IIt includes data that were used in the manuscript(A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems.) It includes layers that were created in online ArcGIS pro in manuscript and result of regression model that was done in the manuscript.

Question Paper Solutions of chapter Applications of GIS & Remote Sensing of GIS & Remote Sensing, 8th Semester , Civil Engineering

Bolton & Menk, an engineering planning and consulting firm from the Midwestern United States has released a series of illustrated children’s books as a way of helping young people discover several different professions that typically do not get as much attention as other more traditional ones do.Topics of the award winning book series include landscape architecture, civil engineering, water resource engineering, urban planning and now Geographic Information Systems (GIS). The books are available free online in digital format, and easily accessed via a laptop, smart phone or tablet.The book Lindsey the GIS Specialist – A GIS Mapping Story Tyler Danielson, covers some the basics of what geographic information is and the type of work that a GIS Specialist does. It explains what the acronym GIS means, the different types of geospatial data, how we collect data, and what some of the maps a GIS Specialist creates would be used for.Click here to check out the GIS Specialist – A GIS Mapping Story e-book

ArcGIS tool and tutorial to convert the shapefiles into network format. The latest version of the tool is available at http://csun.uic.edu/codes/GISF2E.htmlUpdate: we now have added QGIS and python tools. To download them and learn more, visit http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

This study presents an ArcGIS geoprocessing protocol for quickly processing large amounts of data from publicly available government sources to consider both water quality standards (WQS) and nonpoint pollution source (NPS) control, on a watershed-by-watershed basis to administratively predict locations where nonpoint source pollutants may contribute to the impairment of downstream waters and locations where nonpoint source pollutants are not expected to contribute to the impairment of downstream waters. This dissertation also presents an ArcGIS geoprocessing protocol to calculate the hydrological response time of a watershed and to predict the potential for soil erosion and nonpoint source pollutant movement on a landscape scale. The standardized methodologies employed by the protocol allow for its use in various geographic regions. The methodology has been performed on sites in Linn County and Boone County, Missouri, and produces results consistent with those expected from other widely accepted methods. These protocols were developed studying the movement of atrazine. but may be used for various nonpoint source pollutants that are water soluble, have an affinity to soil binding, and associated with a particular land use. All data and code are available in Mendeley Data (doi: 10.17632/wdjzftxyfd.1).

Question Paper Solutions of chapter Database and Coordinate System of GIS & Remote Sensing, 8th Semester , Civil Engineering

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Civil Engineering Market Size 2024-2028

The civil engineering market size is forecast to increase by USD 2.57 billion at a CAGR of 3.9% between 2023 and 2028.

The market is experiencing significant growth, driven by the surge in construction activities in developing countries. This trend is expected to continue as infrastructure development remains a priority for many governments. Another key factor fueling market growth is the adoption of intelligent processing in civil engineering projects. This includes the use of technologies such as Building Information Modeling (BIM) and Geographic Information Systems (GIS) to improve project efficiency and accuracy. 
However, the market is also facing challenges, including the decline in construction activities in some regions due to economic downturns and natural disasters. Despite these challenges, the future of the market looks promising, with continued investment in infrastructure development and the ongoing integration of advanced technologies.

What will be the Size of the Civil Engineering Market During the Forecast Period?

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The civil engineering services market encompasses a broad range of construction activities, including social infrastructure, residential, offices, educational institutes, luxury hotels, restaurants, transport buildings, online retail warehousing, and various types of infrastructure projects such as roads, bridges, railroads, airports, and ports. This market is driven by various factors, including population growth, urbanization, and the increasing demand for sustainable and energy-efficient structures. 
Digitalization plays a significant role In the civil engineering sector, with the adoption of digital civil engineering, smart grids, urban transportation systems, industrial automation, parking systems, and IT services. Additionally, there is a growing trend towards the development of zero-energy buildings, insulated buildings, double skin facades, PV panels, and e-permit systems.
Inspection technology and integrated 3D modeling are also becoming increasingly important In the civil engineering industry, enabling more accurate and efficient design and construction processes. The market is expected to continue growing, driven by the increasing demand for infrastructure development and the ongoing digital transformation of the industry.

How is this Civil Engineering Industry segmented and which is the largest segment?

