NM Environment Department Surface Water Quality Bureau GIS Web Mapping Tool

The Web Map Service (WMS) is defined by the Open Geospatial Consortium (OGC) in order to dynamically produce maps from geographic information. This standard defines a "map" as a representation of geographic information in the form of a digital image file. The maps produced by WMS are normally generated in an image format such as PNG or JPEG and can be invoked by any web protocol or software trained for the visualization of this type of services. The standard defines three operations: GetCapabilities, GetFeature and DescribeFeatureType.

Abstract

MEJ aims to create easy-to-use, publicly-available maps that paint a holistic picture of intersecting environmental, social, and health impacts experienced by communities across the US.

With guidance from the residents of impacted communities, MEJ combines environmental, public health, and demographic data into an indicator of vulnerability for communities in every state. MEJ’s goal is to fill an existing data gap for individual states without environmental justice mapping tools, and to provide a valuable tool for advocates, scholars, students, lawyers, and policy makers.

Methodology

The negative effects of pollution depend on a combination of vulnerability and exposure. People living in poverty, for example, are more likely to develop asthma or die due to air pollution. The method MEJ uses, following the method developed for CalEnviroScreen, reflects this in the two overall components of a census tract’s final “Cumulative EJ Impact”: population characteristics and pollution burden. The CalEnviroScreen methodology was developed through an intensive, multi-year effort to develop a science-backed, peer-reviewed tool to assess environmental justice in a holistic way, and has since been replicated by several other states.

CalEnviroScreen Methodology:

• Population characteristics are a combination of socioeconomic data (often referred to as the social determinants of health) and health data that together reflect a populations' vulnerability to pollutants. Pollution burden is a combination of direct exposure to a pollutant and environmental effects, which are adverse environmental conditions caused by pollutants, such as toxic waste sites or wastewater releases. Together, population characteristics and pollution burden help describe the disproportionate impact that environmental pollution has on different communities.

• Every indicator is ranked as a percentile from 0 to 100 and averaged with the others of the same component to form an overall score for that component. Each component score is then percentile ranked to create a component percentile. The Sensitive Populations component score, for example, is the average of a census tract’s Asthma, Low Birthweight Infants, and Heart Disease indicator percentiles, and the Sensitive Populations component percentile is the percentile rank of the Sensitive Populations score.

• The Population Characteristics score is the average of the Sensitive Populations component score and the Socioeconomic Factors component score. The Population Characteristics percentile is the percentile rank of the Population Characteristics score.

• The Pollution Burden score is the average of the Pollution Exposure component score and one half of the Environmental Effects component score (Environmental Effects may have a smaller effect on health outcomes than the indicators included the Exposures component so are weighted half as much as Exposures). The Pollution Burden percentile is the percentile rank of the Pollution Burden score.

• The Populaton Characteristics and Pollution Burden scores are then multiplied to find the final Cumulative EJ Impact score for a census tract, and then this final score is percentile-ranked to find a census tract's final Cumulative EJ Impact percentile.

• Census tracts with no population aren't given a Population Characteristics score.

• Census tracts with an indicator score of zero are assigned a percentile rank of zero. Percentile rank is then only calculated for those census tracts with a score above zero.

• Census tracts that are missing data for more than two indicators don't receive a final Cumulative EJ Impact ranking.

%3C!-- --%3E

Geographic Information System Software Market Outlook

The global Geographic Information System (GIS) Software market size was valued at approximately USD 7.8 billion in 2023 and is projected to reach USD 15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.3% during the forecast period. This impressive growth can be attributed to the increasing demand for efficient data management tools across various industries, which rely on spatial data for decision-making and strategic planning. The rapid advancements in technology, such as the integration of AI and IoT with GIS software, have further propelled the market, enabling organizations to harness the full potential of geographic data in innovative ways.

