribution of varying slum categories. Maps were validated with field survey and with field photographs.

Urbanisation is the process of becoming urban. It is an anthropologic process which studies rising proportion of population of a region or city lives in urban area. Urbanization can be a result of demographic phenomenon, structural change in society or it can also be a result of behavioural processes. Various aspects of remote sensing technique i.e. spectral, temporal, and spatial aspect of remote sensing techniques can be effectively used in the study of such dynamic phenomenon. Remote sensing data can be effectively used in change detection mapping and processes, and therefore aiding in urban planning and management. The present study aims to study urban growth and sprawl in Dehradun city of Uttarakhand, which is one of the city in government’s smart city project list. By using the approach of Shannon’s Entropy, urban sprawl of Dehradun can be analysed. As per the result the entropy value obtained for the year 2008 is 0.877 and 2016 is 1.598, in which the value of 2016 is near to the value of upper limit of log n (i.e. 1.591) which depicts more urban sprawl in 2016 than in 2008. The present study effectively uses Landsat TM data of year 2008 and 2016. Urbanization have different impacts on natural, economic and social structure of any region, therefore this study can help for better planning and sustainable management of resources of a certain region and can help government officials and planners to monitor and analyse current urbanization and plan for future growth and requirements. Particularly Dehradun is selected for this study as there is a rapid increase in urbanization in the city since 2008–09 and also the city is considered by Indian government for its Smart city project. The chief goal of government is to prepare a green, clean and economically attractive city. This particular study can be helpful to understand the urbanisation pattern in the city.

Ever-increasing population and industrialization are mainly responsible for the conversion of significant amount of change in land use. The change in land use pattern is considered as key parameter to evaluate global change in different spatiotemporal scales. The quantitative analysis of changes in land use pattern is needed to assess the impacts of change in the natural vegetation on the earth’s environment for sustainable utilization of the resources. The aim of the study is to map and analyze the dynamics of land use/land cover changes using IRS LISS-III data for the years 2011–2012 and 2015–2016 of Andhra Pradesh State, India. On-screen visual interpretation techniques have been used to delineate the land use/land cover classes in ArcGIS environment and cross-tabulation used for quantifying the changes in land use pattern. The study reveals that built-up area, agriculture land, and water bodies have been increased about 0.21% (343.06 km²), 0.11% (176.21 km²), and 0.02% (32.08 km²), respectively, while area under other land categories such as forest area, wastelands, and wetlands have decreased about 0.02% (107.44 km²), 0.20% (333.38 km²), and 0.07% (110.53 km²), respectively. The results of this study would be helpful for planners, decision-makers, and administrators to plan and implement appropriate decisions in order to sustainable resource utilization.

The unprecedented urbanisation of Megacities like Delhi at an irreversible rate has played a significant role expansion of Delhi Metro projects in the public urban transit system in the Delhi-NCR region. The current work tried to envisage the study on urbanisation transitions due to the launch of the metro rail network in the NCR region. Apart from urban, it has influenced the periphery and rural areas of Delhi. These regions are now hastening towards development at a higher pace. Apart from these, the metro network is contributing to the linear development or parallel development of infrastructures along with the network. Adjoining cities of Uttar Pradesh and Haryana states containing Gurugram, Noida, Bahadurgarh and Faridabad have become major intersections of the metro network. These are also contributing to urbanisation. Thus the current work tries to visualize urbanisation with the social scenario, as it has a massive network of nearly 288 km length comprising of six different lines. The people from different parts are commuting daily via the metro network. In conclusion, it proposes to identify the push and pull to further analyse the urbanisation pattern due to the expansion of the network in the region, as the growing population in the region requires further expansion. Hence, metro projects are expanding continuously and providing a new stimulus towards the increasing urbanisation.

Rapid urbanization and unsustainable industrialization have shown negative impact on climate, which has led to climate change and ultimately leading towards global warming. It is estimated that presently global warming is increasing at the rate of 0.2 °C per decade, eventually making urban areas warmer. Haphazard development in the Indian cities have made them prone to urban heat island (UHI) phenomenon. Higher temperature in core urban areas due to concretization and excessive energy usage in comparison to its rural surroundings is known as the UHI effect. Higher UHI intensity in certain urban core areas put the population at a great risk of morbidity, and mortality makes the UHI assessment prerequisite during current times. This study has assessed the spatiotemporal effect of UHI in Rajkot city using LANDSAT5TMand LANDSAT 8 OLI remote sensing data. The study distinguished the Land use/ Land cover (LULC) using Landsat images for the year 2009 and 2017 in order to perform maximum livelihood classification. Utilizing classified results and Normalized Difference Vegetation Index (NDVI), land surface temperature (LST) was derived using mono-window algorithm. Subsequently, ambient air temperature was scrutinized and isotherm was derived for three locations in Rajkot city such as Madhapar chowk, Trikon Baugh and Atika industrial area of different typology. Later on, discrepancy between LST and Ambient air temperature was figured out. Some environmental factors such as the concentrations of carbon dioxide and carbon monoxide, which contribute in UHI effect, were also analysed for the above-mentioned locations. On the basis of various results derived and analysis of temperature trend of past 60 years, it was determined that UHI effect was more prominent in the central business district (CBD) area of the selected regions. The results also revealed that the study region has experienced an increase of 0.3 °C in ambient air temperature in past 60 years. The built-up area and LST for LULC classes have also increased by 8.42% between 2009 and 2017 in Rajkot. The reasons behind increment in temperature can be: Rajkot, being the largest city of Saurashtra region has experienced rapid urbanization, higher energy consumption, rural to urban migration, which has modified the LU/LC of the city and eventually resulted into haphazard development that subsequently increase land surface temperature (LST).