The civil engineering industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Real estate
  Infrastructure
  Industrial


Geography

  APAC

    China
    India


  North America

    Canada
    US


  Europe

    Germany


  Middle East and Africa



  South America

By Application Insights

The real estate segment is estimated to witness significant growth during the forecast period. The real estate market encompasses the development, acquisition, and sale of property, land, and buildings. Global urbanization and infrastructure investment growth have significantly impacted this sector. In particular, the Asia Pacific region has seen rapid expansion in various sectors, such as commercial construction, with India leading the charge. Notably, international real estate development is projected to present opportunities for countries like India, as demonstrated by the October 2021 MoU between the Jammu and Kashmir administration and the Dubai government, focusing on industrial parks, IT towers, and super-specialty hospitals. Civil engineering services play a crucial role in real estate development, with a focus on social infrastructure, residential, construction activities, offices, educational institutes, hotels, restaurants, transport buildings, online retail warehousing, immigration, housing, and construction.

Innovations in green building products, energy efficiency, sustainable construction materials, such as cross-laminated timber, and digital technology are transforming the industry. Key areas of growth include infrastructure, oil and gas, energy and power, aviation, public spending, non-residential construction, healthcare centers, infrastructure projects, and digital civil engineering. Civil engineering firms provide essential services, including rail structures, tunnels, bridges, maintenance services, renovation activities, and energy-efficient products. The real estate segment also includes industrial real estate and housing development, with a shift towards flexible infrastructure, roads, railroads, airports, ports, single-family houses, and home remodeling. The industry is embracing advanced simulation tools, drone technology, and carbon emissions reduction initiatives, such as net-zero energy buildings, pre-fabrica

Civil Engineering Market Outlook

The global civil engineering market size was valued at approximately $9.7 trillion in 2023 and is projected to reach nearly $14.6 trillion by 2032, growing at a compound annual growth rate (CAGR) of 4.5% during the forecast period. This substantial growth is driven by increasing urbanization, infrastructure development, and investments in residential and commercial projects worldwide. The burgeoning demand for sustainable construction practices and innovative engineering solutions is further bolstering market expansion.

One of the primary growth factors of the civil engineering market is the rapid pace of urbanization. As more people move into urban areas, the demand for new housing, transportation systems, utilities, and social infrastructure escalates. Governments and private sectors are heavily investing in smart city initiatives, which require extensive civil engineering expertise to ensure that infrastructure is both efficient and sustainable. Furthermore, the expansion of megacities in emerging economies is creating a significant need for advanced civil engineering services, ranging from planning and design to construction and maintenance.

Another significant growth driver is the increasing focus on sustainable and resilient infrastructure. The threat of climate change has led to an emphasis on building structures that can withstand extreme weather conditions and natural disasters. This involves incorporating green building materials, energy-efficient designs, and disaster-resistant technologies into construction projects. Governments and regulatory bodies are also implementing stringent building codes and standards, which necessitate the involvement of skilled civil engineers to ensure compliance. As a result, the demand for specialized civil engineering services is on the rise.

Technological advancements are also playing a crucial role in the growth of the civil engineering market. The adoption of Building Information Modeling (BIM), Geographic Information Systems (GIS), and other advanced software tools has revolutionized the way civil engineering projects are planned and executed. These technologies improve precision, reduce errors, and enhance collaboration among stakeholders. Additionally, innovations in materials science, such as the development of high-performance concrete and smart materials, are contributing to the creation of more durable and efficient infrastructures. These technological strides are attracting significant investment and interest in the civil engineering sector.

Regionally, the Asia-Pacific area is expected to dominate the civil engineering market due to rapid economic growth and substantial infrastructure development in countries like China and India. North America and Europe are also significant markets, driven by the need to upgrade aging infrastructure and implement smart city projects. The Middle East & Africa and Latin America regions present considerable growth opportunities due to ongoing urbanization and investment in infrastructure projects. Each region has its unique drivers and challenges, but the overall outlook for the civil engineering market remains robust.

Service Type Analysis

Planning & Design

The planning and design segment is a critical component of the civil engineering market. This segment involves the initial stages of any construction project, where feasibility studies, site surveys, and detailed project plans are developed. The rising complexity of modern infrastructure projects necessitates meticulous planning and innovative design solutions. Advanced software tools such as AutoCAD, Revit, and BIM are extensively utilized in this segment to create accurate and efficient designs. The integration of these tools helps streamline the planning process, reduce errors, and ensure that the final design meets all regulatory and safety standards.

Sustainable design practices are gaining prominence within the planning and design segment. With increasing awareness of environmental issues, there is a growing emphasis on creating eco-friendly and energy-efficient building designs. This involves the use of green building materials, renewable energy sources, and waste reduction strategies. Civil engineers are now focusing on designing structures that minimize environmental impact while maximizing functionality and aesthetics. This shift towards sustainability is driving innovation and growth in the planning and design segment.