One of the primary growth drivers of the GIS Software market is the burgeoning need for urban planning and smart city initiatives worldwide. As urbanization trends escalate, cities are increasingly relying on GIS technology to manage resources more effectively, optimize transportation networks, and enhance public safety. The ability of GIS software to provide real-time data and spatial analysis is vital for city planners and administrators faced with the challenges of modern urban environments. Furthermore, the trend towards digital transformation in governmental organizations is boosting the adoption of GIS solutions, as they seek to improve operational efficiency and service delivery.

The agricultural sector is also experiencing significant transformations due to the integration of GIS software, which is another pivotal growth factor for the market. Precision agriculture, which involves the use of GIS technologies to monitor and manage farming practices, is enabling farmers to increase crop yields while reducing resource consumption. By leveraging spatial data, farmers can make informed decisions about planting, irrigation, and harvesting, ultimately leading to more sustainable agricultural practices. This trend is particularly prominent in regions where agriculture forms a substantial portion of the economy, encouraging the adoption of advanced GIS tools to maintain competitive advantage.

Another influential factor contributing to the growth of the GIS Software market is the increasing importance of environmental management and disaster response. GIS technology plays a crucial role in assessing environmental changes, managing natural resources, and planning responses to natural disasters. The ability to overlay various data sets onto geographic maps allows for better analysis and understanding of environmental phenomena, making GIS indispensable in tackling issues such as climate change and resource depletion. Moreover, governments and organizations are investing heavily in GIS tools that aid in disaster preparedness and response, ensuring timely and effective action during emergencies.

The evolution of GIS Mapping Software has been instrumental in transforming how spatial data is utilized across various sectors. These software solutions offer robust tools for visualizing, analyzing, and interpreting geographic data, enabling users to make informed decisions based on spatial insights. With the ability to integrate multiple data sources, GIS Mapping Software provides a comprehensive platform for conducting spatial analysis, which is crucial for applications ranging from urban planning to environmental management. As technology continues to advance, the capabilities of GIS Mapping Software are expanding, offering more sophisticated features such as 3D visualization and real-time data processing. These advancements are not only enhancing the utility of GIS tools but also making them more accessible to a wider range of users, thereby driving their adoption across different industries.

Regionally, North America and Europe have traditionally dominated the GIS Software market, thanks to their robust technological infrastructure and higher adoption rates of advanced technologies. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increased government spending on infrastructure development, and the expanding telecommunications sector. The growing awareness and adoption of GIS solutions in countries like China and India are significant contributors to this regional growth. Furthermore, Latin America and the Middle East & Africa regions are slowly catching up, with ongoing investments in smart city projects and infrastructure development driving the demand for GIS software.

Component Analysis</h2&

800+ GIS Engineers with 25+ years of experience in geospatial, We provide following as Advance Geospatial Services:

Analytics (AI) Change detection Feature extraction Road assets inventory Utility assets inventory Map data production Geodatabase generation Map data Processing /Classifications
Contour Map Generation Analytics (AI) Change Detection Feature Extraction Imagery Data Processing Ortho mosaic Ortho rectification Digital Ortho Mapping Ortho photo Generation Analytics (Geo AI) Change Detection Map Production Web application development Software testing Data migration Platform development

AI-Assisted Data Mapping Pipeline AI models trained on millions of images are used to predict traffic signs, road markings , lanes for better and faster data processing

Our Value Differentiator

Experience & Expertise -More than Two decade in Map making business with 800+ GIS expertise -Building world class products with our expertise service division & skilled project management -International Brand “Mappls” in California USA, focused on “Advance -Geospatial Services & Autonomous drive Solutions”

Value Added Services -Production environment with continuous improvement culture -Key metrics driven production processes to align customer’s goals and deliverables -Transparency & visibility to all stakeholder -Technology adaptation by culture

Flexibility -Customer driven resource management processes -Flexible resource management processes to ramp-up & ramp-down within short span of time -Robust training processes to address scope and specification changes -Priority driven project execution and management -Flexible IT environment inline with critical requirements of projects

