Environmental impact assessment (EIA) is a procedure that ensures that the

environmental implications of decisions of a proposed project are taken into

account before the decisions are made. EIA is one of the oldest and most
institutionalized procedures, and refers primarily to the environmental assessment of
project level interventions. It is the one framework that is most firmly embedded in
national legislation. EIAs are carried out for projects.

During an EIA procedure environmental consequences of projects are identified and

assessed before authorization is given to the project. The assessment could lead to
making modifications to the project, for example to mitigate or reduce the
expected environmental impacts. Public involvement is a key element of the EIA
procedure. The public is informed of the decision afterwards. EIA process involves an
analysis of the likely effects on the environment, recording those effects in a
report, undertaking a public consultation exercise on the report, taking into account
the comments and the report when making the final decision and informing the public
about that decision afterwards. The International Association for Impact Assessment
describes the following steps as being part of an EIA process: screening, scoping,
examination of alternatives, impact analysis, mitigation and impact management,
evaluation of significance, preparation of environmental impact statement (EIS)
report, review of the EIS, decision making and follow up.
 Screening: process of determining whether an EIA is required for a specific
project.
 Scoping: identifying the impacts that are likely to be important.
 Examination of alternatives: process of determining the environmentally most
desired policy option.
 Impact analysis: process of identifying and predicting the effects of the
proposal.
 Mitigation and impact management: process to establish measures (or
mechanisms) to minimize negative effects.
 Evaluation of significance: process of evaluation if the impacts that cannot be
mitigated are acceptable as compared to the benefits stemming from the proposal.
 Environmental impact statement (EIS) report.
 Review of the EIS: process of assessing the quality of the report.
 Decision making: approving or rejecting the proposal (although arguably not
occurring within the EIA process).
 Follow up: process of monitoring impacts and effectiveness of mitigation
measures as well as reflecting on the EIA to strengthen future applications.

WHAT ARE GEOGRAPHIC INFORMATION SYSTEMS?

Geographic Information Systems are a set of tools for collecting, storing,
retrieving at will, transforming and displaying spatial data from the world for a
particular set of purposes. Geographical information systems can be applied at all
EIA stages. GIS can be explored within the EIA process to improve different features,
mainly related to data storage and access, to the analytical capabilities and to the
communicability of the results. The development of such a system will allow a more
realistic approach to the environmental signifiers or descriptors and a better
understanding of their interrelationships. GIS will bring to the EIA process a new way
of analyzing and manipulating spatial objects and an improved way of
communicating the results of the analysis, which can be of great importance to the
public participation process.

GIS is crucial in environmental studies because it allows for detailed spatial analysis
of environmental data, enabling researchers to visualize, map, and understand the
relationships between different environmental factors, which is vital for effective
environmental planning, impact assessment, resource management, and decision-
making regarding conservation and mitigation strategies across various landscapes.

APPLICATION OF GIS IN EIA

The following are the examples of the usefulness of GIS

A. DATA MANAGEMENT
GIS can store, organize, and integrate various environmental data layers (e.g., land
cover, topography, wildlife habitats, water bodies, soil types) from multiple sources,
creating a comprehensive spatial database for analysis. Typically, a GIS data base is
divided into geographic units or cells. The data associated with each cell can be based
on political, geographic, geological, or biological characteristics or a combination of
any of these. Environmental and social statistics can then be organized as attributes or
tables within each cell. With GIS , data are readily displayed and interpreted in a
conventional map format. Both the proposed development project and existing
environmental characteristics can be displayed as an overlay or attribute on the map,
allowing easy visual interpretation of the impact potential. Data often can be directly
imported into a GIS data base from other spatial display programs such as
spreadsheet or database files. The GIS data base can in turn be exported to other
spatial, spreadsheet, or database files.

B. DATA OVERLAY AND ANALYSIS

By overlaying different data layers, GIS enables the identification of sensitive
environmental areas that may be affected by a project, such as wetlands, protected
species habitats, or steep slopes. One of the early methods of environmental planning
used an overlay approach, where environmental (including socioeconomic and
cultural) data were graphically displayed on Mylar sheets that could be assembled in
various combinations to determine areas of environmental constraint. Areas of
constraint were determined by visual interpretation of the varying degrees of darkness
as the mylar sheets marked with constraints were overlain. The extent of the
constraints in any given area was measured and calculated manually. GIS improves
on this system in several ways. The attribute layers are stored electronically rather
than on mylar sheets. Different layers can be electronically combined, removed, or
ignored at any time. Constraint areas and degrees of multiple constraint can be
calculated by computer. Constraints also can be assigned numerical weights that can
be compounded mathematically.