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Field Data Collection Apps for Civil Engineering Market Outlook

According to our latest research, the Field Data Collection Apps for Civil Engineering market size reached USD 1.45 billion in 2024 and is expected to grow at a robust CAGR of 13.8% during the forecast period, reaching a projected value of USD 4.11 billion by 2033. This dynamic growth is primarily driven by increasing digitalization in the civil engineering sector, the need for real-time data acquisition, and the growing emphasis on project efficiency and compliance. As per our analysis, the market is experiencing accelerated adoption due to the rising demand for accurate field data, streamlined workflows, and integration with advanced analytics platforms.

One of the primary growth factors for the Field Data Collection Apps for Civil Engineering market is the rapid digital transformation across the construction and engineering industries. The adoption of mobile technologies and smart devices on job sites has enabled civil engineers to collect, analyze, and transmit data in real time, significantly reducing manual errors and paperwork. The increasing complexity of civil infrastructure projects, combined with the need for precise data to ensure safety and regulatory compliance, has further fueled the demand for field data collection apps. These solutions empower project teams to collaborate seamlessly, enhance productivity, and maintain up-to-date records, which are essential for timely project delivery and cost control.

Another significant driver is the integration of field data collection apps with other digital platforms such as Building Information Modeling (BIM), Geographic Information Systems (GIS), and cloud-based project management tools. This interoperability allows for the seamless flow of information between field teams and office-based stakeholders, enhancing decision-making and reducing project delays. The ability to capture geospatial data, photographic evidence, and inspection results directly from the field and sync them with centralized databases has become a critical requirement for modern civil engineering projects. Moreover, the increasing emphasis on sustainability and resource optimization is pushing organizations to leverage digital tools that provide actionable insights from field data, further propelling market growth.

The proliferation of government regulations and industry standards mandating accurate documentation and traceability in civil engineering projects is also contributing to the expansion of the Field Data Collection Apps for Civil Engineering market. Regulatory bodies are increasingly requiring project documentation to be digital, auditable, and easily accessible, which has led to widespread adoption of advanced field data collection solutions. Additionally, the rising focus on infrastructure modernization in emerging economies, coupled with substantial investments in smart city initiatives, is creating new growth opportunities. The demand for scalable, customizable, and secure data collection platforms is expected to remain strong as the civil engineering sector continues to embrace digital transformation.

Regionally, North America holds the largest market share in 2024, driven by the presence of leading construction technology providers, high adoption rates of digital tools, and stringent regulatory frameworks. Europe follows closely, with significant investments in infrastructure renewal and sustainability initiatives. The Asia Pacific region is experiencing the fastest growth, fueled by rapid urbanization, government-led infrastructure projects, and increasing awareness of the benefits of digital field data collection. Latin America and the Middle East & Africa are also witnessing steady growth, supported by modernization efforts and the gradual adoption of digital construction practices.

Component Analysis

The Field Data Collection Apps for Civil Engineering market is segmented by component into software and services, each playing a pivotal role in shaping the market landscape. The software segment dominates the market, accounting for the largest revenue share in 2024. This dominance is attributed to the increasing demand for intuitive, feature-rich applications that enable real-time data capture, analysis, and reporting. Modern field data collection software offers functionalities such as offline data entry, GPS integration, photo capture, and automated synchronization with central databases. The continuous evolution

Question Paper Solutions of GIS & Remote Sensing (CE(PE)801A),8th Semester,Civil Engineering,Maulana Abul Kalam Azad University of Technology