Quality First -Delivering high quality & cost effective services -Business continuity process in place to address situation like Covid-19/ natural disasters -Secure & certified infrastructure with highly skilled resources and management -Dedicated SME team to ensure project quality, specification & deliverables

The global arborist software market was valued at USD 350.79 Million in 2022 and is projected to reach USD 881.04 Million by 2030, registering a CAGR of 12.2% for the forecast period 2023-2030. Factors Affecting Arborist Software Market Growth

Growing awareness of tree care coupled with benefits of arborist software

With increased awareness of environmental conservation and the importance of urban green spaces, there's a rising demand for professional tree care services. Growing environmental education coupled with technology adoption in tree management helps to drive the arborist software demand. Arborist software helps urban planners, municipalities, and property owners effectively manage and care for trees in cities and suburbs. Arborist software streamlines various tasks like tree inventory management, maintenance scheduling, and communication with clients. This leads to improved efficiency and productivity for arborists.

The Restraining Factor of Arborist Software:

Data Security, privacy concerns;

Data security and privacy concerns are indeed significant factors that can impact the adoption of arborist software. Arborist software often stores information about clients' properties, contact details, and potentially even financial information. Many arborist software solutions use location data to map and manage trees. This location data could be misused if it falls into the wrong hands.

Market Opportunity:

Rising need to improve tree inventory practices;

The rising need to improve tree inventory practices is driven by several factors, including urbanization, environmental awareness, and advancements in technology. As cities grow and expand, urban planners need accurate tree inventory data to ensure that trees are integrated into urban design. Tree inventory helps prevent conflicts between infrastructure development and tree preservation. Arborists software helps to create and maintain digital inventories of trees, including information about species, location, size, health, and maintenance history. In addition, features like Geographic Information Systems (GIS), remote sensing, and mobile data collection technologies have made it easier to create, update, and manage tree inventories.

The COVID-19 impact on Arborist Software Market

The COVID-19 pandemic had various impacts on industries and markets, including the arborist software market. During lockdowns and restrictions, some tree care activities might have been deprioritized due to the sudden focus on healthcare sector. However, the pandemic accelerated digital transformation across industries. Arborists who were previously reliant on manual processes might have recognized the benefits of adopting software for tasks like inventory management, reporting, and client communication. Introduction of Arborist Software

An arborist is a professional who specializes in the cultivation, management, and study of trees, shrubs, and other woody plants. Arborists are trained in tree care practices, including planting, pruning, disease and pest management, and overall tree health maintenance. Arborist software are tools used to assist arborists in their work. These software solutions can provide various functionalities to help arborists manage and maintain trees effectively. Arborists can use software to create and maintain digital inventories of trees, including information about species, location, size, health, and maintenance history. Some common features of arborist software include tree inventory management, health assessment, risk assessment, mapping and GIS integration etc.

The datasets represent topographic description (cost and accessibility maps) of Khabarovsk and Primorsky Krais of the Russian Far East divided into unit areas with a 10x10 km grid in WGS84. The datasets are in MID/MIF formats to be processed in QGIS with use of self-written open source software. The datasets are used to model single or multiple socio-economic scenarios of regional spatial development and inter-regional economic cooperation.

TDEC is continuously striving to create better business practices through GIS and one way that we have found to provide information and answer some question is utilizing an interactive map. An interactive map is a display of geospatial data that allows you to manipulate and query the contents to get the information needed using a set of provided tools. Interactive maps are created using GIS software, and then distributed to users, usually over a computer network. The TDEC Land and Water interactive map will allow you to do simple tasks such as pan, zoom, measure and find a lat/long, while also giving you the capability of running simple queries to locate land and waters by name, entity, and number. With the ability to turn off and on back ground images such as aerial imagery (both black and white as well as color), we hope that you can find much utility in the tools provided.