As in the time of economic development, various rural towns are developing into urban towns, and hence, for a balanced and a proper development, a planning is required as it is a process through which proper development can be executed accordingly to the requirements. There are various criterions which are to be followed to create a proper development plan. Remote sensing is the acquiring of the data about the item without contacting it or without physically being present there. Due to advanced technology and new innovations, satellite imaging has enabled to collect and interpret various data which earlier was done physically and consumed a lot of time. A surface analysis is conducted with the help of remote sensing which gives a lot information regarding various aspects, whereas it also interprets the physical data with other socioeconomic data. This interpretation helps in getting a link to the planning process. The information collected through satellites helps planning in various formats such as time, efficiency and other ways. Therefore, it enables to a lot of things for a better planning.

In the past, urban green space was regarded as one of the most important aspects of a healthy city. However, with rapid urbanisation, urban sprawl, and population growth, there has been a sharp decline in open green spaces in cities, particularly in metropolitan areas. Also, over the last few decades, there has been a shift in land use and land cover, with a decrease in the area of green spaces, agricultural lands, and urban greenery. This study was carried out to assess green spaces in Vijayawada's Urban Local Body. Because of better economic opportunities, the city has seen a surge in population inflow. Furthermore, the city's outskirts are more vulnerable to transition due to the presence of the Krishna River. As a result of these factors, there has been a decrease in urban green spaces from 2012 to 2020. This has skewed per capita greenness of the city. It is only 16 m² at present. The results show that there exists a negative correlation of −0.46 between per capita green and population; therefore, with every one unit increase of population, the demand for built up and urban amenities will increase, thereby, impacting the per capita green and overall greenness index of the city negatively. The study also compares the normalised difference vegetation index (NDVI) to the transformed difference vegetation index (TDVI). It is a new index that is not widely used. Because it does not saturate, TDVI has proven to be superior to NDVI for urban green analysis. NDVI shows vegetation of 21.25 km² whereas TDVI shows vegetation of 16 km². Not only this, there has been an increase of merely 2% of vegetation in past 8 years span in the Vijayawada city.

The objective of this work is to investigate the suitability of such measurements for indicating heavy metal contamination. Magnetic susceptibility measurements were carried out of agricultural soil which was collected from 23 locations from Kopargaon area of Ahmadnagar district, Maharashtra State of India, using AGICO-MFK1-FA multifunction frequency Kappabridge KLY4S with low frequency susceptibility (F1) 976 Hz and high frequency susceptibility (F2) 15,616 Hz. The magnetic susceptibility values at low frequency were observed ranging from 16.83 × 10^–7 m³/kg⁻¹ to 59.38 × 10^–7 m³/kg⁻¹, whereas at high frequency, magnetic susceptibility found ranged from 16.17 × 10^–7 m³/kg⁻¹ to 56.38 × 10^–7 m³/kg⁻¹. This significant magnetic enhancement is an indication of presence of ferromagnetic minerals in agricultural soil from the studied area. Heavy metals in soil samples were analyzed by using double beam atomic absorption spectrophotometer. The mean concentration of Mn (6.760 mg/kg) followed by Fe (3.929 mg/kg), Cu (2.284 mg/kg), Pb (1.328 mg/kg), Zn (0.936 mg/kg), Cd (0.682 mg/kg) and Ni (0.595 mg/kg) was observed. The evaluation of anthropogenic influence and contamination with trace elements in soil from study area was carried out using geoaccumulation index. Soil geoaccumulation index (Igeo) shows that maximum values of Fe (5.599) and least value of Cd (−0.976) were observed. The geoaccumulation class (Igeo class) sequence was observed to be Cd > Pb > Ni > Zn > Cu > Mn > Fe. The interpretation of the obtained field measurements and the laboratory analyzes indicates that Cd, Pb and Ni provide the potential risk, whilst the other heavy metals are in the safe limits.