The GIS-based Time model of Gothenburg aims to map the process of urban development in Gothenburg since 1960 and in particular to document the changes in the spatial form of the city - streets, buildings and plots - through time. Major steps have in recent decades been taken when it comes to understanding how cities work. Essential is the change from understanding cities as locations to understanding them as flows (Batty 2013)1. In principle this means that we need to understand locations (or places) as defined by flows (or different forms of traffic), rather than locations only served by flows. This implies that we need to understand the built form and spatial structure of cities as a system, that by shaping flows creates a series of places with very specific relations to all other places in the city, which also give them very specific performative potentials. It also implies the rather fascinating notion that what happens in one place is dependent on its relation to all other places (Hillier 1996)2. Hence, to understand the individual place, we need a model of the city as a whole. Extensive research in this direction has taken place in recent years, that has also spilled over to urban design practice, not least in Sweden, where the idea that to understand the part you need to understand the whole is starting to be established. With the GIS-based Time model for Gothenburg that we present here, we address the next challenge. Place is not only something defined by its spatial relation to all other places in its system, but also by its history, or its evolution over time. Since the built form of the city changes over time, often by cities growing but at times also by cities shrinking, the spatial relation between places changes over time. If cities tend to grow, and most often by extending their periphery, it means that most places get a more central location over time. If this is a general tendency, it does not mean that all places increase their centrality to an equal degree. Depending on the structure of the individual city’s spatial form, different places become more centrally located to different degrees as well as their relative distance to other places changes to different degrees. The even more fascinating notion then becomes apparent; places move over time! To capture, study and understand this, we need a "time model". The GIS-based time model of Gothenburg consists of: • 12 GIS-layers of the street network, from 1960 to 2015, in 5-year intervals • 12 GIS-layers of the buildings from 1960 to 2015, in 5-year intervals • 12 GIS- layers of the plots from1960 to 2015, in 5-year intervals In the GIS-based Time model, for every time-frame, the combination of the three fundamental components of spatial form, that is streets, plots and buildings, provides a consistent description of the built environment at that particular time. The evolution of three components can be studied individually, where one could for example analyze the changing patterns of street centrality over time by focusing on the street network; or, the densification processes by focusing on the buildings; or, the expansion of the city by way of occupying more buildable land, by focusing on plots. The combined snapshots of street centrality, density and land division can provide insightful observations about the spatial form of the city at each time-frame; for example, the patterns of spatial segregation, the distribution of urban density or the patterns of sprawl. The observation of how the interrelated layers of spatial form together evolved and transformed through time can provide a more complete image of the patterns of urban growth in the city. The Time model was created following the principles of the model of spatial form of the city, as developed by the Spatial Morphology Group (SMoG) at Chalmers University of Technology, within the three-year research project ‘International Spatial Morphology Lab (SMoL)’. The project is funded by Älvstranden Utveckling AB in the framework of a larger cooperation project called Fusion Point Gothenburg. The data is shared via SND to create a research infrastructure that is open to new study initiatives. 1. Batty, M. (2013), The New Science of Cities, Cambridge: MIT Press. 2. Hillier, B., (1996), Space Is the Machine. Cambridge: University of Cambridge

This layer shows the Geological Map of Hong Kong in 1: 20000. It is a subset of the geo-referenced data made available by the Civil Engineering and Development Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data has been processed and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

Planning, Engineering & Permitting - Birmingham Civil Rights National Monument Boundary

A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.

Contents:

..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.

..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs.

drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.

drainages_original - Drainges identified in the original DEM stored as GeoTIFF.

..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs.

LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF.

LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF.

..\visibility\ - Viewsheds computed over the original and filtered DEMs.

Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice.

Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF.

Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF.

observer_points - Observer points used for calculating the viewsheds.

regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds.

visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.

visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF.

visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.

visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.

Preprint version of the related paper:

Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: https://ssrn.com/abstract=4063514

Civil Engineering Market Outlook

According to our latest research, the global civil engineering market size reached USD 9.4 trillion in 2024, reflecting robust activity across key infrastructure and construction segments. The market is poised for continued expansion, projected to achieve a value of USD 14.1 trillion by 2033, growing at a steady CAGR of 4.6% over the forecast period. This growth is primarily driven by sustained investments in infrastructure modernization, rapid urbanization, and the increasing adoption of advanced technologies across both developed and emerging economies. The civil engineering sector’s dynamism is underpinned by the need for resilient infrastructure, smart city initiatives, and a rising demand for both residential and commercial construction worldwide.

The growth trajectory of the civil engineering market is largely influenced by the escalating demand for infrastructure development across urban and semi-urban areas. Governments globally are prioritizing large-scale infrastructure projects, including transportation networks, energy facilities, water management systems, and smart city solutions. These initiatives are not only aimed at improving connectivity and quality of life but also at fostering economic development and sustainability. The integration of digital technologies such as Building Information Modeling (BIM), Geographic Information Systems (GIS), and advanced project management tools has further enhanced the efficiency, accuracy, and cost-effectiveness of civil engineering projects. Additionally, the growing focus on green and sustainable construction practices is driving innovation in materials, design, and construction methodologies, further propelling market growth.