The Monitoring and Mapping Software market is experiencing robust growth, driven by the increasing adoption of drones, advanced sensors, and the rising need for precise geospatial data across diverse sectors. The market's expansion is fueled by applications in construction, agriculture, mining, and urban planning, where real-time data and accurate 3D models are crucial for efficient operations and informed decision-making. The integration of AI and machine learning capabilities within these software solutions is further enhancing their analytical power, enabling automated feature extraction, object recognition, and predictive modeling. This leads to improved efficiency, reduced operational costs, and enhanced safety measures. Key players like Hexagon, Trimble, and Autodesk are driving innovation through continuous product development and strategic acquisitions, while the emergence of open-source solutions like Regard3D and Alicevision fosters community development and wider accessibility. The market is segmented by software type (image/video-based, 3D scanning-based) and deployment (cloud, on-premise), with cloud-based solutions gaining significant traction due to their scalability and accessibility. Looking ahead, the market is expected to witness continued expansion, propelled by ongoing technological advancements, including the development of higher-resolution sensors, improved processing power, and the integration of Internet of Things (IoT) devices. The growing demand for precise mapping and monitoring in infrastructure projects, environmental monitoring, and disaster management will also contribute significantly to market growth. However, factors such as the high initial investment costs associated with sophisticated software and hardware, and the need for specialized expertise to operate and interpret the data, could pose challenges to market penetration. Nevertheless, the overall outlook remains positive, with a substantial increase in market size projected over the forecast period. The market's competitiveness is expected to intensify as more players enter the market and existing companies strive to enhance their product offerings to meet evolving customer demands.

The Drinking Water Mapping Application (DWMA) is a web-based geographic information system (GIS) that enhances the capabilities to identify major contaminant risks to public drinking water supplies. The DWMA includes functionality for both surface and ground-water based public water systems, including a well visualization tool (under development), non-point source and non-NHD data layer analyses, and multi-program analyses.

Mapping Software Market Outlook

The global mapping software market size was valued at approximately USD 5.7 billion in 2023 and is projected to reach USD 11.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.1% during the forecast period. The growth of this market is driven by the increasing need for spatial data in various industries, advancements in geographic information system (GIS) technology, and the growing trend of digitalization across different sectors.

One of the primary growth factors in the mapping software market is the rising demand for location-based services (LBS). These services are essential for numerous applications, from navigation and route planning to marketing and asset tracking. The proliferation of smartphones and wearable devices equipped with GPS has significantly boosted the use of LBS, thereby driving the demand for advanced mapping software. Furthermore, businesses are increasingly leveraging spatial data to enhance decision-making processes, optimize operations, and improve customer experiences, all of which contribute to the market's expansion.

Another significant driver is the increasing usage of mapping software in urban planning and smart city initiatives. With the global urban population expected to rise continuously, cities are turning to technology to manage resources efficiently, ensure sustainable development, and improve the quality of life for residents. Mapping software plays a crucial role in urban planning by providing detailed spatial data, enabling planners to visualize and analyze various urban scenarios, plan infrastructure development, and manage urban growth effectively. Additionally, governments are investing heavily in smart city projects, creating a substantial demand for sophisticated mapping tools.

Technological advancements in GIS and remote sensing technologies are also fueling the growth of the mapping software market. Innovations such as 3D mapping, real-time data integration, and cloud-based GIS solutions have expanded the capabilities and applications of mapping software. These advancements allow for more accurate and comprehensive spatial analysis, facilitating better decision-making and problem-solving in numerous fields, including environmental monitoring, disaster management, and transportation planning. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) with mapping software is further enhancing its functionality, enabling predictive analytics and automated data processing.

Regionally, North America holds a significant share of the mapping software market, driven by the widespread adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to rapid urbanization, increasing investments in infrastructure development, and the growing adoption of digital solutions across various sectors. Europe also presents substantial growth opportunities due to the increasing focus on smart city projects and environmental sustainability initiatives.

Component Analysis

The mapping software market is segmented by component into software and services. The software segment is further categorized into desktop, web-based, and mobile software, each catering to different user needs and preferences. Desktop software continues to be widely used due to its robust functionalities and ability to handle complex spatial data analysis. Web-based software, on the other hand, offers flexibility and ease of access, making it popular among users who require real-time data and collaboration capabilities. Mobile mapping software is gaining traction, especially among field workers and on-the-go professionals, due to its portability and convenience.