Analysis results can be displayed numerically in tables or graphically with colors or

shades being assigned to depict areas where limits would preclude specific types of
development by;
I. Site Impact Prediction
Impacts can be predicted by overlaying various development scenarios. Areas can be
calculated for each ecosystem or land use type affected by construction or other
developmental activities. A real, linear, or point impacts can be calculated. For
example, an area affected by a construction project could be identified within an
ecological data base and the GIS program could than calculate the size of each
resource within that area.
II. Wider Area Impact Prediction
The use of buffers in GIS allows calculation of impacts in an area of influence,
reflecting the distance that the impacts penetrate into the surrounding environment.
For example, large game hunting in northern areas quickly affects animal populations
within a kilometer (km) of any new access road. By placing a I-km-wide buffer on
either side of the access road, one can calculate the area in which big game animals
will be at risk. Many species, such as bald eagles or spotted owls, are susceptible to
impacts from significant human activities within their nesting areas. By putting
appropriate buffer circles around the known nesting habitats, one can depict the area
of constraint or impact potential.
III. Corridor Analysis
Corridor analysis has become an important development planning concept. GIS is
used to determine both the location and area of existing natural corridors needing
protection and the potential for linking these corridors further and extending their
natural value. This is very important in a highly developed area because many species
that require large areas of continuous natural habitat or migration routes depend on
such corridor linkages.
IV. Cumulative Effects Analysis and EA Audits
The ability to store environmental and developmental data electronically also
facilitates cumulative effects analysis (CEA) and EA audits. Once the GIS data layers
are recorded and stored, they are available for analysis of future projects and can
easily be updated. Each new development proposal can be overlain with previous and
other foreseeable proposals to allow evaluation of the cumulative effects. If these data
files are stored in a central location,the costly redundancy of having to recollect the
same environmental and developmental information for different projects is avoided.

C. TREND ANALYSIS
GIS can be used to make more reliable long-term impact predictions. Impacts can be
predicted in a real-time environment. Data can be continuously updated.
I. Predicting Impacts in a Real-time Environment
Natural, social, and cultural environments are not static. They are evolving
continuously in time and space. This change can result from the replacement, growth,
and maturation of natural populations over time, annual seasonal changes, or long-
term changes such as global warming. Because of this, the standard approach to
environmental assessment, based on data collected at a specific time and place, can
often be out-of-date before the planning or development are completed. Many
developments also are not static. Developments such as town sites, forest harvesting,
or agriculture change over time. Such natural and developmental changes in time and
space can be modeled in the GIS environment to allow real-time predictions of
environmental interactions.

For example, in an area of approximately 1.4 million hectares, forest management

and habitat suitability models can be combined with social, economic, natural, and
cultural data to evaluate impacts and recommend optimal forest management
approaches over a 100-year forest cycle. Initially geographic cells will be created
based on areas with similar forest vegetation (species, age, size), climate, and soils. In
each cell, all available and relevant data on natural, social, economic, and cultural
resources of the area will be recorded on the attribute tables. Based on the average
harvest requirements of the forest industry, a forest management model will be run in
the GIS. This allowed predictions, on a cell-by-cell basis, of the harvesting areas and
road network required to meet annual industrial harvest plans. The model will also be
used to project the subsequent growth and aging of the forest. Thus, calculations
could be made of the size and distribution of every forest type by species, age, and
size for any future time. These calculations will be used in parallel with habitat
suitability index (HSI) models to predict the effects on a variety of representative
wildlife species from the area.

The GIS modeling also predicted potential future times when the reforestation rate
might not meet the forest harvesting requirements. Thus, plans could be made for how
to handle such potential, in light of the ultimate goal of sustainability . Overall
impacts on each environmental resource in the area also could be evaluated over the
life cycle of the forest. The results could be used to help optimize forest management
decisions from both industrial and environmental perspectives. This approach can
bring EA closer to the goal of planning for long-term, sustainable development
management, something we all discuss but seldom know how to attain.

II. Continuous Updating

GIS allows continuous updating of information. For example, a forest fire can
consume large areas. The GIS database can be easily adjusted and analysis models
recalibrated to accommodate such environmental catastrophes.

Stages of EIA where GIS is utilized

 Screening and Scoping: Identifying potential environmental impacts based on

the project location and surrounding environmental features.
 Baseline Data Collection: Mapping existing environmental conditions to
establish a reference point for comparison.
 Impact Prediction and Analysis: Performing spatial analysis to predict the
potential impacts of a project on various environmental components.
 Mitigation Planning: Identifying and mapping mitigation measures to minimize
negative environmental impacts.
 Monitoring and Reporting: Tracking environmental changes over time to assess
the effectiveness of mitigation measures.