Another significant growth driver for the civil engineering market is the increasing involvement of private sector players and public-private partnerships (PPPs) in infrastructure development. The expanding role of private investment has accelerated project timelines, improved quality standards, and introduced innovative financing models. This trend is particularly evident in sectors such as transportation, energy, and urban development, where the scale and complexity of projects demand substantial capital and expertise. The proliferation of mega-projects, especially in emerging economies, is creating lucrative opportunities for civil engineering firms, consultants, and contractors. Moreover, the ongoing urbanization in regions like Asia Pacific, Latin America, and Africa is generating a sustained demand for housing, commercial spaces, and industrial facilities, further stimulating market expansion.

The civil engineering market is also benefiting from advancements in construction materials and techniques, which are enabling the development of more durable, resilient, and cost-efficient structures. Innovations such as prefabricated components, high-performance concrete, and modular construction are gaining traction, reducing project timelines and minimizing environmental impact. The adoption of smart construction equipment and automation technologies is enhancing productivity and safety on job sites. Furthermore, the increasing emphasis on disaster-resilient infrastructure, driven by the rising frequency of natural calamities, is shaping the design and execution of civil engineering projects. These factors collectively underscore the sector’s pivotal role in supporting sustainable urbanization and economic growth.

From a regional perspective, Asia Pacific continues to dominate the global civil engineering market, accounting for the largest share in 2024, followed by North America and Europe. The rapid pace of urbanization, population growth, and industrialization in countries such as China, India, and Southeast Asian nations is fueling massive investments in infrastructure and construction. North America remains a key market, driven by the need to upgrade aging infrastructure and the increasing adoption of smart technologies. Europe is witnessing significant activity in sustainable and green construction, aligned with stringent regulatory standards and climate goals. Meanwhile, the Middle East & Africa and Latin America are emerging as promising markets, bolstered by government-led development programs and foreign direct investment in infrastructure projects.

National Forest Estate Bridges are managed by Forestry Civil Engineering in one of the Forestry Commission's Forester GIS modules. This data set comprises location and category of construction.

Attributes; FCE_REF - Unique ID ref LOCATION - Geographical descriptor GRID_REF - Ordnance Survey National Grid Reference BRIDGE_TYPE - Bridge construction type

Normalized Ground Snow Loads for Idaho which was released in 1986 by the Department of Civil Engineering at the University of Idaho. The original paper map printed in 1986 was scanned, georeferenced, and rectified to broaden access and to facilitate use in GIS software. The positional accuracy of this digital map is limited. DISCLAIMER: Great care has been taken to be accurate in preparing this map, but neither the publishers nor the University of Idaho can accept responsibility for any errors which appear or their consequences. The final design snow loads are the ultimate responsibility of the engineer, architect, local building official, and/or contractor in charge of the project.

Australia is one of the most flammable counties due to fuel accumulation and frequent droughts. The number and size of wildfire incidents have increased during the last decades. Global warming, industrialisation and extensive human activities played an important role in the increase of wildfire incidents. Wildfires are a considerable threat to human lives and properties, especially in populated areas. In addition, wildfires will negatively impact the components of our ecosystem such as vegetation, soil, water and forests. Wildfire susceptibility maps show the areas with different probabilities of fire occurrence. These maps help managers and policymakers to act efficiently and reduce the negative impacts of wildfires. Many models were created by Geospatial Information System (GIS) and Remote Sensing (RS) to predict wildfires. This thesis aims to investigate wildfire susceptibility in Victoria located in south-eastern Australia with an area of 227,444 km2. The elevation in this area ranged between -76 m to 1,986 m. More than a million hectares burned in Victoria in the last bushfire season in 2019-2020. In addition, more than 110 homes or businesses were destroyed during this period. A wildfire susceptibility model could be a useful tool to control and manage the future wildfires by predicting vulnerable areas. This study aims to generate wildfire susceptibility maps for the south-eastern part of Australia. The main research objectives are as follows. 1. To generate a wildfire inventory map from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. 2. To develop the conditioning factors and map layers. 3. To generate wildfire susceptibility maps using statistical methods e.g., Frequency Ratio (FR) and Logistic Regression (LR) and evolutionary algorithms separately. 4. To apply ensemble techniques (statistical methods combined with evolutionary algorithms) to generate wildfire susceptibility maps. 5. To evaluate the performance of the proposed methods by using the Receiver Operating Characteristics (ROC) curve.

Question Paper Solutions of chapter Spatial Data Analysis of GIS & Remote Sensing, 8th Semester , Civil Engineering