Services in the mapping software market encompass a range of offerings, including consulting, implementation, training, and support services. Consulting services are essential for organizations looking to integrate mapping software into their existing systems and workflows. Implementation services ensure the smooth deployment and customization of software solutions to meet specific business requirements. Training services are crucial for enhancing user proficiency and maximizing the software's potential, while support services provide necessary technical assistance and software maintenance. The growing complexity of spatial data applications and the need for expert guidance are driving the demand for these services.

The software segment dominates the mapping softwar

The cloud-based mapping service market is experiencing robust growth, driven by increasing demand for location-based services across diverse sectors. The market size in 2025 is estimated at $15 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors, including the rising adoption of cloud computing, the increasing availability of high-resolution geospatial data, and the growing need for real-time location intelligence in applications like urban planning, logistics, and environmental monitoring. Furthermore, advancements in mapping technologies such as AI-powered image analysis and 3D modeling are enhancing the capabilities of cloud-based mapping services, making them more versatile and valuable to businesses and governments alike. The ease of accessibility, scalability, and cost-effectiveness offered by cloud-based solutions are further propelling market growth, attracting a wide range of users from small businesses to large enterprises. This growth trajectory is further supported by the ongoing integration of cloud-based mapping services with other technologies like IoT (Internet of Things) and big data analytics. This convergence enables the creation of sophisticated location-based applications that offer advanced functionalities, such as predictive analytics, route optimization, and asset tracking. While challenges remain, such as data security concerns and the need for robust internet connectivity, the overall market outlook remains positive, with a projected market value exceeding $45 billion by 2033. The competitive landscape includes established players like ESRI and Trimble, alongside emerging innovative companies continuously improving the technology and expanding market reach. This dynamic interplay of technological advancements, increasing demand, and competitive innovation is set to shape the future of cloud-based mapping services.

The Geographic Information System (GIS) Tools market is experiencing robust growth, projected to reach $2890.3 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.3% from 2025 to 2033. This expansion is driven by several key factors. Increasing urbanization and the need for efficient city planning and management are fueling demand for sophisticated GIS solutions. Furthermore, the rising adoption of cloud-based GIS platforms offers scalability, accessibility, and cost-effectiveness, attracting both SMEs and large enterprises. The integration of GIS with other technologies, such as IoT and AI, is enhancing data analysis capabilities and creating new applications in areas like precision agriculture, environmental monitoring, and disaster response. However, challenges remain, including the high initial investment costs associated with implementing GIS systems and the need for skilled professionals to manage and interpret complex spatial data. The market is segmented by deployment type (cloud-based and on-premises) and user type (SMEs and large enterprises), with the cloud-based segment demonstrating faster growth due to its inherent flexibility and affordability. North America currently holds a significant market share, driven by the presence of major technology companies and a high rate of GIS adoption across various sectors. However, developing regions in Asia-Pacific and the Middle East & Africa present significant growth opportunities, fueled by increasing infrastructure development and government initiatives promoting digital transformation. The competitive landscape is highly dynamic, with both established players like IBM TRIRIGA and Infor EAM, and emerging companies such as UpKeep and Samsara competing for market share. The success of these companies hinges on their ability to offer innovative solutions tailored to specific industry needs, coupled with robust customer support and seamless integration with existing IT infrastructure. Future market growth will depend on continued technological advancements, the expanding applications of GIS technology across diverse sectors, and effective strategies to overcome the challenges related to data security, interoperability, and skills development. The forecast period of 2025-2033 anticipates a continued upward trajectory, with ongoing expansion in both established and emerging markets globally.