KEY GIS TECHNIQUES USED IN EIA

A. Overlay Analysis:
Combining multiple layers of spatial data (e.g., land use, vegetation, water bodies,
protected areas) to identify areas where potential impacts might occur.
B. Buffer Zone Analysis:
Creating buffer zones around sensitive features (like rivers, wetlands, or endangered
species habitats) to assess the proximity of a project and potential impacts.
C. Suitability Analysis:
Evaluating the suitability of a proposed project location based on environmental
factors, identifying areas with the least potential negative impact.
D. Distance Calculations:
Determining the distance between project components and environmental features to
assess potential interactions and impacts.
E. Network Analysis:
Analyzing transportation networks to assess potential impacts on traffic patterns and
related environmental effects
F. Spatial Modeling:
Creating simulations to predict potential environmental impacts based on different
project scenarios

G. Visualizations:
Presenting complex spatial data through maps, graphs, and 3D models to effectively
communicate potential environmental impacts to stakeholders

Case studies showcasing the application of GIS in Environmental Impact Assessments

(EIA) often involve utilizing spatial data analysis to identify sensitive environmental
areas, assess potential impacts of proposed projects like dams, roads, or industrial
developments on those areas, and visualize the potential risks and mitigation
strategies through detailed mapping. Example of Case Studies:

i. Dam Construction Project:

 Analysis of Erosion Risk: A GIS study could map areas with high erosion
potential around a proposed dam site, considering factors like slope gradient,
soil type, and land cover, allowing for targeted mitigation measures to be
implemented.
 Floodplain Mapping: By overlaying digital elevation models with river
data, GIS can identify potential flood inundation zones to assess the impact of a
dam on downstream communities.

ii. Road Development Project:

 Habitat Fragmentation Assessment: Overlaying proposed road alignment
with wildlife habitat data in GIS helps identify potential fragmentation of
species movement corridors, allowing for adjustments to the road design to
minimize impacts.
 Landslide Risk Analysis: Mapping areas with high landslide susceptibility
based on slope angle, geology, and land cover using GIS can guide road
construction planning to avoid high-risk zones.

iii. Wind Farm Development:

  Visual Impact Assessment: GIS can be used to generate 3D visualizations
of the proposed wind turbines within the landscape, allowing for evaluation of
the visual impact on surrounding areas.

 Bird Migration Analysis: Overlaying bird migration routes with potential

wind turbine locations to identify areas with high collision risk, enabling
mitigation strategies like turbine placement adjustments.

GEOSPATIAL DATA AND MAPPING TOOLS

Geospatial data are any data that have a geographical component such as location,
distance, area or shape. They can be derived from variuos sources such as GPS,
surveys or census. Mapping tools are softwares applications that allow you to create,
edit, and display geospatial data in the form of maps, charts, or graphs. Some
examples of mapping tools are ArcGIS, QGIS, and Google Earth.

When choosing geospatial data anfd mapping tools for your EIA project, there are
several factors to consider such as the scope, scale, objectives, data availability and
quality, etc. You should ask yourself what the key environmental and social aspects
you need to assess and map.

When presenting geospatial data and mapping tools in your EIA report, it is essential
to use appropiate and consistent map projections, scales, symbols, and colors for
accuracy and readability. Additionally, labels, captions, titles, and references should
be included to provide context and explanation of your maps. Effectively presenting
geospatial data and mapping tools enhances communication and decision-making.
Visualizations such as interactive maps and 3D models simplify complex information,
making it accessible to diverse stakeholders

Examples of GIS Tools Used in EIA

 ArcGIS – A widely used GIS software for spatial analysis, mapping, and
geostatistical modeling.
  QGIS – An open-source GIS tool providing robust spatial analysis and data
visualization capabilities.
 GRASS GIS – A powerful open-source tool for environmental modeling and
remote sensing integration.
 Google Earth Engine – A cloud-based platform for large-scale geospatial
data analysis using satellite imagery.
 ENVI – Specializes in remote sensing applications and image processing for
environmental assessments.
 IDRISI – A GIS and remote sensing tool designed for raster data analysis and
environmental modeling.
 ERDAS IMAGINE – Used for image processing, terrain analysis, and land
cover classification.

Practical Use of ArcGIS and Google Earth Engine in EIA

 Using ArcGIS:

1. Import spatial data (e.g., satellite imagery, land use maps).

2. Perform overlay analysis to assess environmental impacts.
3. Create buffer zones around sensitive environmental features.
4. Apply spatial interpolation techniques to predict pollution dispersion.
5. Generate detailed environmental impact maps and reports.

 Using Google Earth Engine:

1. Access large-scale satellite imagery datasets.

2. Use cloud-based computing for real-time analysis of land cover
changes.
3. Apply machine learning algorithms to detect deforestation or pollution
trends.
4. Generate time-series visualizations of environmental changes.
5. Share and integrate GIS outputs into web-based dashboards for
decision-making.