Simultaneous Localization And Mapping Software Market Outlook

According to our latest research, the global Simultaneous Localization and Mapping (SLAM) Software market size reached USD 2.13 billion in 2024. The market is expected to expand at a robust CAGR of 21.8% from 2025 to 2033, projecting the market to attain a value of USD 15.2 billion by 2033. This remarkable growth is primarily driven by the accelerating adoption of automation technologies in industries such as robotics, automotive, and consumer electronics, alongside the rapid advancements in artificial intelligence and sensor technologies that underpin SLAM solutions.

One of the primary growth factors for the SLAM Software market is the surging demand for autonomous systems across various industries. As robotics and autonomous vehicles become increasingly mainstream, the need for accurate real-time mapping and localization capabilities has become critical. SLAM software, which enables machines to map unknown environments while simultaneously tracking their location within them, is at the heart of these innovations. The rapid integration of SLAM algorithms in warehouse automation, manufacturing robotics, and logistics is enhancing operational efficiency and reducing human intervention, thereby fueling market expansion. Furthermore, the proliferation of Internet of Things (IoT) devices and edge computing is allowing SLAM software to process data more efficiently, further boosting its adoption across multiple sectors.

Another significant driver is the technological advancements in computer vision and sensor fusion. The evolution of sensors such as LiDAR, RGB-D cameras, and IMUs, combined with breakthroughs in machine learning and deep learning, has substantially improved the accuracy and robustness of SLAM solutions. These advancements have enabled SLAM software to function effectively in complex and dynamic environments, including indoor and outdoor settings with varying lighting and structural conditions. The growing investment in research and development by both established technology giants and innovative startups is leading to the continuous refinement of SLAM algorithms, making them more accessible and cost-effective for a wider range of applications, from consumer electronics to advanced industrial automation.

The expanding application of SLAM software in emerging fields such as augmented reality (AR) and virtual reality (VR) is also contributing to market growth. SLAM plays a pivotal role in enabling immersive and interactive experiences by providing real-time positional tracking and environmental mapping. The increasing adoption of AR/VR technologies in sectors like healthcare, education, retail, and entertainment is driving demand for high-performance SLAM solutions. Additionally, the integration of SLAM with drone and unmanned aerial vehicle (UAV) navigation systems is opening new avenues for market expansion, particularly in areas such as aerial surveying, agriculture, and disaster management, where precise localization and mapping are essential.

From a regional perspective, North America currently dominates the SLAM Software market, with significant contributions from the United States due to its strong technological infrastructure and substantial investments in robotics and autonomous vehicle development. However, the Asia Pacific region is anticipated to witness the fastest growth during the forecast period, propelled by rapid industrialization, increasing adoption of automation technologies, and supportive government initiatives in countries such as China, Japan, and South Korea. Europe also remains a key market, driven by advancements in automotive and manufacturing sectors. The Middle East & Africa and Latin America are gradually emerging as promising markets, supported by growing investments in smart city projects and digital transformation initiatives.

Offering Analysis

The SLAM Software market is segmented by offering into software and services, each playing a pivotal role in the ecosystem. The softw

The global mapping software market is experiencing robust growth, driven by increasing demand across various sectors. While precise figures for market size and CAGR are absent from the provided data, a reasonable estimation can be made based on industry trends. Considering the presence of major players like Adobe, Autodesk, and Microsoft, and the consistent advancements in GIS technology and location-based services, a conservative estimate places the 2025 market size at approximately $15 billion USD. Assuming a steady growth trajectory influenced by factors like increasing adoption of cloud-based solutions, the integration of AI and machine learning for enhanced mapping capabilities, and the growing need for precise location data in logistics, urban planning, and environmental monitoring, a Compound Annual Growth Rate (CAGR) of 8-10% over the forecast period (2025-2033) seems plausible. This would project market values significantly higher by 2033. This growth is fueled by several key trends. The increasing availability of high-resolution satellite imagery and other geospatial data provides richer inputs for mapping applications. Furthermore, the rising adoption of mobile devices equipped with GPS technology and the proliferation of location-based services (LBS) are expanding the market's addressable user base. However, challenges remain, such as the high cost of advanced mapping software and the complexities associated with data integration and management. Nevertheless, the overall market outlook remains positive, with continued expansion anticipated across various segments and geographic regions. The competitive landscape is marked by a mix of established players and emerging startups, leading to innovation and the continuous improvement of mapping technologies.

The lake mapping service market is experiencing robust growth, driven by increasing demand for effective resource management, environmental monitoring, and ecological studies. A rising global population and the consequent pressure on water resources are key factors fueling this expansion. Furthermore, advancements in remote sensing technologies, such as aerial photography and satellite imagery, are providing higher-resolution data, leading to more accurate and detailed lake mapping. This enhanced accuracy enables better informed decision-making for various applications, including identifying pollution sources, assessing water quality, monitoring shoreline changes, and managing aquatic vegetation. The market is segmented by application (environmental monitoring, resource management, ecological studies, and others) and type of imagery (aerial photography, satellite imagery, and others). While precise market sizing data was not provided, a conservative estimate based on industry trends and comparable markets suggests a current market value of approximately $500 million in 2025, with a compound annual growth rate (CAGR) of around 7% projected through 2033. This growth is expected across all regions, with North America and Europe currently holding significant market shares due to higher adoption rates and established regulatory frameworks for environmental monitoring. However, Asia-Pacific is poised for significant expansion in the coming years due to increasing government investments in infrastructure and water resource management. Potential restraints include the high initial investment costs associated with advanced mapping technologies and the need for skilled professionals to interpret and utilize the data effectively. The competitive landscape is characterized by a mix of established environmental consulting firms and specialized lake management companies. Key players are focusing on strategic partnerships and technological advancements to strengthen their market positions. The increasing availability of affordable, high-resolution imagery and user-friendly data analysis software is democratizing access to lake mapping services, making them more accessible to smaller organizations and government agencies with limited budgets. This trend is expected to accelerate market penetration and contribute to overall market growth. The future of lake mapping services is linked to the integration of advanced analytics, artificial intelligence, and machine learning for improved data interpretation, predictive modeling, and automated reporting. This will enhance the efficiency and effectiveness of lake management initiatives globally.

The Environmental Response Management Application (ERMA®) is a web-based Geographic Information System (GIS) tool that assists both emergency responders and environmental resource managers in dealing with incidents that may adversely impact the environment. ERMA® integrates and synthesizes various real-time and static datasets into a single interactive map, thus provides fast visualization of the situation and improves communication and coordination among responders and environmental stakeholders.

Pacific Northwest ERMA is an online mapping tool that allows stakeholders and communities to visualize ecological, land use, and infrastructure data in one centralized location. With the increase in oil transported by rail in the region, along with existing marine traffic, emergency planners are relying upon ERMA to help prepare and respond to environmental pollution incidents in Washington and Oregon.

ERMA® is a registered trademark.

This paper presents an analysis of an environmental conflict that arose in a Thai industrial zone. The authors analyse state policies to resolve the conflict, and draw lessons for other industrializing nations adopting industrial zone models. The study revealed that a root cause of the conflict was violation of land-use planning regulations and expansion of the industrial zone into community areas. Through legal action, civil society successfully forced the state and industries to halt unplanned expansion. However, inadequate commitment by the state and industry stakeholders seems to perpetuate the conflict. A Geographic Information Systems (GIS)-based analysis confirmed that the state policy interventions did not produce significant results. This paper highlights the need for GIS-based environmental quality monitoring to guide industrialization-based urban development towards sustainability.

Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...

The Digital Environmental Geologic-GIS Map for San Antonio Missions National Historical Park and Vicinity, Texas is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (saan_environmental_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (saan_environmental_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (saan_environmental_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (saan_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (saan_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (saan_environmental_geology_metadata_faq.pdf). Please read the saan_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Bureau of Economic Geology, University of Texas at Austin. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (saan_environmental_geology_metadata.txt or saan_environmental_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). Purpose: